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    Visibility and attractiveness of Fritillaria (Liliaceae) flowers to potential pollinators

    1.Warren, J. & Mackenzie, S. Why are all colour combinations not equally represented as flower-colour polymorphisms?. New Phytol. 151, 237–241 (2001).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    2.Armbruster, S., Fenster, C. & Dudash, M. Pollination ‘principles’ revisited: specialization, pollination syndromes, and the evolution of flowers. Scandanavian Assoc. Pollinat. Ecol. 39, 179–200 (2000).
    Google Scholar 
    3.Hargreaves, A. L., Harder, L. D. & Johnson, S. D. Consumptive emasculation: the ecological and evolutionary consequences of pollen theft. Biol. Rev. 84, 259–276 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    4.Hansen, D. M., van der Niet, T. & Johnson, S. D. Floral signposts: testing the significance of visual ‘nectar guides’ for pollinator behaviour and plant fitness. Proc. R. Soc. B Biol. Sci. 279, 634–639 (2012).Article 

    Google Scholar 
    5.Rosas-Guerrero, V. et al. A quantitative review of pollination syndromes: do floral traits predict effective pollinators?. Ecol. Lett. 17, 388–400 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    6.Narbona, E., Wang, H., Ortiz, P. L., Arista, M. & Imbert, E. Flower colour polymorphism in the Mediterranean Basin: occurrence, maintenance and implications for speciation. Plant Biol. 20, 8–20 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    7.Altshuler, D. L. Flower color, hummingbird pollination, and habitat irradiance in four neotropical forests1. Biotropica 35, 344 (2003).Article 

    Google Scholar 
    8.Riordan, C. E., Ault, J. G., Langreth, S. G. & Keithly, J. S. Cryptosporidium parvum Cpn60 targets a relict organelle. Curr. Genet. 44, 138–147 (2003).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    9.Rodríguez-Gironés, M. A. & Santamaría, L. Why are so many bird flowers red?. PLoS Biol. 2, 1515–1519 (2004).Article 
    CAS 

    Google Scholar 
    10.Whibley, A. C. et al. Evolutionary paths underlying flower color variation in Antirrhinum. Science (80-.) 313, 963–966 (2006).CAS 
    Article 
    ADS 

    Google Scholar 
    11.Papiorek, S. et al. Bees, birds and yellow flowers: pollinator-dependent convergent evolution of UV patterns. Plant Biol. 18, 46–55 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    12.Wilson, P., Castellanos, M., Wolfe, A. D. & Thomson, J. D. Shifts between bee and bird pollination in penstemons. Plant-Pollinat. Interact. Spec. Gen. 3, 47–68 (2006).13.Wilson, P., Castellanos, M. C., Hogue, J. N., Thomson, J. D. & Armbruster, W. S. A multivariate search for pollination syndromes among penstemons. Oikos 104, 345–361 (2004).Article 

    Google Scholar 
    14.Sutherland, S. D. & Vickery, R. K. Jr. On the relative importance of floral color, shape, and nectar rewards in attracting pollinators to Mimulus. Gt. Basin Nat. 53, 107–117 (1993).
    Google Scholar 
    15.Wester, P. & Lunau, K. Plant-Pollinator Communication. Advances in Botanical Research Vol. 82 (Elsevier, 2017).
    Google Scholar 
    16.de Camargo, M. G. G. et al. How flower colour signals allure bees and hummingbirds: a community-level test of the bee avoidance hypothesis. New Phytol. 222, 1112–1122 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    17.van der Kooi, C. J., Dyer, A. G., Kevan, P. G. & Lunau, K. Functional significance of the optical properties of flowers for visual signalling. Ann. Bot. https://doi.org/10.1093/aob/mcy119 (2018).Article 
    PubMed Central 

    Google Scholar 
    18.Castellanos, M. C., Wilson, P. & Thomson, J. D. ‘ Anti-bee ’ and ‘ pro-bird ’ changes during the evolution of hummingbird pollination in Penstemon flowers. J. Evol. Biol. 17, 876–885 (2004).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    19.del Carmen Salas-Arcos, L., Lara, C., Castillo-Guevara, C., Cuautle, M. & Ornelas, J. F. “Pro-bird” floral traits discourage bumblebee visits to Penstemon gentianoides (Plantaginaceae), a mixed-pollinated herb. Sci. Nat. 106, 1–11 (2019).Article 
    CAS 

    Google Scholar 
    20.Armbruster, W. S. Evolution of floral morphology and function: an integrative approach to adaptation, constraint, and compromise in Dalechampia (Euphorbiaceae). Flor. Biol. https://doi.org/10.1007/978-1-4613-1165-2_9 (1996).Article 

    Google Scholar 
    21.Chittka, L. & Schürkens, S. Successful invasion of a floral market. Nature 411, 653 (2001).CAS 
    PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    22.Ellis, T. J. & Field, D. L. Repeated gains in yellow and anthocyanin pigmentation in flower colour transitions in the Antirrhineae. Ann. Bot. 117, 1133–1140 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    23.Tanaka, Y., Sasaki, N. & Ohmiya, A. Biosynthesis of plant pigments: anthocyanins, betalains and carotenoids. Plant J. 54, 733–749 (2008).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    24.Lázaro, A., Lundgren, R. & Totland, Ø. Pollen limitation, species’ floral traits and pollinator visitation: different relationships in contrasting communities. Oikos 124, 174–186 (2015).Article 

    Google Scholar 
    25.Jones, K. N. & Reithel, J. S. Pollinator-mediated selection on a flower color polymorphism in experimental populations of Anthirrhinum (Scrophulariaceae). Am. J. Bot. 88, 447–454 (2001).Article 

    Google Scholar 
    26.Teixido, A. L., Barrio, M. & Valladares, F. Size matters: understanding the conflict faced by large flowers in mediterranean environments. Bot. Rev. 82, 204–228 (2016).Article 

    Google Scholar 
    27.Ortiz, P. L., Fernández-Díaz, P., Pareja, D., Escudero, M. & Arista, M. Do visual traits honestly signal floral rewards at community level?. Funct. Ecol. 35, 369–383 (2021).Article 

    Google Scholar 
    28.Fenster, C. B., Cheely, G., Dudash, M. R. & Reynolds, R. J. Nectar reward and advertisement in hummingbird. Am. J. Bot. 93, 1800 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    29.Simpson, B. B., Neff, J. L. & Simpson, B. B. Floral rewards: alternatives to pollen and nectar. Ann. Mo. Bot. Gard. 68, 301–322 (2015).Article 

    Google Scholar 
    30.Canto, A., Herrera, C. M., García, I. M., Pérez, R. & Vaz, M. Intraplant variation in nectar traits in Helleborus foetidus (Ranunculaceae) as related to floral phase, environmental conditions and pollinator exposure. Flora Morphol. Distrib. Funct. Ecol. Plants 206, 668–675 (2011).
    Google Scholar 
    31.Parachnowitsch, A. L., Manson, J. S. & Sletvold, N. Evolutionary ecology of nectar. Ann. Bot. https://doi.org/10.1093/aob/mcy132 (2018).Article 
    PubMed Central 

    Google Scholar 
    32.Gómez, J. M. et al. Association between floral traits and rewards in Erysimum mediohispanicum (Brassicaceae). Ann. Bot. 101, 1413–1420 (2008).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    33.Worley, A. C. & Barrett, S. C. H. Evolution of floral display in Eichhornia paniculata (Pontederiaceae): genetic correlations between flower size and number. J. Evol. Biol. 14, 469–481 (2001).Article 

    Google Scholar 
    34.Lunau, K. The ecology and evolution of visual pollen signals. Plant Syst. Evol. 222, 89–111 (2000).Article 

    Google Scholar 
    35.Nicholls, E. & Hempel de Ibarra, N. Assessment of pollen rewards by foraging bees. Funct. Ecol. 31, 76–87 (2017).Article 

    Google Scholar 
    36.Tang, L.-L. & Huang, S.-Q. Evidence for reductions in floral attractants with increased selfing rates in two heterandrous species. New Phytol. https://doi.org/10.1111/j.1469-8137.2007.02115.x (2007).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    37.Faegri, K. & Van Der Pijl, L. Principles of Pollination Ecology (Elsevier, 2013).
    Google Scholar 
    38.Dellinger, A. S. Pollination syndromes in the 21st century: where do we stand and where may we go?. New Phytol. https://doi.org/10.1111/nph.16793 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    39.Kostyun, J. L., Gibson, M. J. S., King, C. M. & Moyle, L. C. A simple genetic architecture and low constraint allow rapid floral evolution in a diverse and recently radiating plant genus. New Phytol. 223, 1009–1022 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    40.Roguz, K. et al. Diversity of nectar amino acids in the Fritillaria (Liliaceae) genus: ecological and evolutionary implications. Sci. Rep. 9, 1–12 (2019).CAS 
    Article 
    ADS 

    Google Scholar 
    41.Roguz, K. et al. Functional diversity of nectary structure and nectar composition in the genus Fritillaria (liliaceae). Front. Plant Sci. 9, 1–21 (2018).Article 
    ADS 

    Google Scholar 
    42.Zych, M. & Stpiczyńska, M. Neither protogynous nor obligatory out-crossed: Pollination biology and breeding system of the European Red List Fritillaria meleagris L. (Liliaceae). Plant Biol. 14, 285–294 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Day, P. D. et al. Evolutionary relationships in the medicinally important genus Fritillaria L. (Liliaceae). Mol. Phylogenet. Evol. 80, 11–19 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    44.Hayashi, K. Molecular systematics of Lilium and allied genera (Liliaceae): phylogenetic relationships among Lilium and related genera based on the rbcL and matK gene sequence data. Plant Species Biol. 15, 73–93 (2000).Article 

    Google Scholar 
    45.Stpiczyńska, M., Nepi, M. & Zych, M. Nectaries and male-biased nectar production in protandrous flowers of a perennial umbellifer Angelica sylvestris L. (Apiaceae). Plant Syst. Evol. https://doi.org/10.1007/s00606-014-1152-3 (2014).Article 

    Google Scholar 
    46.Hill, L. A taxonomic history of Japanese endemic Fritillaria (Liliaceae). Kew Bull. 66, 227–240 (2018).Article 

    Google Scholar 
    47.Kiani, M. et al. Iran supports a great share of biodiversity and floristic endemism for Fritillaria spp. (Liliaceae): a review. Plant Divers. 39, 245–262 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    48.Shaw, A. J. Phylogeny of the Sphgnpsida based on chloroplast and nuclear DNA sequences. Bryologist 103, 277–306 (2000).CAS 
    Article 

    Google Scholar 
    49.Rønsted, N., Law, S., Thornton, H., Fay, M. F. & Chase, M. W. Molecular phylogenetic evidence for the monophyly of Fritillaria and Lilium (Liliaceae; Liliales) and the infrageneric classification of Fritillaria. Mol. Phylogenet. Evol. 35, 509–527 (2005).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    50.Tekşen, M. & Aytaç, Z. The revision of the genus Fritillaria L. (Liliaceae) in the Mediterranean region (Turkey). Turk. J. Bot. 35, 447–478 (2011).
    Google Scholar 
    51.Roguz, K., Hill, L., Roguz, A. & Zych, M. Evolution of bird and insect flower traits in Fritillaria L. (Liliaceae). Front. Plant Sci. 12, 656783 (2020).Article 

    Google Scholar 
    52.Zaharof, E. Variation and taxonomy of Fritillaria graeca (Liliaceae) in Greece. Plant Syst. Evol. 154, 41–61 (1986).Article 

    Google Scholar 
    53.Búrquez, A. & Burquez, A. Blue tits, Parus caeruleus, as pollinators of the crown imperial, Fritillaria imperialis, in Britain. Oikos 55, 335 (1989).Article 

    Google Scholar 
    54.Peters, W. S., Pirl, M., Gottsberger, G. & Peters, D. Pollination of the crown imperial Fritillaria imperialis by great tits Parus major. J. Ornithol. 136, 207–212 (1995).Article 

    Google Scholar 
    55.Pendegrass, K. & Robinson, A. A recovery plan for Fritillaria gentneri (Gentner’s fritillary). Agric. U.S.F.a.W. Serv. (2005).56.Zox, H. Ecology of black lily (Fritillaria camschatcensis): a Washington State sensitive species. Douglasia (2008).57.Cronk, Q. & Ojeda, I. Bird-pollinated flowers in an evolutionary and molecular context. J. Exp. Bot. 59, 715–727 (2008).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    58.Lunau, K. & Verhoeven, C. Wie Bienen Blumen sehen: Falschfarbenaufnahmen von Blüten. Biol. Unserer Zeit 47, 120–127 (2017).Article 

    Google Scholar 
    59.Kranas, H., Spalik, K. & Banasiak, Ł. MatPhylobi, 0.1 (University of Warsaw, 2018).
    Google Scholar 
    60.Kuraku, S., Zmasek, C. M., Nishimura, O. & Katoh, K. Leaves facilitates on-demand exploration of metazoan gene family trees on MAFFT sequence alignment server with enhanced interactivity. Nucleic Acids Res. https://doi.org/10.1093/nar/gkt389 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    61.Maddison, W. P. & Maddison, D. R. Mesquite: a modular system for evolutionary analysis. Evolution 62, 1103–1118 (2018).
    Google Scholar 
    62.Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinform. Appl. 30, 1312–1313 (2014).CAS 
    Article 

    Google Scholar 
    63.Suchard, M. A. et al. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. https://doi.org/10.1093/ve/vey016 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    64.Kim, J. S. & Kim, J. H. Updated molecular phylogenetic analysis, dating and biogeographical history of the lily family (Liliaceae: Liliales). Bot. J. Linn. Soc. 187, 579–593 (2018).Article 

    Google Scholar 
    65.Cockerell, T. D. A. Two new plants from the tertiary rocks of the west. Torrey Bot. Soc. 14, 135–137 (1914).
    Google Scholar 
    66.Ettingshausen, C. B. III. ‘ Report on Phyto-Palaeontologieal Investigations of Fossil Flora of Alum Bay.’ By Dr. (1AD).67.Conran, J. G., Carpenter, R. J. & Jordan, G. J. Early Eocene Ripogonum (Liliales: Ripogonaceae) leaf macrofossils from southern Australia. Aust. Syst. Bot. 22, 219–228 (2009).Article 

    Google Scholar 
    68.Lanfear, R., Calcott, B., Ho, S. Y. W. & Guindon, S. PartitionFinder: combined selection of partitioning schemes and substitution models for phylogenetic analyses. Mol. Biol. Evol. https://doi.org/10.1093/molbev/mss020 (2012).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    69.Paradis, E. & Schliep, K. Phylogenetics ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics https://doi.org/10.1093/bioinformatics/bty633 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    70.Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).Article 

    Google Scholar 
    71.Garland, T., Dickerman, A. W., Janis, C. M. & Jones, J. A. Phylogenetic Analysis of Covariance by Computer Simulation. vol. 42, 1993. https://academic.oup.com/sysbio/article/42/3/265/1629506 (Accessed 09 March 2021).72.Orme, C. D. L. The caper package: comparative analyses in phylogenetics and evolution in R, 1–36, 2012. See http://caper.r-forge.r-project.org/. (Accessed 09 March 2021).73.TEAM, R. C. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2018).
    Google Scholar 
    74.Dyer, A. G. et al. Parallel evolution of angiosperm colour signals: common evolutionary pressures linked to hymenopteran vision. Proc. R. Soc. B Biol. Sci. 279, 3606–3615 (2012).Article 

    Google Scholar 
    75.Ollerton, J. Reconciling ecological processes with phylogenetic patterns: the apparent paradox of plant-pollinator systems. J. Ecol. 84, 767–769 (1996).Article 

    Google Scholar 
    76.Wessinger, C. A. & Rausher, M. D. Predictability and irreversibility of genetic changes associated with flower color evolution in Penstemon barbatus. Evolution (N. Y.) 68, 1058–1070 (2014).CAS 

    Google Scholar 
    77.Wittmann, D., Radtke, R., Cure, J. R. & Schifino-Wittmann, M. T. Coevolved reproductive strategies in the oligolectic bee Callonychium petuniae (Apoidea, Andrenidae) and three purple flowered Petunia species (Solanaceae) in southern Brazil. J. Zool. Syst. Evol. Res. 28, 157–165 (1990).Article 

    Google Scholar 
    78.Chittka, L. & Waser, N. M. Why red flowers are not invisible to bees. Isr. J. Plant Sci. 45, 169–183 (1997).Article 

    Google Scholar 
    79.Kołodziejska-Degórska, I. & Zych, M. Bees substitute birds in pollination of ornitogamous climber Campsis radicans (L.) seem. in Poland. Acta Soc. Bot. Pol. 75, 79–85 (2006).Article 

    Google Scholar 
    80.Mayr, G. New specimens of the early oligocene old world hummingbird Eurotrochilus inexpectatus. J. Ornithol. 148, 105–111 (2007).Article 

    Google Scholar 
    81.Mayr, G. Old world fossil record of modern-type hummingbirds. Science (80-.) 304, 861–864 (2004).CAS 
    Article 
    ADS 

    Google Scholar 
    82.Schiestl, F. P. & Johnson, S. D. Pollinator-mediated evolution of floral signals. Trends Ecol. Evol. 28, 307–315 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    83.Daumer, K. Blumenfarben, wie sie die Bienen sehen. Z. Vgl. Physiol. 41, 49–110 (1958).
    Google Scholar 
    84.Kevan, P. G. Floral colours in the high Arctic with reference to insect flower relations and pollination. Can. J. Bot. 50, 2289–2316 (1972).Article 

    Google Scholar 
    85.Chittka, L., Shmida, A., Troje, N. & Menzel, R. Ultraviolet as a component of flower reflections, and the colour perception of hymenoptera. Vis. Res. 34, 1489–1508 (1994).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    86.Lunau, K. Stamens and mimic stamens as components of floral colour patterns. Bot. Jahrbücher für Syst. Pflanzengeschichte und Pflanzengeographie 127, 13–41 (2006).Article 

    Google Scholar 
    87.Koski, M. H. & Ashman, T. L. Dissecting pollinator responses to a ubiquitous ultraviolet floral pattern in the wild. Funct. Ecol. 28, 868–877 (2014).Article 

    Google Scholar 
    88.Menzel, R. & Shmida, A. The ecology of flower colours and the natural colour vision of insect pollinators: the Israeli flora as a study case. Biol. Rev. 68, 81–120 (1993).Article 

    Google Scholar 
    89.van der Kooi, C. J. & Stavenga, D. G. Vividly coloured poppy flowers due to dense pigmentation and strong scattering in thin petals. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 205, 363–372 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    90.Kevan, P., Giurfa, M. & Chittka, L. Why are there so many and so few white flowers?. Trends Plant Sci. 1, 280–284 (1996).Article 

    Google Scholar 
    91.Kapustjansky, A., Chittka, L. & Spaethe, J. Bees use three-dimensional information to improve target detection. Naturwissenschaften 97, 229–233 (2010).CAS 
    PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    92.Chittka, L. & Raine, N. E. Recognition of flowers by pollinators. Curr. Opin. Plant Biol. 9, 428–435 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    93.Hansen, D. M., Olesen, J. M., Mione, T., Johnson, S. D. & Müller, C. B. Coloured nectar: Distribution, ecology, and evolution of an enigmatic floral trait. Biol. Rev. 82, 83–111 (2007).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    94.Raguso, R. A. Start making scents: the challenge of integrating chemistry into pollination ecology. Entomol. Exp. Appl. 128, 196–207 (2008).CAS 
    Article 

    Google Scholar 
    95.Sapir, Y., Shmida, A. & Ne’eman, G. Morning floral heat as a reward to the pollinators of the Oncocyclus irises. Oecologia 147, 53–59 (2006).PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    96.Bazzaz, F. A. & Carslon, R. W. Photosynthetic contribution of flowers and seeds to reproductive effort of an annual colonizer. New Phytol. 82, 223–232 (1979).Article 

    Google Scholar  More

  • in

    Influence of intrinsic and extrinsic attributes on neonate survival in an invasive large mammal

    1.Sæther, B.-E. Environmental stochasticity and population dynamics of large herbivores: A search for mechanisms. Trends Ecol. Evol. 12, 143–149 (1997).PubMed 
    Article 

    Google Scholar 
    2.Gaillard, J.-M., Festa-Bianchet, M. & Yoccoz, N. G. Population dynamics of large herbivores: Variable recruitment with constant adult survival. Trends Ecol. Evol. 13, 58–63 (1998).CAS 
    PubMed 
    Article 

    Google Scholar 
    3.Coulson, T. et al. Estimating individual contributions to population growth: Evolutionary fitness in ecological time. Proc. R. Soc. B 273, 547–555 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    4.Pelletier, F., Clutton-Brock, T., Pemberton, J., Tuljapurkar, S. & Coulson, T. The evolutionary demography of ecological change: Linking trait variation and population growth. Science 315, 1571–1574 (2007).ADS 
    CAS 
    PubMed 
    Article 

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

    Google Scholar 
    6.Forchhammer, M. C., Clutton-Brock, T. H., Lindström, J. & Albon, S. D. Climate and population density induce long-term cohort variation in a northern ungulate. J. Anim. Ecol. 70, 721–729 (2001).Article 

    Google Scholar 
    7.Owen-Smith, N., Mason, D. R. & Ogutu, J. O. Correlates of survival rates for 10 African ungulate populations: Density, rainfall and predation. J. Anim. Ecol. 74, 774–788 (2005).Article 

    Google Scholar 
    8.Gaillard, J.-M., Festa-Bianchet, M., Yoccoz, N., Loison, A. & Toigo, C. Temporal variation in fitness components and population dynamics of large herbivores. Annu. Rev. Ecol. Syst. 31, 367–393 (2000).Article 

    Google Scholar 
    9.Griffin, K. A. et al. Neonatal mortality of elk driven by climate, predator phenology and predator community composition. J. Anim. Ecol. 80, 1246–1257 (2011).PubMed 
    Article 

    Google Scholar 
    10.Kilgo, J. C., Vukovich, M., Scott Ray, H., Shaw, C. E. & Ruth, C. Coyote removal, understory cover, and survival of white-tailed deer neonates. J. Wildl. Manag. 78, 1261–1271 (2014).Article 

    Google Scholar 
    11.Coltman, D. W., Bowen, W. D. & Wright, J. M. Birth weight and neonatal survival of harbour seal pups are positively correlated with genetic variation measured by microsatellites. Proc. R. Soc. B 265, 803–809 (1998).CAS 
    PubMed 
    Article 

    Google Scholar 
    12.Kolbe, J. & Janzen, F. The influence of propagule size and maternal nest-site selection on survival and behaviour of neonate turtles. Funct. Ecol. 15, 772–781 (2001).Article 

    Google Scholar 
    13.Kissner, K. J. & Weatherhead, P. J. Phenotypic effects on survival of neonatal northern watersnakes Nerodia sipedon. J. Anim. Ecol. 74, 259–265 (2005).Article 

    Google Scholar 
    14.Carstensen, M., Delgiudice, G. D., Sampson, B. A. & Kuehn, D. W. Survival, birth characteristics, and cause-specific mortality of white-tailed deer neonates. J. Wildl. Manag. 73, 175–183 (2009).Article 

    Google Scholar 
    15.Guttery, M. R. et al. Effects of landscape-scale environmental variation on greater sage-grouse chick survival. PLoS One 8, e65582 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    16.Duquette, J. F., Belant, J. L., Svoboda, N. J., Beyer, D. E. Jr. & Lederle, P. E. Effects of maternal nutrition, resource use and multi-predator risk on neonatal white-tailed deer survival. PLoS One 9, 1–10 (2014).Article 

    Google Scholar 
    17.Pimentel, D. In Managing Vertebrate Invasive Species: Proceedings of an International Symposium. (eds. Pitt, W.C. et al.) 2–8 (USDA/APHIS/WS, 2007).18.Pitt, W. C., Beasley, J. & Witmer, G. W. Ecology and Management of Terrestrial Vertebrate Invasive Species in the United States. 7–31 (CRC Press, 2018).19.Strickland, B. K., Smith, M. D., Smith, A. L. Wild pig damage to resources. In Invasive Wild Pigs in North America: Ecology, Impacts, and Management (eds. Vercauteren, K. C. et al.) 143–174 (CRC Press, 2020).20.Lowe, S., Browne, M., Boudjelas, S. & De Poorter, M. In 100 of the World’s Worst Invasive Alien Species: A Selection from the Global Invasive Species Database. Vol. 12 (Invasive Species Specialist Group, Species Survival Commission, World Conservation Union (IUCN), 2000).21.Keiter, D. A., Mayer, J. J. & Beasley, J. C. What is in a “common” name? A call for consistent terminology for nonnative Sus scrofa. Wild. Soc. Bull. 40, 384–387 (2016).Article 

    Google Scholar 
    22.Smyser, T. J. et al. Mixed ancestry from wild and domestic lineages contributes to the rapid expansion of invasive feral swine. Mol. Ecol. 29, 1103–1119 (2020).PubMed 
    Article 

    Google Scholar 
    23.Bevins, S. N., Pedersen, K., Lutman, M. W., Gidlewski, T. & Deliberto, T. J. Consequences associated with the recent range expansion of nonnative feral swine. BioSci. 64, 291–299 (2014).Article 

    Google Scholar 
    24.Mohr, D., Cohnstaedt, L. W. & Topp, W. Wild boar and red deer affect soil nutrients and soil biota in steep oak stands of the Eifel. Soil Biol. Biochem. 37, 693–700 (2005).CAS 
    Article 

    Google Scholar 
    25.Barrios-García, M. N. & Ballari, S. A. Impact of wild boar (Sus scrofa) in its introduced and native range: A review. Biol. Invasions 14, 2283–2300 (2012).Article 

    Google Scholar 
    26.Beasley, J. C., Ditchkoff, S. S., Mayer, J. J., Smith, M. D. & Vercauteren, K. C. Research priorities for managing invasive wild pigs in North America. J. Wildl. Manag. 82, 674–681 (2018).Article 

    Google Scholar 
    27.Ditchkoff, S. S. & Bodenchuk, M. J. Management of wild pigs. In Invasive Wild Pigs in North America: Ecology, Impacts, and Management (eds. Vercauteren, K. C. et al.) 175–198 (CRC Press, 2020).28.Bieber, C. & Ruf, T. Population dynamics in wild boar Sus scrofa: Ecology, elasticity of growth rate and implications for the management of pulsed resource consumers. J. Appl. Ecol. 42, 1203–1213 (2005).Article 

    Google Scholar 
    29.Hanson, L. B. et al. Effect of experimental manipulation on survival and recruitment of feral pigs. Wildl. Res. 36, 185–191 (2009).Article 

    Google Scholar 
    30.Keiter, D. A. et al. Effects of scale of movement, detection probability, and true population density on common methods of estimating population density. Sci. Rep. 7, 1–12 (2017).CAS 
    Article 

    Google Scholar 
    31.Keiter, D. A., Kilgo, J. C., Vukovich, M. A., Cunningham, F. L. & Beasley, J. C. Development of known-fate survival monitoring techniques for juvenile wild pigs (Sus scrofa). Wildl. Res. 44, 165–173 (2017).Article 

    Google Scholar 
    32.Snow, N. P., Miller, R. S., Beasely, J. C. & Pepin, K. M. Wild pig population dynamics. In Invasive Wild Pigs in North America: Ecology, Impacts, and Management (eds. Vercauteren, K. C. et al.) 57–82 (CRC Press, 2020).33.Alonso-Spilsbury, M., Ramirez-Necoechea, R., Gonzalez-Lozano, M., Mota-Rojas, D. & Trujillo-Ortega, M. Piglet survival in early lactation: A review. J. Anim. Vet. Adv. 1, 76–86 (2007).
    Google Scholar 
    34.Baubet, E., Servanty, S. & Brandt, S. Tagging piglets at the farrowing nest in the wild: Some preliminary guidelines. Acta Sylvatica Lig. Hung. 5, 159–166 (2009).
    Google Scholar 
    35.Kerr, J. & Cameron, N. Reproductive performance of pigs selected for components of efficient lean growth. Anim. Sci. 60, 281–290 (1995).Article 

    Google Scholar 
    36.Van der Lende, T., KnoI, E. & Leenhouwers, J. Prenatal development asa predisposing factor for perinatal lossesin pigs. Reproduction 58, 247–261 (2001).PubMed 
    PubMed Central 

    Google Scholar 
    37.Mount, L. The heat loss from new-born pigs to the floor. Res. Vet. Sci. 8, 175–186 (1967).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    38.Herpin, P., Damon, M. & Le Dividich, J. Development of thermoregulation and neonatal survival in pigs. Livest. Prod. Sci. 78, 25–45 (2002).Article 

    Google Scholar 
    39.Gaillard, J.-M., Pontier, D., Brandt, S., Jullien, J.-M. & Allaine, D. Sex differentiation in postnatal growth rate: A test in a wild boar population. Oecologia 90, 167–171 (1992).ADS 
    Article 

    Google Scholar 
    40.Trivers, R. L. & Willard, D. E. Natural selection of parental ability to vary the sex ratio of offspring. Science 179, 90–92 (1973).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    41.Clutton-Brock, T. H., Albon, S. D. & Guinness, F. E. Parental investment and sex differences in juvenile mortality in birds and mammals. Nature 313, 131–133 (1985).ADS 
    Article 

    Google Scholar 
    42.Theil, P. K., Nielsen, M. O., Sørensen, M. T. & Lauridsen, C. Lactation, milk and suckling. In Nutritional Physiology of Pigs: with emphasis on Danish production conditions (eds. Knudsen et al.) 1–49 (University of Copenhagen, 2012).43.Theil, P. K., Lauridsen, C. & Quesnel, H. Neonatal piglet survival: Impact of sow nutrition around parturition on fetal glycogen deposition and production and composition of colostrum and transient milk. Animal 8, 1021–1030 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    44.Mayer, J. & Brisbin Jr, I. L. Wild pigs of the Savannah River Site. Report No. SRNL-RP-2011-00295, 114 (Savannah River National Laboratory, 2012).45.Withey, J. C., Bloxton, T. D. & Marzluff, J. M. Effects of tagging and location error in wildlife telemetry studies. In Radio Tracking and Animal Populations. 43–75 (Academic Press, 2001).46.Webster, S. C. & Beasley, J. C. Influence of lure choice and survey duration on scent stations for carnivore surveys. Wildl. Soc. Bull. 43, 661–668 (2019).Article 

    Google Scholar 
    47.Matschke, G. H. Aging European wild hogs by dentition. J. Wildl. Manag. 31, 109–113 (1967).Article 

    Google Scholar 
    48.Mayer, J. J., Martin, F. D. & Brisbin, I. L. Characteristics of wild pig farrowing nests and beds in the upper Coastal Plain of South Carolina. Appl. Anim. Behav. Sci. 78, 1–17 (2002).Article 

    Google Scholar 
    49.Kilgo, J. C., Ray, H. S., Vukovich, M., Goode, M. J. & Ruth, C. Predation by coyotes on white-tailed deer neonates in South Carolina. J. Wildl. Manag. 76, 1420–1430 (2012).Article 

    Google Scholar 
    50.Mayer, J. J. & Brisbin, I. J., Jr. Wild Pigs: Biology, Damage, Control Techniques and Management. Report No. SRNL-RP-2009-00869, 77–104 (Savannah River National Laboratory, 2009).51.Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using {lme4}. J. Stat. Softw. 67, 1–48 (2015).
    Google Scholar 
    52.R: A language and environment for statistical computing. v. 3.5.3 (R Foundation for Statistical Computing, Vienna, Austria, 2020).53.Weinbeck, S. W., Viner, B. J., Rivera-Giboyeaux A. M. Meteorological Monitoring Program at the Savannah River Site. Report No. SRNL-TR-2020-00197 (Savannah River National Laboratory, 2020).54.Plummer, M. In Proceedings of the 3rd International Workshop on Distributed Statistical Computing. 1–10 (Vienna, Austria).55.Denwood, M. J. runjags: An R package providing interface utilities, model templates, parallel computing methods and additional distributions for MCMC models in JAGS. J. Stat. Softw. 71, 1–25 (2016).Article 

    Google Scholar 
    56.Gelman, A. & Rubin, D. B. Inference from iterative simulation using multiple sequences. Stat. Sci. 7, 457–472 (1992).MATH 

    Google Scholar 
    57.Pollock, K. H., Winterstein, S. R., Bunck, C. M. & Curtis, P. D. Survival analysis in telemetry studies: The staggered entry design. J. Wildl. Manag. 53, 7–15 (1989).Article 

    Google Scholar 
    58.Harrell, F. Regression Modeling Strategies (ed. Harrell, F.) 60–64 (Springer, 2001).59.McCoy, D. E. et al. A comparative study of litter size and sex composition in a large dataset of callitrichine monkeys. Am. J. Primatol. 81, e23038. https://doi.org/10.1002/ajp.23038 (2019).60.Watanabe, S. Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory. J. Mach. Learn. Res. 11, 3571–3594 (2010).61.Burnham, K. P. & Anderson, D. R. A practical information-theoretic approach. In Model Selection and Multimodel Inference, 2nd edn. 75–117 (Springer, 2002).62.Taylor, R. B., Hellgren, E. C., Gabor, T. M. & Ilse, L. M. Reproduction of feral pigs in southern Texas. J. Mammal. 79, 1325–1331 (1998).Article 

    Google Scholar 
    63.Mittwoch, U. Blastocysts prepare for the race to be male. Hum. Reprod. 8, 1550–1555 (1993).CAS 
    PubMed 
    Article 

    Google Scholar 
    64.Stanton, H. & Carroll, J. Potential mechanisms responsible for prenatal and perinatal mortality or low viability of swine. J. Anim. Sci. 38, 1037–1044 (1974).CAS 
    PubMed 
    Article 

    Google Scholar 
    65.Hartsock, T. G. & Graves, H. Neonatal behavior and nutrition-related mortality in domestic swine. J. Anim. Sci. 42, 235–241 (1976).CAS 
    PubMed 
    Article 

    Google Scholar 
    66.Spicer, E. et al. Causes of preweaning mortality on a large intensive piggery. Aus. Vet. J. 63, 71–75 (1986).CAS 
    Article 

    Google Scholar 
    67.Hendrix, W. F., Kelley, K. W., Gaskins, C. T. & Hinrichs, D. J. Porcine neonatal survival and serum gamma globulins. J. Anim. Sci. 47, 1281–1286 (1978).CAS 
    PubMed 
    Article 

    Google Scholar 
    68.De Roth, L. & Downie, H. Evaluation of viability of neonatal swine. Can. Vet. J. 17, 275–279 (1976).PubMed 
    PubMed Central 

    Google Scholar 
    69.Williams, G. The question of adaptive sex ratio in outcrossed vertebrates. Proc. R. Soc. Lond. B 205, 567–580 (1979).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    70.Servanty, S., Gaillard, J.-M., Allainé, D., Brandt, S. & Baubet, E. Litter size and fetal sex ratio adjustment in a highly polytocous species: The wild boar. Behav. Ecol. 18, 427–432 (2007).Article 

    Google Scholar 
    71.Fernández-Llario, P., Carranza, J. & Mateos-Quesada, P. Sex allocation in a polygynous mammal with large litters: The wild boar. Anim. Behav. 58, 1079–1084 (1999).PubMed 
    Article 

    Google Scholar 
    72.Focardi, S., Gaillard, J.-M., Ronchi, F. & Rossi, S. Survival of wild boars in a variable environment: unexpected life-history variation in an unusual ungulate. J. Mammal. 89, 1113–1123 (2008).Article 

    Google Scholar 
    73.Gamelon, M. et al. Do age-specific survival patterns of wild boar fit current evolutionary theories of senescence?. Evolution 68, 3636–3643 (2014).PubMed 
    Article 

    Google Scholar 
    74.Saïd, S., Tolon, V., Brandt, S. & Baubet, E. Sex effect on habitat selection in response to hunting disturbance: The study of wild boar. Eur. J. Wildl. Res. 58, 107–115 (2012).Article 

    Google Scholar 
    75.Caro, T. The adaptive significance of coloration in mammals. BioSci. 55, 125–136 (2005).Article 

    Google Scholar 
    76.Tewes, M. E., Mock, J. M. & Young, J. H. Bobcat predation on quail, birds, and mesomammals. In Proc. Nat. Quail Symp. 65–70. (2002).77.Jones, M. P., Pierce, K. E. Jr. & Ward, D. Avian vision: a review of form and function with special consideration to birds of prey. J. Ex. Pet Med. 16, 69–87 (2007).Article 

    Google Scholar 
    78.Walsberg, G. E. Coat color and solar heat gain in animals. BioSci. 33, 88–91 (1983).Article 

    Google Scholar 
    79.Lack, D. The Natural Regulation of Animal Numbers. (ed. Lack, D.) 343 (Oxford University Press, 1954).80.Stearns, S. C. Life-history tactics: A review of the ideas. Q. Rev. Biol. 51, 3–47 (1976).CAS 
    PubMed 
    Article 

    Google Scholar 
    81.Gamelon, M. et al. The relationship between phenotypic variation among offspring and mother body mass in wild boar: Evidence of coin-flipping?. J. Anim. Ecol. 82, 937–945 (2013).PubMed 
    Article 

    Google Scholar 
    82.Mitchell, G. & Stevens, C. Primiparous and multiparous monkey mothers in a mildly stressful social situation: First three months. Dev. Psychobiol. J. Int. Soc. Dev. Psychobiol. 1, 280–286 (1968).Article 

    Google Scholar 
    83.Okai, D., Aherne, F. & Hardin, R. Effects of sow nutrition in late gestation on the body composition and survival of the neonatal pig. Can. J. Anim. Sci. 57, 439–448 (1977).CAS 
    Article 

    Google Scholar  More

  • in

    Thermally tolerant intertidal triplefin fish (Tripterygiidae) sustain ATP dynamics better than subtidal species under acute heat stress

    1.Somero, G. N. Thermal physiology and vertical zonation of intertidal animals: Optima, limits, and costs of living. Integr. Comp. Biol. 42(4), 780–789 (2002).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    2.Hochachka, P. W. & Somero, G. N. Biochemical Adaptation: Mechanism and Process in Physiological Evolution (Oxford University Press, 2002).
    Google Scholar 
    3.Helmuth, B. et al. Living on the Edge of Two Changing Worlds: Forecasting the Responses of Rocky Intertidal Ecosystems to Climate Change Vol. 37 (ECU Publications, 2006).
    Google Scholar 
    4.Harley, C. D. et al. The impacts of climate change in coastal marine systems. Ecol. Lett. 9(2), 228–241 (2006).ADS 
    MathSciNet 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    5.Woodward, A. Climate change: Disruption, risk and opportunity. Glob. Transit. 1, 44–49 (2019).Article 

    Google Scholar 
    6.Hoffmann, K. H. 6—Metabolic and enzyme adaptation to temperature and pressure. In The Mollusca (ed. Hochachka, P. W.) 219–255 (Academic Press, 1983).
    Google Scholar 
    7.Pörtner, H. O. & Knust, R. Climate change affects marine fishes through the oxygen limitation of thermal tolerance. Science 315(5808), 95 (2007).ADS 
    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    8.Pörtner, H.-O., Bock, C. & Mark, F. C. Oxygen- and capacity-limited thermal tolerance: Bridging ecology and physiology. J. Exp. Biol. 220(15), 2685–2696 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    9.Pörtner, H. Climate change and temperature-dependent biogeography: Oxygen limitation of thermal tolerance in animals. Naturwissenschaften 88(4), 137–146 (2001).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    10.Verberk, W. C. et al. Does oxygen limit thermal tolerance in arthropods? A critical review of current evidence. Comp. Biochem. Physiol. A Mol. Integr. Physiol. 192, 64–78 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    11.Jutfelt, F. et al. Oxygen- and capacity-limited thermal tolerance: Blurring ecology and physiology. J. Exp. Biol. 221(1), jeb169615 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    12.Ern, R. et al. Some like it hot: Thermal tolerance and oxygen supply capacity in two eurythermal crustaceans. Sci. Rep. 5, 10743 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    13.Mitchell, P. et al. Regulation of Metabolic Processes in Mitochondria (Elsevier, 1966).
    Google Scholar 
    14.Hüttemann, M. et al. Regulation of oxidative phosphorylation, the mitochondrial membrane potential, and their role in human disease. J. Bioenerg. Biomembr. 40(5), 445 (2008).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    15.Iftikar, F. I. & Hickey, A. J. Do mitochondria limit hot fish hearts? Understanding the role of mitochondrial function with heat stress in Notolabrus celidotus. PLoS One 8(5), e64120 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    16.Schulte, P. M. The effects of temperature on aerobic metabolism: Towards a mechanistic understanding of the responses of ectotherms to a changing environment. J. Exp. Biol. 218(Pt 12), 1856–1866 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    17.Power, A. et al. Uncoupling of oxidative phosphorylation and ATP synthase reversal within the hyperthermic heart. Physiol. Rep. 2(9), e12138 (2014).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    18.Lemieux, H., Blier, P. U. & Gnaiger, E. Remodeling pathway control of mitochondrial respiratory capacity by temperature in mouse heart: Electron flow through the Q-junction in permeabilized fibers. Sci. Rep. 7(1), 2840 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    19.Christen, F. et al. Thermal tolerance and thermal sensitivity of heart mitochondria: Mitochondrial integrity and ROS production. Free Radic. Biol. Med. 116, 11–18 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    20.Kiyatkin, E. A. Brain hyperthermia as physiological and pathological phenomena. Brain Res. Brain Res. Rev. 50(1), 27–56 (2005).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    21.Kiyatkin, E. A. Brain temperature homeostasis: Physiological fluctuations and pathological shifts. Front. Biosci. (Landmark Ed) 15, 73–92 (2010).CAS 
    Article 

    Google Scholar 
    22.Wang, H. et al. Brain temperature and its fundamental properties: A review for clinical neuroscientists. Front. Neurosci.-switz 8, 307–307 (2014).
    Google Scholar 
    23.Pellerin, L. & Magistretti, P. J. How to balance the brain energy budget while spending glucose differently. J. Physiol. 546(Pt 2), 325–325 (2003).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    24.Zhao, Y. & Boulant, J. A. Temperature effects on neuronal membrane potentials and inward currents in rat hypothalamic tissue slices. J. Physiol. 564(Pt 1), 245–257 (2005).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    25.Obel, L. F. et al. Brain glycogen-new perspectives on its metabolic function and regulation at the subcellular level. Front. Neuroenergetics 4, 3 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    26.White, M. G. et al. Mitochondrial dysfunction induced by heat stress in cultured rat CNS neurons. J. Neurophysiol. 108(8), 2203–2214 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    27.Walter, E. J. & Carraretto, M. The neurological and cognitive consequences of hyperthermia. Crit. Care (London, England) 20(1), 199–199 (2016).Article 

    Google Scholar 
    28.Vornanen, M. & Paajanen, V. Seasonal changes in glycogen content and Na+-K+-ATPase activity in the brain of crucian carp. Am. J. Physiol. Regul. Integr. Comp. Physiol. 291(5), R1482–R1489 (2006).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    29.Hochachka, P. W. et al. Unifying theory of hypoxia tolerance: Molecular/metabolic defense and rescue mechanisms for surviving oxygen lack. Proc. Natl. Acad. Sci. U. S. A. 93(18), 9493–9498 (1996).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    30.Chung, D. J., Bryant, H. J. & Schulte, P. M. Thermal acclimation and subspecies-specific effects on heart and brain mitochondrial performance in a eurythermal teleost (Fundulus heteroclitus). J. Exp. Biol. 220(8), 1459–1471 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    31.Brahim, A., Mustapha, N. & Marshall, D. J. Non-reversible and reversible heat tolerance plasticity in tropical intertidal animals: Responding to habitat temperature heterogeneity. Front. Physiol. 9, 1909–1909 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    32.Pagel, M. Inferring evolutionary processes from phylogenies. Zool. Scr. 26(4), 331–348 (1997).Article 

    Google Scholar 
    33.Hilton, Z., Clements, K. D. & Hickey, A. J. Temperature sensitivity of cardiac mitochondria in intertidal and subtidal triplefin fishes. J. Comp. Physiol. B 180(7), 979–990 (2010).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    34.McArley, T. J., Hickey, A. J. R. & Herbert, N. A. Hyperoxia increases maximum oxygen consumption and aerobic scope of intertidal fish facing acutely high temperatures. J. Exp. Biol. 221(22), 189993 (2018).Article 

    Google Scholar 
    35.Gout, E. et al. Interplay of Mg2+, ADP, and ATP in the cytosol and mitochondria: Unravelling the role of Mg2+ in cell respiration. Proc. Natl. Acad. Sci. U. S. A. 111(43), E4560–E4567 (2014).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    36.Pham, T. et al. Mitochondrial inefficiencies and anoxic ATP hydrolysis capacities in diabetic rat heart. Am. J. Physiol. Cell Physiol. 307(6), C499-507 (2014).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    37.Masson, S. W. C. et al. Mitochondrial glycerol 3-phosphate facilitates bumblebee pre-flight thermogenesis. Sci. Rep. 7(1), 13107 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    38.Chinopoulos, C. et al. A novel kinetic assay of mitochondrial ATP-ADP exchange rate mediated by the ANT. Biophys. J. 96(6), 2490–2504 (2009).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    39.Devaux, J. B. L. et al. Acidosis maintains the function of brain mitochondria in hypoxia-tolerant triplefin fish: A strategy to survive acute hypoxic exposure? Front. Physiol. 9, 1941 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    40.Goo, S. et al. Multiscale measurement of cardiac energetics. Clin. Exp. Pharmacol. Physiol. 40(9), 671–681 (2013).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    41.Lagerspetz, K. Y. Temperature effects on different organization levels in animals. Symp. Soc. Exp. Biol. 41, 429–449 (1987).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    42.Rosenthal, J. J. & Bezanilla, F. A comparison of propagated action potentials from tropical and temperate squid axons: Different durations and conduction velocities correlate with ionic conductance levels. J. Exp. Biol. 205(Pt 12), 1819–1830 (2002).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Robertson, R. M. Thermal stress and neural function: Adaptive mechanisms in insect model systems. J. Therm. Biol. 29(7), 351–358 (2004).CAS 
    Article 

    Google Scholar 
    44.Miller, N. A. & Stillman, J. H. Neural thermal performance in porcelain crabs, Genus Petrolisthes. Physiol. Biochem. Zool. 85(1), 29–39 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    45.Gladwell, R. T., Bowler, K. & Duncan, C. J. Heat death in the crayfish Austropotamobius pallipes—Ion movements and their effects on excitable tissues during heat death. J. Therm. Biol. 1(2), 79–94 (1976).CAS 
    Article 

    Google Scholar 
    46.Chen, I. & Lui, F. Neuroanatomy, Neuron Action Potential (StatPearls Publishing, 2019).
    Google Scholar 
    47.Milligan, L. P. & McBride, B. W. Energy costs of ion pumping by animal tissues. J. Nutr. 115(10), 1374–1382 (1985).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    48.Buzatu, S. The temperature-induced changes in membrane potential. Riv. Biol. 102(2), 199–217 (2009).PubMed 
    PubMed Central 

    Google Scholar 
    49.Krans, J. L., Rivlin, P. K. & Hoy, R. R. Demonstrating the temperature sensitivity of synaptic transmission in a Drosophila mutant. J. Undergrad. Neurosci. Educ. 4(1), A27–A33 (2005).PubMed 
    PubMed Central 

    Google Scholar 
    50.Khan, J. R. et al. Thermal plasticity of skeletal muscle mitochondrial activity and whole animal respiration in a common intertidal triplefin fish, Forsterygion lapillum (Family: Tripterygiidae). J. Comp. Physiol. B 184(8), 991–1001 (2014).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    51.McArley, T. et al. Intertidal triplefin fishes have a lower critical oxygen tension (Pcrit), higher maximal aerobic capacity, and higher tissue glycogen stores than their subtidal counterparts. J. Comp. Physiol. B. 189, 399–411 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    52.Pfleger, J., He, M. & Abdellatif, M. Mitochondrial complex II is a source of the reserve respiratory capacity that is regulated by metabolic sensors and promotes cell survival. Cell Death Dis. 6(7), e1835–e1835 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    53.Brand, M. D. The efficiency and plasticity of mitochondrial energy transduction. Biochem. Soc. Trans. 33(Pt 5), 897–904 (2005).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    54.Brown, J. H. et al. Toward a metabolic theory of ecology. Ecology 85(7), 1771–1789 (2004).ADS 
    Article 

    Google Scholar 
    55.Salin, K. et al. Variation in the link between oxygen consumption and ATP production, and its relevance for animal performance. Proc. Biol. Sci. 2015(282), 20151028–20151028 (1812).
    Google Scholar 
    56.Findly, R. C., Gillies, R. J. & Shulman, R. G. In vivo phosphorus-31 nuclear magnetic resonance reveals lowered ATP during heat shock of Tetrahymena. Science 219(4589), 1223 (1983).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    57.Sharma, H. S. Neurobiology of Hyperthermia (Elsevier, 2011).
    Google Scholar 
    58.Salin, K. et al. Simultaneous measurement of mitochondrial respiration and ATP production in tissue homogenates and calculation of effective P/O ratios. Physiol. Rep. 4(20), e13007 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    59.Hinkle, P. C. P/O ratios of mitochondrial oxidative phosphorylation. Biochim. Biophys. Acta BBA Bioenerg. 1706(1), 1–11 (2005).CAS 

    Google Scholar  More

  • in

    Parental morph combination does not influence innate immune function in nestlings of a colour-polymorphic African raptor

    1.Lindström, J. Early development and fitness in birds and mammals. Trends Ecol. Evol. 14, 343–348 (1999).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    2.Cam, E. & Aubry, L. Early development, recruitment and life history trajectory in long-lived birds. J. Ornithol. 152, 187–201 (2011).Article 

    Google Scholar 
    3.Cam, E., Monnat, J. Y. & Hines, J. E. Long-term fitness consequences of early conditions in the kittiwake. J. Anim. Ecol. 72, 411–424 (2003).Article 

    Google Scholar 
    4.Tilgar, V., Mänd, R., Kilgas, P. & Mägi, M. Long-term consequences of early ontogeny in free-living Great Tits Parus major. J. Ornithol. 151, 61–68 (2010).Article 

    Google Scholar 
    5.Stamps, J. A. The silver spoon effect and habitat selection by natal dispersers. Ecol. Lett. 9, 1179–1185 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    6.Briga, M., Koetsier, E., Boonekamp, J. J., Jimeno, B. & Verhulst, S. Food availability affects adult survival trajectories depending on early developmental conditions. Proc. R. Soc. B Biol. Sci. 284, 20162287 (2017).Article 

    Google Scholar 
    7.Cooper, E. B. & Kruuk, L. E. Ageing with a silver-spoon: A meta-analysis of the effect of developmental environment on senescence. Evol. Lett. 2, 460–471 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    8.Song, Z. et al. Silver spoon effects of hatching order in an asynchronous hatching bird. Behav. Ecol. Sociobiol. 30, 509–517 (2019).Article 

    Google Scholar 
    9.Descamps, S., Boutin, S., Berteaux, D., McAdam, A. G. & Gaillard, J. M. Cohort effects in red squirrels: The influence of density, food abundance and temperature on future survival and reproductive success. J. Anim. Ecol. 77, 305–314 (2008).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    10.Van De Pol, M., Bruinzeel, L. W., Heg, D., Van Der Jeugd, H. P. & Verhulst, S. A silver spoon for a golden future: Long-term effects of natal origin on fitness prospects of oystercatchers (Haematopus ostralegus). J. Anim. Ecol. 75, 616–626 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    11.Murgatroyd, M. et al. Sex-specific patterns of reproductive senescence in a long-lived reintroduced raptor. J. Anim. Ecol. 87, 1587–1599 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    12.Dmitriew, C. & Rowe, L. Effects of early resource limitation and compensatory growth on lifetime fitness in the ladybird beetle (Harmonia axyridis). J. Evol. Biol. 20, 1298–1310 (2007).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Hopwood, P. E., Moore, A. J. & Royle, N. J. Effects of resource variation during early life and adult social environment on contest outcomes in burying beetles: A context-dependent silver spoon strategy?. Proc. R. Soc. B Biol. Sci. 281, 20133102 (2014).Article 

    Google Scholar 
    14.Royle, N. J., Lindström, J. & Metcalfe, N. B. A poor start in life negatively affects dominance status in adulthood independent of body size in green swordtails Xiphophorus helleri. Proc. R. Soc. B Biol. Sci. 272, 1917–1922 (2005).Article 

    Google Scholar 
    15.Mugabo, M., Marquis, O., Perret, S. & Le Galliard, J. F. Immediate and delayed life history effects caused by food deprivation early in life in a short-lived lizard. J. Evol. Biol. 23, 1886–1898 (2010).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    16.Vitikainen, E. I., Thompson, F. J., Marshall, H. H. & Cant, M. A. Live long and prosper: Durable benefits of early-life care in banded mongooses. Philos. Trans. R. Soc. B Biol. Sci. 374, 20180114 (2019).Article 

    Google Scholar 
    17.Sumasgutner, P., Tate, G. J., Koeslag, A. & Amar, A. Family morph matters: Factors determining survival and recruitment in a long-lived polymorphic raptor. J. Anim. Ecol. 85, 1043–1055 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    18.Emaresi, G. et al. Melanin-specific life-history strategies. Am. Nat. 183, 269–280 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    19.Grunst, M. L. et al. Actuarial senescence in a dimorphic bird: Different rates of ageing in morphs with discrete reproductive strategies. Proc. R. Soc. B Biol. Sci. 285, 20182053 (2018).Article 

    Google Scholar 
    20.Nebel, C., Sumasgutner, P., McPherson, S. C., Tate, G. J. & Amar, A. Contrasting parental color-morphs increase regularity of prey deliveries in an African raptor. Behav. Ecol. 31, 1142–1149 (2020).Article 

    Google Scholar 
    21.Morosinotto, C. et al. Fledging mass is color morph specific and affects local recruitment in a wild bird. Am. Nat. 196, 609–619 (2020).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.Chakarov, N., Boerner, M. & Krüger, O. Fitness in common buzzards at the cross-point of opposite melanin–parasite interactions. Funct. Ecol. 22, 1062–1069 (2008).Article 

    Google Scholar 
    23.Roulin, A. Proximate basis of the covariation between a melanin-based female ornament and offspring quality. Oecologia 140, 668–675 (2004).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    24.Rödel, H. G., Von Holst, D. & Kraus, C. Family legacies: short-and long-term fitness consequences of early-life conditions in female European rabbits. J. Anim. Ecol. 78, 789–797 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    25.Clutton-Brock, T. H. The Evolution of Parental Care (Princeton University Press, 1991).Book 

    Google Scholar 
    26.Cockburn, A. Prevalence of different modes of parental care in birds. Proc. R. Soc. B Biol. Sci. 273, 1375–1383 (2006).Article 

    Google Scholar 
    27.Norris, K. & Evans, M. R. Ecological immunology: Life history trade-offs and immune defense in birds. Behav. Ecol. Sociobiol. 11, 19–26 (2000).Article 

    Google Scholar 
    28.van der Most, P. J., de Jong, B., Parmentier, H. K. & Verhulst, S. Trade-off between growth and immune function: A meta-analysis of selection experiments. Funct. Ecol. 25, 74–80 (2011).Article 

    Google Scholar 
    29.Aastrup, C. & Hegemann, A. Jackdaw nestlings rapidly increase innate immune function during the nestling phase but no evidence for a trade-off with growth. Dev. Comparat. Immunol. 2, 103967 (2020).
    Google Scholar 
    30.Ratikainen, I. I. & Kokko, H. Differential allocation and compensation: Who deserves the silver spoon?. Behav. Ecol. Sociobiol. 21, 195–200 (2010).Article 

    Google Scholar 
    31.Limbourg, T., Mateman, A. C. & Lessells, C. M. Opposite differential allocation by males and females of the same species. Biol. Let. 9, 20120835 (2013).Article 

    Google Scholar 
    32.Järvistö, P. E., Calhim, S., Schuett, W., Velmala, W. & Laaksonen, T. Foster, but not genetic, father plumage coloration has a temperature-dependent effect on offspring quality. Behav. Ecol. Sociobiol. 69, 335–346 (2015).Article 

    Google Scholar 
    33.Pryke, S. R. & Griffith, S. C. Socially mediated trade-offs between aggression and parental effort in competing color morphs. Am. Nat. 174, 455–464 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    34.Amar, A., Koeslag, A. & Curtis, O. Plumage polymorphism in a newly colonized black sparrowhawk population: Classification, temporal stability and inheritance patterns. J. Zool. 289, 60–67 (2013).Article 

    Google Scholar 
    35.Tate, G., Sumasgutner, P., Koeslag, A. & Amar, A. Pair complementarity influences reproductive output in the polymorphic black sparrowhawk Accipiter melanoleucus. J. Avian Biol. 48, 387–398 (2017).Article 

    Google Scholar 
    36.Tinbergen, J. M. & Boerlijst, M. C. Nestling weight and survival in individual great tits (Parus major). J. Anim. Ecol. 59, 1113–1127 (1990).Article 

    Google Scholar 
    37.Cleasby, I. R., Nakagawa, S., Gillespie, D. O. S. & Burke, T. The influence of sex and body size on nestling survival and recruitment in the house sparrow. Biol. J. Lin. Soc. 101, 680–688 (2010).Article 

    Google Scholar 
    38.Christe, P., Møller, A. P. & de Lope, F. Immunocompetence and nestling survival in the house martin: The tasty chick hypothesis. Oikos 83, 175–179 (1998).CAS 
    Article 

    Google Scholar 
    39.Ringsby, T. H., Sæther, B.-E. & Solberg, E. J. Factors affecting juvenile survival in house sparrow Passer domesticus. J. Avian Biol. 29, 241–247 (1998).Article 

    Google Scholar 
    40.Losdat, S. et al. Nestling erythrocyte resistance to oxidative stress predicts fledging success but not local recruitment in a wild bird. Biol. Lett. 9, 20120888 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    41.Vermeulen, A., Müller, W. & Eens, M. J. Vitally important–does early innate immunity predict recruitment and adult innate immunity?. Ecol. Evol. 6, 1799–1808 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    42.Vennum, C. R. et al. Early life conditions and immune defense in nestling Swainson’s Hawks. Physiol. Biochem. Zool. 92, 419–429 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Bowers, E. K. et al. Neonatal body condition, immune responsiveness, and hematocrit predict longevity in a wild bird population. Ecology 95, 3027–3034 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    44.Calder, P. C. & Sonnenfeld, G. in Nutrition, Immunity, and Infection 1–18 (CRC Press, 2017).Book 

    Google Scholar 
    45.Wilcoxen, T. E., Boughton, R. K. & Schoech, S. J. Selection on innate immunity and body condition in Florida scrub-jays throughout an epidemic. Biol. Let. 6, 552–554 (2010).Article 

    Google Scholar 
    46.Hegemann, A., Marra, P. P. & Tieleman, B. I. Causes and consequences of partial migration in a passerine bird. Am. Nat. 186, 531–546 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    47.Hegemann, A., Matson, K. D., Flinks, H. & Tieleman, B. I. Offspring pay sooner, parents pay later: Experimental manipulation of body mass reveals trade-offs between immune function, reproduction and survival. Front. Zool. 10, 77 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    48.Apanius, V. Ontogeny of Immune Function (Oxford University Press, 1998).
    Google Scholar 
    49.Klasing, K. C. & Leshchinksy, T. V. Functions, Costs, and Benefits of the Immune System During Development and Growth Ostrich, 69, 2817–2835 (1999).50.Bonneaud, C. et al. Assessing the cost of mounting an immune response. Am. Nat. 161, 367–379 (2003).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    51.Costantini, D. & Moller, A. P. Does immune response cause oxidative stress in birds? A meta-analysis. Comparat. Biochem. Physiol. Part A 153, 339–344 (2009).Article 
    CAS 

    Google Scholar 
    52.Hanssen, S. A., Hasselquist, D., Folstad, I. & Erikstad, K. E. Costs of immunity: Immune responsiveness reduces survival in a vertebrate. Proc. R. Soc. Lond. Ser. B Biol. Sci. 271, 925–930 (2004).Article 

    Google Scholar 
    53.Hanssen, S. A. Costs of an immune challenge and terminal investment in a long-lived bird. Ecology 87, 2440–2446 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    54.Matson, K. D., Ricklefs, R. E. & Klasing, K. C. A hemolysis–hemagglutination assay for characterizing constitutive innate humoral immunity in wild and domestic birds. Dev. Comp. Immunol. 29, 275–286 (2005).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    55.Müller-Eberhard, H. J. Molecular organization and function of the complement system. Annu. Rev. Biochem. 57, 321–347 (1988).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    56.Dobryszycka, W. Biological functions of haptoglobin-new pieces to an old puzzle. Eur. J. Clin. Chem. Clin. Biochem. 35, 647–654 (1997).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    57.Matson, K. D., Horrocks, N. P. C., Versteegh, M. A. & Tieleman, B. I. Baseline haptoglobin concentrations are repeatable and predictive of certain aspects of a subsequent experimentally-induced inflammatory response. Comparat. Biochem. Physiol. Part A Mol. Integr. Physiol. 162, 7–15 (2012).CAS 
    Article 

    Google Scholar 
    58.Cray, C., Zaias, J. & Altman, N. H. Acute phase response in animals: A review. Comp. Med. 59, 517–526 (2009).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    59.Hegemann, A., Matson, K. D., Both, C. & Tieleman, B. I. Immune function in a free-living bird varies over the annual cycle, but seasonal patterns differ between years. Oecologia 170, 605–618 (2012).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    60.Alexander, C. & Rietschel, E. T. Invited review: Bacterial lipopolysaccharides and innate immunity. J. Endotoxin Res. 7, 167–202 (2016).
    Google Scholar 
    61.Hegemann, A., Matson, K. D., Versteegh, M. A., Villegas, A. & Tieleman, B. I. Immune response to an endotoxin challenge involves multiple immune parameters and is consistent among the annual-cycle stages of a free-living temperate zone bird. J. Exp. Biol. 216, 2573–2580 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    62.Vermeulen, A., Eens, M., Zaid, E. & Müller, W. Baseline innate immunity does not affect the response to an immune challenge in female great tits (Parus major). Behav. Ecol. Sociobiol. 70, 585–592 (2016).Article 

    Google Scholar 
    63.Vinterstare, J., Hegemann, A., Nilsson, P. A., Hulthén, K. & Brönmark, C. Defence versus defence: Are crucian carp trading off immune function against predator-induced morphology?. J. Anim. Ecol. 88, 1510–1521 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    64.Lei, B., Amar, A., Koeslag, A., Gous, T. A. & Tate, G. J. Differential haemoparasite intensity between black sparrowhawk (Accipiter melanoleucus) morphs suggests an adaptive function for polymorphism. PLoS ONE 8, e81607 (2013).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    65.Suri, J., Sumasgutner, P., Hellard, É., Koeslag, A. & Amar, A. Stability in prey abundance may buffer Black Sparrowhawks Accipiter melanoleucus from health impacts of urbanization. Ibis 159, 38–54 (2017).Article 

    Google Scholar 
    66.Råberg, L., Grahn, M., Hasselquist, D. & Svensson, E. On the adaptive significance of stress-induced immunosuppression. Proc. R. Soc. Lond. Ser. B Biol. Sci. 265, 1637–1641 (1998).Article 

    Google Scholar 
    67.Sadd, B. M. & Siva-Jothy, M. T. Self-harm caused by an insect’s innate immunity. Proc. R. Soc. Lond. Ser. B Biol. Sci. 273, 2571–2574 (2006).
    Google Scholar 
    68.Gyan, B. et al. Elevated levels of nitric oxide and low levels of haptoglobin are associated with severe malarial anaemia in African children. Acta Trop. 83, 133–140 (2002).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    69.Alonso-Alvarez, C. & Tella, J. L. Effects of experimental food restriction and body-mass changes on the avian T-cell-mediated immune response. Can. J. Zool. 79, 101–105 (2001).Article 

    Google Scholar 
    70.Merino, S. et al. Phytohaemagglutinin injection assay and physiological stress in nestling house martins. Anim. Behav. 58, 219–222 (1999).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    71.Ochsenbein, A. F. & Zinkernagel, R. M. Natural antibodies and complement link innate and acquired immunity. Immunol. Today 21, 624–630 (2000).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    72.Boes, M. Role of natural and immune IgM antibodies in immune responses. Mol. Immunol. 37, 1141–1149 (2000).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    73.Grönwall, C., Vas, J. & Silverman, G. J. Protective roles of natural IgM antibodies. Front. Immunol. 3, 66 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    74.Martin, L. B., Weil, Z. M. & Nelson, R. J. Seasonal changes in vertebrate immune activity: Mediation by physiological trade-offs. Philos. Trans. R. Soc. B Biol. Sci. 363, 321–339 (2008).Article 

    Google Scholar 
    75.Klasing, K. C. The costs of immunity. Acta Zool. Sin. 50, 961–969 (2004).CAS 

    Google Scholar 
    76.Van Noordwijk, A. J. & de Jong, G. Acquisition and allocation of resources: Their influence on variation in life history tactics. Am. Nat. 128, 137–142 (1986).Article 

    Google Scholar 
    77.Glazier, D. S. Trade-offs between reproductive and somatic (storage) investments in animals: A comparative test of the Van Noordwijk and De Jong model. Evol. Ecol. 13, 539–555 (1999).Article 

    Google Scholar 
    78.Newton, I., McGrady, M. J. & Oli, M. K. A review of survival estimates for raptors and owls. Ibis 158, 227–248 (2016).Article 

    Google Scholar 
    79.Kennedy, P. L. & Ward, J. M. Effects of experimental food supplementation on movements of juvenile northern goshawks (Accipiter gentilis atricapillus). Oecologia 134, 284–291 (2003).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    80.Terraube, J., Vasko, V. & Korpimäki, E. Mechanisms and reproductive consequences of breeding dispersal in a specialist predator under temporally varying food conditions. Oikos 124, 762–771 (2015).Article 

    Google Scholar 
    81.Delgado, M. D. M., Penteriani, V. & Nams, V. O. How fledglings explore surroundings from fledging to dispersal. A case study with Eagle Owls Bubo bubo. Ardea 97, 7–15 (2009).Article 

    Google Scholar 
    82.Rosenfield, R. N. et al. Body mass of female Cooper’s Hawks is unrelated to longevity and breeding dispersal: Implications for the study of breeding dispersal. J. Raptor Res. 50, 305–312 (2016).Article 

    Google Scholar 
    83.Klein, S. L. Hormonal and immunological mechanisms mediating sex differences in parasite infection. Parasite Immunol. 26, 247–264 (2004).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    84.Klein, S. L. & Flanagan, K. L. Sex differences in immune responses. Nat. Rev. Immunol. 16, 626 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    85.Zuk, M. Reproductive strategies and disease susceptibility: An evolutionary viewpoint. Parasitol. Today 6, 231–233 (1990).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    86.Zuk, M. & McKean, K. A. Sex differences in parasite infections: patterns and processes. Int. J. Parasitol. 26, 1009–1024 (1996).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    87.Alexander, J. & Stimson, W. H. Sex hormones and the course of parasitic infection. Parasitol. Today 4, 189–193 (1988).Article 

    Google Scholar 
    88.Roulin, A. et al. Which chick is tasty to parasites? The importance of host immunology vs. parasite life history. J. Anim. Ecol. 72, 75–81 (2003).Article 

    Google Scholar 
    89.Hockey, P. A. R., Dean, W. R. J., Ryan, P. G., Maree, S. & Brickman, B. M. Roberts’ Birds of Southern Africa 7th edn. (John Voelcker Bird Book Fund, 2005).
    Google Scholar 
    90.Christie, D. A. & Ferguson-Lees, J. Raptors of the World (Christopher Helm Publishers, 2010).
    Google Scholar 
    91.Martin, R. O. et al. Phenological shifts assist colonisation of a novel environment in a range-expanding raptor. Oikos 123, 1457–1468 (2014).Article 

    Google Scholar 
    92.Rose, S., Sumasgutner, P., Koeslag, A. & Amar, A. Does seasonal decline in breeding performance differ for an African raptor across an urbanization gradient?. Front. Ecol. Evol. 5, 47 (2017).Article 

    Google Scholar 
    93.Horrocks, N. P. et al. Immune indexes of larks from desert and temperate regions show weak associations with life history but stronger links to environmental variation in microbial abundance. Physiol. Biochem. Zool. 85, 504–515 (2012).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    94.Horrocks, N. P. et al. Environmental proxies of antigen exposure explain variation in immune investment better than indices of pace of life. Oecologia 177, 281–290 (2015).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    95.Sergio, F., Blas, J., Forero, M. G., Donázar, J. A. & Hiraldo, F. Sequential settlement and site dependence in a migratory raptor. Behav. Ecol. Sociobiol. 18, 811–821 (2007).Article 

    Google Scholar 
    96.Rose, S., Thomson, R. L., Oschadleus, H.-D. & Lee, A. T. Summarising biometrics from the SAFRING database for southern African birds. Ostrich 2, 1–5 (2019).
    Google Scholar 
    97.Paijmans, D. M., Rose, S., Oschadleus, H.-D. & Thomson, R. L. SAFRING ringing report for 2017. Biodivers. Observ. 10, 1–11 (2019).
    Google Scholar 
    98.Katzenberger, J., Tate, G., Koeslag, A. & Amar, A. Black Sparrowhawk brooding behaviour in relation to chick age and weather variation in the recently colonised Cape Peninsula, South Africa. J. Ornithol. 156, 903–913 (2015).Article 

    Google Scholar 
    99.Buehler, D. M. et al. Constitutive immune function responds more slowly to handling stress than corticosterone in a shorebird. Physiol. Biochem. Zool. 81, 673–681 (2008).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    100.Zylberberg, M. Common measures of immune function vary with time of day and sampling protocol in five passerine species. J Exp Biol 218, 757–766 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    101.van de Crommenacker, J. et al. Effects of immune supplementation and immune challenge on oxidative status and physiology in a model bird: Implications for ecologists. J. Exp. Biol. 213, 3527–3535 (2010).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    102.French, S. S. & Neuman-Lee, L. A. Improved ex vivo method for microbiocidal activity across vertebrate species. Biol. Open 1, 482–487 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    103.Eikenaar, C. & Hegemann, A. Migratory common blackbirds have lower innate immune function during autumn migration than resident conspecifics. Biol. Let. 12, 20160078 (2016).Article 
    CAS 

    Google Scholar 
    104.Hegemann, A., Pardal, S. & Matson, K. D. Indices of immune function used by ecologists are mostly unaffected by repeated freeze-thaw cycles and methodological deviations. Front. Zool. 14, 43 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    105.R Core Team. R: A language and environment for statistical computing. Vienna, Austria (R Foundation for Statistical Computing, 2019).106.Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: Tests in linear mixed effects models. J. Stat. Softw. 82, 2 (2017).Article 

    Google Scholar 
    107.McCurdy, D. G., Shutler, D., Mullie, A. & Forbes, M. R. Sex-biased parasitism of avian hosts: relations to blood parasite taxon and mating system. Oikos 82, 303–312 (1998).CAS 
    Article 

    Google Scholar 
    108.Parejo, D., Silva, N. & Avilés, J. M. Within-brood size differences affect innate and acquired immunity in roller Coracias garrulus nestlings. J. Avian Biol. 38, 717–725 (2007).Article 

    Google Scholar 
    109.Kanikowska, D., Hyun, K. J., Tokura, H., Azama, T. & Nishimura, S. Circadian rhythm of acute phase proteins under the influence of bright/dim light during the daytime. Chronobiol. Int. 22, 137–143 (2005).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    110.Laake, J. L. RMark: an R interface for analysis of capture-recapture data with MARK. AFSC Processed Rep 2013-01, Seattle, WA (Alaska Fish. Sci. Cent., NOAA, Natl. Mar. Fish. Serv., 2013).111.White, G. C. & Burnham, K. P. Program MARK: Survival estimation from populations of marked animals. Bird Study 46, S120–S139 (1999).Article 

    Google Scholar 
    112.Burnham, K. P. Design and Analysis Methods for Fish Survival Experiments Based on Release-Recapture (American Fisheries Society, 1987).
    Google Scholar 
    113.Coquet, R., Lebreton, J.-D., Gimenez, O. & Reboulet, A.-M. U-CARE: Utilities for performing goodness of fit tests and manipulating CApture-REcapture data. Ecography 32, 1071–1074 (2009).Article 

    Google Scholar 
    114.Sauer, J. R. & Byron, K. W. Generalized procedures for testing hypotheses about survival or recovery raes. J. Wildl. Manag. 53, 137–142 (1989).Article 

    Google Scholar 
    115.Nebel, C., Amar, A., Hegemann, A., Isaksson, C. & Sumasgutner, P. Parental morph combination does not influence innate immune function in nestlings of a colour-polymorphic African raptor: Data, Zivahub, https://doi.org/10.25375/uct.12780803 (2021). More

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    Arbuscular mycorrhizal trees influence the latitudinal beta-diversity gradient of tree communities in forests worldwide

    1.Myers, J. A. & LaManna, J. A. The promise and pitfalls of beta-diversity in ecology and conservation. J. Veg. Sci. 27, 1081–1083 (2016).Article 

    Google Scholar 
    2.Socolar, J. B., Gilroy, J. J., Kunin, W. E. & Edwards, D. P. How should beta-diversity inform biodiversity conservation? Trends Ecol. Evol. 31, 67–80 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    3.Xing, D. L. & He, F. L. Environmental filtering explains a U-shape latitudinal pattern in regional beta-deviation for eastern North American trees. Ecol. Lett. 22, 284–291 (2019).PubMed 
    Article 
    PubMed Central 

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

    Google Scholar 
    5.Baselga, A. Partitioning the turnover and nestedness components of beta diversity. Glob. Ecol. Biogeogr. 19, 134–143 (2010).Article 

    Google Scholar 
    6.Menegotto, A., Dambros, C. S. & Netto, S. A. The scale-dependent effect of environmental filters on species turnover and nestedness in an estuarine benthic community. Ecology 100, e02721 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    7.Whittaker, R. H. Vegetation of the Siskiyou mountains, Oregon and California. Ecol. Monogr. 30, 279–338 (1960).Article 

    Google Scholar 
    8.Hubbell, S. P. The unified neutral theory of biodiversity and biogeography. (Princeton University Press, 2001).9.Nekola, J. C. & White, P. S. The distance decay of similarity in biogeography and ecology. J. Biogeogr. 26, 867–878 (1999).Article 

    Google Scholar 
    10.da Silva, P. G., Lobo, J. M., Hensen, M. C., Vaz-de-Mello, F. Z. & Hernandez, M. I. M. Turnover and nestedness in subtropical dung beetle assemblages along an elevational gradient. Divers Distrib. 24, 1277–1290 (2018).Article 

    Google Scholar 
    11.Wang, X. G. et al. Ecological drivers of spatial community dissimilarity, species replacement and species nestedness across temperate forests. Glob. Ecol. Biogeogr. 27, 581–592 (2018).Article 

    Google Scholar 
    12.McFadden, I. R. et al. Temperature shapes opposing latitudinal gradients of plant taxonomic and phylogenetic beta diversity. Ecol. Lett. 22, 1126–1135 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Qian, H., Chen, S., Mao, L. & Ouyang, Z. Drivers of β‐diversity along latitudinal gradients revisited. Glob. Ecol. Biogeogr. 22, 659–670 (2013).Article 

    Google Scholar 
    14.Xu, W. B., Chen, G. K., Liu, C. R. & Ma, K. P. Latitudinal differences in species abundance distributions, rather than spatial aggregation, explain beta-diversity along latitudinal gradients. Glob. Ecol. Biogeogr. 24, 1170–1180 (2015).Article 

    Google Scholar 
    15.Kraft, N. J. et al. Disentangling the drivers of β diversity along latitudinal and elevational gradients. Science 333, 1755–1758 (2011).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    16.Griffiths, D. Connectivity and vagility determine beta diversity and nestedness in North American and European freshwater fish. J. Biogeogr. 44, 1723–1733 (2017).Article 

    Google Scholar 
    17.Soininen, J., Heino, J. & Wang, J. J. A meta-analysis of nestedness and turnover components of beta diversity across organisms and ecosystems. Glob. Ecol. Biogeogr. 27, 96–109 (2018).Article 

    Google Scholar 
    18.LaManna, J. A., Belote, R. T., Burkle, L. A., Catano, C. P. & Myers, J. A. Negative density dependence mediates biodiversity-productivity relationships across scales. Nat. Ecol. Evol. 1, 1107–1115 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    19.van der Heijden, M. G. A., Martin, F. M., Selosse, M. A. & Sanders, I. R. Mycorrhizal ecology and evolution: the past, the present, and the future. New Phytol. 205, 1406–1423 (2015).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    20.Brundrett, M. C. Mycorrhizal associations and other means of nutrition of vascular plants: understanding the global diversity of host plants by resolving conflicting information and developing reliable means of diagnosis. Plant Soil 320, 37–77 (2009).CAS 
    Article 

    Google Scholar 
    21.Gibert, A., Tozer, W. & Westoby, M. Plant performance response to eight different types of symbiosis. New Phytol. 222, 526–542 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.Veresoglou, S. D., Rillig, M. C. & Johnson, D. Responsiveness of plants to mycorrhiza regulates coexistence. J. Ecol. 106, 1864–1875 (2018).Article 

    Google Scholar 
    23.Delavaux, C. S. et al. Mycorrhizal fungi influence global plant biogeography. Nat. Ecol. Evol. 3, 424–429 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    24.Barcelo, M., van Bodegom, P. M. & Soudzilovskaia, N. A. Climate drives the spatial distribution of mycorrhizal host plants in terrestrial ecosystems. J. Ecol. 107, 2564–2573 (2019).Article 

    Google Scholar 
    25.Steidinger, B. S. et al. Climatic controls of decomposition drive the global biogeography of forest-tree symbioses. Nature 571, E8–E8 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    26.Bennett, J. A. et al. Plant-soil feedbacks and mycorrhizal type influence temperate forest population dynamics. Science 355, 181–184 (2017).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    27.Johnson, D. J., Clay, K. & Phillips, R. P. Mycorrhizal associations and the spatial structure of an old-growth forest community. Oecologia 186, 195–204 (2018).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    28.Hargreaves, A. L., Germain, R. M., Bontrager, M., Persi, J. & Angert, A. L. Local adaptation to biotic interactions: a meta-analysis across latitudes. Am. Nat. 195, 395–411 (2020).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    29.Liu, X. B. et al. Partitioning of soil phosphorus among arbuscular and ectomycorrhizal trees in tropical and subtropical forests. Ecol. Lett. 21, 713–723 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    30.Jacquemyn, H., De Kort, H., Vanden Broeck, A. & Brys, R. Immigrant and extrinsic hybrid seed inviability contribute to reproductive isolation between forest and dune ecotypes of Epipactis helleborine (Orchidaceae). Oikos 127, 73–84 (2018).Article 

    Google Scholar 
    31.Osborne, O. G. et al. Arbuscular mycorrhizal fungi promote coexistence and niche divergence of sympatric palm species on a remote oceanic island. New Phytol. 217, 1254–1266 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    32.Myers, J. A. et al. Beta-diversity in temperate and tropical forests reflects dissimilar mechanisms of community assembly. Ecol. Lett. 16, 151–157 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    33.Jankowski, J. E., Ciecka, A. L., Meyer, N. Y. & Rabenold, K. N. Beta diversity along environmental gradients: implications of habitat specialization in tropical montane landscapes. J. Anim. Ecol. 78, 315–327 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    34.McCarthy-Neumann, S. & Ibáñez, I. Tree range expansion may be enhanced by escape from negative plant–soil feedbacks. Ecology 93, 2637–2649 (2012).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    35.Peay, K. G. The mutualistic niche: mycorrhizal symbiosis and community dynamics. Annu. Rev. Ecol., Evol. Syst. 47, 143–164 (2016).Article 

    Google Scholar 
    36.Wang, Z. H., Fang, J. Y., Tang, Z. Y. & Shi, L. Geographical patterns in the beta diversity of China’s woody plants: the influence of space, environment and range size. Ecography 35, 1092–1102 (2012).Article 

    Google Scholar 
    37.Liang, M. X. et al. Soil fungal networks maintain local dominance of ectomycorrhizal trees. Nat. Commun. 11, 2636 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    38.Segnitz, R. M., Russo, S. E., Davies, S. J. & Peay, K. G. Ectomycorrhizal fungi drive positive phylogenetic plant-soil feedbacks in a regionally dominant tropical plant family. Ecology 101, e03083 (2020).39.Chen, L. et al. Differential soil fungus accumulation and density dependence of trees in a subtropical forest. Science 366, 124–128 (2019).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    40.Brundrett, Mark, Murase, Gracia & K, B. Comparative anatomy of roots and mycorrhizae of common Ontario trees. Can. J. Bot. 68, 551–578 (1990).Article 

    Google Scholar 
    41.Liu, Y. & He, F. L. Incorporating the disease triangle framework for testing the effect of soil-borne pathogens on tree species diversity. Funct. Ecol. 33, 1211–1222 (2019).MathSciNet 
    Article 

    Google Scholar 
    42.LaManna, J. A. et al. Plant diversity increases with the strength of negative density dependence at the global scale. Science 356, 1389–1392 (2017).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Johnson, D. J., Beaulieu, W. T., Bever, J. D. & Clay, K. Conspecific negative density dependence and forest diversity. Science 336, 904–907 (2012).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    44.Crawford, K. M. et al. When and where plant-soil feedback may promote plant coexistence: a meta-analysis. Ecol. Lett. 22, 1274–1284 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    45.Liu, X. B., Etienne, R. S., Liang, M. X., Wang, Y. F. & Yu, S. X. Experimental evidence for an intraspecific Janzen-Connell effect mediated by soil biota. Ecology 96, 662–671 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    46.Chu, C. J. et al. Direct and indirect effects of climate on richness drive the latitudinal diversity gradient in forest trees. Ecol. Lett. 22, 245–255 (2019).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    47.Gavito, M. E. & Azcon-Aguilar, C. Temperature stress in arbuscular mycorrhizal fungi: a test for adaptation to soil temperature in three isolates of Funneliformis mosseae from different climates. Agr. Food Sci. 21, 2–11 (2012).Article 

    Google Scholar 
    48.Hetrick, B. D. & Bloom, J. The influence of temperature on colonization of winter wheat by vesicular-arbuscular mycorrhizal fungi. Mycologia 76, 953–956 (1984).Article 

    Google Scholar 
    49.Anderson-Teixeira, K. J. et al. CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change. Glob. Change Biol. 21, 528–549 (2015).ADS 
    Article 

    Google Scholar 
    50.Condit, R. Tropical forest census plots: methods and results from Barro Colorado Island, Panama and a comparison with other plots. (Springer-Verlag andRG. Landes Company, 1998).51.Stillhard, J. et al. Stand inventory data from the 10-ha forest research plot in Uholka: 15 yr of primeval beech forest development. Ecology 100, e02845 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    52.Marion, Z. H., Fordyce, J. A. & Fitzpatrick, B. M. Pairwise beta diversity resolves an underappreciated source of confusion in calculating species turnover. Ecology 98, 933–939 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    53.Bennett, J. R. & Gilbert, B. Contrasting beta diversity among regions: how do classical and multivariate approaches compare? Glob. Ecol. Biogeogr. 25, 368–377 (2016).Article 

    Google Scholar 
    54.Legendre, P. & De Caceres, M. Beta diversity as the variance of community data: dissimilarity coefficients and partitioning. Ecol. Lett. 16, 951–963 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    55.Baselga, A. Separating the two components of abundance-based dissimilarity: balanced changes in abundance vs. abundance gradients. Methods Ecol. Evol. 4, 552–557 (2013).Article 

    Google Scholar 
    56.De Cáceres, M. et al. The variation of tree beta diversity across a global network of forest plots. Glob. Ecol. Biogeogr. 21, 1191–1202 (2012).Article 

    Google Scholar 
    57.Yen, J. D. L., Fleishman, E., Fogarty, F. & Dobkin, D. S. Relating beta diversity of birds and butterflies in the Great Basin to spatial resolution, environmental variables and trait-based groups. Glob. Ecol. Biogeogr. 28, 328–340 (2019).Article 

    Google Scholar 
    58.Craven, D., Knight, T. M., Barton, K. E., Bialic-Murphy, L. & Chase, J. M. Dissecting macroecological and macroevolutionary patterns of forest biodiversity across the Hawaiian archipelago. Proc. Natl Acad. Sci. USA 116, 16436–16441 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    59.Brundrett, M. & Tedersoo, L. Misdiagnosis of mycorrhizas and inappropriate recycling of data can lead to false conclusions. New Phytol. 221, 18–24 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    60.Soudzilovskaia, N. A. et al. FungalRoot: global online database of plant mycorrhizal associations. New Phytol. 227, 955–966 (2020).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    61.Furniss, T. J., Larson, A. J. & Lutz, J. A. Reconciling niches and neutrality in a subalpine temperate forest. Ecosphere 8 (2017).62.Jucker, T. et al. Canopy structure and topography jointly constrain the microclimate of human-modified tropical landscapes. Glob. Change Biol. 24, 5243–5258 (2018).ADS 
    Article 

    Google Scholar 
    63.Legendre, P. et al. Partitioning beta diversity in a subtropical broad-leaved forest of China. Ecology 90, 663–674 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    64.Robert J., H. raster: Geographic data analysis and modeling. R package version 2.6-7 (2017). .65.Alahuhta, J. et al. Global variation in the beta diversity of lake macrophytes is driven by environmental heterogeneity rather than latitude. J. Biogeogr. 44, 1758–1769 (2017).Article 

    Google Scholar 
    66.Cribari-Neto, F. & Zeileis, A. Beta regression in R. J. Stat. Softw. 34, 1–24 (2010).Article 

    Google Scholar 
    67.Jump, A. S., Matyas, C. & Penuelas, J. The altitude-for-latitude disparity in the range retractions of woody species. Trends Ecol. Evol. 24, 694–701 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    68.Oksanen, J. et al. vegan: Community ecology package. R package version 2.5-2 (2018). .69.Gilbert, B. & Bennett, J. R. Partitioning variation in ecological communities: do the numbers add up? J. Appl Ecol. 47, 1071–1082 (2010).Article 

    Google Scholar 
    70.Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).MATH 
    Article 

    Google Scholar 
    71.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2019). .72.Baselga, A., Orme, D., Villeger, S., De Bortoli, J. & Leprieur, F. Partitioning beta diversity into turnover and nestedness components. R package version 1.5.0 (2019). .73.Harrell Jr, F. E. & Dupont, C. Hmisc: Harrell miscellaneous. R package version 4.2-3 (2019). .74.Liaw, A. & Wiener, M. Classification and regression by randomForest. R News. 2, 18–22 (2002).
    Google Scholar 
    75.Archer, E. rfPermute: estimate permutation p-values for random forest importance metrics. R package version 2.1.6 (2018). . More

  • in

    Impact of diesel and biodiesel contamination on soil microbial community activity and structure

    1.Mnif, I., Sahnoun, R. & Ellouz-Chaabouni, S. Application of bacterial biosurfactants for enhanced removal and biodegradation of diesel oil. Process Saf. Environ. Prot. 109, 72–81 (2017).CAS 
    Article 

    Google Scholar 
    2.Abioye, O. P. Biological remediation of hydrocarbon and heavy metals contaminated soil. In Soil Contamination (ed. Pascucci, S.) 127–142 (InTech Europe, 2011).
    Google Scholar 
    3.Zarinkamar, F., Reypour, F. & Soleimanpour, S. Effect of diesel fuel contaminated soil on the germination and the growth of Festuca arundinacea. Res. J. Chem. Environ. Sci. 1, 37–41 (2013).
    Google Scholar 
    4.Ashnani, M. H. M., Johari, A., Hashim, H. & Hasani, E. A source of renewable energy in Malaysia, why biodiesel? Renew. Sustain. Energy Rev. 35, 244–257 (2014).Article 

    Google Scholar 
    5.Bücker, F. et al. Impact of biodiesel on biodeterioration of stored Brazilian diesel oil. Int. Biodeterior. Biodegrad. 65, 172–178 (2011).Article 
    CAS 

    Google Scholar 
    6.Hawrot-Paw, M. & Izwikow, M. Ecotoxicologial effects of biodiesel in the soil. J. Ecol. Eng. 16, 34–39 (2015).Article 

    Google Scholar 
    7.Restrepo-Flórez, J.-M., Bassi, A., Rehmann, L. & Thompson, M. R. Effect of biodiesel addition on microbial community structure in a simulated fuel storage system. Bioresour. Technol. 147, 456–463 (2013).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    8.Silva, G. S. et al. Biodegradability of soy biodiesel in microcosm experiments using soil from the Atlantic Rain Forest. Appl. Soil Ecol. 55, 27–35 (2012).Article 

    Google Scholar 
    9.Prosser, J. I. Dispersing misconceptions and identifying opportunities for the use of ‘omics’ in soil microbial ecology. Nat. Rev. Microbiol. 13, 439–446 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    10.Hawrot-Paw, M. & Martynus, M. The influence of diesel fuel and biodiesel on soil microbial biomass. Pol. J. Environ. Stud. 20, 497–501 (2011).CAS 

    Google Scholar 
    11.Lahel, A. et al. Effect of process parameters on the bioremediation of diesel contaminated soil by mixed microbial consortia. Int. Biodeterior. Biodegrad. 113, 375 (2016).CAS 
    Article 

    Google Scholar 
    12.Nwankwegu, A. S., Orji, M. U. & Onwosi, C. O. Studies on organic and in-organic biostimulants in bioremediation of diesel-contaminated arable soil. Chemosphere 162, 148–156 (2016).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Woźniak-Karczewska, M. et al. Effect of bioaugmentation on long-term biodegradation of diesel/biodiesel blends in soil microcosms. Sci. Total Environ. 671, 948–958 (2019).ADS 
    Article 
    CAS 

    Google Scholar 
    14.Caspi, R. et al. The MetaCyc database of metabolic pathways and enzymes. Nucleic Acids Res. 46, D633–D639 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    15.Lapinskiene, A., Martinkus, P. & Rebzdaite, V. Eco-toxicological studies of diesel and biodiesel fuels in aerated soil. Environ. Pollut. 142, 432–437 (2006).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    16.Schiewer, S. & Horel, A. Biodiesel addition influences biodegradation rates of fresh and artificially weathered diesel fuel in Alaskan sand. J. Cold Reg. Eng. 31, 1–14 (2017).Article 

    Google Scholar 
    17.Schreier, C. G., Walker, W. J., Burns, J. & Wilkenfeld, R. Total organic carbon as a screening method for petroleum hydrocarbons. Chemosphere 39, 503–510 (1999).ADS 
    CAS 
    Article 

    Google Scholar 
    18.Nimmo, M. Carbon. In Encyclopedia of Analytical Science (eds Worsfold, P. & Alan Townshend, C. P.) 453–457 (Elsevier, 2005).
    Google Scholar 
    19.Margesin, R. & Schinner, F. Bioremediation of diesel-oil-contaminated alpine soils at low temperatures. Appl. Microbiol. Biotechnol. 47, 462–468 (1997).CAS 
    Article 

    Google Scholar 
    20.Møller, J., Winther, P., Lund, B., Kirkebjerg, K. & Westermann, P. Bioventing of diesel oil-contaminated soil: Comparison of degradation rates in soil based on actual oil concentration and on respirometric data. J. Ind. Microbiol. 16, 110–116 (1996).Article 

    Google Scholar 
    21.Nakatsu, C. H. Microbial processes: Community analysis. Ref. Modul. Earth Syst. Environ. Sci. https://doi.org/10.1016/B978-0-12-409548-9.05218-0 (2013).Article 

    Google Scholar 
    22.Margesin, R., Hämmerle, M. & Tscherko, D. Microbial activity and community composition during bioremediation of diesel-oil-contaminated soil: Effects of hydrocarbon concentration, fertilizers, and incubation time. Microb. Ecol. 53, 259–269 (2007).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    23.Owsianiak, M. et al. Biodegradation of diesel/biodiesel blends by a consortium of hydrocarbon degraders: Effect of the type of blend and the addition of biosurfactants. Bioresour. Technol. 100, 1497–1500 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    24.Quideau, S. A. et al. Extraction and analysis of microbial phospholipid fatty acids in soils. J. Vis. Exp. https://doi.org/10.3791/54360 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    25.Frostegård, Å., Tunlid, A. & Bååth, E. Use and misuse of PLFA measurements in soils. Soil Biol. Biochem. 43, 1–5 (2010).
    Google Scholar 
    26.Ruess, L. & Chamberlain, P. M. The fat that matters: Soil food web analysis using fatty acids and their carbon stable isotope signature. Soil Biol. Biochem. 42, 1898–1910 (2010).CAS 
    Article 

    Google Scholar 
    27.Davila, S. et al. Actinobacteria: Current research and perspectives for bioremediation of pesticides and heavy metals. Chemosphere 166, 41–62 (2017).ADS 
    Article 
    CAS 

    Google Scholar 
    28.Sutton, N. B. et al. Impact of long-term diesel contamination on soil microbial cummunity structure. Appl. Environ. Microbiol. 79, 619–630 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    29.Kersters, K., Vos, P. D. E., Gillis, M., Swings, J. & Vandamme, P. Introduction to the Proteobacteria. In The Prokaryotes: A Handbook on the Biology of Bacteria (eds Dworkin, M. et al.) 3–37 (Springer, 2006).
    Google Scholar 
    30.Bell, T. H. et al. Predictable bacterial composition and hydrocarbon degradation in Arctic soils following diesel and nutrient disturbance. ISME J. 7, 1200–1210 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    31.Brzeszcz, J. & Kaszycki, P. Aerobic bacteria degrading both n-alkanes and aromatic hydrocarbons: An undervalued strategy for metabolic diversity and flexibility. Biodegradation 29, 359–407 (2018).PubMed 
    Article 

    Google Scholar 
    32.Elumalai, P. et al. Role of thermophilic bacteria (Bacillus and, Geobacillus) on crude oil degradation and biocorrosion in oil reservoir environment. 3Biotech 9, 79 (2019).
    Google Scholar 
    33.Mitter, E. K., de Freitas, J. R. & Germida, J. J. Bacterial root microbiome of plants growing in oil sands reclamation covers. Front. Microbiol. https://doi.org/10.3389/fmicb.2017.00849 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    34.Bundy, J. G., Paton, G. I. & Campbell, C. D. Microbial communities in different soil types do not converge after diesel contamination. J. Appl. Microbiol. 92, 276–288 (2002).CAS 
    PubMed 
    Article 

    Google Scholar 
    35.Korenblum, E., Souza, D. B., Penna, M. & Seldin, L. Molecular analysis of the bacterial communities in crude oil Samples from two Brazilian offshore petroleum platforms. Int. J. Microbiol. 2012, 1–8 (2012).Article 
    CAS 

    Google Scholar 
    36.Kim, T. J., Lee, E. Y., Kim, Y. J., Cho, K. S. & Ryu, H. W. Degradation of polyaromatic hydrocarbons by Burkholderia cepacia 2A–12. World J. Microbiol. Biotechnol. 19, 411–417 (2003).CAS 
    Article 

    Google Scholar 
    37.Revathy, T., Jayasri, M. A. & Suthindhiran, K. Biodegradation of PAHs by Burkholderia sp. VITRSB1 isolated from marine sediments. Scientifica (Cairo) 2015, 1–9 (2015).
    Google Scholar 
    38.Ramos, D. T., da Silva, M. L. B., Nossa, C. W., Alvarez, P. J. J. & Corseuil, H. X. Assessment of microbial communities associated with fermentative-methanogenic biodegradation of aromatic hydrocarbons in groundwater contaminated with a biodiesel blend (B20). Biodegradation 25, 681–691 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    39.Whyte, L. G. et al. Gene cloning and characterization of multiple alkane hydroxylase systems in Rhodococcus strains Q15 and NRRL B-16531. Appl. Environ. Microbiol. 68, 5933–5942 (2002).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    40.Lee, M., Kim, M. K., Singleton, I., Goodfellow, M. & Lee, S.-T. Enhanced biodegradation of diesel oil by a newly identified Rhodococcus baikonurensis EN3 in the presence of mycolic acid. J. Appl. Microbiol. 100, 325–333 (2006).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    41.Bateman, J. N., Speer, B., Feduik, L. & Hartline, R. A. Naphthalene association and uptake in Pseudomonas putida. J. Bacteriol. 166, 155–161 (1986).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    42.Rentz, J. A., Alvarez, P. J. J. & Schnoor, J. L. Repression of Pseudomonas putida phenanthrene-degrading activity by plant root extracts and exudates. Environ. Microbiol. 6, 574–583 (2004).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Shukor, M. Y. et al. Isolation and characterization of Pseudomonas diesel-degrading strain from Antartica. J. Environ. Biol. 30, 1–6 (2009).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    44.Meyer, D. D. et al. Bioremediation strategies for diesel and biodiesel in oxisol from southern Brazil. Int. Biodeterior. Biodegrad. 95, 356–363 (2014).CAS 
    Article 

    Google Scholar 
    45.Taccari, M., Milanovic, V., Comitini, F., Casucci, C. & Ciani, M. Effects of biostimulation and bioaugmentation on diesel removal and bacterial community. Int. Biodeterior. Biodegrad. 66, 39–46 (2012).CAS 
    Article 

    Google Scholar 
    46.Fosso-Kankeu, E. et al. Adaptation behaviour of bacterial species and impact on the biodegradation of biodiesel-diesel. Braz. J. Chem. Eng. 34, 469–480 (2017).CAS 
    Article 

    Google Scholar 
    47.Lutz, G., Chavarría, M., Arias, M. L. & Mata-Segreda, J. F. Microbial degradation of palm (Elaeis guineensis) biodiesel. Rev. Biol. Trop. 54, 59–63 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    48.Holmes, A. J. et al. Diverse, yet-to-be-cultured members of the Rubrobacter subdivision of the Actinobacteria are widespread in Australian arid soils. FEMS Microbiol. Ecol. 33, 111–120 (2000).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    49.Wollherr, A. et al. Pyrosequencing-based assessment of bacterial community structure along different management types in German forest and grassland soils. PLoS ONE 6, 1–12 (2011).
    Google Scholar 
    50.Crampon, M., Bodilis, J. & Portet-Koltalo, F. Linking initial soil bacterial diversity and polycyclic aromatic hydrocarbons (PAHs) degradation potential. J. Hazard. Mater. 359, 500–509 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    51.Wang, L., Li, F., Zhan, Y. & Zhu, L. Shifts in microbial community structure during in situ surfactant-enhanced bioremediation of polycyclic aromatic hydrocarbon-contaminated soil. Environ. Sci. Pollut. Res. 23, 14451–14461 (2016).CAS 
    Article 

    Google Scholar 
    52.van Beilen, J. B., Kingma, J. & Witholt, B. Substrate specificity of the alkane hydroxylase system of Pseudomonas oleovorans GPo1. Enzyme Microb. Technol. 16, 904–911 (1994).Article 

    Google Scholar 
    53.Mukherjee, A. et al. Bioinformatic approaches including predictive metagenomic profiling reveal characteristics of bacterial response to petroleum hydrocarbon contamination in diverse environments. Sci. Rep. 7, 1108 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    54.Ono, K., Nozaki, M. & Hayaishi, O. Purification and some properties of protocatechuate 4,5-dioxygenase. Biochim. Biophys. Acta Enzymol. 220, 224–238 (1970).CAS 
    Article 

    Google Scholar 
    55.Fung, H. K. H. et al. Biochemical and biophysical characterisation of haloalkane dehalogenases DmrA and DmrB in Mycobacterium strain JS60 and their role in growth on haloalkanes. Mol. Microbiol. 97, 439–453 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    56.Kang, Y.-S. & Park, W. Protection against diesel oil toxicity by sodium chloride-induced exopolysaccharides in Acinetobacter sp. strain DR1. J. Biosci. Bioeng. 109, 118–123 (2010).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    57.Ramadass, K., Megharaj, M., Venkateswarlu, K. & Naidu, R. Ecotoxicity of measured concentrations of soil-applied diesel: Effects on earthworm survival, dehydrogenase, urease and nitrification activities. Appl. Soil Ecol. 119, 1–7 (2017).Article 

    Google Scholar 
    58.Moreno, R. & Rojo, F. Enzymes for aerobic degradation of alkanes in bacteria. In Aerobic Utilization of Hydrocarbons, Oils and Lipids (ed. Rojo, F.) 1–25 (Springer, 2017).
    Google Scholar 
    59.Mitter, E. K., de Freitas, J. R. & Germida, J. J. Hydrocarbon-degrading genes in root endophytic communities on oil sands reclamation covers. Int. J. Phytoremediat. 22, 703–712 (2020).CAS 
    Article 

    Google Scholar 
    60.Mitter, E. K., Kataoka, R., de Freitas, J. R. & Germida, J. J. Potential use of endophytic root bacteria and host plants to degrade hydrocarbons. Int. J. Phytoremediat. 21, 928–938 (2019).CAS 
    Article 

    Google Scholar 
    61.Rojo, F. Degradation of alkanes by bacteria: Minireview. Environ. Microbiol. 11, 2477–2490 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    62.Dincer, K. Lower emissions from biodiesel combustion. Energy Sources A Recov. Util. Environ. Eff. 30, 963–968 (2008).CAS 
    Article 

    Google Scholar 
    63.Miri, M., Bambai, B., Tabandeh, F., Sadeghizadeh, M. & Kamali, N. Production of a recombinant alkane hydroxylase (AlkB2) from Alcanivorax borkumensis. Biotechnol. Lett. 32, 497–502 (2010).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    64.Schomburg, D. & Stephan, D. Rubredoxin-NAD+ reductase. In Enzyme Handbook (eds Schomburg, D. & Stephan, D.) 917–920 (Springer, 1994).
    Google Scholar 
    65.Eggink, G., Engel, H., Vriend, G., Terpstra, P. & Witholt, B. Rubredoxin reductase of Pseudomonas oleovorans. J. Mol. Biol. 212, 135–142 (1990).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    66.Hagelueken, G. et al. Crystal structure of the electron transfer complex rubredoxin rubredoxin reductase of Pseudomonas aeruginosa. Proc. Natl. Acad. Sci. 104, 12276–12281 (2007).ADS 
    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    67.Lyu, Y., Zheng, W., Zheng, T. & Tian, Y. Biodegradation of polycyclic aromatic hydrocarbons by Novosphingobium pentaromativorans US6-1. PLoS ONE 9, e101438 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    68.Wang, J. et al. Comparative genomics of degradative Novosphingobium strains with special reference to microcystin-degrading Novosphingobium sp. THN1. Front. Microbiol. 9, 1–17 (2018).Article 

    Google Scholar 
    69.Dhillon, G. S., Amichev, B. Y., de Freitas, J. R. & van Rees, K. Accurate and precise measurement of organic carbon content in carbonate-rich soils. Commun. Soil Sci. Plant Anal. 3624, 2707–2720 (2015).Article 
    CAS 

    Google Scholar 
    70.McKeague, J. A. Manual on SOIL sampling and Methods of Analysis (Canadian Society of Soil Science, 1978).
    Google Scholar 
    71.Laverty, D. H. & Bollo-Kamara, A. Recommended Methods of Soil Analysis for Canadian Prairie Agricultural Soils (Alberta Agriculture, 1988).
    Google Scholar 
    72.Qian, P., Schoenaru, J. J. & Karamanos, R. E. Simultaneous extraction of available phosphorus and potassium with a new soil test: A modification of Kelowna extraction. Commun. Soil Sci. Plant Anal. 25, 627–635 (1994).CAS 
    Article 

    Google Scholar 
    73.Anderson, J. P. E. & Domsch, K. H. A physiological method for the quantitative measurement of microbial biomass in soils. Soil Biol. Biochem. 10, 215–221 (1978).CAS 
    Article 

    Google Scholar 
    74.de Freitas, J. R., Schoenau, J. J., Boyetchko, S. M. & Cyrenne, S. A. Soil microbial populations, community composition, and activity as affected by repeated applications of hog and cattle manure in eastern Saskatchewan. Can. J. Microbiol. 49, 538–548 (2003).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    75.Ramirez, K. S., Craine, J. M. & Fierer, N. Consistent effects of nitrogen amendments on soil microbial communities and processes across biomes. Glob. Change Biol. 18, 1918–1927 (2012).ADS 
    Article 

    Google Scholar 
    76.Craine, J. M., Fierer, N. & McLauchlan, K. K. Widespread coupling between the rate and temperature sensitivity of organic matter decay. Nat. Geosci. 3, 854–857 (2010).ADS 
    CAS 
    Article 

    Google Scholar 
    77.Helgason, B. L., Walley, F. L. & Germida, J. J. Long-term no-till management affects microbial biomass but not community composition in Canadian prairie agroecosytems. Soil Biol. Biochem. 42, 2192–2202 (2010).CAS 
    Article 

    Google Scholar 
    78.Drenovsky, R. E., Elliott, G. N., Graham, K. J. & Scow, K. M. Comparison of phospholipid fatty acid (PLFA) and total soil fatty acid methyl esters (TSFAME) for characterizing soil microbial communities. Soil Biol. Biochem. 36, 1793–1800 (2004).CAS 
    Article 

    Google Scholar 
    79.Macdonald, L. M., Paterson, E., Dawson, L. A. & McDonald, A. J. S. Short-term effects of defoliation on the soil microbial community associated with two contrasting Lolium perenne cultivars. Soil Biol. Biochem. 36, 489–498 (2004).CAS 
    Article 

    Google Scholar 
    80.Zelles, L., Bai, Q. Y., Beck, T. & Beese, F. Signature fatty acids in phospholipids and lipopolysaccharides as indicators of microbial biomass and community structure in agricultural soils. Soil Biol. Biochem. 24, 317–323 (1992).CAS 
    Article 

    Google Scholar 
    81.Hynes, H. M. & Germida, J. J. Relationship between ammonia oxidizing bacteria and bioavailable nitrogen in harvested forest soils of central Alberta. Soil Biol. Biochem. 46, 18–25 (2012).CAS 
    Article 

    Google Scholar 
    82.McCune, B. & Mefford, M. J. Multivariate analysis of Ecological Data (2011).83.Helgason, B. L., Walley, F. L. & Germida, J. J. No-till soil management increases microbial biomass and alters community profiles in soil aggregates. Appl. Soil Ecol. 46, 390–397 (2010).Article 

    Google Scholar 
    84.McCune, B. & Grace, J. B. Analysis of Ecological Communities (2002).85.Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    86.Boylen, E. et al. QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science. PeerJ Prepr. https://doi.org/10.7287/peerj.preprints.27295 (2018).Article 

    Google Scholar 
    87.Caporaso, J. G. et al. Moving pictures of the human microbiome. Genome Biol. 12, 1–8 (2011).Article 

    Google Scholar 
    88.Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    89.Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral. Ecol. 26, 32–46 (2001).
    Google Scholar 
    90.Oksanen, J. et al. Community Ecology Package ‘vegan’ (2020).91.Hamilton, N. ggtern: An Extension to ‘ggplot2’, for the Creation of Ternary Diagrams (2018).92.Douglas, G. M. et al. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 38, 685–688 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    93.Langille, M. G. I. et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31, 814–821 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    94.Kanehisa, M., Sato, Y., Furumichi, M., Morishima, K. & Tanabe, M. New approach for understanding genome variations in KEGG. Nucleic Acids Res. 47, D590–D595 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    95.Parks, D. H. & Beiko, R. G. Identifying biologically relevant differences between metagenomic communities. Bioinformatics 26, 715–721 (2010).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar  More

  • in

    Heterogeneity in patterns of helminth infections across populations of mountain gorillas (Gorilla beringei beringei)

    1.Weber, A. W. & Vedder, A. Population dynamics of the Virunga gorillas: 1959–1978. Biol. Conserv. 26, 341–366 (1983).Article 

    Google Scholar 
    2.Granjon, A.-C. et al. Estimating abundance and growth rates in a wild mountain gorilla population. Anim. Conserv. 23, 455–465 (2020).Article 

    Google Scholar 
    3.Gray, M. et al. Virunga Massif Mountain Gorilla Census—2010 Summary Report (IGCP & Partners, 2010).
    Google Scholar 
    4.Gray, M. et al. Genetic census reveals increased but uneven growth of a critically endangered mountain gorilla population. Biol. Conserv. 158, 230–238 (2013).Article 

    Google Scholar 
    5.Robbins, M. M. et al. Extreme conservation leads to recovery of the Virunga mountain gorillas. PLoS One 6, e19788 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    6.Hickey, J. R., Granjon, A.-C. & Vigilant, L. Virunga 2015–2016 Surveys: Monitoring Mountain Gorillas, Other Select Mammals, and Illegal Activities (IGCP & Partners, 2019).
    Google Scholar 
    7.Kalpers, J. et al. Gorillas in the crossfire: Population dynamics of the Virunga mountain gorillas over the past three decades. Oryx 37, 326–337 (2003).Article 

    Google Scholar 
    8.Robbins, M. M., Gray, M., Kagoda, E. & Robbins, A. M. Population dynamics of the Bwindi mountain gorillas. Biol. Conserv. 142, 2886–2895 (2009).Article 

    Google Scholar 
    9.Hickey, J. R., Uzabaho, E. & Akantorana, M. Bwindi-Sarambwe EM 2018 Surveys: Monitoring Mountain Gorillas, Other Select Mammals, and Human Activities 40 (GVTC, IGCP & Partners, 2019).
    Google Scholar 
    10.Roy, J. et al. Challenges in the use of genetic mark-recapture to estimate the population size of Bwindi mountain gorillas (Gorilla beringei beringei). Biol. Conserv. 180, 249–261 (2014).Article 

    Google Scholar 
    11.McNeilage, A. J. Mountain Gorillas in the Virunga Volcanoes: Ecology and Carrying Capacity (University of Bristol, 1995).
    Google Scholar 
    12.Caillaud, D., Ndagijimana, F., Giarrusso, A. J., Vecellio, V. & Stoinski, T. S. Mountain gorilla ranging patterns: Influence of group size and group dynamics. Am. J. Primatol. 76, 730–746 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Caillaud, D. et al. Violent encounters between social units hinder the growth of a high-density mountain gorilla population. Sci. Adv. 6, eaba0724 (2020).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    14.Watts, D. P. Causes and consequences of variation in male mountain gorilla life histories and group membership. In Primate Males (ed. Kappeler, P. M.) 169–179 (Cambridge University Press, 2000).
    Google Scholar 
    15.Robbins, M. M., Robbins, A. M., Gerald-Steklis, N. & Steklis, H. D. Socioecological influences on the reproductive success of female mountain gorillas (Gorilla beringei beringei). Behav. Ecol. Sociobiol. 61, 919–931 (2007).Article 

    Google Scholar 
    16.Robbins, A. M. et al. Impact of male Infanticide on the social structure of mountain gorillas. PLoS One 8, e78256 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    17.Grueter, C. C. et al. Quadratic relationships between group size and foraging efficiency in a herbivorous primate. Sci. Rep. 8, 16718 (2018).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    18.Eckardt, W., Stoinski, T. S., Rosenbaum, S. & Santymire, R. Social and ecological factors alter stress physiology of Virunga mountain gorillas (Gorilla beringei beringei). Ecol. Evol. 9, 5248–5259 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    19.Harcourt, A. H., Parks, S. A. & Woodroffe, R. Human density as an influence on species/area relationships: Double jeopardy for small African reserves?. Biodivers. Conserv. 10, 1011–1026 (2001).Article 

    Google Scholar 
    20.Citterio, C. V. et al. Abomasal nematode community in an alpine chamois (Rupicapra r. rupicapra) population before and after a die-off. J. Parasitol. 92, 918–927 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    21.Hudson, P. J. Macroparasites: Observed patterns. Ecol. Infect. Dis. Nat. Popul. 20, 144–176 (1995).
    Google Scholar 
    22.Albon, S. D. et al. The role of parasites in the dynamics of a reindeer population. Proc. R. Soc. Lond. B Biol. Sci. 269, 1625–1632 (2002).CAS 
    Article 

    Google Scholar 
    23.Anderson, R. M. & May, R. M. Age-related changes in the rate of disease transmission: Implications for the design of vaccination programmes. Epidemiol. Infect. 94, 365–436 (1985).CAS 

    Google Scholar 
    24.Lloyd-Smith, J. O., Schreiber, S. J., Kopp, P. E. & Getz, W. M. Superspreading and the effect of individual variation on disease emergence. Nature 438, 355–359 (2005).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    25.Anderson, R. M. & May, R. M. Regulation and stability of host-parasite population interactions: I. Regulatory processes. J. Anim. Ecol. 47, 219–247 (1978).Article 

    Google Scholar 
    26.Arneberg, P., Skorping, A., Grenfell, B. & Read, A. F. Host densities as determinants of abundance in parasite communities. Proc. R. Soc. Lond. B Biol. Sci. 265, 1283–1289 (1998).Article 

    Google Scholar 
    27.Gillespie, T. R. & Chapman, C. A. Forest fragmentation, the decline of an endangered primate, and changes in host–parasite interactions relative to an unfragmented forest. Am. J. Primatol. 70, 222–230 (2008).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    28.Mbora, D. N. M. & McPeek, M. A. Host density and human activities mediate increased parasite prevalence and richness in primates threatened by habitat loss and fragmentation. J. Anim. Ecol. 78, 210–218 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    29.dos Santos, C. N. et al. Seasonal dynamics of cyathostomin (Nematoda–Cyathostominae) infective larvae in Brachiaria humidicola grass in tropical southeast Brazil. Vet. Parasitol. 180, 274–278 (2011).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    30.Silangwa, S. M. & Todd, A. C. Vertical migration of trichostrongylid larvae on grasses. J. Parasitol. 50, 278–285 (1964).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    31.Callinan, A. P. L. & Westcott, J. M. Vertical distribution of trichostrongylid larvae on herbage and in soil. Int. J. Parasitol. 16, 241–244 (1986).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    32.Crofton, H. D. The ecology of immature phases of trichostrongyle nematodes: II. The effect of climatic factors on the availability of the infective larvae of Trichostrongylus retortaeformis to the host. Parasitology 39, 26–38 (1948).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    33.Zanet, S. et al. Higher risk of gastrointestinal parasite infection at lower elevation suggests possible constraints in the distributional niche of Alpine marmots. PLoS One 12, e0182477 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    34.Derek Scasta, J. Livestock parasite management on high-elevation rangelands: Ecological interactions of climate, habitat, and wildlife. J. Integr. Pest Manag. 6, 20 (2015).Article 

    Google Scholar 
    35.Huffman, M. A., Gotoh, S., Turner, L. A., Hamai, M. & Yoshida, K. Seasonal trends in intestinal nematode infection and medicinal plant use among chimpanzees in the Mahale Mountains, Tanzania. Primates 38, 111–125 (1997).Article 

    Google Scholar 
    36.MacIntosh, A. J. J., Hernandez, A. D. & Huffman, M. A. Host age, sex, and reproductive seasonality affect nematode parasitism in wild Japanese macaques. Primates 51, 353–364 (2010).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    37.Pafčo, B. et al. Do habituation, host traits and seasonality have an impact on protist and helminth infections of wild western lowland gorillas?. Parasitol. Res. 116, 3401–3410 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    38.Rothman, J. M., Pell, A. N. & Bowman, D. D. Host-parasiteecology of the helminths in mountain gorillas. J. Parasitol. 94, 834–840 (2008).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    39.Müller-Graf, C. D. M., Collins, D. A. & Woolhouse, M. E. J. Intestinal parasite burden in five troops of olive baboons (Papio cynocephalus anubis) in Gombe Stream National Park, Tanzania. Parasitology 112, 489–497 (1996).PubMed 
    Article 

    Google Scholar 
    40.Alexander, J. & Stimson, W. H. Sex hormones and the course of parasitic infection. Parasitol. Today 4, 189–193 (1988).Article 

    Google Scholar 
    41.Bundy, D. A. P. Gender-dependent patterns of infections and disease. Parasitol. Today 4, 186–189 (1988).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    42.Zuk, M. Reproductive strategies and disease susceptibility: An evolutionary viewpoint. Parasitol. Today 6, 231–233 (1990).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Nunn, C. & Altizer, S. Infectious Diseases in Primates: Behavior (Ecology and Evolution. Oxford University Press, Oxford, 2006).Book 

    Google Scholar 
    44.Wilson, K. et al. Heterogeneities in macroparasite infections: Patterns and processes. In The Ecology of Wildlife Diseases 6–44 (2002).45.Cattadori, I. M., Boag, B., Bjørnstad, O. N., Cornell, S. J. & Hudson, P. J. Peak shift and epidemiology in a seasonal host–nematode system. Proc. R. Soc. B Biol. Sci. 272, 1163–1169 (2005).CAS 
    Article 

    Google Scholar 
    46.Terio, K. A. et al. Oesophagostomiasis in non-human primates of Gombe National Park, Tanzania. Am. J. Primatol. 80, e22572 (2018).Article 

    Google Scholar 
    47.Gillespie, T. R., Nunn, C. L. & Leendertz, F. H. Integrative approaches to the study of primate infectious disease: Implications for biodiversity conservation and global health. Am. J. Phys. Anthropol. 137, 53–69 (2008).Article 

    Google Scholar 
    48.Collett, M. G. et al. Gastric Ollulanus tricuspis infection identified in captive cheetahs (Acinonyx jubatus) with chronic vomiting: Case report. J. S. Afr. Vet. Assoc. 71, 251–255 (2000).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    49.Dennis, M. M., Bennett, N. & Ehrhart, E. J. Gastric adenocarcinoma and chronic gastritis in two related Persian cats. Vet. Pathol. 43, 358–362 (2006).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    50.Smetana, H. F. & Orihel, T. C. Gastric papillomata in Macaca speciosa induced by Nochtia nochti (Nematoda: Trichostrongyloidea). J. Parasitol. 55, 349–351 (1969).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    51.Nybelin, O. Anoplocephala gorillae n. sp. Ark Zool. 19, 1–3 (1924).
    Google Scholar 
    52.Sleeman, J. M., Meader, L. L., Mudakikwa, A. B., Foster, J. W. & Patton, S. Gastrointestinal parasites of mountain gorillas (Gorilla gorilla beringei) in the Parc National des Volcans, Rwanda. J. Zool. Wildl. Med. 31, 322–328 (2000).CAS 
    Article 

    Google Scholar 
    53.Ashford, R. W., Lawson, H., Butynski, T. M. & Reid, G. D. F. Patterns of intestinal parasitism in the mountain gorilla Gorilla gorilla in the Bwindi-Impenetrable Forest, Uganda. J. Zool. 239, 507–514 (1996).Article 

    Google Scholar 
    54.Kalema-Zikusoka, G., Rothman, J. M. & Fox, M. T. Intestinal parasites and bacteria of mountain gorillas (Gorilla beringei beringei) in Bwindi Impenetrable National Park, Uganda. Primates 46, 59–63 (2005).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    55.Owiunji, I, et al. The biodiversity of the Virunga Volcanoes. https://programs.wcs.org/portals/49/media/file/volcanoes_biodiv_survey.pdf (2005).56.Langdale-Brown, I., Osmaston, H. & Wilson, J. G. The Vegetation of Uganda and Its Bearing on Land-Use (Governmentt of Uganda, 1964).
    Google Scholar 
    57.Ashford, R. W., Reid, G. D. F. & Butynski, T. M. The intestinal faunas of man and mountain gorillas in a shared habitat. Ann. Trop. Med. Parasitol. 84, 337–340 (1990).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    58.Shutt, K. et al. Effects of habituation, research and ecotourism on faecal glucocorticoid metabolites in wild western lowland gorillas: Implications for conservation management. Biol. Conserv. 172, 72–79 (2014).Article 

    Google Scholar 
    59.Kayiranga, A. et al. Analysis of climate and topography impacts on the spatial distribution of vegetation in the Virunga Volcanoes Massif of East-Central Africa. Geosciences 7, 17 (2017).ADS 
    Article 

    Google Scholar 
    60.Cousins, D. & Huffman, M. A. Medicinal properties in the diet of gorillas: An ethno-phramacological evaluation. Afr. Stud. Monogr. 23, 65–89 (2002).
    Google Scholar 
    61.Woolhouse, M. E. J. Patterns in parasite epidemiology: The peak shift. Parasitol. Today 14, 428–434 (1998).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    62.Hayes, K. S., Bancroft, A. J. & Grencis, R. K. Immune-mediated regulation of chronic intestinal nematode infection. Immunol. Rev. 201, 75–88 (2004).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    63.Maizels, R. M. et al. Helminth parasites—masters of regulation. Immunol. Rev. 201, 89–116 (2004).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    64.Proudman, C. J., Holmes, M. A., Sheoran, A. S., Edwards, S. E. R. & Trees, A. J. Immunoepidemiology of the equine tapeworm Anoplocephala perfoliata: Age-intensity profile and age-dependency of antibody subtype responses. Parasitology 114, 89–94 (1997).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    65.Gergócs, V., Garamvölgyi, Á., Homoródi, R. & Hufnagel, L. Seasonal change of oribatid mite communities (Acari, Oribatida) in three different types of microhabitats in an oak forest. Appl. Ecol. Environ. Res. 9, 181–195 (2011).Article 

    Google Scholar 
    66.Dobson, A. & Foufopoulos, J. Emerging infectious pathogens of wildlife. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 356, 1001–1012 (2001).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    67.Xue, Y. et al. Mountain gorilla genomes reveal the impact of long-term population decline and inbreeding. Science 348, 242–245 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    68.Reed, D. H. & Frankham, R. Correlation between fitness and genetic diversity. Conserv. Biol. 17, 230–237 (2003).Article 

    Google Scholar 
    69.Pafčo, B. et al. Metabarcoding analysis of strongylid nematode diversity in two sympatric primate species. Sci. Rep. 8, 5933 (2018).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    70.McNeilage, A. Diet and habitat use of two mountain gorilla groups in contrasting habitats in the Virunga. In Mountain Gorillas: Three Decades of Research at Karisoke (Cambridge University Press, 2001).
    Google Scholar 
    71.Sinayitutse, E. et al. Daily defecation outputs of mountain gorillas (Gorilla beringei beringei) in the Volcanoes National Park, Rwanda. Primates https://doi.org/10.1007/s10329-020-00874-7 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    72.Burgunder, J. et al. Complexity in behavioural organization and strongylid infection among wild chimpanzees. Anim. Behav. 129, 257–268 (2017).Article 

    Google Scholar 
    73.Chapman, C. A., Speirs, M. L., Gillespie, T. R., Holland, T. & Austad, K. M. Life on the edge: Gastrointestinal parasites from the forest edge and interior primate groups. Am. J. Primatol. 68, 397–409 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    74.Anderson, R. M. & Schad, G. A. Hookworm burdens and faecal egg counts: An analysis of the biological basis of variation. Trans. R. Soc. Trop. Med. Hyg. 79, 812–825 (1985).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    75.Warnick, L. D. Daily variability of equine fecal strongyle egg counts. Cornell Vet. 82, 453–463 (1992).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    76.Tomczuk, K. et al. Comparison of the sensitivity of coprological methods in detecting Anoplocephala perfoliata invasions. Parasitol. Res. 113, 2401–2406 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    77.Williamson, R., Beveridge, I. & Gasser, R. Coprological methods for the diagnosis of Anoplocephala perfoliata infection of the horse. Aust. Vet. J. 76, 618–621 (1998).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    78.Cringoli, G. et al. The Mini-FLOTAC technique for the diagnosis of helminth and protozoan infections in humans and animals. Nat. Protoc. 12, 1723–1732 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    79.Guschanski, K. et al. Counting elusive animals: Comparing field and genetic census of the entire mountain gorilla population of Bwindi Impenetrable National Park, Uganda. Biol. Conserv. 142, 290–300 (2009).Article 

    Google Scholar 
    80.Zuur, A., Ieno, E. N., Walker, N., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer, 2009).MATH 
    Book 

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

    Google Scholar 
    82.R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ (2020).83.Forstmeier, W. & Schielzeth, H. Cryptic multiple hypotheses testing in linear models: Overestimated effect sizes and the winner’s curse. Behav. Ecol. Sociobiol. 65, 47–55 (2011).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    84.Engqvist, L. The mistreatment of covariate interaction terms in linear model analyses of behavioural and evolutionary ecology studies. Anim. Behav. 70, 20 (2005).Article 

    Google Scholar 
    85.Gelman, A. & Hill, J. Data Analysis Using Regression and Multilevel/Hierarchical Models (Cambridge University Press, 2007).
    Google Scholar 
    86.Schielzeth, H. Simple means to improve the interpretability of regression coefficients. Methods Ecol. Evol. 1, 103–113 (2010).Article 

    Google Scholar 
    87.Johnson, J. B. & Omland, K. S. Model selection in ecology and evolution. Trends Ecol. Evol. 19, 101–108 (2004).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    88.Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (Springer, 2002).MATH 

    Google Scholar 
    89.Barton, K. MuMIn: Multi-Model Inference. R package version 1.43.17. https://CRAN.R-project.org/package=MuMIn (2020). More

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    Correction: Gulf of Mexico blue hole harbors high levels of novel microbial lineages

    N. V. PatinPresent address: Ocean Chemistry and Ecosystems Division, Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Administration, Miami, FL, USAN. V. PatinPresent address: Cooperative Institute for Marine and Atmospheric Studies, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, USAN. V. PatinPresent address: Stationed at Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, La Jolla, CA, USASchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USAN. V. Patin & F. J. StewartCenter for Microbial Dynamics and Infection, Georgia Institute of Technology, Atlanta, GA, USAN. V. Patin & F. J. StewartBowdoin College, Brunswick, ME, USAZ. A. DietrichHarbor Branch Oceanographic Institute, Florida Atlantic University, Ft. Pierce, FL, USAA. Stancil, M. Quinan & J. S. BecklerMote Marine Laboratory, Sarasota, FL, USAE. R. Hall & J. CulterU.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, USAC. G. SmithSchool of Earth & Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USAM. TaillefertDepartment of Microbiology & Immunology, Montana State University, Bozeman, MT, USAF. J. Stewart More