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    Importance of old bulls: leaders and followers in collective movements of all-male groups in African savannah elephants (Loxodonta africana)

    1.
    King, A. J., Douglas, C. M. S., Huchard, E., Isaac, N. J. B. & Cowlishaw, G. Dominance and affiliation mediate despotism in a social primate. Curr. Biol. 18, 1833–1838 (2008).
    CAS  PubMed  Google Scholar 
    2.
    Harcourt, J. L., Ang, T. Z., Sweetman, G., Johnstone, R. A. & Manica, A. Social feedback and the emergence of leaders and followers. Curr. Biol. 19, 248–252 (2009).
    CAS  PubMed  Google Scholar 

    3.
    Maransky, B. P. & Bildstein, K. L. Follow your elders: age-related differences in the migration behavior of broad-winged hawks at hawk mountain sanctuary, Pennsylvania. Wilson Bull. 113, 350–353 (2001).
    Google Scholar 

    4.
    King, A. J., Johnson, D. D. P. & Van Vugt, M. The origins and evolution of leadership. Curr. Biol. 19, R911–R916 (2009).
    CAS  PubMed  Google Scholar 

    5.
    Dyer, J. R. G. et al. Consensus decision making in human crowds. Anim. Behav. 75, 461–470 (2008).
    Google Scholar 

    6.
    Lusseau, D. & Conradt, L. The emergence of unshared consensus decisions in bottlenose dolphins. Behav. Ecol. Sociobiol. 63, 1067–1077 (2009).
    Google Scholar 

    7.
    Diamond, J. Unwritten knowledge. Nature 410, 521–521 (2001).
    ADS  CAS  PubMed  Google Scholar 

    8.
    McComb, K. et al. Leadership in elephants: the adaptive value of age. Proc. R. Soc. B Biol. Sci. 278, 3270–3276 (2011).
    Google Scholar 

    9.
    McComb, K., Moss, C., Durant, S. M., Baker, L. & Sayialel, S. Matriarchs as repositories of social knowledge in African elephants. Science 292, 491–494 (2001).
    ADS  CAS  PubMed  Google Scholar 

    10.
    Brent, L. J. N. et al. Ecological knowledge, leadership, and the evolution of menopause in killer whales. Curr. Biol. 25, 746–750 (2015).
    CAS  PubMed  Google Scholar 

    11.
    Stephen Dobson, F. Competition for mates and predominant juvenile male dispersal in mammals. Anim. Behav. 30, 1183–1192 (1982).
    Google Scholar 

    12.
    Baker, J. E. Trophy hunting as a sustainable use of wildlife resources in Southern and Eastern Africa. J. Sustain. Tour. 5, 306–321 (1997).
    Google Scholar 

    13.
    Hurt, R. & Ravn, P. Hunting and its benefits: an overview of hunting in Africa with special reference to Tanzania. In Wildlife Conservation by Sustainable Use, 295–313 (Springer, 2000). https://doi.org/10.1007/978-94-011-4012-6_15.

    14.
    Chiyo, P. I., Obanda, V. & Korir, D. K. Illegal tusk harvest and the decline of tusk size in the African elephant. Ecol. Evol. 5, 5216–5229 (2015).
    PubMed  PubMed Central  Google Scholar 

    15.
    Presotto, A., Fayrer-Hosken, R., Curry, C. & Madden, M. Spatial mapping shows that some African elephants use cognitive maps to navigate the core but not the periphery of their home ranges. Anim. Cogn. 22, 251–263 (2019).
    PubMed  Google Scholar 

    16.
    Von Gerhardt, K., Van Niekerk, A., Kidd, M., Samways, M. & Hanks, J. The role of elephant Loxodonta africana pathways as a spatial variable in crop-raiding location. Oryx 48, 436–444 (2014).
    Google Scholar 

    17.
    Lee, P. C., Poole, J. H., Njiraini, N., Sayialel, C. N. & Moss, C. J. Male social dynamics. In The Amboseli elephants 260–271 (University of Chicago Press, 2011). https://doi.org/10.7208/chicago/9780226542263.003.0017.

    18.
    Ngene, S. M. et al. The ranging patterns of elephants in Marsabit protected area, Kenya: the use of satellite-linked GPS collars. Afr. J. Ecol. 48, 386–400 (2009).
    Google Scholar 

    19.
    Archie, E. A., Moss, C. J. & Alberts, S. C. The ties that bind: genetic relatedness predicts the fission and fusion of social groups in wild African elephants. Proc. R. Soc. B Biol. Sci. 273, 513–522 (2005).
    Google Scholar 

    20.
    Chiyo, P. I. et al. Association patterns of African elephants in all-male groups: the role of age and genetic relatedness. Anim. Behav. 81, 1093–1099 (2011).
    Google Scholar 

    21.
    Poole, J. H. Rutting behavior in African elephants: the phenomenon of musth. Behaviour 102, 283–316 (1987).
    Google Scholar 

    22.
    Hollister-Smith, J. A. et al. Age, musth and paternity success in wild male African elephants, Loxodonta africana. Anim. Behav. 74, 287–296 (2007).
    Google Scholar 

    23.
    Goldenberg, S. Z., de Silva, S., Rasmussen, H. B., Douglas-Hamilton, I. & Wittemyer, G. Controlling for behavioural state reveals social dynamics among male African elephants, Loxodonta africana. Anim. Behav. 95, 111–119 (2014).
    Google Scholar 

    24.
    Moss, C. J. The demography of an African elephant (Loxodonta africana) population in Amboseli, Kenya. J. Zool. 255, 145–156 (2001).
    Google Scholar 

    25.
    Lee, P. C. & Moss, C. J. Statural growth in known-age African elephants (Loxodonta africana). J. Zool. 236, 29–41 (1995).
    Google Scholar 

    26.
    Moss, C. J. & Lee, P. C. Female reproductive strategies. In The Amboseli Elephants 187–204 (University of Chicago Press, 2011). https://doi.org/10.7208/chicago/9780226542263.003.0012.

    27.
    Chiyo, P. I. & Cochrane, E. P. Population structure and behaviour of crop-raiding elephants in Kibale National Park, Uganda. Afr. J. Ecol. 43, 233–241 (2005).
    Google Scholar 

    28.
    Stevens, J. Understanding Human–Elephant Interactions in and Around Makgadikgadi Pans National Park, Botswana. PhD Thesis, University of Bristol (2018).

    29.
    Obanda, V. et al. Injuries of free ranging African elephants (Loxodonta africana africana) in various ranges of Kenya. Pachyderm 44, 54–58 (2008).
    Google Scholar 

    30.
    Foley, C., Pettorelli, N. & Foley, L. Severe drought and calf survival in elephants. Biol. Lett. 4, 541–544 (2008).
    PubMed  PubMed Central  Google Scholar 

    31.
    Evans, K. E. Elephants for Africa: male Savannah elephant Loxodonta africana sociality, the Makgadikgadi and resource competition. Int. Zoo Yearb. 53, 200–207 (2019).
    Google Scholar 

    32.
    Shannon, G., Page, B. R., Duffy, K. J. & Slotow, R. The ranging behaviour of a large sexually dimorphic herbivore in response to seasonal and annual environmental variation. Aust. Ecol. 35, 731–742 (2010).
    Google Scholar 

    33.
    Mueller, T., O’Hara, R. B., Converse, S. J., Urbanek, R. P. & Fagan, W. F. Social learning of migratory performance. Science 341, 999–1002 (2013).
    ADS  CAS  PubMed  Google Scholar 

    34.
    Pettit, B., Ákos, Z., Vicsek, T. & Biro, D. Speed determines leadership and leadership determines learning during pigeon flocking. Curr. Biol. 25, 3132–3137 (2015).
    CAS  PubMed  Google Scholar 

    35.
    Hutchinson, J. R. The locomotor kinematics of Asian and African elephants: changes with speed and size. J. Exp. Biol. 209, 3812–3827 (2006).
    PubMed  Google Scholar 

    36.
    Taylor, L. A. et al. Movement reveals reproductive tactics in male elephants. J. Anim. Ecol. 89, 57–67 (2019).
    PubMed  PubMed Central  Google Scholar 

    37.
    King, A. J. et al. Selfish-herd behaviour of sheep under threat. Curr. Biol. 22, R561–R562 (2012).
    CAS  PubMed  Google Scholar 

    38.
    Joubert, D. Hunting behaviour of lions (Panthera leo) on elephants (Loxodonta africana) in the Chobe National Park, Botswana. Afr. J. Ecol. 44, 279–281 (2006).
    Google Scholar 

    39.
    de Boer, W. F. et al. Spatial distribution of lion kills determined by the water dependency of prey species. J. Mammal. 91, 1280–1286 (2010).
    Google Scholar 

    40.
    Wittemyer, G., Daballen, D. & Douglas-Hamilton, I. Comparative demography of an at-risk African elephant population. PLoS ONE 8, e53726 (2013).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    41.
    Jones, T. et al. Age structure as an indicator of poaching pressure: Insights from rapid assessments of elephant populations across space and time. Ecol. Ind. 88, 115–125 (2018).
    Google Scholar 

    42.
    Conradt, L., Krause, J., Couzin, I. D. & Roper, T. J. “Leading according to need” self-organizing groups. Am. Nat. 173, 304–312 (2009).
    CAS  PubMed  Google Scholar 

    43.
    Hoare, D., Reeves, P. & Krause, J. Positioning behaviour in roach shoals: the role of body length and nutritional state. Behaviour 135, 1031–1039 (1998).
    Google Scholar 

    44.
    Fischhoff, I. R. et al. Social relationships and reproductive state influence leadership roles in movements of plains zebra, Equus burchellii. Anim. Behav. 73, 825–831 (2007).
    Google Scholar 

    45.
    Leggett, K. Effects of artificial water points on the movement and behaviour of desert-dwelling elephants in north-western Namibia. Pachyderm 40, 40–51 (2006).
    Google Scholar 

    46.
    Bell, R. H. V. The effect of soil nutrient availability on community structure in African ecosystems. In Ecological Studies 193–216 (Springer, Berlin, 1982). https://doi.org/10.1007/978-3-642-68786-0_10.

    47.
    Mramba, R. P., Andreassen, H. P., Mlingi, V. & Skarpe, C. Activity patterns of African elephants in nutrient-rich and nutrient-poor savannas. Mammal. Biol. 94, 18–24 (2019).
    Google Scholar 

    48.
    Mutinda, H., Poole, J. H. & Moss, C. J. Decision making and leadership in using the ecosystem. In The Amboseli Elephants 246–259 (University of Chicago Press, 2011). https://doi.org/10.7208/chicago/9780226542263.003.0016.

    49.
    Aureli, F. et al. Fission-fusion dynamics. Curr. Anthropol. 49, 627–654 (2008).
    Google Scholar 

    50.
    Moss, C. J. & Poole, J. H. Relationships and social structure in African elephants. In Primate Social Relationships: An Integrated Approach (ed. Hinde, R. A.) (Blackwell, Oxford, 1983).
    Google Scholar 

    51.
    Wittemyer, G., Douglas-Hamilton, I. & Getz, W. M. The socioecology of elephants: analysis of the processes creating multitiered social structures. Anim. Behav. 69, 1357–1371 (2005).
    Google Scholar 

    52.
    Bates, L. A. et al. African elephants have expectations about the locations of out-of-sight family members. Biol. Let. 4, 34–36 (2007).
    Google Scholar 

    53.
    Couzin, I. D., Krause, J., Franks, N. R. & Levin, S. A. Effective leadership and decision-making in animal groups on the move. Nature 433, 513–516 (2005).
    ADS  CAS  PubMed  Google Scholar 

    54.
    Hanks, J. Growth of the African elephant (Loxodonta africana). Afr. J. Ecol. 10, 251–272 (1972).
    Google Scholar 

    55.
    Muposhi, V. K., Gandiwa, E., Bartels, P., Makuza, S. M. & Madiri, T. H. Trophy hunting and sustainability: temporal dynamics in trophy quality and harvesting patterns of wild herbivores in a tropical semi-arid savanna ecosystem. PLoS ONE 11, e0164429 (2016).
    PubMed  PubMed Central  Google Scholar 

    56.
    DG Ecological Consulting. Policy and Strategy for the Conservation and Management of Elephants in Botswana (Department of Wildlife and National Parks, Gaberone, 2003).
    Google Scholar 

    57.
    Pilgram, T. & Western, D. Inferring the sex and age of African elephants from tusk measurements. Biol. Conserv. 36, 39–52 (1986).
    Google Scholar 

    58.
    De Villiers PA. Aspect of the Behaviour and Ecology of Elephant (Loxodonta Africana, Blumenbach, 1797) in the Eastern Transvaal Lowveld with Special Reference to Environmental Interactions. PhD thesis, University of the Orange Free State (1994).

    59.
    Lindsey, P. A., Frank, L. G., Alexander, R., Mathieson, A. & Romañach, S. S. Trophy hunting and conservation in Africa: problems and one potential solution. Conserv. Biol. 21, 880–883 (2007).
    PubMed  Google Scholar 

    60.
    Selier, S.-A.J., Page, B. R., Vanak, A. T. & Slotow, R. Sustainability of elephant hunting across international borders in southern Africa: a case study of the greater Mapungubwe Transfrontier Conservation Area. J. Wildl. Manag. 78, 122–132 (2013).
    Google Scholar 

    61.
    Archie, E. A. et al. Fine-scale population genetic structure in a fission–fusion society. Mol. Ecol. 17, 2666–2679 (2008).
    PubMed  Google Scholar 

    62.
    Evans, K. E. & Harris, S. Adolescence in male African elephants, Loxodonta africana, and the importance of sociality. Anim. Behav. 76, 779–787 (2008).
    Google Scholar 

    63.
    Poole, J. H., Lee, P. C., Njiraini, N. & Moss, C. J. Longevity, competition, and musth. In The Amboseli Elephants 272–288 (University of Chicago Press, 2011). https://doi.org/10.7208/chicago/9780226542263.003.0018.

    64.
    CITES. 2020 CITES national export quotas. https://www.cites.org/eng/resources/quotas/index.php (2020).

    65.
    Mbaiwa, J. E. Effects of the safari hunting tourism ban on rural livelihoods and wildlife conservation in Northern Botswana. S. Afr. Geogr. J. 100, 41–61 (2017).
    Google Scholar 

    66.
    Thouless C.R. et al. African Elephant Status Report 2016: an update from the African Elephant Database. Occasional Paper Series of the IUCN Species Survival Commission, No. 60 IUCN/SSC Africa Elephant Specialist Group. IUCN, Gland, Switzerland (2016).

    67.
    Pitfield A. R. The Social and Environmental Factors Affecting the Life of Bull African Elephants (Loxodonta africana) in a ‘Bull Area’—A Social Network Analysis. Masters Thesis, University of Bristol (2017) (email info@elephantsforafrica.org for a PDF)

    68.
    Moss, C. Getting to know a population. In Studying Elephants (ed. Kangwana, K.) 58–74 (The African Wildlife Foundation, Nairobi, 1996).
    Google Scholar 

    69.
    Lee, H. C. & Teichroeb, J. A. Partially shared consensus decision making and distributed leadership in vervet monkeys: older females lead the group to forage. Am. J. Phys. Anthropol. 161, 580–590 (2016).
    PubMed  Google Scholar 

    70.
    Mayberry, A. L., Hovorka, A. J. & Evans, K. E. Well-being impacts of human-elephant conflict in Khumaga, Botswana: exploring visible and hidden dimensions. Conser. Soc. 15, 280–291. https://doi.org/10.4103/cs.cs_16_132 (2017).
    Article  Google Scholar  More

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    Releasing uncurated datasets is essential for reproducible phylogenomics

    E.D.S. was supported by the International Mobilities of Researchers of the Biology Centre (grant no. CZ.02.2.69/0.0/0.0/16_027/0008357). L.E. is supported by funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (ERC Starting grant no. 803151). M.W.B. was supported by the United States National Science Foundation Division of Environmental Biology (grant no. 1456054). M.K. was supported by Fellowship Purkyně (Czech Academy of Sciences) and by the project Centre for research of pathogenicity and virulence of parasites r.n.: CZ.02.1.01/0.0/0.0/16_019/0000759. More

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    Testing for context-dependent effects of prenatal thyroid hormones on offspring survival and physiology: an experimental temperature manipulation

    1.
    Moore, M. P., Whiteman, H. H. & Martin, R. A. A mother’s legacy: The strength of maternal effects in animal populations. Ecol. Lett. 22, 1620–1628 (2019).
    PubMed  Google Scholar 
    2.
    Yin, J. J., Zhou, M., Lin, Z. R., Li, Q. S. Q. & Zhang, Y. Y. Transgenerational effects benefit offspring across diverse environments: A meta-analysis in plants and animals. Ecol. Lett. 22, 1976–1986 (2019).
    PubMed  Google Scholar 

    3.
    Groothuis, T. G. G., Hsu, B.-Y., Kumar, N. & Tschirren, B. Revisiting mechanisms and functions of prenatal hormone-mediated maternal effects using avian species as a model. Philos. Trans. R. Soc. B 374, 20180115 (2019).
    CAS  Google Scholar 

    4.
    Ruuskanen, S. & Hsu, B.-Y. Maternal thyroid hormones: An unexplored mechanism underlying maternal effects in an ecological framework. Physiol. Biochem. Zool. 91, 904–916 (2018).
    PubMed  Google Scholar 

    5.
    Meylan, S., Miles, D. B. & Clobert, J. Hormonally mediated maternal effects, individual strategy and global change. Philos. Trans. R. Soc. B 367, 1647–1664 (2012).
    Google Scholar 

    6.
    Donelson, J. M., Salinas, S., Munday, P. L. & Shama, L. N. S. Transgenerational plasticity and climate change experiments: Where do we go from here?. Glob. Change Biol. 24, 13–34 (2018).
    ADS  Google Scholar 

    7.
    Ruuskanen, S., Hsu, B.-Y. & Nord, A. Endocrinology of thermoregulation of birds in a changing climate. https://doi.org/10.32942/osf.io/jzam3 (2020).

    8.
    Sheriff, M. J. et al. Integrating ecological and evolutionary context in the study of maternal stress. Integr. Comp. Biol. 57, 437–449 (2017).
    PubMed  PubMed Central  Google Scholar 

    9.
    Schoech, S. J., Rensel, M. A. & Heiss, R. S. Short- and long-term effects of developmental corticosterone exposure on avian physiology, behavioral phenotype, cognition, and fitness: A review. Curr. Zool. 57, 514–530 (2011).
    CAS  Google Scholar 

    10.
    Love, O. P. & Williams, T. D. The adaptive value of stress-induced phenotypes: Effects of maternally derived corticosterone on sex-biased investment, cost of reproduction, and maternal fitness. Am. Nat. 172, E135–E149 (2008).
    PubMed  Google Scholar 

    11.
    Weber, B. M. et al. Pre- and postnatal effects of experimentally manipulated maternal corticosterone on growth, stress reactivity and survival of nestling house wrens. Funct. Ecol. 32, 1995–2007 (2018).
    PubMed  PubMed Central  Google Scholar 

    12.
    Dantzer, B. et al. Density triggers maternal hormones that increase adaptive offspring growth in a wild mammal. Science 340, 1215–1217 (2013).
    ADS  CAS  PubMed  Google Scholar 

    13.
    Zimmer, C., Boogert, N. J. & Spencer, K. A. Developmental programming: Cumulative effects of increased pre-hatching corticosterone levels and post-hatching unpredictable food availability on physiology and behaviour in adulthood. Horm. Behav. 64, 494–500 (2013).
    CAS  PubMed  PubMed Central  Google Scholar 

    14.
    Muriel, J. et al. Context-dependent effects of yolk androgens on nestling growth and immune function in a multibrooded passerine. J. Evol. Biol. 28, 1476–1488 (2015).
    CAS  PubMed  Google Scholar 

    15.
    Gil, D. Hormones in avian eggs: Physiology, ecology and behavior. Adv. Study Behav. 38, 337–398 (2008).
    Google Scholar 

    16.
    Hsu, B.-Y., Doligez, B., Gustafsson, L. & Ruuskanen, S. Transient growth-enhancing effects of elevated maternal thyroid hormones at no apparent oxidative cost during early postnatal period. J. Avian Biol. 50, jav-01919 (2019).
    Google Scholar 

    17.
    Sarraude, T., Hsu, B.-Y., Groothuis, T. G. G. & Ruuskanen, S. Manipulation of prenatal thyroid hormones does not influence growth or physiology in nestling pied flycatchers. Physiol. Biochem. Zool. 93, 255–266 (2020).
    PubMed  Google Scholar 

    18.
    Hsu, B.-Y., Dijkstra, C., Darras, V. M., de Vries, B. & Groothuis, T. G. G. Maternal thyroid hormones enhance hatching success but decrease nestling body mass in the rock pigeon (Columba livia). Gen. Comp. Endocrinol. 240, 174–181 (2017).
    CAS  PubMed  Google Scholar 

    19.
    Auer, S. K., Salin, K., Rudolf, A. M., Anderson, G. J. & Metcalfe, N. B. The optimal combination of standard metabolic rate and aerobic scope for somatic growth depends on food availability. Funct. Ecol. 29, 479–486 (2015).
    Google Scholar 

    20.
    McNabb, F. M. A. The hypothalamic–pituitary–thyroid (HPT) axis in birds and its role in bird development and reproduction. Crit. Rev. Toxicol. 37, 163–193 (2007).
    CAS  PubMed  Google Scholar 

    21.
    Price, E. R. & Dzialowski, E. M. Development of endothermy in birds: Patterns and mechanisms. J. Comp. Physiol. B 188, 373–391 (2018).
    CAS  PubMed  Google Scholar 

    22.
    Ruuskanen, S. et al. Temperature-induced variation in yolk androgen and thyroid hormone levels in avian eggs. Gen. Comp. Endocrinol. 235, 29–37 (2016).
    CAS  PubMed  Google Scholar 

    23.
    Stier, A., Bize, P., Hsu, B.-Y. & Ruuskanen, S. Plastic but repeatable: Rapid adjustments of mitochondrial function and density during reproduction in a wild bird species. Biol. Lett. 15, 20190536 (2019).
    CAS  PubMed  Google Scholar 

    24.
    Salin, K., Auer, S. K., Rey, B., Selman, C. & Metcalfe, N. B. Variation in the link between oxygen consumption and ATP production, and its relevance for animal performance. Proc. R. Soc. B 282, 20151028 (2015).
    PubMed  Google Scholar 

    25.
    Lassiter, K., Dridi, S., Greene, E., Kong, B. & Bottje, W. G. Identification of mitochondrial hormone receptors in avian muscle cells. Poult. Sci. 97, 2926–2933 (2018).
    CAS  PubMed  Google Scholar 

    26.
    Lanni, A., Moreno, M. & Goglia, F. Mitochondrial actions of thyroid hormone. Compr. Physiol. 6, 1591–1607 (2016).
    PubMed  Google Scholar 

    27.
    Weitzel, J. M. & Iwen, K. A. Coordination of mitochondrial biogenesis by thyroid hormone. Mol. Cell. Endocrinol. 342, 1–7 (2011).
    CAS  PubMed  Google Scholar 

    28.
    Clarke, A. & Portner, H. O. Temperature, metabolic power and the evolution of endothermy. Biol. Rev. 85, 703–727 (2010).
    PubMed  Google Scholar 

    29.
    Xia, T., Zhang, X., Wang, Y. & Deng, D. Effect of maternal hypothyroidism during pregnancy on insulin resistance, lipid accumulation, and mitochondrial dysfunction in skeletal muscle of fetal rats. Biosci. Rep. 38, BSR20171731 (2018).
    PubMed  PubMed Central  Google Scholar 

    30.
    Halliwell, B. & Gutteridge, J. M. C. Free Radicals in Biology and Medicine (Oxford University Press, New York, 2015).
    Google Scholar 

    31.
    Villanueva, I., Alva-Sanchez, C. & Pacheco-Rosado, J. The role of thyroid hormones as inductors of oxidative stress and neurodegeneration. Oxid. Med. Cell. Longev. 2013, 218145 (2013).
    CAS  PubMed  PubMed Central  Google Scholar 

    32.
    Stier, A. et al. Elevation impacts the balance between growth and oxidative stress in coal tits. Oecologia 175, 791–800 (2014).
    ADS  PubMed  Google Scholar 

    33.
    Stier, A., Massemin, S. & Criscuolo, F. Chronic mitochondrial uncoupling treatment prevents acute cold-induced oxidative stress in birds. J. Comp. Physiol. B 184, 1021–1029 (2014).
    CAS  PubMed  Google Scholar 

    34.
    Andreasson, F., Nord, A. & Nilsson, J. -Å. Experimentally increased nest temperature affects body temperature, growth and apparent survival in blue tit nestlings. J. Avian Biol. 49, jav-01620 (2018).
    Google Scholar 

    35.
    PodmokƂa, E., Drobniak, S. M. & Rutkowska, J. Chicken or egg? Outcomes of experimental manipulations of maternally transmitted hormones depend on administration method—a meta-analysis. Biol. Rev. 93, 1499–1517 (2018).
    PubMed  Google Scholar 

    36.
    Lundberg, A. & Alatalo, R. The Pied Flycatcher (Poyser, London, 1992).
    Google Scholar 

    37.
    Haggerty, T. M. Effects of nestling age and brood size on nestling care in the Bachman’s sparrow (Aimophila aestivalis). Am. Midl. Nat. 128, 115–125 (1992).
    Google Scholar 

    38.
    Chastel, O. & Kersten, M. Brood size and body condition in the house sparrow Passer domesticus: The influence of brooding behaviour. Ibis 144, 284–292 (2002).
    Google Scholar 

    39.
    Ruuskanen, S. et al. A new method for measuring thyroid hormones using nano-LC-MS/MS. J. Chromatogr. B 1093–1094, 24–30 (2018).
    Google Scholar 

    40.
    Chang, H.-W. et al. High-throughput avian molecular sexing by SYBR green-based real-time PCR combined with melting curve analysis. BMC Biotechnol. 8, 12 (2008).
    PubMed  PubMed Central  Google Scholar 

    41.
    Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
    Google Scholar 

    42.
    Halekoh, U. & Hþjsgaard, S. Kenward–Roger approximation and parametric bootstrap methods for tests in linear mixed models—the R package pbkrtest. J. Stat. Softw. 59, 1–32 (2014).
    Google Scholar 

    43.
    Schielzeth, H. Simple means to improve the interpretability of regression coefficients. Methods Ecol. Evol. 1, 103–113 (2010).
    Google Scholar 

    44.
    Ruuskanen, S., Darras, V. M., Visser, M. E. & Groothuis, T. G. G. Effects of experimentally manipulated yolk thyroid hormone levels on offspring development in a wild bird species. Horm. Behav. 81, 38–44 (2016).
    CAS  PubMed  Google Scholar 

    45.
    RodrĂ­guez, S., Diez-MĂ©ndez, D. & Barba, E. Negative effects of high temperatures during development on immediate post-fledging survival in great tits Parus major. Acta Ornithol. 51, 235–244 (2016).
    Google Scholar 

    46.
    RodrĂ­guez, S. & Barba, E. Nestling growth is impaired by heat stress: An experimental study in a Mediterranean great tit population. Zool. Stud. 55, 13 (2016).
    Google Scholar 

    47.
    Dawson, R. D., Lawrie, C. C. & O’Brien, E. L. The importance of microclimate variation in determining size, growth and survival of avian offspring: Experimental evidence from a cavity nesting passerine. Oecologia 144, 499–507 (2005).
    ADS  PubMed  Google Scholar 

    48.
    Stier, A., Massemin, S., Zahn, S., Tissier, M. L. & Criscuolo, F. Starting with a handicap: Effects of asynchronous hatching on growth rate, oxidative stress and telomere dynamics in free-living great tits. Oecologia 179, 999–1010 (2015).
    ADS  PubMed  Google Scholar 

    49.
    Wikelski, M. & Cooke, S. J. Conservation physiology. Trends Ecol. Evol. 21, 38–46 (2006).
    PubMed  Google Scholar 

    50.
    Darras, V. M. The role of maternal thyroid hormones in avian embryonic development. Front. Endocrinol. 10, 66 (2019).
    Google Scholar 

    51.
    Huget-Penner, S. & Feig, D. S. Maternal thyroid disease and its effects on the fetus and perinatal outcomes. Prenat. Diagn. https://doi.org/10.1002/pd.5684 (2020).
    Article  PubMed  Google Scholar 

    52.
    Kulkami, S. S. & Buchholz, K. R. Beyond synergy: Corticosterone and thyroid hormone have numerous interaction effects on gene regulation in Xenopus tropicalis tadpoles. Endocrinology 153, 5309–5324 (2012).
    Google Scholar 

    53.
    Watanabe, Y., Grommern, S. V. H. & de Groef, B. Corticotropin-releasing hormone: Mediator of vertebrate life stage trasitions?. Gen. Comp. Endocrinol. 228, 60–68 (2016).
    CAS  PubMed  Google Scholar 

    54.
    Sechman, A. The role of thyroid hormones in regulation of chicken ovarian steroidogenesis. Gen. Comp. Endocrinol. 190, 68–75 (2013).
    CAS  PubMed  Google Scholar 

    55.
    Flood, D. E. K., Fernandino, J. I. & Langlois, V. S. Thyroid hormones in male reproductive develoment: Evidence for direct crosstalk between the androgen and thyroid hormones axes. Gen. Comp. Endocrinol. 192, 2–14 (2013).
    CAS  PubMed  Google Scholar 

    56.
    Duarte-Guterman, P., Navarro-Martín, L. & Trudeau, V. L. Mechanisms of crosstalk between endocrine systems: Regulation of sex steroid hormone synthesis and action by thyroid hormones. Gen. Comp. Endocrinol. 203, 69–85 (2014).
    CAS  PubMed  Google Scholar 

    57.
    Stier, A. et al. How to measure mitochondrial function in birds using red blood cells: A case study in the king penguin and perspectives in ecology and evolution. Methods Ecol. Evol. 8, 1172–1182 (2017).
    Google Scholar  More

  • in

    Increased insect herbivore performance under elevated CO2 is associated with lower plant defence signalling and minimal declines in nutritional quality

    1.
    Gregory, P. J., Johnson, S. N., Newton, A. C. & Ingram, J. S. I. Integrating pests and pathogens into the climate change/food security debate. J. Exp. Bot. 60, 2827–2838 (2009).
    CAS  Article  Google Scholar 
    2.
    Birch, A. N. E., Begg, G. S. & Squire, G. R. How agro-ecological research helps to address food security issues under new IPM and pesticide reduction policies for global crop production systems. J. Exp. Bot. 62, 3251–3261 (2011).
    CAS  Article  Google Scholar 

    3.
    Johnson, S. N. & Jones, T. H. Global Climate Change and Terrestrial Invertebrates (John Wiley & Son Ltd., New York, 2017).
    Google Scholar 

    4.
    Robinson, E. A., Ryan, G. D. & Newman, J. A. A meta-analytical review of the effects of elevated CO2 on plant-arthropod interactions highlights the importance of interacting environmental and biological variables. New Phytol. 194, 321–336 (2012).
    CAS  Article  Google Scholar 

    5.
    Zavala, J. A., Nabity, P. D. & DeLucia, E. H. An emerging understanding of mechanisms governing insect herbivory under elevated CO2. Annu. Rev. Entomol. 58, 79–97 (2013).
    CAS  Article  Google Scholar 

    6.
    Ode, P. J., Johnson, S. N. & Moore, B. D. Atmospheric change and induced plant secondary metabolites—Are we reshaping the building blocks of multi-trophic interactions? Curr. Opin. Ins. Sci. 5, 57–65 (2014).
    Article  Google Scholar 

    7.
    DeLucia, E. H., Nabity, P. D., Zavala, J. A. & Berenbaum, M. R. Climage change: Resetting plant–insect interactions. Plant Physiol. 160, 1677–1685 (2012).
    CAS  Article  Google Scholar 

    8.
    Facey, S. L., Ellsworth, D. S., Staley, J. T., Wright, D. J. & Johnson, S. N. Upsetting the order: How climate and atmospheric change affects herbivore–enemy interactions. Curr. Opin. Insect Sci. 5, 66–74 (2014).
    Article  Google Scholar 

    9.
    Newman, J. A., Anand, M., Henry, H. A. L., Hunt, S. & Gedalof, Z. Climate Change Biology (CABI, 2011).

    10.
    Mattson, W. J. Herbivory in relation to plant nitrogen content. Annu. Rev. Ecol. Syst. 11, 119–161 (1980).
    Article  Google Scholar 

    11.
    Drake, B. G., Gonzalez-Meler, M. A. & Long, S. P. More efficient plants: A consequence of rising atmospheric CO2? Annu. Rev. Plant Physiol. Plant Mol. Biol. 48, 609–639 (1997).
    CAS  Article  Google Scholar 

    12.
    Stiling, P. & Cornelissen, T. How does elevated carbon dioxide (CO2) affect plant–herbivore interactions? A field experiment and meta-analysis of CO2-mediated changes on plant chemistry and herbivore performance. Glob. Change Biol. 13, 1823–1842 (2007).
    ADS  Article  Google Scholar 

    13.
    Pang, J. et al. A new explanation of the N concentration decrease in tissues of rice (Oryza sativa L.) exposed to elevated atmospheric pCO2. Environ. Exp. Bot. 57, 98–105 (2006).

    14.
    Taub, D. R. & Wang, X. Z. Why are nitrogen concentrations in plant tissues lower under elevated CO2? A critical examination of the hypotheses. J. Integr. Plant Biol. 50, 1365–1374 (2008).
    CAS  Article  Google Scholar 

    15.
    Howe, G. A. & Jander, G. Plant immunity to insect herbivores. Annu. Rev. Plant Biol. 59, 41–66 (2008).
    CAS  Article  Google Scholar 

    16.
    Wu, J. Q. & Baldwin, I. T. New insights into plant responses to the attack from insect herbivores. Annu. Rev. Genet. 44, 1–24 (2010).
    CAS  Article  Google Scholar 

    17.
    Erb, M., Meldau, S. & Howe, G. A. Role of phytohormones in insect-specific plant reactions. Trends Plant Sci. 17, 250–259 (2012).
    CAS  Article  Google Scholar 

    18.
    Anderson, C. J. et al. Hybridization and gene flow in the mega-pest lineage of moth, Helicoverpa. Proc. Natl. Acad. Sci. U.S.A. 115, 5034–5039 (2018).
    CAS  Article  Google Scholar 

    19.
    Jones, C. M., Parry, H., Tay, W. T., Reynolds, D. R. & Chapman, J. W. Movement ecology of pest Helicoverpa: Implications for ongoing spread. Annu. Rev. Entomol. 64, 277–295 (2019).
    CAS  Article  Google Scholar 

    20.
    Sharma, H. C. et al. Elevated CO2 influences host plant defense response in chickpea against Helicoverpa armigera. Arthropod-Plant Interact. 10, 171–181 (2016).
    Article  Google Scholar 

    21.
    Khadar, B. A., Prabhuraj, A., Rao, M. S., Sreenivas, A. G. & Naganagoud, A. Influence of elevated CO2 associated with chickpea on growth performance of gram caterpillar, Helicoverpa armigera (HĂŒb.). Appl. Ecol. Environ. Res. 12, 345–353 (2014).

    22.
    Chen, F., Wu, G., Parajulee, M. N. & Ge, F. Long-term impacts of elevated carbon dioxide and transgenic Bt cotton on performance and feeding of three generations of cotton bollworm. Entomol. Exp. Appl. 124, 27–35 (2007).
    Article  Google Scholar 

    23.
    Chen, F. J., Wu, G., Ge, F., Parajulee, M. N. & Shrestha, R. B. Effects of elevated CO2 and transgenic Bt cotton on plant chemistry, performance, and feeding of an insect herbivore, the cotton bollworm. Entomol. Exp. Appl. 115, 341–350 (2005).
    CAS  Article  Google Scholar 

    24.
    Coll, M. & Hughes, L. Effects of elevated CO2 on an insect omnivore: A test for nutritional effects mediated by host plants and prey. Agric. Ecosyst. Environ. 123, 271–279 (2008).
    CAS  Article  Google Scholar 

    25.
    Gang, W., Chen, F. J., Sun, Y. C. & Feng, G. Response of successive three generations of cotton bollworm, Helicoverpa armigera (HĂŒbner), fed on cotton bolls under elevated CO2. J. Environ. Sci. 19, 1318–1325 (2007).
    Article  Google Scholar 

    26.
    Yin, J., Sun, Y. C., Wu, G. & Ge, F. Effects of elevated CO2 associated with maize on multiple generations of the cotton bollworm, Helicoverpa armigera. Entomol. Exp. Appl. 136, 12–20 (2010).
    CAS  Article  Google Scholar 

    27.
    Wu, G., Chen, F. J. & Ge, F. Response of multiple generations of cotton bollworm Helicoverpa armigera HĂŒbner, feeding on spring wheat, to elevated CO2. J. Appl. Entomol. 130, 2–9 (2006).
    Article  Google Scholar 

    28.
    Hall, C. R., Mikhael, M., Hartley, S. E. & Johnson, S. N. Elevated atmospheric CO2 suppresses jasmonate and silicon-based defences without affecting herbivores. Funct. Ecol. 34, 993–1002 (2020).
    Article  Google Scholar 

    29.
    Guo, H. J. et al. Elevated CO2 reduces the resistance and tolerance of tomato plants to Helicoverpa armigera by suppressing the JA signaling pathway. PloS One 7, e41426, https://doi.org/10.1371/journal.pone.0041426 (2012).

    30.
    Soussana, J. F. & Hartwig, U. A. The effects of elevated CO2 on symbiotic N2 fixation: A link between the carbon and nitrogen cycles in grassland ecosystems. Plant Soil 187, 321–332 (1996).
    CAS  Article  Google Scholar 

    31.
    Johnson, S. N., Gherlenda, A. N., Frew, A. & Ryalls, J. M. W. The importance of testing multiple environmental factors in legume-insect research: Replication, reviewers and rebuttal. Front. Plant Sci. 7, 489, https://doi.org/10.3389/fpls.2016.00489 (2016).

    32.
    Guo, H. et al. Pea aphid promotes amino acid metabolism both in Medicago truncatula and bacteriocytes to favor aphid population growth under elevated CO2. Global Change Biol. 19, 3210–3223 (2013).
    ADS  Article  Google Scholar 

    33.
    Johnson, S. N., Ryalls, J. M. W. & Karley, A. J. Global climate change and crop resistance to aphids: contrasting responses of lucerne genotypes to elevated atmospheric carbon dioxide. Ann. Appl. Biol. 165, 62–72 (2014).
    CAS  Article  Google Scholar 

    34.
    Deng, Y. & Lu, S. Biosynthesis and regulation of phenylpropanoids in plants. Crit. Rev. Plant Sci. 36, 257–290 (2017).
    Article  Google Scholar 

    35.
    Winter, G., Todd, C. D., Trovato, M., Forlani, G. & Funck, D. Physiological implications of arginine metabolism in plants. Front. Plant Sci. 6, 534, https://doi.org/10.3389/fpls.2015.00534 (2015).

    36.
    Schortemeyer, M., Hartwig, U. A., Hendrey, G. R. & Sadowsky, M. J. Microbial community changes in the rhizospheres of white clover and perennial ryegrass exposed to Free Air Carbon dioxide Enrichment (FACE). Soil Biol. Biochem. 28, 1717–1724 (1996).
    CAS  Article  Google Scholar 

    37.
    Ryle, G. J. A. & Powell, C. E. The influence of elevated CO2 and temperature on biomass production of continuously defoliated white clover. Plant Cell Environ. 15, 593–599 (1992).
    CAS  Article  Google Scholar 

    38.
    Norby, R. J. Nodulation and nitrogenase activity in nitrogen-fixing woody plants stimulated by CO2 enrichment of the atmosphere. Physiol. Plantarum 71, 77–82 (1987).
    CAS  Article  Google Scholar 

    39.
    Edwards, E. J., McCaffery, S. & Evans, J. R. Phosphorus availability and elevated CO2 affect biological nitrogen fixation and nutrient fluxes in a clover-dominated sward. New Phytol. 169, 157–167 (2006).
    CAS  Article  Google Scholar 

    40.
    Goodspeed, D., Chehab, E. W., Min-Venditti, A., Braam, J. & Covington, M. F. Arabidopsis synchronizes jasmonate-mediated defense with insect circadian behavior. Proc. Natl. Acad. Sci. U.S.A. 109, 4674–4677 (2012).
    ADS  CAS  Article  Google Scholar 

    41.
    Thaler, J. S., Humphrey, P. T. & Whiteman, N. K. Evolution of jasmonate and salicylate signal crosstalk. Trends Plant Sci. 17, 260–270 (2012).
    CAS  Article  Google Scholar 

    42.
    IPCC. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2014).

    43.
    Teakle, R. E. & Jensen, J. M. in Handbook of Insect Rearing, Vol. 2 (eds R. Singh & R.F. Moore) 312–322 (Elsevier, London, 1985).

    44.
    Jones, C. G., Hare, J. D. & Compton, S. J. Measuring plant protein with the Bradford assay. 1. Evaluation and standard method. J. Chem. Ecol. 15, 979–992 (1989).

    45.
    Bradford, M. M. Rapid and sensitive method for quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254 (1976).
    CAS  Article  Google Scholar 

    46.
    Furota, S., Ogawa, N. O., Takano, Y., Yoshimura, T. & Ohkouchi, N. Quantitative analysis of underivatized amino acids in the sub- to several-nanomolar range by ion-pair HPLC using a corona-charged aerosol detector (HPLC-CAD). J. Chromatogr. B 1095, 191–197 (2018).
    CAS  Article  Google Scholar 

    47.
    Bligh, E. G. & Dyer, W. J. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917 (1959).
    CAS  Article  Google Scholar 

    48.
    Viechtbauer, W. Conducting meta-analyses in R with the metafor Package. J. Stat. Softw. 36, 1–48 (2010).
    Article  Google Scholar 

    49.
    Hedges, L. V. & Olkin, I. Statistical Methods for Meta-Analysis (Academic Press, New York, 1985). More

  • in

    Application of image processing to evidence for the persistence of the Ivory-billed Woodpecker (Campephilus principalis)

    The videos were imported from digital videotapes using iMovie 4 and iMovie HD 6.0.3. They were deinterlaced using JES Deinterlacer 3.8.4. Images are processed here using QuickTime Player 7.3.3, GraphicConverter 8.8.3, and GIMP 2.10. Within these applications, it is possible to interpolate and adjust brightness, contrast, color, and other parameters. The simple processing applied here is effective for some cases. With advanced processing techniques that involve greater control and analysis of parameters, experts in image processing might be able to extract additional information.
    The 2006 video
    The first video was obtained from a kayak with a Sony DCR-HC36 standard video camera (which captures interlaced video at 720 × 480 pixels) in the Pearl River swamp in Louisiana on February 20, 2006, in an area along English Bayou where there were five sightings that week; the ‘kent’ calls of the Ivory-billed Woodpecker were heard twice during the same period, once coming simultaneously from different directions. The 2006 video shows a large woodpecker perched on a tree, climbing upward, taking a short flight between limbs, and then taking off into a longer flight. Part of the perch tree, which includes two forks that facilitated scaling, was used in the size comparison in Fig. 2; the bird in the video appears to be larger than a Pileated Woodpecker specimen8. According to Julie Zickefoose, whose paintings of the Ivory-billed Woodpecker have appeared on the covers of the January 2006 issue of the Auk and both editions of Ref.3, the “long but fluffy and squared-off crest,” “extremely long, erect head and neck,” “large, long bill,” “bill to head proportions,” “rared-back pose,” “long and thin” wings, “flapping leap” between limbs, and “ponderous and heavy” flight are suggestive of the Ivory-billed Woodpecker but not the Pileated Woodpecker13.
    Figure 2

    A pileated Woodpecker specimen is mounted on part of the perch tree. Frames from the 2006 video were scaled using forks in the tree (dashed lines). A meter stick is placed at the point where the flight between limbs occurred. The inset shows Pileated Woodpecker and Ivory-billed Woodpecker specimens that were photographed side by side at the National Museum of Natural History. The bird in the video is partially hidden by vegetation in the image on the lower left, but it is fully in view in the images at the top when it took the flight between limbs.

    Full size image

    The 2008 video
    A short distance up the same bayou, another video was obtained with the same camera on March 29, 2008, from 23 m up a tree that was used as an observation platform for keeping watch for Ivory-billed Woodpeckers flying over the treetops in the distance. A large bird that flew along the bayou and passed below was identified as an Ivory-billed Woodpecker on the basis of two white stripes on the back and black leading edges and white trailing edges on the dorsal surfaces of the wings (those definitive field marks were observed from an ideal vantage point at close range and nearly directly above). The appearance in the video of the bird, its reflection from the still surface of the bayou, and reference objects made it possible to determine positions along the flight path and obtain estimates of the flight speed and wingspan. The bird in the 2008 video folded its wings closed during the middle of each upstroke as illustrated in Fig. 3. The two large woodpeckers are the only large birds north of the Rio Grande that have this distinctive wing motion, which is clearly resolved in the video. Using an approach that he had previously developed and applied to other woodpeckers17, Bret Tobalske, an expert on woodpecker flight mechanics, digitized the horizontal and vertical motions of the wingtips and concluded that the bird in the video is a large woodpecker13. The flap rate of the bird in the video is about ten standard deviations greater than the mean flap rate of the Pileated Woodpecker13.
    Figure 3

    Illustrations of large woodpeckers in flight. Left: The Pileated Woodpecker typically swoops upward a short distance before landing on a surface that faces the direction of approach; the Ivory-billed Woodpecker has long vertical ascents that allow time for maneuvering and landing on surfaces that do not face the direction of approach. Center: An Ivory-billed Woodpecker takes off with rapid wingbeats into a horizontal flight that quickly transitions into an upward swooping flight. Right: Illustration of a flight in the Pearl River swamp on March 29, 2008, that was viewed from 23 m up in a cypress tree. When the wings are folded closed in flight, the dorsal stripes and the white triangular patch have the same appearance as they do for the perched birds in Fig. 1. As discussed in Movie S6 of Ref.8, the wings of an Ivory-billed Woodpecker in a historical photo and of the bird in the 2008 video have the swept-back appearance of the wings in the middle image.

    Full size image

    Additional characteristics of the bird in the video that are consistent with the Ivory-billed Woodpecker but not the Pileated Woodpecker are the high flight speed, narrow wings, swept back wings, and prominent white patches on the dorsal surfaces of the wings8,13. There is one characteristic of the bird in the video that was initially thought to be inconsistent with the Ivory-billed Woodpecker. On the basis of historical accounts of a ‘duck-like’ flight, the Ivory-billed Woodpecker was thought to have a duck-like wing motion in which the wings remain extended throughout the flap cycle. In a series of paintings of the large woodpeckers in flight by Zickefoose18, the wings of the Pileated Woodpecker are correctly shown folding closed during the middle of the upstroke; in a proper representation of conventional wisdom at the time, the wings of the Ivory-billed Woodpecker are shown remaining extended throughout the flap cycle (duck-like flaps). An apparent paradox arose during the initial inspection of the video, which revealed an unexpected wing motion. The paradox was resolved after the discovery that a photo from 1939 shows an Ivory-billed Woodpecker in flight at an instant when the wings are nearly folded closed13.
    The 2007 video
    The other video was obtained with a Sony HDR-HC3 high-definition video camera (which captures interlaced video at 1,440 × 1,080 pixels) that was mounted on kayak paddles8 in the Choctawhatchee River swamp in Florida on January 19, 2007, in an area where an ornithologist and his colleagues had recently reported a series of sightings7. During an encounter with a pair of birds that were identified as Ivory-billed Woodpeckers on the basis of field marks and remarkable swooping flights, the camera captured a series of events that involve flights, field marks, and other behaviors and characteristics that are consistent with the Ivory-billed Woodpecker but no other species of the region. The analysis of the 2007 video is based in part on the fact that the probability of a series of unlikely events becomes extremely small as the number of events increases12. There is a downward swooping takeoff with a long horizontal glide that is consistent with the following account by Audubon15: “The transit from one tree to another, even should the distance be as much as a hundred yards, is performed by a single sweep, and the bird appears as if merely swinging from the top of the one tree to that of the other, forming an elegantly curved line.” There are upward swooping landings with long vertical ascents that are not consistent with the Pileated Woodpecker but are consistent with an account by Eckleberry of an Ivory-billed Woodpecker that “alighted with one magnificent upward swoop”19.
    A long vertical ascent allows time for maneuvering, and the bird appears to rotate about its axis during two of the ascents as illustrated in Fig. 3. In a film of the closely related Magellanic Woodpecker (Campephilus magellanicus)20, there is maneuvering during a landing with a long vertical ascent. During and after one of the ascents, a woodpecker in the 2007 video shows field marks and body proportions that are consistent with the Ivory-billed Woodpecker but no other species of the region. There is a takeoff into horizontal flight with deep and rapid flaps that are not consistent with the Pileated Woodpecker but are similar to the deep and rapid flaps during a takeoff of the closely related Imperial Woodpecker (Campephilus imperialis)21. In another event, a woodpecker climbs upward and engages in a series of behaviors that are consistent with the Ivory-billed Woodpecker but no other species of the region, including delivering a blow that produces an audible double knock and taking off with rapid wingbeats into a flight that immediately transitions into an upward swooping flight that is illustrated in Fig. 3. More

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    Evolution of diversity explains the impact of pre-adaptation of a focal species on the structure of a natural microbial community

    1.
    Hairston NG Jr, Ellner SP, Geber MA, Yoshida T, Fox JA. Rapid evolution and the convergence of ecological and evolutionary time. Ecol Lett. 2005;8:1114–27.
    Google Scholar 
    2.
    Ellner SP, Geber MA, Hairston NG Jr. Does rapid evolution matter? Measuring the rate of contemporary evolution and its impacts on ecological dynamics. Ecol Lett. 2011;14:603–14.
    PubMed  Google Scholar 

    3.
    GĂłmez P, Paterson S, De Meester L, Liu X, Lenzi L, Sharma MD, et al. Local adaptation of a bacterium is as important as its presence in structuring a natural microbial community. Nat Commun. 2016;7:12453.
    PubMed  PubMed Central  Google Scholar 

    4.
    Buckling A, Craig Maclean R, Brockhurst MA, Colegrave N. The beagle in a bottle. Nature. 2009;457:824–9.
    CAS  PubMed  Google Scholar 

    5.
    Gómez P, Buckling A. Real-time microbial adaptive diversification in soil. Ecol Lett. 2013;16:650–5.
    PubMed  Google Scholar 

    6.
    Lawrence D, Fiegna F, Behrends V, Bundy JG, Phillimore AB, Bell T, et al. Species interactions alter evolutionary responses to a novel environment. PLoS Biol. 2012;10:e1001330.
    CAS  PubMed  PubMed Central  Google Scholar 

    7.
    Lankau RA. Rapid evolutionary change and the coexistence of species. Annu Rev Ecol Evol Syst. 2011;42:335–54.
    Google Scholar 

    8.
    Pantel JH, Duvivier C, Meester LD. Rapid local adaptation mediates zooplankton community assembly in experimental mesocosms. Ecol Lett. 2015;18:992–1000.
    PubMed  Google Scholar 

    9.
    Hart SP, Turcotte MM, Levine JM. Effects of rapid evolution on species coexistence. Proc Natl Acad Sci. 2019;116:2112–7.
    CAS  PubMed  Google Scholar 

    10.
    Rainey PB, Travisano M. Adaptive radiation in a heterogeneous environment. Nature. 1998;394:69.
    CAS  PubMed  Google Scholar 

    11.
    Hughes AR, Inouye BD, Johnson MT, Underwood N, Vellend M. Ecological consequences of genetic diversity. Ecol Lett. 2008;11:609–23.
    PubMed  Google Scholar 

    12.
    Bolnick DI, Amarasekare P, AraĂșjo MS, BĂŒrger R, Levine JM, Novak M, et al. Why intraspecific trait variation matters in community ecology. Trends Ecol evolution. 2011;26:183–92.
    Google Scholar 

    13.
    Violle C, Enquist BJ, McGill BJ, Jiang LIN, Albert CH, Hulshof C, et al. The return of the variance: intraspecific variability in community ecology. Trends Ecol Evol. 2012;27:244–52.
    PubMed  Google Scholar 

    14.
    Bolnick DI, Ingram T, Stutz WE, Snowberg LK, Lau OL, Paull JS. Ecological release from interspecific competition leads to decoupled changes in population and individual niche width. Proc R Soc B Biol Sci. 2010;277:1789–97.
    Google Scholar 

    15.
    Bailey SF, Dettman JR, Rainey PB, Kassen R. Competition both drives and impedes diversification in a model adaptive radiation. Proc R Soc B Biol Sci. 2013;280:20131253.
    Google Scholar 

    16.
    Jousset A, Eisenhauer N, Merker M, Mouquet N, Scheu S. High functional diversity stimulates diversification in experimental microbial communities. Sci Adv. 2016;2:e1600124.
    PubMed  PubMed Central  Google Scholar 

    17.
    Schluter D. Experimental evidence that competition promotes divergence in adaptive radiation. Science. 1994;266:798–801.
    CAS  PubMed  Google Scholar 

    18.
    Ellis CN, Traverse CC, Mayo-Smith L, Buskirk SW, Cooper VS. Character displacement and the evolution of niche complementarity in a model biofilm community. Evolution. 2015;69:283–93.
    PubMed  PubMed Central  Google Scholar 

    19.
    Zee PC, Fukami T. Priority effects are weakened by a short, but not long, history of sympatric evolution. Proc R Soc B Biol Sci. 2018;285:20171722.
    Google Scholar 

    20.
    Schluter D. Ecological character displacement in adaptive radiation. Am Nat. 2000;156:S4–S16.
    Google Scholar 

    21.
    Urban MC, De Meester L. Community monopolization: local adaptation enhances priority effects in an evolving metacommunity. Proc R Soc B Biol Sci. 2009;276:4129–38.
    Google Scholar 

    22.
    De Meester L, Vanoverbeke J, Kilsdonk LJ, Urban MC. Evolving perspectives on monopolization and priority effects. Trends Ecol Evol. 2016;31:136–46.
    PubMed  Google Scholar 

    23.
    LujĂĄn AM, GĂłmez P, Buckling A. Siderophore cooperation of the bacterium Pseudomonas fluorescens in soil. Biol Lett. 2015;11:20140934.
    PubMed  PubMed Central  Google Scholar 

    24.
    O’Brien S, Hesse E, Luján A, Hodgson DJ, Gardner A, Buckling A. No effect of intraspecific relatedness on public goods cooperation in a complex community. Evolution. 2018;72:1165–73.
    PubMed  PubMed Central  Google Scholar 

    25.
    Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17:10–12.
    Google Scholar 

    26.
    Li H Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv preprint arXiv:13033997 2013.

    27.
    Garrison E, Marth G Haplotype-based variant detection from short-read sequencing. arXiv preprint arXiv:12073907 2012.

    28.
    Garrison E Vcflib: A C++ library for parsing and manipulating VCF files. GitHub https://www.githubcom/ekg/vcflib 2012.

    29.
    Callahan BJ, Sankaran K, Fukuyama JA, McMurdie PJ, Holmes SP Bioconductor workflow for microbiome data analysis: from raw reads to community analyses. F1000Research 2016;5:1492.

    30.
    Maidak BL, Cole JR, Lilburn TG, Parker CT Jr, Saxman PR, Stredwick JM, et al. The RDP (ribosomal database project) continues. Nucleic Acids Res. 2000;28:173–4.
    CAS  PubMed  PubMed Central  Google Scholar 

    31.
    Schliep KP. phangorn: phylogenetic analysis in R. Bioinformatics. 2010;27:592–3.
    PubMed  PubMed Central  Google Scholar 

    32.
    Hall AR, Colegrave N. How does resource supply affect evolutionary diversification? Proc R Soc B Biol Sci. 2006;274:73–78.
    Google Scholar 

    33.
    Venail PA, MacLean RC, Bouvier T, Brockhurst MA, Hochberg ME, Mouquet N. Diversity and productivity peak at intermediate dispersal rate in evolving metacommunities. Nature. 2008;452:210.
    CAS  PubMed  Google Scholar 

    34.
    Robertson A. Experimental design on the measurement of heritabilities and genetic correlations: biometrical genetics. Biometrics. 1959;15:219–26.
    Google Scholar 

    35.
    Barrett RD, MacLean RC, Bell G. Experimental evolution of pseudomonas fluorescens in simple and complex environments. Am Naturalist. 2005;166:470–80.
    Google Scholar 

    36.
    Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B (Methodol). 1995;57:289–300.
    Google Scholar 

    37.
    Lozupone C, Lladser ME, Knights D, Stombaugh J, Knight R. UniFrac: an effective distance metric for microbial community comparison. ISME J. 2011;5:169–72.
    PubMed  Google Scholar 

    38.
    McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. 2013;8:e61217.
    CAS  PubMed  PubMed Central  Google Scholar 

    39.
    Oksanen J, Kindt R, Legendre P, O’Hara B, Stevens MHH, Oksanen MJ, et al. The vegan package. Community Ecol Package. 2007;10:631–7.
    Google Scholar 

    40.
    Paradis E, Schliep K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics. 2019;35:526–8.
    CAS  PubMed  Google Scholar 

    41.
    Cailliez F. The analytical solution of the additive constant problem. Psychometrika. 1983;48:305–8.
    Google Scholar 

    42.
    Love M, Anders S, Huber W. Differential analysis of count data–the DESeq2 package. Genome Biol. 2014;15:10–1186.
    Google Scholar 

    43.
    McMurdie PJ, Holmes S. Waste not, want not: why rarefying microbiome data is inadmissible. PLoS computational Biol. 2014;10:e1003531.
    Google Scholar 

    44.
    Jombart T, Balloux F, Dray S. Adephylo: new tools for investigating the phylogenetic signal in biological traits. Bioinformatics. 2010;26:1907–9.
    CAS  PubMed  Google Scholar 

    45.
    Lenth R Emmeans: Estimated marginal means, aka least-squares means. R Package Version 2018; 1.

    46.
    R Core Team. R: A language and environment for statistical computing. 2013.

    47.
    Wickham H ggplot2: elegant graphics for data analysis. 2016. Springer.

    48.
    Vellend M. The consequences of genetic diversity in competitive communities. Ecology. 2006;87:304–11.
    PubMed  Google Scholar 

    49.
    Hunt DE, David LA, Gevers D, Preheim SP, Alm EJ, Polz MF. Resource partitioning and sympatric differentiation among closely related bacterioplankton. Science. 2008;320:1081–5.
    CAS  PubMed  Google Scholar 

    50.
    Narwani A, Alexandrou MA, Herrin J, Vouaux A, Zhou C, Oakley TH, et al. Common ancestry is a poor predictor of competitive traits in freshwater green algae. PLoS ONE. 2015;10:e0137085.
    PubMed  PubMed Central  Google Scholar 

    51.
    Buckling A, Kassen R, Bell G, Rainey PB. Disturbance and diversity in experimental microcosms. Nature. 2000;408:961.
    CAS  PubMed  Google Scholar 

    52.
    Castledine M, Buckling A, Padfield D. A shared coevolutionary history does not alter the outcome of coalescence in experimental populations of Pseudomonas fluorescens. J Evol Biol. 2019;32:58–65.
    CAS  PubMed  Google Scholar  More

  • in

    Mass mortality in freshwater mussels (Actinonaias pectorosa) in the Clinch River, USA, linked to a novel densovirus

    1.
    Vaughn, C. C. Ecosystem services provided by freshwater mussels. Hydrobiologia 810, 15–27. https://doi.org/10.1007/s10750-017-3139-x (2018).
    Article  Google Scholar 
    2.
    Christian, A. D., Smith, B. N., Berg, D. J., Smoot, J. C. & Findlay, R. H. Trophic position and potential food sources of 2 species of unionid bivalves (Mollusca:Unionidae) in 2 small Ohio streams. Freshw. Sci. 23, 101–113 (2004).
    Google Scholar 

    3.
    Vaughn, C. C. Biodiversity losses and ecosystem function in freshwaters: emerging conclusions and research directions. Bioscience 60, 25–35. https://doi.org/10.1525/bio.2010.60.1.7 (2010).
    Article  Google Scholar 

    4.
    Howard, J. K. & Cuffey, K. M. The functional role of native freshwater mussels in the fluvial benthic environment. Freshw. Biol. 51, 460–474. https://doi.org/10.1111/j.1365-2427.2005.01507.x (2006).
    Article  Google Scholar 

    5.
    Izumi, T., Yagita, K., Izumiyama, S., Endo, T. & Itoh, Y. Depletion of Cryptosporidium parvum oocysts from contaminated sewage by using freshwater benthic pearl clams (Hyriopsis schlegeli). Appl. Environ. Microbiol. 78, 7420–7428. https://doi.org/10.1128/AEM.01502-12 (2012).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    6.
    Ismail, N. S., MĂŒller, C. E., Morgan, R. R. & Luthy, R. G. Uptake of contaminants of emerging concern by the bivalves Anodonta californiensis and Corbicula fluminea. Environ. Sci. Technol. 48, 9211–9219. https://doi.org/10.1021/es5011576 (2014).
    ADS  CAS  Article  PubMed  Google Scholar 

    7.
    Ismail, N. S. et al. Improvement of urban lake water quality by removal of Escherichia coli through the action of the bivalve Anodonta californiensis. Environ. Sci. Technol. 49, 1664–1672. https://doi.org/10.1021/es5033212 (2015).
    ADS  CAS  Article  PubMed  Google Scholar 

    8.
    Williams, J. D. et al. A revised list of the freshwater mussels (Mollusca: Bivalvia: Unionida) of the United States and Canada. Freshw. Mollusk Biol. Conserv. 20, 33. https://doi.org/10.31931/fmbc.v20i2.2017.33-58 (2017).
    Article  Google Scholar 

    9.
    Lydeard, C. et al. The global decline of nonmarine mollusks. Bioscience 54, 321. https://doi.org/10.1641/0006-3568(2004)054[0321:TGDONM]2.0.CO;2 (2004).
    Article  Google Scholar 

    10.
    Haag, W. R. North American Freshwater Mussels: Natural History, Ecology, and Conservation (Cambridge University Press, Cambridge, 2012).
    Google Scholar 

    11.
    Strayer, D. L. Effects of alien species on freshwater mollusks in North America. J. N. Am. Benthol. Soc. 18, 74–98. https://doi.org/10.2307/1468010 (1999).
    Article  Google Scholar 

    12.
    Haag, W. R. Reassessing enigmatic mussel declines in the United States. Freshw. Mollusk Biol. Conserv. 22, 43–60 (2019).
    Article  Google Scholar 

    13.
    Goldberg, T. L., Dunn, C. D., Leis, E. & Waller, D. L. A novel picornalike virus in a Wabash Pigtoe (Fusconaia flava) from the Upper Mississippi River, USA. Freshw. Mollusk Biol. Conserv. 22, 81–84 (2019).
    Google Scholar 

    14.
    Downing, J. A., Van Meter, P. & Woolnough, D. A. Suspects and evidence: a review of the causes of extirpation and decline in freshwater mussels. Anim. Biodivers. Conserv. 33, 151–185 (2010).
    Google Scholar 

    15.
    Zipper, C. E. et al. Freshwater mussel population status and habitat quality in the Clinch Rver, Virginia and Tennessee, USA: a featured collection. J. Am. Water Resour. Assoc. 50, 807–819 (2014).
    ADS  Article  Google Scholar 

    16.
    Jones, J. et al. Clinch River freshwater mussels upstream of Norris Reservoir, Tennessee and Virginia: a quantitative assessment from 2004 to 2009. J. Am. Water Resour. Assoc. 50, 820–836. https://doi.org/10.1111/jawr.12222 (2014).
    ADS  Article  Google Scholar 

    17.
    Jones, J. W. et al. Collapse of the Pendleton Island mussel fauna in the Clinch River, Virginia: setting baseline conditions to guide recovery and restoration. Freshw. Mollusk Biol. Conserv. 21, 36–56 (2018).
    Google Scholar 

    18.
    Cope, W. G. & Jones, J. W. Recent precipitous declines of endangered freshwater mussels in the Clinch River: an in situ assessment of water quality stressors related to energy development and other land-use. 244 (U.S. Fish and Wildlife Service, Southwestern Virginia Field Office, 2016).

    19.
    Richard, J. C. Clinch River mussel die-off. Ellipsaria 20, 1–3 (2018).
    Google Scholar 

    20.
    Neves, R. J. Proceedings of the Workshop on Die-offs of Freshwater Mussels in the United States (U.S. Fish and Wildlife Service, Upper Mississippi River Conservation Committee, 1986).

    21.
    Starliper, C. E., Powell, J., Garner, J. T. & Schill, W. B. Predominant bacteria isolated from moribund Fusconaia ebena ebonyshells experiencing die-offs in Pickwick Reservoir, Tennessee River, Alabama. J. Shellfish Res. 30, 359–366. https://doi.org/10.2983/035.030.0223 (2011).
    Article  Google Scholar 

    22.
    Grizzle, J. M. & Brunner, C. J. Infectious diseases of freshwater mussels and other freshwater bivalve mollusks. Rev. Fish. Sci. 17, 425–467 (2009).
    Article  Google Scholar 

    23.
    Leis, E. et al. Building a response network to investigate potential pathogens associated with unionid mortality events. Ellipsaria 20, 44–45 (2018).
    Google Scholar 

    24.
    Henley, W. F., Beaty, B. B. & Jones, J. W. Evaluations of organ tissues from Actinonaias pectorosa collected during a mussel die-off in 2016 at Kyles Ford, Clinch River, Tennessee. J. Shellfish Res. 38, 681. https://doi.org/10.2983/035.038.0320 (2019).
    Article  Google Scholar 

    25.
    Leis, E., Erickson, S., Waller, D., Richard, J. & Goldberg, T. A comparison of bacteria cultured from unionid mussel hemolymph between stable populations in the Upper Mississippi River basin and populations affected by a mortality event in the Clinch River. Freshw. Mollusk Biol. Conserv. 22, 70–80 (2019).
    Google Scholar 

    26.
    Garcia, C. et al. Ostreid herpesvirus 1 detection and relationship with Crassostrea gigas spat mortality in France between 1998 and 2006. Vet. Res. 42, 73. https://doi.org/10.1186/1297-9716-42-73 (2011).
    ADS  Article  PubMed  PubMed Central  Google Scholar 

    27.
    Arzul, I., Corbeil, S., Morga, B. & Renault, T. Viruses infecting marine molluscs. J. Invertebr. Pathol. 147, 118–135. https://doi.org/10.1016/j.jip.2017.01.009 (2017).
    Article  PubMed  Google Scholar 

    28.
    Zhang, Z., Sufang, D., Yimin, X. & Jie, W. Studies on the mussel Hyriopsis cumingii plague. I. a new viral infectious disease. Acta Hydrobiol. Sin. 26, 308–312 (1986).
    Google Scholar 

    29.
    Zhong, L., Xiao, T.-Y., Huang, J., Dai, L.-Y. & Liu, X.-Y. Histopathological examination of bivalve mussel Hyriopsis cumingii lea artificially infected by virus. Acta Hydrobiol. Sin. 35, 666–671 (2011).
    Google Scholar 

    30.
    Shi, M. et al. Redefining the invertebrate RNA virosphere. Nature 540, 539–543. https://doi.org/10.1038/nature20167 (2016).
    ADS  CAS  Article  PubMed  Google Scholar 

    31.
    Zhang, Y. Z., Shi, M. & Holmes, E. C. Using metagenomics to characterize an expanding vrosphere. Cell 172, 1168–1172. https://doi.org/10.1016/j.cell.2018.02.043 (2018).
    CAS  Article  PubMed  Google Scholar 

    32.
    Bergoin, M. & Tijssen, P. Molecular biology of Densovirinae. Contrib. Microbiol. 4, 12–32. https://doi.org/10.1159/000060329 (2000).
    CAS  Article  PubMed  Google Scholar 

    33.
    Mietzsch, M., Penzes, J. J. & Agbandje-McKenna, M. Twenty-five years of structural parvovirology. Viruses https://doi.org/10.3390/v11040362 (2019).
    Article  PubMed  PubMed Central  Google Scholar 

    34.
    Cotmore, S. F. et al. ICTV virus taxonomy profile: Parvoviridae. J. Gen. Virol. 100, 367–368. https://doi.org/10.1099/jgv.0.001212 (2019).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    35.
    Ganesh, B., Masachessi, G. & Mladenova, Z. Animal picobirnavirus. Virus Dis. 25, 223–238. https://doi.org/10.1007/s13337-014-0207-y (2014).
    Article  Google Scholar 

    36.
    Gustafson, L. L. et al. Evaluation of a nonlethal technique for hemolymph collection in Elliptio complanata, a freshwater bivalve (Mollusca: Unionidae). Dis. Aquat. Organ. 65, 159–165. https://doi.org/10.3354/dao065159 (2005).
    Article  PubMed  Google Scholar 

    37.
    Lees, D. Viruses and bivalve shellfish. Int. J. Food Microbiol. 59, 81–116. https://doi.org/10.1016/S0168-1605(00)00248-8 (2000).
    CAS  Article  PubMed  Google Scholar 

    38.
    Faust, C., Stallknecht, D., Swayne, D. & Brown, J. Filter-feeding bivalves can remove avian influenza viruses from water and reduce infectivity. Proc. R. Soc. B 276, 3727–3735. https://doi.org/10.1098/rspb.2009.0572 (2009).
    Article  PubMed  Google Scholar 

    39.
    FĂ©diĂšre, G. in Parvoviruses. From Molecular Biology to Pathology and Therapeutic Uses. Contributions to Microbiology. Vol. 4 (eds S. Faisst & J. Rommelaere) 1–11 (Karger, 2000).

    40.
    Kalagayan, H. et al. IHHN virus as an etiological factor in runt-deformity syndrome (RDS) of juvenile Penaeus vannamei cultured in Hawaii. J. World Aquacult. Soc. 22, 235–243. https://doi.org/10.1111/j.1749-7345.1991.tb00740.x (1991).
    Article  Google Scholar 

    41.
    Ito, K., Kidokoro, K., Shimura, S., Katsuma, S. & Kadono-Okuda, K. Detailed investigation of the sequential pathological changes in silkworm larvae infected with Bombyx densovirus type 1. J. Invertebr. Pathol. 112, 213–218. https://doi.org/10.1016/j.jip.2012.12.005 (2013).
    Article  PubMed  Google Scholar 

    42.
    Jiang, H. et al. Genetic engineering of Periplaneta fuliginosa densovirus as an improved biopesticide. Arch. Virol. 152, 383–394. https://doi.org/10.1007/s00705-006-0844-6 (2007).
    CAS  Article  PubMed  Google Scholar 

    43.
    Ledermann, J. P., Suchman, E. L., Black, W. C. & Carlson, J. O. Infection and pathogenicity of the mosquito densoviruses AeDNV, HeDNV, and APeDNV in Aedes aegypti mosquitoes (Diptera: Culicidae). J. Econ. Entomol. 97, 1828–1835. https://doi.org/10.1093/jee/97.6.1828 (2004).
    Article  PubMed  Google Scholar 

    44.
    Szelei, J. et al. Susceptibility of North-American and European crickets to Acheta domesticus densovirus (AdDNV) and associated epizootics. J. Invertebr. Pathol. 106, 394–399. https://doi.org/10.1016/j.jip.2010.12.009 (2011).
    CAS  Article  PubMed  Google Scholar 

    45.
    Kouassi, N. et al. Pathogenicity of diatraea saccharalis densovirus to host insets and characterization of its viral genome. Virol. Sin. 22, 53–60. https://doi.org/10.1007/s12250-007-0062-8 (2007).
    CAS  Article  Google Scholar 

    46.
    Bowater, R. et al. A parvo-like virus in cultured redclaw crayfish Cherax quadricarinatus from Queensland, Australia. Dis. Aquat. Organ. 50, 79–86. https://doi.org/10.3354/dao050079 (2002).
    Article  PubMed  Google Scholar 

    47.
    Johnson, R. M. & Rasgon, J. L. Densonucleosis viruses (‘densoviruses’) for mosquito and pathogen control. Curr. Opin. Insect. Sci. 28, 90–97. https://doi.org/10.1016/j.cois.2018.05.009 (2018).
    Article  PubMed  Google Scholar 

    48.
    Hewson, I. et al. Densovirus associated with sea-star wasting disease and mass mortality. Proc. Natl. Acad. Sci. USA 111, 17278–17283. https://doi.org/10.1073/pnas.1416625111 (2014).
    ADS  CAS  Article  PubMed  Google Scholar 

    49.
    Fritts, A. K., Peterson, J. T., Hazelton, P. D. & Bringolf, R. B. Evaluation of methods for assessing physiological biomarkers of stress in freshwater mussels. Can. J. Fish. Aquat. Sci. 72, 1450–1459. https://doi.org/10.1139/cjfas-2014-0564 (2015).
    CAS  Article  Google Scholar 

    50.
    Cunningham, A. A., Daszak, P. & Wood, J. L. N. One health, emerging infectious diseases and wildlife: two decades of progress?. Philos. Trans. R. Soc. Lond. B https://doi.org/10.1098/rstb.2016.0167 (2017).
    Article  Google Scholar 

    51.
    Patterson, M. A. et al. Freshwater Mussel Propagation for Restoration (Cambridge University Press, Cambridge, 2018).
    Google Scholar 

    52.
    Toohey-Kurth, K., Sibley, S. D. & Goldberg, T. L. Metagenomic assessment of adventitious viruses in commercial bovine sera. Biologicals 47, 64–68. https://doi.org/10.1016/j.biologicals.2016.10.009 (2017).
    CAS  Article  PubMed  Google Scholar 

    53.
    Löytynoja, A. Phylogeny-aware alignment with PRANK. Methods Mol. Biol. 1079, 155–170. https://doi.org/10.1007/978-1-62703-646-7_10 (2014).
    Article  PubMed  Google Scholar 

    54.
    Talavera, G. & Castresana, J. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst. Biol. 56, 564–577. https://doi.org/10.1080/10635150701472164 (2007).
    CAS  Article  PubMed  Google Scholar 

    55.
    Abascal, F., Zardoya, R. & Telford, M. TranslatorX: multiple alignment of nucleotide sequences guided by amino acid translations. Nucleic Acids Res. 38, W7-13. https://doi.org/10.1093/nar/gkq291 (2010).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    56.
    Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321. https://doi.org/10.1093/sysbio/syq010 (2010).
    CAS  Article  Google Scholar 

    57.
    R Core Team. R: A language and environment for statistical computing, version 3.6.3. https://www.R-project.org (R Foundation for Statistical Computing, Vienna, 2019). More

  • in

    Repellent, oviposition-deterrent, and insecticidal activity of the fungal pathogen Colletotrichum fioriniae on Drosophila suzukii (Diptera: Drosophilidae) in highbush blueberries

    1.
    Walsh, D. B. et al. Drosophila suzukii (Diptera: Drosophilidae): Invasive pest of ripening soft fruit expanding its geographic range and damage potential. J. Integr. Pest Manag 2, G1–G7 (2011).
    Google Scholar 
    2.
    Hauser, M. A historic account of the invasion of Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) in the continental United States, with remarks on their identification. Pest Manag. Sci. 67, 1352–1357 (2011).
    CAS  PubMed  Google Scholar 

    3.
    Asplen, M. K. et al. Invasion biology of spotted wing drosophila (Drosophila suzukii): a global perspective and future priorities. J. Pest. Sci. 88, 469–494 (2015).
    Google Scholar 

    4.
    Arnó, J., Solà, M., Riudavets, J. & Gabarra, R. Population dynamics, non-crop hosts, and fruit susceptibility of Drosophila suzukii in Northeast Spain. J. Pest. Sci. 89, 713–723 (2016).
    Google Scholar 

    5.
    Keesey, I. W., Knaden, M. & Hansson, B. S. Olfactory specialization in Drosophila suzukii supports an ecological shift in host preference from rotten to fresh fruit. J. Chem. Ecol. 41, 121–128 (2015).
    CAS  PubMed  PubMed Central  Google Scholar 

    6.
    Karageorgi, M. et al. Evolution of multiple sensory systems drives novel egg-laying behavior in the fruit pest Drosophila suzukii. Curr. Biol. 27, 847–853 (2017).
    CAS  PubMed  PubMed Central  Google Scholar 

    7.
    Lee, J. C. et al. The susceptibility of small fruits and cherries to the spotted-wing drosophila Drosophila suzukii. Pest Manag. Sci. 67, 1358–1367 (2011).
    CAS  PubMed  Google Scholar 

    8.
    Raffa, K. F., Bonello, P. & Orrock, J. L. Why do entomologists and plant pathologists approach trophic relationships so differently? Identifying biological distinctions to foster synthesis. New Phytol. 225, 609–620 (2020).
    PubMed  Google Scholar 

    9.
    Scheidler, N. H., Liu, C., Hamby, K. A., Zalom, F. G. & Syed, Z. Volatile codes: Correlation of olfactory signals and reception in Drosophila-yeast chemical communication. Sci. Rep. 5, 1–13 (2015).
    Google Scholar 

    10.
    Hamm, C. A. et al. Wolbachia do not live by reproductive manipulation alone: Infection polymorphism in Drosophila suzukii and D Subpulchrella. Mol. Ecol. 23, 4871–4885 (2014).
    PubMed  PubMed Central  Google Scholar 

    11.
    Cha, D. H. et al. Behavioral evidence for contextual olfactory-mediated avoidance of the ubiquitous phytopathogen Botrytis cinerea by Drosophila suzukii. Insect Sci. 27, 771–779 (2019).
    PubMed  Google Scholar 

    12.
    Bellutti, N. et al. Dietary yeast affects preference and performance in Drosophila suzukii. J. Pest. Sci. 91, 651–660 (2018).
    Google Scholar 

    13.
    Hamby, K. A., Hernández, A., Boundy-Mills, K. & Zalom, F. G. Associations of yeasts with spotted-wing drosophila (Drosophila suzukii; Diptera: Drosophilidae) in cherries and raspberries. Appl. Environ. Microbiol. 78, 4869–4873 (2012).
    CAS  PubMed  PubMed Central  Google Scholar 

    14.
    Mori, B. A. et al. Enhanced yeast feeding following mating facilitates control of the invasive fruit pest Drosophila suzukii. J. Appl. Ecol. 54, 170–177 (2017).
    Google Scholar 

    15.
    Goodhue, R. E., Bolda, M., Farnsworth, D., Williams, J. C. & Zalom, F. G. Spotted wing drosophila infestation of California strawberries and raspberries: Economic analysis of potential revenue losses and control costs. Pest Manag. Sci. 67, 1396–1402 (2011).
    CAS  PubMed  Google Scholar 

    16.
    Barata, A., Malfeito-Ferreira, M. & Loureiro, V. The microbial ecology of wine grape berries. Int. J. Food Microbiol. 153, 243–259 (2012).
    CAS  PubMed  Google Scholar 

    17.
    Cloonan, K. R., Abraham, J., Angeli, S., Syed, Z. & Rodriguez-Saona, C. Advances in the chemical ecology of the spotted wing drosophila (Drosophila suzukii) and its Applications. J. Chem. Ecol. 44, 922–939 (2018).
    CAS  PubMed  Google Scholar 

    18.
    Cloonan, K. R. et al. Laboratory and field evaluation of host-related foraging odor-cue combinations to attract Drosophila suzukii (Diptera: Drosophilidae). J. Econ. Entomol. 112, 2850–2860 (2019).
    PubMed  Google Scholar 

    19.
    Waller, T. J., Vaiciunas, J., Constantelos, C. & Oudemans, P. V. Evidence that blueberry floral extracts influence secondary conidiation and appressorial formation of Colletotrichum fioriniae. Phytopathology 108, 561–567 (2018).
    PubMed  Google Scholar 

    20.
    PszczóƂkowska, A. & Okorski, A. First report of anthracnose disease caused by Colletotrichum fioriniae on blueberry in western Poland. Plant. Dis. 100, 21–67 (2016).
    Google Scholar 

    21.
    Wharton, P. & DiĂ©guez-Uribeondo, J. The biology of Colletotrichum acutatum. An del JardĂ­n BotĂĄnico Madrid 61, 3–22 (2004).
    Google Scholar 

    22.
    Peres, N. A., Timmer, L. W., Adaskaveg, J. E. & Correll, J. C. Lifestyles of Colletotrichum acutatum. Plant Dis. 89, 784–796 (2005).
    CAS  PubMed  Google Scholar 

    23.
    Polashock, J. J., Caruso, F. L., Averill, A. L. & Schilder, A. C. Compendium of Bluberry, Cranberry, and Lingonberry Diseases and Pests (APS Publications, St. Paul, MN, 2017).
    Google Scholar 

    24.
    Wharton, P. S. & Schilder, A. C. Novel infection strategies of Colletotrichum acutatum on ripe blueberry fruit. Plant Pathol. 57, 122–134 (2008).
    Google Scholar 

    25.
    Verma, N., MacDonald, L. & Punja, Z. K. Inoculum prevalence, host infection and biological control of Colletotrichum acutatum: causal agent of blueberry anthracnose in British Columbia. Plant Pathol. 55, 442–450 (2006).
    Google Scholar 

    26.
    Verma, N., MacDonald, L. & Punja, Z. K. Environmental and host requirements for field infection of blueberry fruits by Colletotrichum acutatum in British Columbia. Plant Pathol. 56, 107–113 (2007).
    Google Scholar 

    27.
    Miles, T. D. & Schilder, A. C. Host defenses associated with fruit infection by Colletotrichum species with an emphasis on anthracnose of blueberries. Plant Health Prog. 14, 30 (2013).
    Google Scholar 

    28.
    Miles, T. D., Hancock, J. F., Callow, P. & Schilder, A. M. C. Evaluation of screening methods and fruit composition in relation to anthracnose fruit rot resistance in blueberries. Plant Pathol. 61, 555–566 (2012).
    Google Scholar 

    29.
    Janzen, D. H. Why fruits rot, seeds mold, and meat spoils. Am. Nat. 111, 691–713 (1977).
    CAS  Google Scholar 

    30.
    Cipollini, M. L. & Stiles, E. W. Fruit rot, antifungal defense, and palatability of fleshy fruits for frugivorous birds. Ecology 74, 751–762 (1993).
    Google Scholar 

    31.
    Peris, J. E., Rodríguez, A., Penã, L. & Fedriani, J. M. Fungal infestation boosts fruit aroma and fruit removal by mammals and birds. Sci. Rep. 7, 1–9 (2017).
    CAS  Google Scholar 

    32.
    Lee, J. C. et al. Characterization and manipulation of fruit susceptibility to Drosophila suzukii. J. Pest. Sci. 89, 771–780 (2016).
    Google Scholar 

    33.
    Choi, M. Y. et al. Effect of non-nutritive sugars to decrease the survivorship of spotted wing drosophila Drosophila suzukii. J Insect Physiol 99, 86–94 (2017).
    CAS  PubMed  Google Scholar 

    34.
    Tochen, S., Walton, V. M. & Lee, J. C. Impact of floral feeding on adult Drosophila suzukii survival and nutrient status. J. Pest Sci. 89, 793–802 (2016).
    Google Scholar 

    35.
    Young, Y., Buckiewicz, N. & Long, T. A. F. Nutritional geometry and fitness consequences in Drosophila suzukii, the spotted-wing drosophila. Ecol. Evol. 8, 2842–2851 (2018).
    PubMed  PubMed Central  Google Scholar 

    36.
    Graziosi, I. & Rieske, L. K. A plant pathogen causes extensive mortality in an invasive insect herbivore. Agric. For. Entomol. 17, 366–374 (2015).
    Google Scholar 

    37.
    Wallingford, A. K., Hesler, S. P., Cha, D. H. & Loeb, G. M. Behavioral response of spotted-wing drosophila, Drosophila suzukii Matsumura, to aversive odors and a potential oviposition deterrent in the field. Pest Manag. Sci. 72, 701–706 (2016).
    CAS  PubMed  Google Scholar 

    38.
    Wallingford, A. K., Cha, D. H., Linn, C. E., Wolfin, M. S. & Loeb, G. M. Robust manipulations of pest insect behavior using repellents and practical application for integrated pest management. Environ. Entomol. 46, 1041–1050 (2017).
    CAS  PubMed  Google Scholar 

    39.
    Göhre, V. & Robatzek, S. Breaking the barriers: microbial effector molecules subvert plant immunity. Annu. Rev. Phytopathol. 46, 189–215 (2008).
    PubMed  Google Scholar 

    40.
    Csorba, T., Kontra, L. & Burgyán, J. Viral silencing suppressors: tools forged to fine-tune host-pathogen coexistence. Virology 479–480, 85–103 (2015).
    PubMed  Google Scholar 

    41.
    Stringlis, I. A., Zhang, H., Pieterse, C. M. J., Bolton, M. D. & De Jonge, R. Microbial small molecules-weapons of plant subversion. Nat. Prod. Rep. 35, 410–433 (2018).
    CAS  PubMed  Google Scholar 

    42.
    McLeod, G. et al. The pathogen causing Dutch elm disease makes host trees attract insect vectors. Proc. Biol. Sci. 272, 2499–2503 (2005).
    PubMed  PubMed Central  Google Scholar 

    43.
    Raguso, R. A. & Roy, B. A. ‘Floral’ scent production by Puccinia rust fungi that mimic flowers. Mol. Ecol. 7, 1127–1136 (1998).
    CAS  PubMed  Google Scholar 

    44.
    Bruce, T. J. A. & Pickett, J. A. Perception of plant volatile blends by herbivorous insects—finding the right mix. Phytochemistry 72, 1605–1611 (2011).
    CAS  PubMed  Google Scholar 

    45.
    Revadi, S. et al. Sexual behavior of Drosophila suzukii. Insects 6, 183–196 (2015).
    PubMed  PubMed Central  Google Scholar 

    46.
    Polashock, J. J., Ehlenfeldt, M. K., Stretch, A. W. & Kramer, M. Anthracnose fruit rot resistance in blueberry cultivars. Plant Dis. 89, 33–38 (2005).
    PubMed  Google Scholar 

    47.
    Hartung, J. S., Burton, C. & Ramsdell, D. C. Epidemiological studies of blueberry anthracnose disease caused by Colletotrichum gloeosporioides. Phytopathology 71, 449 (1981).
    Google Scholar 

    48.
    Cai, P. et al. Potential host fruits for Drosophila suzukii: olfactory and oviposition preferences and suitability for development. Entomol. Exp. Appl. 167, 880–890 (2019).
    Google Scholar 

    49.
    Rodriguez-Saona, C. et al. Differential susceptibility of wild and cultivated blueberries to an invasive frugivorous pest. J. Chem. Ecol. 45, 286–297 (2018).
    PubMed  Google Scholar 

    50.
    Hodge, S. The effect of pH and water content of natural resources on the development of Drosophila melanogaster larvae. Dros. Inf. Serv. 84, 38–43 (2001).
    Google Scholar 

    51.
    Schilder, A. M. C., Gillett, J. M. & Woodworth, J. A. The kaleidoscopic nature of blueberry fruit roots. Acta Hortic. 574, 81–83 (2002).
    Google Scholar 

    52.
    Jaramillo, S. L., Mehlferber, E. & Moore, P. J. Life-history trade-offs under different larval diets in Drosophila suzukii (Diptera: Drosophilidae). Physiol. Entomol. 40, 2–9 (2015).
    Google Scholar 

    53.
    Dalton, D. T. et al. Laboratory survival of Drosophila suzukii under simulated winter conditions of the Pacific Northwest and seasonal field trapping in five primary regions of small and stone fruit production in the United States. Pest Manag. Sci. 67, 1368–1374 (2011).
    CAS  PubMed  Google Scholar 

    54.
    Miller, P. M. V-8 juice agar as a general purpose medium for fungi and bacteria. Phytopathology 45, 461–462 (1955).
    Google Scholar 

    55.
    Feng, Y., Bruton, R., Park, A. & Zhang, A. Identification of attractive blend for spotted wing drosophila, Drosophila suzukii, from apple juice. J. Pest Sci. 91, 1251–1267 (2018).
    Google Scholar 

    56.
    Tochen, S. et al. Temperature-related development and population parameters for Drosophila suzukii (Diptera: Drosophilidae) on cherry and blueberry. Environ. Entomol. 43, 501–510 (2014).
    PubMed  Google Scholar  More