Philippa Kaur

1.
Romano, P., Ciani, M. & Fleet, G. Yeast Ecology of Wine Production in Yeast in the Production of Wine 2–31 (Springer, New York, 2020).
Google Scholar 
2.
Zott, K., Miot-Sertier, C., Claisse, O., Lonvaud-Funel, A. & Masneuf-Pomarede, I. Dynamics and diversity of non-Saccharomyces yeasts during the early stages in winemaking. Int. J. Food Microbiol. 125(2), 197–203 (2008).
CAS  PubMed  Article  PubMed Central  Google Scholar 

3.
Zott, K. et al. Characterization of the yeast ecosystem in grape must and wine using real-time PCR. Food Microbiol. 27(5), 559–567 (2010).
CAS  PubMed  Article  PubMed Central  Google Scholar 

4.
Goddard, M. R. Quantifying the complexities of Saccharomyces cerevisiae’s ecosystem engineering via fermentation. Ecology 89(8), 2077–2082 (2008).
PubMed  Article  PubMed Central  Google Scholar 

5.
Salvadó, Z., Arroyo-López, F. N., Barrio, E., Querol, A. & Guillamón, J. M. Quantifying the individual effects of ethanol and temperature on the fitness advantage of Saccharomyces cerevisiae. Food Microbiol. 28(6), 1155–1161 (2011).
PubMed  Article  CAS  PubMed Central  Google Scholar 

6.
Mcgovern, P. E., Hartung, U., Badler, V. R., Glusker, D. L. & Exner, L. J. The Beginnings of Winemaking and Viticulture in the Ancient Near East and Egypt. Expedition 39(1), 3–21 (1997).
Google Scholar 

7.
Cavalieri, D., McGovern, P. E., Hartl, D. L., Mortimer, R. & Polsinelli, M. Evidence for S. cerevisiae fermentation in ancient wine. J. Mol. Evol. 57(1), S226–S232 (2003).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

8.
Fay, J. C. & Benavides, J. A. Evidence for domesticated and wild populations of Saccharomyces cerevisiae. PLoS Genet. 1(1), e5 (2005).
PubMed Central  Article  CAS  Google Scholar 

9.
Legras, J. L., Merdinoglu, D., Cornuet, J. M. & Karst, F. Bread, beer and wine: Saccharomyces cerevisiae diversity reflects human history. Mol. Ecol. 16(10), 2091–2102 (2007).
CAS  PubMed  Article  PubMed Central  Google Scholar 

10.
Almeida, P. et al. A population genomics insight into the Mediterranean origins of wine yeast domestication. Mol. Ecol. 24(21), 5412–5427 (2015).
PubMed  PubMed Central  Google Scholar 

11.
Dubourdieu, D. et al. Identification de souches de levures de vin par l’analyse de leur AND mitochondrial. Connaissance Vigne Vin 4, 267–278 (1987).
Google Scholar 

12.
Querol, A., Barrio, E., Huerta, T. & Ramón, D. Molecular monitoring of wine fermentations conducted by active dry yeast strains. Appl. Environ. Microbiol. 58(9), 2948–2953 (1992).
CAS  PubMed  PubMed Central  Article  Google Scholar 

13.
Cappello, M. S., Bleve, G., Grieco, F., Dellaglio, F. & Zacheo, G. Characterization of Saccharomyces cerevisiae strains isolated from must of grape grown in experimental vineyard. J. Appl. Microbiol. 97(6), 1274–1280 (2004).
CAS  PubMed  Article  PubMed Central  Google Scholar 

14.
Schuller, D., Alves, H., Dequin, S. & Casal, M. Ecological survey of Saccharomyces cerevisiae strains from vineyards in the Vinho Verde Region of Portugal. FEMS Microbiol. Ecol. 51(2), 167–177 (2005).
CAS  PubMed  Article  PubMed Central  Google Scholar 

15.
Cubillos, F. A., Vásquez, C., Faugeron, S., Ganga, A. & Martínez, C. Self-fertilization is the main sexual reproduction mechanism in native wine yeast populations. FEMS Microbiol. Ecol. 67(1), 162–170 (2009).
CAS  PubMed  Article  PubMed Central  Google Scholar 

16.
Vezinhet, F., Blondin, B. & Hallet, J. N. Chromosomal DNA patterns and mitochondrial DNA polymorphism as tools for identification of enological strains of Saccharomyces cerevisiae. Appl. Microbiol. Biotechnol. 32(5), 568–571 (1990).
CAS  Article  Google Scholar 

17.
Frezier, V. & Dubourdieu, D. Ecology of yeast strains Saccharomyces cerevisiae during spontaneous fermentation in Bordeaux Winery. Am. J. Enol. Vitic. 43(4), 375–380 (1992).
Google Scholar 

18.
Versavaud, A., Courcoux, P., Roulland, C., Dulau, L. & Hallet, J. N. Genetic diversity and geographical distribution of wild Saccharomyces cerevisiae strains from the wine-producing area of Charentes, France. Appl. Environ. Microbiol. 61(10), 3521–3529 (1995).
CAS  PubMed  PubMed Central  Article  Google Scholar 

19.
Valero, E., Cambon, B., Schuller, D., Casal, M. & Dequin, S. Biodiversity of Saccharomyces yeast strains from grape berries of wine-producing areas using starter commercial yeasts. FEMS Yeast Res. 7, 317–329 (2007).
CAS  PubMed  Article  PubMed Central  Google Scholar 

20.
Ness, F., Lavalle, F., Dubourdieu, D., Aigle, M. & Dulau, L. Identification of yeast strains unsing polymerase chain reaction. J. Sci Food Agric. 62, 89–94 (1993).
CAS  Google Scholar 

21.
Legras, J. L. & Karst, F. Optimisation of interdelta analysis for Saccharomyces cerevisiae strain characterisation. FEMS Microbiol. Lett. 221(2), 249–255 (2003).
CAS  PubMed  PubMed Central  Google Scholar 

22.
Ciani, M., Mannazzu, I., Marinangeli, P., Clementi, F. & Martini, A. Contribution of winery-resident Saccharomyces cerevisiae strains to spontaneous grape must fermentation. Antonie Van Leeuwenhoek 85(2), 159–164 (2004).
CAS  PubMed  PubMed Central  Google Scholar 

23.
Le Jeune, C., Erny, C., Demuyter, C. & Lollier, M. Evolution of the population of Saccharomyces cerevisiae from grape to wine in a spontaneous fermentation. Food Microbiol. 23(8), 709–716 (2006).
PubMed  PubMed Central  Google Scholar 

24.
Vigentini, I. et al. The vintage effect overcomes the terroir effect: A three year survey on the wine yeast biodiversity in Franciacorta and Oltrepo Pavese, two Northern Italian Vine-Growing Areas. Microbiology 161(Pt_2), 362–373 (2015).
CAS  PubMed  PubMed Central  Google Scholar 

25.
Legras, J. L., Ruh, O., Merdinoglu, D. & Karst, F. Selection of hypervariable microsatellite loci for the characterization of Saccharomyces cerevisiae strains. Int. J. Food Microbiol. 102(1), 73–83 (2005).
CAS  PubMed  PubMed Central  Google Scholar 

26.
Schuller, D. et al. Genetic characterization of commercial Saccharomyces cerevisiae isolates recovered from vineyard environments. Yeast 24(8), 625–636 (2007).
CAS  PubMed  PubMed Central  Google Scholar 

27.
Schuller, D. et al. Genetic diversity and population structure of Saccharomyces cerevisiae strains isolated from different grape varieties and winemaking regions. PLoS ONE 7(2), e32507 (2012).
ADS  CAS  PubMed  PubMed Central  Google Scholar 

28.
Catlin, D. H. et al. Metapopulation viability of an endangered shorebird depends on dispersal and human-created habitats: Piping plovers (Charadrius melodus) and prairie rivers. Mov. Ecol. 4, 6 (2016).
PubMed  PubMed Central  Google Scholar 

29.
Knight, S. & Goddard, M. R. Quantifying separation and similarity in a Saccharomyces cerevisiae metapopulation. ISME J. 9(2), 361–370 (2015).
CAS  PubMed  PubMed Central  Google Scholar 

30.
Knight, S. J., Karon, O. & Goddard, M. R. Small scale fungal community differentiation in a vineyard system. Food Microbiol. 87, 103358 (2020).
PubMed  Article  PubMed Central  Google Scholar 

31.
Goddard, M. R., Anfang, N., Tang, R., Gardner, R. C. & Jun, C. A Distinct population of Saccharomyces cerevisiae in New Zealand: Evidence for local dispersal by insects and human-aided global dispersal in Oak Barrels. Environ. Microbiol. 12(1), 63–73 (2010).
CAS  PubMed  Article  PubMed Central  Google Scholar 

32.
Stefanini, I. et al. Role of social wasps in Saccharomyces cerevisiae ecology and evolution. Proc. Natl. Acad. Sci. U.S.A. 109(33), 13398–13403 (2012).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

33.
Buser, C. C., Newcomb, R. D., Gaskett, A. C. & Goddard, M. R. Niche construction initiates the evolution of mutualistic interactions. Ecol. Lett. 17(10), 1257–1264 (2014).
PubMed  Article  PubMed Central  Google Scholar 

34.
Francesca, N., Canale, D. E., Settanni, L. & Moschetti, G. Dissemination of Wine-Related Yeasts by Migratory Birds. Environmental Microbiology Reports 4(1), 105–112 (2012).
PubMed  Article  PubMed Central  Google Scholar 

35.
Gayevskiy, V. & Goddard, M. R. Geographic delineations of yeast communities and populations associated with vines and wines in New Zealand. ISME J. 6(7), 1281–1290 (2012).
CAS  PubMed  Article  PubMed Central  Google Scholar 

36.
Cordero-Bueso, G., Arroyo, T. & Valero, E. A long term field study of the effect of fungicides penconazole and sulfur on yeasts in the vineyard. Int. J. Food Microbiol. 189, 189–194 (2014).
CAS  PubMed  Article  PubMed Central  Google Scholar 

37.
Oliva, J. et al. Influence of fungicides on grape yeast content and its evolution in the fermentation. Commun. Agric. Appl. Biol. Sci. 72, 181–189 (2007).
CAS  PubMed  PubMed Central  Google Scholar 

38.
Cordero-Bueso, G. et al. Influence of the farming system and vine variety on yeast communities associated with grape berries. Int. J. Food Microbiol. 145(1), 132–139 (2011).
PubMed  Article  Google Scholar 

39.
Milanović, V., Comitini, F. & Ciani, M. Grape berry yeast communities: Influence of fungicide treatments. Int. J. Food Microbiol. 161, 240–246 (2013).
PubMed  Article  CAS  Google Scholar 

40.
de Celis, M. et al. Diversity of Saccharomyces Cerevisiae yeasts associated to spontaneous and inoculated fermenting grapes from Spanish Vineyards. Lett. Appl. Microbiol. 68(6), 580–588 (2019).
PubMed  Article  PubMed Central  Google Scholar 

41.
Valero, E., Schuller, D., Cambon, B., Casal, M. & Dequin, S. Dissemination and survival of commercial wine yeast in the vineyard: A large-scale, three-years study. FEMS Yeast Res. 5, 959–969 (2005).
CAS  PubMed  Article  PubMed Central  Google Scholar 

42.
Franco-Duarte, R. et al. Intrastrain genomic and phenotypic variability of the commercial Saccharomyces cerevisiae strain Zymaflore VL1 reveals microevolutionary adaptation to vineyard environments. FEMS Yeast Res. 15(6), fov063 (2015).
PubMed  Article  CAS  PubMed Central  Google Scholar 

43.
Cordero-Bueso, G., Arroyo, T., Serrano, A. & Valero, E. Remanence and survival of commercial yeast in different ecological niches of the vineyard. FEMS Microbiol. Ecol. 77, 429–437 (2011).
CAS  PubMed  Article  PubMed Central  Google Scholar 

44.
Mortimer, R. & Polsinelli, M. On the origins of wine yeast. Res. Microbiol. 150(3), 199–204 (1999).
CAS  PubMed  Article  PubMed Central  Google Scholar 

45.
Rosini, G., Federici, F. & Martini, A. Yeast flora of grape berries during ripening. Microb. Ecol. 8(1), 83–89 (1982).
CAS  PubMed  Article  PubMed Central  Google Scholar 

46.
Bokulich, N. A., Ohta, M., Richardson, P. M. & Mills, D. A. Monitoring seasonal changes in winery-resident microbiota. PLoS ONE 8(6), e66437 (2013).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

47.
Dion, R. Aux origines du vignoble bordelais: La création du vignoble bordelais, Angers, Éditions de l’Ouest (1952).

48.
Aubin, G., Lavaud, R.P. (1996). Bordeaux: vignoble millénaire.Bordeaux : l’Horizon chimérique. 1, 215.

49.
Liti, G. et al. Population genomics of domestic and wild yeasts. Nature 458(7236), 337–341 (2009).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

50.
Bruvo, R., Michiels, N. K., D’souza, T. G. & Schulenburg, H. A simple method for the calculation of microsatellite genotype distances irrespective of ploidy level. Mol. Ecol. 13(7), 2101–2106 (2004).
CAS  PubMed  PubMed Central  Google Scholar 

51.
Gao, H., Williamson, S. & Bustamante, C. D. A Markov chain Monte Carlo approach for joint inference of population structure and inbreeding rates from multilocus genotype data. Genetics 176(3), 1635–1651 (2007).
PubMed  PubMed Central  Google Scholar 

52.
Gayevskiy, V., Klaere, S., Knight, S. & Goddard, M. R. ObStruct: A method to objectively analyse factors driving population structure using Bayesian ancestry profiles. PLoS ONE 9(1), e85196 (2014).
ADS  PubMed  PubMed Central  Google Scholar 

53.
Sundqvist, L., Keenan, K., Zackrisson, M., Prodöhl, P. & Kleinhans, D. Directional genetic differentiation and relative migration. Ecol. Evol. 6, 3461–3475 (2016).
PubMed  PubMed Central  Google Scholar 

54.
Gayevskiy, V., Lee, S. & Goddard, M. R. European derived Saccharomyces cerevisiae colonisation of New Zealand vineyards aided by humans retorius I, editor. FEMS Yeast Res. 16(7), 091 (2016).
Google Scholar 

55.
Setati, M. E., Jacobson, D., Andong, U. C. & Bauer, F. The vineyard yeast microbiome, a mixed model microbial map. PLoS ONE 7(12), e52609 (2012).
ADS  CAS  PubMed  PubMed Central  Google Scholar 

56.
Cus, F. & Raspor, P. The Effect of Pyrimethanil on the Growth of Wine Yeasts. Lett. Appl. Microbiol. 47(1), 54–59 (2008).
CAS  PubMed  PubMed Central  Google Scholar 

57.
Viel, A. et al. The geographic distribution of Saccharomyces cerevisiae isolates within three italian neighboring winemaking regions reveals strong differences in yeast abundance, genetic diversity and industrial strain dissemination. Front Microbiol 8, 1595 (2017).
PubMed  PubMed Central  Article  Google Scholar 

58.
Garijo, P. et al. The occurrence of fungi, yeasts and bacteria in the air of a Spanish winery during vintage. Int. J. Food Microbiol. 125(2), 141–145 (2008).
CAS  PubMed  Article  PubMed Central  Google Scholar 

59.
Schacherer, J., Shapiro, J. A., Ruderfer, D. M. & Kruglyak, L. Comprehensive polymorphism survey elucidates population structure of S. cerevisiae. Nature 458(7236), 342–345 (2009).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

60.
White, T., Bruns, T., Lee, S., & Taylor, T. Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In PCR Protocols: A Guide to Methods and Applications (eds Innis, M. et al.), 315–22. (Academic Press, Cambridge, 1990).

61.
Granchi, L., Bosco, M., Messini, A. & Vincenzini, M. Rapid detection and quantification of yeast species during spontaneous wine fermentation by PCR-RFLP analysis of the rDNA ITS region. J. Appl. Microbiol. 87(6), 949–956 (1999).
CAS  PubMed  PubMed Central  Google Scholar 

62.
Field, D. & Wills, C. Abundant microsatellite polymorphism in Saccharomyces cerevisiae, and the different distributions of microsatellites in eight prokaryotes and S. cerevisiae, result from strong mutation pressures and a variety of selective forces. Proc. Natl. Acad. Sci. U. S. A. 95(4), 1647–1652 (1998).
ADS  CAS  PubMed  PubMed Central  Google Scholar 

63.
González Techera, A., Jubany, S., Carrau, F. M. & Gaggero, C. Differentiation of industrial wine yeast strains using microsatellite markers. Lett. Appl. Microbiol. 33(1), 71–75 (2001).
PubMed  PubMed Central  Google Scholar 

64.
Hennequin, C. et al. Microsatellite typing as a new tool for identification of Saccharomyces cerevisiae strains. J. Clin. Microbiol. 39(2), 551–559 (2001).
CAS  PubMed  PubMed Central  Google Scholar 

65.
Pérez, M. A., Gallego, F. J., Martínez, I. & Hidalgo, P. Detection, distribution and selection of microsatellites (SSRs) in the genome of the yeast Saccharomyces cerevisiae as molecular markers. Lett. Appl. Microbiol. 33(6), 461–466 (2001).
PubMed  PubMed Central  Google Scholar 

66.
Bradbury, J. E. et al. A homozygous diploid subset of commercial wine yeast strains. Antonie Van Leeuwenhoek 89(1), 27–37 (2005).
PubMed  PubMed Central  Google Scholar 

67.
Colwell, R. K. Interpolating, extrapolating, and comparing incidence-based species accumulation curves. Ecology 85(10), 2717–2727 (2004).
ADS  Google Scholar 

68.
Arnaud-Haond, S. & Belkhir, K. GENCLONE: A computer program to analyse genotypic data, test for clonality and describe spatial clonal organization. Mol. Ecol. Notes 7(1), 15–17 (2007).
CAS  Google Scholar 

69.
Cormack, R. M. A review of classification. J. R. Stat. Soc. A 134, 321–367 (1971).
MathSciNet  Google Scholar 

70.
Kamvar, Z. N., Tabima, J. F. & Grünwald, N. J. Poppr: An R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. Peer J 2, e281 (2014).
PubMed  Article  PubMed Central  Google Scholar 

71.
Paradis, E., Claude, J. & Strimmer, K. APE: Analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).
CAS  Article  Google Scholar 

72.
Legras, J. L. et al. Adaptation of S. cerevisiae to fermented food environments reveals remarkable genome plasticity and the footprints of domestication. Mol. Biol. Evol. 35(7), 1712–1727 (2018).
CAS  PubMed  PubMed Central  Article  Google Scholar 

73.
Suzuki, R., & Shimodaira, H. R package: Pvclust: Hierarchical Clustering with P-values via multiscale bootstrap resampling. (2014).

74.
Mantel, N. The detection of disease clustering and a generalized regression approach. Cancer Res. 27(2 Part 1), 209–220 (1967).
CAS  PubMed  PubMed Central  Google Scholar 

75.
Peakall, R. & Smouse, P. E. GenAlEx 6.5: Genetic analysis in excel. Population genetic software for teaching and research—An update. Bioinformatics 28(19), 2537–2539 (2012).
CAS  PubMed  PubMed Central  Article  Google Scholar 

76.
Diniz-Filho, J. A. et al. Mantel test in population genetics. Genet. Mol. Biol. 36(4), 475–485 (2013).
PubMed  PubMed Central  Article  Google Scholar 

77.
Jost, L. GST and its relatives do not measure differentiation. Mol. Ecol. 17, 4015–4026 (2008).
PubMed  Article  PubMed Central  Google Scholar 

78.
Beerli, P. & Michal, P. Unified framework to evaluate panmixia and migration direction among multiple sampling locations. Genetics 185(1), 313–326 (2010).
PubMed  PubMed Central  Article  Google Scholar  More

1.
Lau, C. et al. Absence of neurogenic response following robust predator-induced stress response. Neuroscience 339, 276–286 (2016).
CAS  PubMed  Article  Google Scholar 
2.
Park, C. R., Zoladz, P. R., Conrad, C. D., Fleshner, M. & Diamond, D. M. Acute predator stress impairs the consolidation and retrieval of hippocampus-dependent memory in male and female rats. Learn. Mem. 15, 271–280 (2008).
PubMed  PubMed Central  Article  Google Scholar 

3.
Bauer, C. M. et al. Habitat type influences endocrine stress response in the degu (Octodon degus). Gen. Comp. Endocrinol. 186, 136–144 (2013).
CAS  PubMed  Article  Google Scholar 

4.
Rochester, C. J. et al. Reptile and amphibian responses to large-scale wildfires in southern California. J. Herpetol. 44, 333–351 (2010).
Article  Google Scholar 

5.
Romero, L. M., Dickens, M. J. & Cyr, N. E. The reactive scope model—A new model integrating homeostasis, allostasis, and stress. Horm. Behav. 55, 375–389 (2009).
PubMed  Article  Google Scholar 

6.
Romero, L. M. Physiological stress in ecology: Lessons from biomedical research. Trends Ecol. Evol. 19, 249–255 (2004).
PubMed  Article  Google Scholar 

7.
Romero, L. M. & Reed, J. M. Collecting baseline corticosterone samples in the field: is under 3 min good enough?. Comp. Biochem. Physiol. A Mol. Integr. Physiol. 140, 73–79 (2005).
PubMed  Article  CAS  Google Scholar 

8.
Sapolsky, R. M., Romero, L. M. & Munck, A. U. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocr. Rev. 21, 55–89 (2000).
CAS  PubMed  Google Scholar 

9.
Norris, D. & Lopez, K. Hormones and Reproduction of Vertebrates (Academic Press, Cambridge, 2010).
Google Scholar 

10.
Sheriff, M. J., Dantzer, B., Delehanty, B., Palme, R. & Boonstra, R. Measuring stress in wildlife: Techniques for quantifying glucocorticoids. Oecologia 166, 869–887 (2011).
ADS  Article  Google Scholar 

11.
Angilletta, M. J. Thermal and physiological constraints on energy assimilation in a widespread lizard (Sceloporus undulatus). Ecology 82, 3044–3056 (2001).
Article  Google Scholar 

12.
Angilletta, M. J., Hill, T. & Robson, M. A. Is physiological performance optimized by thermoregulatory behavior? A case study of the eastern fence lizard, Sceloporus undulatus. J. Therm. Biol. 27, 199–204 (2002).
Article  Google Scholar 

13.
Davidson, J. O. et al. Effect of cerebral hypothermia on cortisol and adrenocorticotropic hormone responses after umbilical cord occlusion in preterm fetal sheep. Pediatr. Res. 63, 51–55 (2008).
CAS  PubMed  Article  Google Scholar 

14.
Hume, D. M. & Egdahl, R. H. Effect of hypothermia and of cold exposure on adrenal cortical and medullary secretion. Ann. N. Y. Acad. Sci. 80, 435–444 (1959).
ADS  CAS  PubMed  Article  Google Scholar 

15.
Hinds, D. S., Baudinette, R. V., MacMillen, R. E. & Halpern, E. A. Maximum metabolism and the aerobic factorial scope of endotherms. J. Exp. Biol. 56, 41–56 (1993).
Google Scholar 

16.
Pough, F. H. The advantages of ectothermy for tetrapods. Am. Nat. 115, 92–112 (1980).
Article  Google Scholar 

17.
Angilletta, M. J., Zelic, M. H., Adrian, G. J., Hurliman, A. M. & Smith, C. D. Heat tolerance during embryonic development has not diverged among populations of a widespread species (Sceloporus undulatus). Conserv. Physiol. 1, 1–9 (2013).
Article  Google Scholar 

18.
Crowley, S. R. Thermal sensitivity of sprint-running in the lizard Sceloporus undulatus: Support for a conservative view of thermal physiology. Oecologia 66, 219–225 (1985).
ADS  PubMed  Article  Google Scholar 

19.
Parker, S. L. & Andrews, R. M. Incubation temperature and phenotypic traits of Sceloporus undulatus: Implications for the northern limits of distribution. Oecologia 151, 218–231 (2007).
ADS  PubMed  Article  Google Scholar 

20.
Ensminger, D. C., Langkilde, T., Owen, D. A. S., MacLeod, K. J. & Sheriff, M. J. Maternal stress alters the phenotype of the mother, her eggs, and her offspring in a wild caught lizard. J. Anim. Ecol. 87, 1685–1697 (2018).
PubMed  Article  Google Scholar 

21.
McCormick, G. L., Robbins, T. R., Cavigelli, S. A. & Langkilde, T. Ancestry trumps experience: Transgenerational but not early life stress affects the adult physiological stress response. Horm. Behav. 87, 115–121 (2017).
CAS  PubMed  Article  Google Scholar 

22.
Telemeco, R. S., Simpson, D. Y., Tylan, C., Langkilde, T. & Schwartz, T. S. Contrasting responses of lizards to divergent ecological stressors across biological levels of organization. Integr. Comp. Biol. 59, 292–305 (2019).
CAS  PubMed  Article  Google Scholar 

23.
McCormick, G. L. & Langkilde, T. Immune responses of eastern fence lizards (Sceloporus undulatus) to repeated acute elevation of corticosterone. Gen. Comp. Endocrinol. 204, 135–140 (2014).
CAS  PubMed  Article  Google Scholar 

24.
McCormick, G. L., Shea, K. & Langkilde, T. How do duration, frequency, and intensity of exogenous CORT elevation affect immune outcomes of stress?. Gen. Comp. Endocrinol. 222, 81–87 (2015).
CAS  PubMed  Article  Google Scholar 

25.
Mccormick, G. L., Robbins, T. R., Cavigelli, S. A. & Langkilde, T. Population history with invasive predators predicts innate immune function response to early-life glucocorticoid exposure in lizards. J. Exp. Biol. 222, jeb188359 (2019).
PubMed  Article  Google Scholar 

26.
MacLeod, K. J., Sheriff, M. J., Ensminger, D. C., Owen, D. A. S. & Langkilde, T. Survival and reproductive costs of repeated acute glucocorticoid elevations in a captive, wild animal. Gen. Comp. Endocrinol. https://doi.org/10.1016/j.ygcen.2018.07.006 (2018).
Article  PubMed  Google Scholar 

27.
John-Alder, H. B., Cox, R. M., Haenel, G. J. & Smith, L. C. Hormones, performance and fitness: Natural history and endocrine experiments on a lizard (Sceloporus undulatus). Integr. Comp. Biol. 49, 393–407 (2009).
CAS  PubMed  Article  Google Scholar 

28.
Owen, D. A. S., Sheriff, M. J., Engler, H. I. & Langkilde, T. Sex-dependent effects of maternal stress: Stressed moms invest less in sons than daughters. J. Exp. Zool. Part A 329, 317–322 (2018).
CAS  Google Scholar 

29.
Graham, S. P., Freidenfelds, N. A., Mccormick, G. L. & Langkilde, T. The impacts of invaders: Basal and acute stress glucocorticoid profiles and immune function in native lizards threatened by invasive ants. Gen. Comp. Endocrinol. 176, 400–408 (2012).
CAS  PubMed  Article  Google Scholar 

30.
Phillips, J. B. & Klukowski, M. Influence of season and adrenocorticotropic hormone on corticosterone in free-living female eastern fence lizards (Sceloporus undulatus). Copeia 3, 570–578 (2008).
Article  Google Scholar 

31.
Conant, R. & Collins, J. T. A Field Guide to Reptiles and Amphibians of Eastern and Central North America (Houghton Mifflin Company, Boston, 1998).
Google Scholar 

32.
Carsia, R. V. & John-Alder, H. Seasonal alterations in adrenocortical cell function associated with stress-responsiveness and sex in the eastern fence lizard (Sceloporus undulatus). Horm. Behav. 43, 408–420 (2003).
CAS  PubMed  Article  Google Scholar 

33.
Anderson, L., Nelson, N. & Cree, A. Glucocorticoids in tuatara (Sphenodon punctatus): Some influential factors, and applications in conservation management. Gen. Comp. Endocrinol. 244, 54–59 (2017).
CAS  PubMed  Article  Google Scholar 

34.
Jessop, T. S. et al. Multiscale evaluation of thermal dependence in the glucocorticoid response of vertebrates. Am. Nat. 188, 342–356 (2016).
PubMed  Article  Google Scholar 

35.
Telemeco, R. S. & Addis, E. A. Temperature has species-specific effects on corticosterone in alligator lizards. Gen. Comp. Endocrinol. 206, 184–192 (2014).
CAS  PubMed  Article  Google Scholar 

36.
Cockrem, J. F. Individual variation in glucocorticoid stress responses in animals. Gen. Comp. Endocrinol. 181, 45–58 (2013).
CAS  PubMed  Article  Google Scholar 

37.
Holding, M. L. et al. Wet- and dry-season steroid hormone profiles and stress reactivity of an insular dwarf snake, the Hog Island boa (Boa constrictor imperator). Physiol. Biochem. Zool. 87, 363–373 (2014).
CAS  PubMed  Article  Google Scholar 

38.
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, 1856–1866 (2015).
PubMed  Article  Google Scholar 

39.
Trompeter, W. P. & Langkilde, T. Invader danger: Lizards faced with novel predators exhibit an altered behavioral response to stress. Horm. Behav. 60, 152–158 (2011).
CAS  PubMed  Article  Google Scholar 

40.
Graham, S. P., Freidenfelds, N. A., Robbins, T. R. & Langkilde, T. Are invasive species stressful? The glucocorticoid profile of native lizards exposed to invasive fire ants depends on the context. Physiol. Biochem. Zool. 90, 328–337 (2016).
PubMed  Article  Google Scholar 

41.
Claunch, N. M. et al. Physiological and behavioral effects of exogenous corticosterone in a free-ranging ectotherm. Gen. Comp. Endocrinol. 248, 87–96 (2017).
CAS  PubMed  Article  Google Scholar 

42.
Holding, M. L. et al. Physiological and behavioral effects of repeated handling and short-distance translocations on free-ranging northern Pacific rattlesnakes (Crotalus oreganus oreganus). J. Herpetol. 48, 233–239 (2014).
Article  Google Scholar  More

1.
Elton, C. The Ecology of Invasions by Animals and Plants (Methuen, London, 1958).
Google Scholar 
2.
Simberloff, D. Invasive Species: What Everyone Needs to Know (Oxford University Press, Oxford, 2013).
Google Scholar 

3.
Ehrenfeld, J. G. Ecosystem consequences of biological invasions. Annu. Rev. Ecol. Evol. Syst. 41, 59–80 (2010).
Article  Google Scholar 

4.
Simberloff, D. How common are invasion-induced ecosystem impacts?. Biol. Invasions 13, 1255–1268 (2011).
Article  Google Scholar 

5.
Simberloff, D. Invasional meltdown 6 years later: important phenomenon, unfortunate metaphor, or both?. Ecol. Lett. 9, 912–919 (2006).
PubMed  Article  Google Scholar 

6.
Fukami, T. et al. Above- and below-ground impacts of introduced predators in seabird-dominated island ecosystems. Ecol. Lett. 9, 1299–1307 (2006).
PubMed  Article  Google Scholar 

7.
Gibbons, J. W. et al. The global decline of reptiles Deja Vu amphibians. Bioscience 50, 653–666 (2000).
Article  Google Scholar 

8.
Blackburn, T. M., Cassey, P., Duncan, R. P., Evans, K. L. & Gaston, K. J. Avian extinction and mammalian introductions on oceanic islands. Science 305, 1955 (2004).
ADS  PubMed  Article  CAS  Google Scholar 

9.
Paini, D. R. et al. Global threat to agriculture from invasive species. Proc. Natl. Acad. Sci. 113, 7575–7579 (2016).
PubMed  Article  CAS  Google Scholar 

10.
Juliano, S. A. & Lounibos, L. P. Ecology of invasive mosquitoes: effects on resident species and on human health. Ecol. Lett. 8, 558–574 (2005).
PubMed  PubMed Central  Article  Google Scholar 

11.
Pimentel, D., Lach, L., Zuniga, R. & Morrison, D. Environmental and economic costs of nonindigenous species in the United States. Bioscience 50, 53–65 (2000).
Article  Google Scholar 

12.
Rogers, W. E. Invasive species. In Reference Module Earth Systems and Environmental Sciences (ed. Flow, E. S.) (Elsevier, Amsterdam, 2017).
Google Scholar 

13.
Booth, B. D., Murphy, S. D. & Swanton, C. J. Weed Ecology in Natural and Agricultural Systems (CABI publishing, Wallingford, 2003).
Google Scholar 

14.
White, E. M., Wilson, J. C. & Clarke, A. R. Biotic indirect effects: a neglected concept in invasion biology. Divers. Distrib. 12, 443–455 (2006).
Article  Google Scholar 

15.
Hui, C. et al. Defining invasiveness and invasibility in ecological networks. Biol. Invasions 18, 971–983 (2016).
Article  Google Scholar 

16.
Ricciardi, A., Hoopes, M. F., Marchetti, M. P. & Lockwood, J. L. Progress toward understanding the ecological impacts of nonnative species. Ecol. Monogr. 83, 263–282 (2013).
Article  Google Scholar 

17.
Kolar, C. S. & Lodge, D. M. Progress in invasion biology: predicting invaders. Trends Ecol. Evol. 16, 199–204 (2001).
PubMed  Article  Google Scholar 

18.
Lodge, D. M. Biological invasions: lessons for ecology. Trends Ecol. Evol. 8, 133–137 (1993).
PubMed  Article  CAS  Google Scholar 

19.
Savidge, J. A., Qualls, F. J. & Rodda, G. H. Reproductive biology of the brown tree snake, Boiga irregularis (Reptilia: Colubridae), during colonization of Guam and comparison with that in their native range. Pac. Sci. 61, 191–199 (2007).
Article  Google Scholar 

20.
Gardner, P. G., Frazer, T. K., Jacoby, C. A. & Yanong, R. P. E. Reproductive biology of invasive lionfish (Pterois spp.). Front. Mar. Sci. 2, 7 (2015).
Article  Google Scholar 

21.
Van Kleunen, M., Dawson, W., Schlaepfer, D., Jeschke, J. M. & Fischer, M. Are invaders different? A conceptual framework of comparative approaches for assessing determinants of invasiveness. Ecol. Lett. 13, 947–958 (2010).
PubMed  Google Scholar 

22.
Barnosky, A. D. et al. Has the Earth/’s sixth mass extinction already arrived?. Nature 471, 51–57 (2011).
ADS  PubMed  Article  CAS  Google Scholar 

23.
Ceballos, G. et al. Accelerated modern human-induced species losses: entering the sixth mass extinction. Sci. Adv. 1, e1400253 (2015).
ADS  PubMed  PubMed Central  Article  Google Scholar 

24.
Measey, G. J. et al. Ongoing invasions of the African clawed frog, Xenopus laevis: a global review. Biol. Invasions 14, 2255–2270 (2012).
Article  Google Scholar 

25.
Bucciarelli, G. M., Blaustein, A. R., Garcia, T. S. & Kats, L. B. Invasion complexities: the diverse impacts of nonnative species on amphibians. Copeia 2014, 611–632 (2014).
Article  Google Scholar 

26.
Measey, G. J. et al. A global assessment of alien amphibian impacts in a formal framework. Divers. Distrib. 22, 970–981 (2016).
Article  Google Scholar 

27.
Kumschick, S. et al. Impact assessment with different scoring tools: how well do alien amphibian assessments match?. NeoBiota 33, 53–66 (2017).
Article  Google Scholar 

28.
Kraus, F. Impacts from invasive reptiles and amphibians. Annu. Rev. Ecol. Evol. Syst. 46, 75–97 (2015).
Article  Google Scholar 

29.
Selechnik, D., Rollins, L. A., Brown, G. P., Kelehear, C. & Shine, R. The things they carried: the pathogenic effects of old and new parasites following the intercontinental invasion of the Australian cane toad (Rhinella marina). Int. J. Parasitol. Parasites Wildl. 6, 375–385 (2017).
PubMed  Article  CAS  Google Scholar 

30.
Shine, R. Invasive species as drivers of evolutionary change: cane toads in tropical Australia. Evol. Appl. 5, 107–116 (2012).
PubMed  Article  Google Scholar 

31.
Adams, M. J. & Pearl, C. A. Problems and opportunities managing invasive bullfrogs: is there any hope? In Biological Invaders in Inland Waters: Profiles, Distribution, and Threats (ed. Gherardi, F.) 679–693 (Springer, Dordrecht, 2007).
Google Scholar 

32.
Pili, A. N., Supsup, C. E., Sy, E. Y., Diesmos, M. L. L. & Diesmos, A. C. Spatial dynamics of invasion and distribution of alien frogs in a biodiversity hotspot archipelago. In Island Invasives: Scaling Up to Meet the Challenge 337–347 (IUCN, 2019).

33.
Pearl, C., Adams, M., Leuthold, N. & Bury, R. Amphibian occurrence and aquatic invaders in a changing landscape: implications for wetland mitigation in the Willamette valley, Oregon, USA. Wetlands 25, 76–88 (2005).
Article  Google Scholar 

34.
Govindarajulu, P., Price, W. M. S. & Anholt, B. R. Introduced bullfrogs (Rana catesbeiana) in western Canada: has their ecology diverged?. J. Herpetol. 40, 249–260 (2006).
Article  Google Scholar 

35.
Bai, C., Liu, X., Fisher, M. C., Garner, T. W. J. & Li, Y. Global and endemic Asian lineages of the emerging pathogenic fungus Batrachochytrium dendrobatidis widely infect amphibians in China. Divers. Distrib. 18, 307–318 (2012).
Article  Google Scholar 

36.
Rago, A., While, G. M. & Uller, T. Introduction pathway and climate trump ecology and life history as predictors of establishment success in alien frogs and toads. Ecol. Evol. 2, 1437–1445 (2012).
PubMed  PubMed Central  Article  Google Scholar 

37.
Xuan, L., Yiming, L. & McGarrity, M. Geographical variation in body size and sexual size dimorphism of introduced American bullfrogs in southwestern China. Biol. Invasions 12, 2037–2047 (2010).
Article  Google Scholar 

38.
Both, C. et al. Widespread occurrence of the American Bullfrog, Lithobates catesbeianus (Shaw, 1802) (Anura: Ranidae) Brazil. South Am. J. Herpetol. 6, 127–134 (2011).
Article  Google Scholar 

39.
Bøhn, T., Terje Sandlund, O., Amundsen, P.-A. & Primicerio, R. Rapidly changing life history during invasion. Oikos 106, 138–150 (2004).
Article  Google Scholar 

40.
Lima, S. L., Costa, C. L. S., Agostinho, C. A., Andrade, D. R. & Pereira, H. P. Estimate of bullfrog size at first sexual maturation, Rana catesbeiana, in the intensive growing Anfigranja system. Rev. Bras. Zootec. Braz. J. Anim. Sci. 27, 416–420 (1998).
Google Scholar 

41.
Leivas, P. T., Moura, M. O. & Favaro, L. F. The reproductive biology of the invasive Lithobates catesbeianus (Amphibia:Anura). J. Herpetol. 46, 153–161 (2012).
Article  Google Scholar 

42.
Bruneau, M. & Magnin, E. Croissance, nutrition et reproduction des ouaouarons Rana catesbeiana Shaw (Amphibia Anura) des Laurentides au nord de Montreal. Can. J. Zool. 58, 175–183 (1980).
Article  Google Scholar 

43.
Shirose, L. J., Brooks, R. J., Barta, J. R. & Desser, S. S. Intersexual differences in growth, mortality, and size at maturity in bullfrogs in central Ontario. Can. J. Zool. 71, 2363–2369 (1993).
Article  Google Scholar 

44.
Jennings, M. R. & Hayes, M. P. Pre-1900 overharvest of California red-legged frogs (Rana aurora draytonii): the inducement for Bullfrog (Rana catesbeiana) introduction. Herpetologica 41, 94–103 (1985).
Google Scholar 

45.
Guariento, R. D., Carneiro, L. S., Jorge, J. S. & Caliman, A. Assessing the risk effects of native predators on the exotic American bullfrog (Lithobates catesbeianus) and their indirect consequences to ecosystem function. Acta Oecologica 91, 50–56 (2018).
ADS  Article  Google Scholar 

46.
Crump, M. L. & Scott, N. J. Jr. Chapter 2. Visual encounter surveys. In Measuring and Monitoring Biological Diversity: Standard Methods for Amphibians (eds Heyer, W. R. et al.) 84–92 (Smithsonian Institution Press, Washington, 1994).
Google Scholar 

47.
Browne, R. K. & Zippel, K. Reproduction and larval rearing of amphibians. ILAR J. 48, 214–234 (2007).
PubMed  Article  CAS  Google Scholar 

48.
Costa, C. L. S., Lima, S. L., Andrade, D. R. & Agostinho, C. A. Morphological characterization of development stages of male reproduction apparel of bullfrog, Rana catesbeiana, in the intensive Anfigranja system. Rev. Bras. Zootec. Braz. J. Anim. Sci. 27, 651–657 (1998).
Google Scholar 

49.
Costa, C. L. S., Lima, S. L., Andrade, D. R. & Agostinho, C. A. Morphological characterization of the development stages of female reproduction apparel of bullfrog, Rana catesbeiana, in the intensive Anfigranja systems. Rev. Bras. Zootec. Braz. J. Anim. Sci. 27, 642–650 (1998).
Google Scholar 

50.
Kaefer, I. L., Boelter, R. A. & Cechin, S. Z. Reproductive biology of the invasive bullfrog Lithobates catesbeianus in southern Brazil. Ann. Zool. Fenn. 44, 435–444 (2007).
Google Scholar 

51.
Howard, R. D. Sexual dimorphism in bullfrogs. Ecology 62, 303–310 (1981).
Article  Google Scholar 

52.
Jones, L. L. C., Leonard, W. P. & Olson, D. H. Amphibians of the Pacific Northwest (Seattle Audubon Society, Seattle, 2005).
Google Scholar 

53.
Nussbaum, R. A., Brodie, E. D. & Storm, R. M. Amphibians and Reptiles of the Pacific Northwest (University Press of Idaho, Moscow, 1983).
Google Scholar 

54.
Govindarajulu, P., Altwegg, R. & Anholt, B. R. Matrix model investigation of invasive species control: bullfrogs on Vancouver Island. Ecol. Appl. 15, 2161–2170 (2005).
Article  Google Scholar 

55.
Cook, M. T., Heppell, S. S. & Garcia, T. S. Invasive bullfrog larvae lack developmental plasticity to changing hydroperiod. J. Wildl. Manag. 77, 655–662 (2013).
Article  Google Scholar 

56.
Jennette, M. A., Snodgrass, J. W. & Forester, D. C. Variation in age, body size, and reproductive traits among urban and rural amphibian populations. Urban Ecosyst. 22, 137–147 (2019).
Article  Google Scholar 

57.
Bredeweg, E. M., Urbina, J., Morzillo, A. T. & Garcia, T. S. Starting on the right foot: carryover effects of larval hydroperiod and terrain moisture on post-metamorphic frog movement behavior. Front. Ecol. Evol. 7, 97 (2019).
Article  Google Scholar 

58.
Burton, O. J., Phillips, B. L. & Travis, J. M. J. Trade-offs and the evolution of life-histories during range expansion. Ecol. Lett. 13, 1210–1220 (2010).
PubMed  Article  Google Scholar 

59.
Chuang, A. & Peterson, C. R. Expanding population edges: theories, traits, and trade-offs. Glob. Change Biol. 22, 494–512 (2016).
ADS  Article  Google Scholar 

60.
Kelehear, C. & Shine, R. Tradeoffs between dispersal and reproduction at an invasion front of cane toads in tropical Australia. Sci. Rep. 10, 486 (2020).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

61.
Hudson, C. M., Phillips, B. L., Brown, G. P. & Shine, R. Virgins in the vanguard: low reproductive frequency in invasion-front cane toads. Biol. J. Linn. Soc. 116, 743–747 (2015).
Article  Google Scholar 

62.
Courant, J., Secondi, J., Bereiziat, V. & Herrel, A. Resources allocated to reproduction decrease at the range edge of an expanding population of an invasive amphibian. Biol. J. Linn. Soc. 122, 157–165 (2017).
Article  Google Scholar 

63.
Vimercati, G., Davies, S. J. & Measey, J. Invasive toads adopt marked capital breeding when introduced to a cooler, more seasonal environment. Biol. J. Linn. Soc. 128, 657–671 (2019).
Article  Google Scholar 

64.
Sol, D. et al. Unraveling the life history of successful invaders. Science 337, 580 (2012).
ADS  PubMed  Article  CAS  PubMed Central  Google Scholar 

65.
Descamps, S. & De Vocht, A. The sterile male release approach as a method to control invasive amphibian populations: a preliminary study on Lithobates catesbeianus. Manag. Biol. Invasions 8, 361–370 (2017).
Article  Google Scholar 

66.
McCoid, M. J. & Fritts, T. H. Growth and fatbody cycles in feral populations of the African clawed frog, Xenopus laevis (Pipidae), in California with comments on reproduction. Southwest. Nat. 34, 499–505 (1989).
Article  Google Scholar 

67.
Werner, E. E. Amphibian metamorphosis: growth rate, predation risk, and the optimal size at transformation. Am. Nat. 128, 319–341 (1986).
Article  Google Scholar 

68.
Howard, R. D. Sexual selection and variation in reproductive success in a long-lived organism. Am. Nat. 122, 301–325 (1983).
ADS  Article  Google Scholar 

69.
Emlen, S. T. ‘Double clutching’ and its possible significance in the bullfrog. Copeia 1977, 749–751 (1977).
Article  Google Scholar 

70.
Kiesecker, J. M. & Blaustein, A. R. Effects of introduced bullfrogs and smallmouth bass on microhabitat use, growth, and survival of native red-legged frogs (Rana aurora). Conserv. Biol. 12, 776–787 (1998).
Article  Google Scholar 

71.
Blaustein, A. R. & Kiesecker, J. M. Complexity in conservation: lessons from the global decline of amphibian populations. Ecol. Lett. 5, 597–608 (2002).
Article  Google Scholar 

72.
Rowe, J. C. et al. Disentangling effects of invasive species and habitat while accounting for observer error in a long-term amphibian study. Ecosphere 10, e02674 (2019).
Article  Google Scholar 

73.
Sharifian-Fard, M. et al. Ranavirosis in invasive bullfrogs Belgium. Emerg. Infect. Dis. 17, 2371–2372 (2011).
PubMed  PubMed Central  Article  Google Scholar 

74.
Gervasi, S. S. et al. Experimental evidence for American bullfrog (Lithobates catesbeianus) susceptibility to chytrid fungus (Batrachochytrium dendrobatidis). EcoHealth 10, 166–171 (2013).
PubMed  Article  Google Scholar 

75.
Martel, A. et al. Batrachochytrium salamandrivorans sp. nov. causes lethal chytridiomycosis in amphibians. Proc. Natl. Acad. Sci. 110, 15325 (2013).
ADS  PubMed  Article  Google Scholar 

76.
Urbina, J., Bredeweg, E. M., Garcia, T. S. & Blaustein, A. R. Host-pathogen dynamics among the invasive American bullfrog (Lithobates catesbeianus) and chytrid fungus (Batrachochytrium dendrobatidis). Hydrobiologia 817, 267–277 (2018).
Article  CAS  Google Scholar 

77.
Ficetola, G. F. et al. Pattern of distribution of the American bullfrog Rana catesbeiana in Europe. Biol. Invasions 9, 767–772 (2007).
Article  Google Scholar 

78.
Ryan, M. J. The reproductive behavior of the bullfrog (Rana catesbeiana). Copeia 1980, 108–114 (1980).
Article  Google Scholar 

79.
Willis, Y. L., Moyle, D. L. & Baskett, T. S. Emergence, breeding, hibernation, movements and transformation of the bullfrog, Rana catesbeiana Missouri. Copeia 1956, 30–41 (1956).
Article  Google Scholar 

80.
Wright, A. & Wright, A. Handbook of Frogs and Toads of the United States and Canada (Comstock, London, 1949).
Google Scholar 

81.
Raney, E. C. & Ingram, W. M. Growth of tagged frogs (Rana catesbeiana Shaw and Rana clamitans Daudin) under natural conditions. Am. Midl. Nat. 26, 201–206 (1941).
Article  Google Scholar 

82.
George, I. A study of the bullfrog, Rana catesbeiana Shaw, at Baton Rouge, Louisiana (University of Michigan, Ann Arbor, 1940).
Google Scholar 

83.
Wright, A. Frogs: Their Natural History and Utilization. Series: Document (Bureau of Fisheries, United States) no. 888. (Govt. Print. Off, Washington, 1920). More

1.
Moss, M. L. Northwest Coast: Archaeology as Deep History (Society for American Archaeology Press, Washington, 2011).
Google Scholar 
2.
McKechnie, I., Moss, M. L. & Crockford, S. J. Dogs and other canids of the northwest coast of North America: animal husbandry in a region without agriculture?. J. Anthrop. Archaeol https://doi.org/10.1016/j.jaa.2020.101209 (2020).
Article  Google Scholar 

3.
Crockford, S. J. Osteometry of Makah and Coast Salish Dogs (Archaeology Press, Simon Fraser University, Burnaby, 1997).
Google Scholar 

4.
Crockford, S. J. A Practical Guide to In Situ Dog Remains for the Field Archaeologist (Pacific Identifications Inc., Berlin, 2009).
Google Scholar 

5.
Guiry, E. J. Dogs as analogs in stable isotope-based human paleodietary reconstructions: a review and considerations for future use. J. Arch. Methods Theory 19, 351–376 (2012).
Article  Google Scholar 

6.
Burleigh, R. & Brothwell, D. Studies on Amerindian dogs, 1: carbon isotopes in relation to maize in the diet of domestic dogs from early Peru and Ecuador. J. Archaeol. Sci. 5, 355–362 (1978).
CAS  Article  Google Scholar 

7.
Cannon, A., Schwarcz, H. P. & Knyf, M. Marine-based subsistence trends and the stable isotope analysis of dog bones from Namu, British Columbia. J. Archaeol. Sci. 26, 399–407 (1999).
Article  Google Scholar 

8.
Chisholm, B. S., Nelson, D. E. & Schwarcz, H. P. Stable carbon isotope ratios as a measure of marine versus terrestrial protein in ancient diets. Science 216, 1131–1132 (1982).
ADS  CAS  PubMed  Article  Google Scholar 

9.
DeNiro, M. J. & Epstein, S. Influence of diet on the distribution of nitrogen isotopes in animals. Geochim. Cosmochim. Acta 45, 341–351 (1981).
ADS  CAS  Article  Google Scholar 

10.
Schoeninger, M. J. & DeNiro, M. J. Nitrogen and carbon isotopic composition of bone collagen from marine and terrestrial animals. Geochim. Cosmochim. Acta 48, 625–639 (1984).
ADS  CAS  Article  Google Scholar 

11.
Guiry, E. J. A canine surrogacy approach to human paleodietary bone chemistry: past development and future directions. Arch. Anthropol. Sci. 5, 275–286 (2013).
Article  Google Scholar 

12.
Guiry, E. J. & Grimes, V. Domestic dog (Canis familiaris) diets among coastal Late Archaic groups of northeastern North America: a case study for the canine surrogacy approach. J. Anthrop. Archaeol. 32, 732–745 (2013).
Article  Google Scholar 

13.
Grier, C. Affluence on the prehistoric northwest coast of North America. In: Beyond ‘Affluent-Foragers’: Rethinking Hunter-Gatherer Complexity. Proceedings of the 9th ICAZ Conference, Durham 2002 (eds Grier, C., Kim, J. & Uchiyama, J.) 126–135 (Oxbow Books, 2006).

14.
Ames, K. M. et al. Stable isotope and ancient DNA analysis of dog remains from Cathlapotle (45CL1), a contact-era site on the Lower Columbia River. J. Archaeol. Sci. 57, 268–282 (2015).
CAS  Article  Google Scholar 

15.
Tifental, E. The Bridge River Dogs: Interpreting aDNA and Stable Isotope Analysis Collected from Dog Remains. MA Thesis, University of Montana (2016).

16.
Barta, J. L. Addressing Issues of Domestication and Cultural Continuity on the Northwest Coast Using Ancient DNA and Dogs. PhD Dissertation, McMaster University (2006).

17.
Guiry, E. et al. Differentiating salmonid migratory ecotypes through stable isotope analysis of collagen: archaeological and ecological applications. PLoS ONE 15, e0232180. https://doi.org/10.1371/journal.pone.0232180 (2020).
CAS  Article  PubMed  PubMed Central  Google Scholar 

18.
Lovell, N. C., Chisholm, B. S., Nelson, D. E. & Schwarcz, H. P. Prehistoric salmon consumption in interior British Columbia. Can. J. Archaeol. 10, 99–106 (1986).
Google Scholar 

19.
Szpak, P., Orchard, T. J. & Gröcke, D. R. A late holocene vertebrate food web from southern Haida Gwaii (Queen Charlotte Islands, British Columbia). J. Archaeol. Sci. 36, 2734–2741 (2009).
Article  Google Scholar 

20.
Stock, B. C. & Semmens, B. X. MixSIAR GUI User Manual, Version 1.0. https://conserver.iugo-cafe.org/user/brice.semmens/MixSIR (2013).

21.
Drucker, P. The Northern and Central Nootkan Tribes, Vol. 144 (Smithsonian Institution, Washington, 1951).
Google Scholar 

22.
Dierks, K. Osteobiography of an Ancient Nuu-chah-nulth Woolly Dog: Investigating the Life and Death of a Domestic Dog from Tseshaht Territory in Barkley Sound. Honours Thesis, University of Victoria (2020).

23.
McKechnie, I. An Archaeology of Food and Settlement on the Northwest Coast. PhD Dissertation, University of British Columbia (2014).

24.
MacLean, K. An Analysis of the Flaked Stone Assemblage from the Hiikwis Site Complex, Barkley Sound, British Columbia. MA Thesis, University of Victoria (2012).

25.
Smith, N. F., McKechnie, I. & St. Claire, D. E. Kakmakimilh–Keith Island Wharf and Gazebo Installation: An Archaeological Impact Assessment (Report Prepared for Tseshaht First Nation and Pacific Rim National Park Reserve of Canada, 2012).

26.
Guiry, E. J., Szpak, P. & Richards, M. P. Effects of lipid extraction and ultrafiltration on stable carbon and nitrogen isotopic compositions of fish bone collagen. Rapid Commun. Mass Spectrom. 30, 1591–1600 (2016).
ADS  CAS  PubMed  Article  Google Scholar 

27.
Guiry, E. J. et al. Lake Ontario salmon (Salmo salar) were not migratory: a long-standing historical debate solved through stable isotope analysis. Sci. Rep. 6, 36249 (2016).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

28.
Szpak, P., Metcalfe, J. Z. & Macdonald, R. A. Best practices for calibrating and reporting stable isotope measurements in archaeology. J. Archaeol. Sci. Rep. 13, 609–616 (2017).
Google Scholar 

29.
Ambrose, S. H. Preparation and characterization of bone and tooth collagen for isotopic analysis. J. Archaeol. Sci. 17, 431–451 (1990).
Article  Google Scholar 

30.
Alter, S. E., Newsome, S. D. & Palumbi, S. R. Pre-whaling genetic diversity and population ecology in eastern Pacific gray whales: insights from ancient DNA and stable isotopes. PLoS ONE 7, e35039 (2012).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

31.
Newsome, S. D. et al. The shifting baseline of northern fur seal ecology in the northeast Pacific Ocean. PNAS 104, 9709–9714 (2007).
ADS  CAS  PubMed  Article  Google Scholar 

32.
Hobson, K. A., Piatt, J. F. & Pitocchelli, J. Using stable isotopes to determine seabird trophic relationships. J. Anim. Ecol. 63, 786–798 (1994).
Article  Google Scholar 

33.
Bocherens, H. & Drucker, D. Trophic level isotopic enrichment of carbon and nitrogen in bone collagen: case studies from recent and ancient terrestrial ecosystems. Int. J. Osteoarchaeol. 13, 46–53 (2003).
Article  Google Scholar 

34.
Szepanski, M. M., Ben-David, M. & Van Ballenberghe, V. Assessment of anadromous salmon resources in the diet of the Alexander Archipelago wolf using stable isotope analysis. Oecologia 120, 327–335 (1999).
ADS  CAS  PubMed  Article  Google Scholar 

35.
Szpak, P., Orchard, T. J., McKechnie, I. & Gröcke, D. R. Historical ecology of late Holocene sea Otters (Enhydra lutris) from northern British Columbia: isotopic and zooarchaeological perspectives. J. Archaeol. Sci. 39, 1553–1571. https://doi.org/10.1016/j.jas.2011.12.006 (2012).
Article  Google Scholar 

36.
Markel, R. W. Rockfish Recruitment and Trophic Dynamics on the West Coast of Vancouver Island: Fishing, Ocean Climate, and Sea Otters. PhD Dissertation, University of British Columbia (2011).

37.
McKechnie, I. & Wigen, R. J. Toward a historical ecology of pinniped and sea otter hunting traditions on the Coast of Southern British Columbia. In Human Impacts on Seals, Sea Lions, and Sea Otters: Integrating Archaeology and Ecology in the Northeast Pacific (eds Braje, T. J. & Rick, T. C.) 129–166 (Univ. of California, Oakland, 2011).
Google Scholar 

38.
McMillan, A. D., McKechnie, I., St. Claire, D. E. & Frederick, S. G. Exploring variability in maritime resource use on the Northwest Coast: a case study from Barkley Sound, Western Vancouver Island. Can. J. Archaeol. 32, 214–238 (2008).
Google Scholar 

39.
Westre, N. J. Vertebrate Faunal Analysis of the Hiikwis Site Complex (DfSh-15 and DfSh-16) in Barkley Sound, British Columbia. MA Thesis, University of Victoria (2014).

40.
Wigen, R. J. Faunal analysis for Kakmakimilh, Keith Island, 306T (DfSh-17) In Kakmakimilh–Keith Island Wharf and Gazebo Installation: An Archaeological Impact Assessment (eds Smith, N. F., McKechnie, I. & St. Claire, D. E.) (Report Prepared by for Tseshaht First Nation and Pacific Rim National Park Reserve of Canada, 2013).

41.
Newsome, S. D., Martinez del Rio, C., Bearhop, S. & Phillips, D. L. A niche for isotopic ecology. Front. Ecol. Environ. 5, 429–443 (2007).
Article  Google Scholar 

42.
Ramshaw, B. C., Pakhomov, E. A., Markel, R. W. & Kaehler, S. Quantifying spatial and temporal variations in phytoplankton and kelp isotopic signatures to estimate the distribution of kelp-derived detritus off the west coast of Vancouver Island, Canada. Limnol. Oceanogr. https://doi.org/10.1002/lno.10555 (2017).
Article  Google Scholar 

43.
Zanden, M. J. V. & Fetzer, W. W. Global patterns of aquatic food chain length. Oikos 116, 1378–1388 (2007).
Article  Google Scholar 

44.
Diaz, A. L. Resource Relationships Along the Fraser River: A Stable Isotope Analysis of Archaeological Foodways and Paleoecological Interactions. PhD Dissertation, University of British Columbia (2019).

45.
McKechnie, I. & Moss, M. L. Meta-analysis in zooarchaeology expands perspectives on Indigenous fisheries of the Northwest Coast of North America. J. Archaeol. Sci. Rep. 8, 470–485. https://doi.org/10.1016/j.jasrep.2016.04.006 (2016).
Article  Google Scholar 

46.
Efford, M. & McKechnie, I. 42nd Annual Conference of the Society of Ethnobiology May 8–11.

47.
Sumpter, I. D. An analysis of three shellfish assemblages from Ts’ishaa, site DfSi-16 (204T), Benson Island, Pacific Rim National Park Reserve. In Ts’ishaa: Archaeology and Ethnography of a Nuu-chah-nulth Origin Site in Barkley Sound (eds McMillan, A. D. & St. Claire, D. E.) 136–172 (Archaeology Press, Simon Fraser University, Burnaby, 2005).
Google Scholar 

48.
Hay, D. E., McCarter, P. B., Kronlund, R. & Roy, C. Spawning areas of British Columbia herring: a review, geographical analysis and classification. Can. MS Rep. Fish. Aquat. Sci. 1–6, 2019 (2004).
Google Scholar 

49.
St. Claire, D. E. Barkley sound tribal territories. In Between Ports Alberni and Renfrew: Notes on West Coast Peoples, Vol. 121 Mercury Series (eds Arima, E. Y. et al.) 13–202 (Canadian Ethnology Service, Canadian Museum of Civilization, Gatineau, 1991).
Google Scholar 

50.
Wright, C. A., Dallimore, A., Thomson, R. E., Patterson, R. T. & Ware, D. M. Late holocene paleofish populations in Effingham Inlet, British Columbia, Canada. Palaeoecology 224, 367–384 (2005).
Article  Google Scholar 

51.
Losey, R. J., Guiry, E., Nomokonova, T., Gusev, A. V. & Szpak, P. Storing fish?: a dog’s isotopic biography provides insight into Iron Age food preservation strategies in the Russian Arctic. Arch. & Anth. Sci. 12, 200. https://doi.org/10.1007/s12520-020-01166-3 (2020).
Article  Google Scholar 

52.
Schalk, R. F. The structure of an anadromous fish resource. In For Theory Building in Archaeology (eds Binford, L. & Binford, S.) 207–249 (Academic Press, London, 1977).
Google Scholar 

53.
Gunther, E. An analysis of the first salmon ceremony. Am. Anthropol. 28, 605–617 (1926).
Article  Google Scholar 

54.
Booth, A. J., Stogdale, L. & Grigor, J. A. Salmon poisoning disease in dogs on southern Vancouver Island. Can. Vet. J. 25, 2–6 (1984).
CAS  PubMed  PubMed Central  Google Scholar 

55.
Mack, C. Big Dog/Little Horse—ethnohistorical and linguistic evidence for the changing role of dogs on the Mid-and-Lower Columbia in the nineteenth century. J. Northwest Anthropol. 49, 61–70 (2015).
Google Scholar 

56.
Bryan, H. M. et al. Seasonal and biogeographical patterns of gastrointestinal parasites in large carnivores: wolves in a coastal archipelago. Parasitology 139, 781–790 (2012).
PubMed  Article  Google Scholar 

57.
Darimont, C. T., Reimchen, T. E. & Paquet, P. C. Foraging behaviour by gray wolves on salmon streams in coastal British Columbia. Can. J. Zool. 81, 349–353 (2003).
Article  Google Scholar 

58.
Price, M. H. H. et al. Genetics of century-old fish scales reveal population patterns of decline. Conserv. Lett. 12, e12669 (2019).
Article  Google Scholar 

59.
Thompson, T. Q. et al. Anthropogenic habitat alteration leads to rapid loss of adaptive variation and restoration potential in wild salmon populations. PNAS https://doi.org/10.1073/pnas.1811559115 (2019).
Article  PubMed  Google Scholar 

60.
Jewitt, J. R. A Narrative of the Adventures and Sufferings of John R. Jewitt: Only Survivor of the Ship Boston During a Captivity of Nearly Three Years Among the Indians of Nootka Sound: with an Account of the Manners, Mode of Living and Religious Opinions of the Natives (Printed by Loomis, and Richards and reprinted by Rowland Hurst, Wakefield, and Published by Longman, Hurst, Rees, Orme and Brown, London, 1816).

61.
McKechnie, I. Investigating the complexities of sustainable fishing at a prehistoric village on western Vancouver Island, British Columbia, Canada. J. Nat. Conserv. 15, 208–222. https://doi.org/10.1016/j.jnc.2007.05.001 (2007).
Article  Google Scholar 

62.
Robinson, B. G., Franke, A. & Derocher, A. E. Stable isotope mixing models fail to estimate the diet of an avian predator. Auk 135, 60–70. https://doi.org/10.1642/AUK-17-143.1 (2018).
Article  Google Scholar 

63.
West, C. F. & France, C. A. Human and canid dietary relationships: comparative stable isotope analysis from the Kodiak Archipelago, Alaska. J. Ethnobiol. 35, 519–535 (2015).
Article  Google Scholar 

64.
McManus-Fry, E., Knecht, R. A., Dobney, K., Richards, M. P. & Britton, K. Dog-human dietary relationships in Yup’ik western Alaska: the stable isotope and zooarchaeological evidence from pre-contact Nunalleq. J. Archaeol. Sci. Rep. 17, 964–972 (2018).
Google Scholar 

65.
Rick, T. C., Culleton, B. J., Smith, C. B., Johnson, J. R. & Kennett, D. J. Stable isotope analysis of dog, fox, and human diets at a Late Holocene Chumash village (CA-SRI-2) on Santa Rosa Island, California. J. Archaeol. Sci. 38, 1385–1393 (2011).
Article  Google Scholar 

66.
Tsutaya, T., Naito, Y. I., Ishida, H. & Yoneda, M. Carbon and nitrogen isotope analyses of human and dog diet in the Okhotsk culture: perspectives from the Moyoro site, Japan. Anthropol. Sci. 122, 89–99 (2014).
Article  Google Scholar 

67.
Baumann, C. et al. Dietary niche partitioning among Magdalenian canids in southwestern Germany and Switzerland. Quat. Sci. Rev. 227, 106032. https://doi.org/10.1016/j.quascirev.2019.106032 (2020).
Article  Google Scholar 

68.
Feranec, R. S. & Hart, J. P. Fish and Maize: Bayesian mixing models of fourteenth- through seventeenth-century AD ancestral Wendat diets, Ontario, Canada. Sci. Rep. 9, 16658. https://doi.org/10.1038/s41598-019-53076-7 (2019).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar  More

When assessing the ecological status and the development of populations, one important factor to consider is the mortality rate and its underlying causes15. If the status of a population is deemed unsustainable due to high mortality rates, this information can then be used to develop and implement specific management measures, for example addressing the major causes of unnatural mortality16. With regard to the potential ecological relevance of the phenomenon of grey seal predation, it is therefore also important to have reliable estimates of harbour porpoise mortalities resulting from grey seal predation as one natural cause. To allow for a standardised assessment of lesions found in suspected grey seal predation cases, this study aims to summarise the knowledge that has been gathered to date.
The parameters described resemble the most commonly detected lesions in “definite”, “likely” and “fox” related cases of the 246 stranding records categorised as “suspicious” in terms of grey seal predation from the coasts of Schleswig–Holstein. With regard to grey seal predation, parameters 1–9 represent typical lesions, whereas the presence of parameters 10 and 11 is consistent with an interaction with a red fox.
Similar to lesions detected in seals, lesions in porpoises most often resemble puncture lesions in the skin and blubber (parameter 1). Yet, visually most striking is the commonly detected large tissue defect with straight, cut-like wound margins with often flaps of skin and blubber remaining only partly attached to the body (parameters 2, 5, 7). Missing blubber (parameter 4) is also recorded, either as reduced blubber thickness on the flaps of skin or as fully removed parts of blubber and skin. As has been described for seals14, the lesion most often originates in the cervical area (parameter 3). A difference that has been detected between the lesions in seals and porpoises is the rate of clear parallel running bite and / or scratch marks in the skin of the animals. Whereas this is rarely detected in seals14, most porpoises show respective marks (parameter 6). One probable explanation for this dissimilarity could be the different physical and morphological properties of the two types of skin. Seal skin is very dense and elastic; tearing and rupturing the skin requires a considerable amount of force17. Porpoise skin, however, is rather susceptible to applied mechanic force and puncturing or tearing it requires comparably little force18. These different mechanical properties might also be the reason why rake marks are found in the blubber (parameter 9) more often in seals (91% of likely cases14) than in porpoises (62% of likely cases). For seals, in the majority of cases, little to no skin is missing (skin missing in 49% of likely cases14), whereas in porpoises, a considerable number of cases (81% of likely cases) have been found where skin is missing (parameter 7). Grey seals have been described to mainly target the energy rich blubber tissue of their prey11,14. For the elastic and robust seal skin, this is done by scraping off the blubber with the teeth. As porpoise skin is fragile, we suggest that the blubber, including the skin, is more often fully removed by the grey seal and swallowed whole. If true, this may also influence the net energetic gain, which is acquired by the predator. Scraping of blubber tissue from seal skin will likely yield less tissue and cost more energy than tearing off whole pieces of blubber (including skin). Thus, it may result in a lower energetic gain. However, it is still unclear if the process of catching a porpoise in comparison to younger seals might also cost a considerably larger amount of energy, negatively influencing the net gain.
Similar to what has been described for seals, the avulsion of one or both scapulae (parameter 8) can be found and is also likely the result of the force applied when detaching the epidermis and blubber from the body of the prey14.
For porpoises, all nine suggested parameters were found in the definite case of grey seal predation. Parameters 1–5 showed a very high (100%) and parameter 6 a high rate (95%) of occurrence in likely cases. Parameters 7–9 occurred less frequently but were still found in > 60% of all likely predation cases. These high rates of occurrence throughout all parameters suggest that wound patterns found in porpoises are less variable than the patterns found in seals14. Whether this difference is a result of the different mechanical skin properties or if other factors are responsible, is beyond the scope of this study.
While for seals a skeletal trauma is used as an indicator of grey seal predation, for respective harbour porpoise cases, this is hardly ever (19% of likely cases) documented. In contrast, for porpoises, a skeletal trauma (parameter 10) is quite frequently detected in cases related to scavenging by foxes (46% of fox cases) where for example extremities can be manipulated19. As has been reported in seals14, the most often detected parameter in fox related cases is the ragged wound margin (parameter 11, 94% of the cases). Therefore, this can be seen as a good indicator of an interaction with a fox in porpoises. This is also supported by a definite case of fox scavenging, which was confirmed using genetic methods20. It needs to be stated though, that scavenging by birds can result in similar looking lesions, increasing the chance of misinterpretation. Scavenging by birds usually also leaves an irregular wound margin with extensive tissue loss. If parallel running lesions are present, the origin of the lesion can additionally be assessed by measuring the distances in between adjacent lesions and comparing them to published values of grey seal, fox and cetacean inter-teeth distances e.g.1. This is especially important when differentiating between for example rake marks by dolphins, which have been documented in porpoises21,22 and marks induced by grey seals. Here, it can be useful to assess the pattern of inter-teeth distances with those of dolphins expected to be consistent in length, whereas for grey seals, variable distances are expected as the result of the polydont dental morphology23. Despite a lack of available data, a differentiation between grey seal claw-induced marks and dolphin rake marks should be possible, as distances between claws of a subadult / adult grey seal male are expected to be considerably larger than for dolphin inter-teeth distances.
Single puncture lesions, in turn, are not considered as a very good indicator despite being present in the definite and all of the likely cases. Mainly due to the susceptibility of the porpoise skin, such lesions can have many different causes (e.g. feeding by birds).
Whether a loss of muscle tissue can be attributed to grey seal predation or is largely caused by scavengers like gulls as has been suggested for seals14, is still not entirely clear. In German as well as bordering waters, no clear pattern prevails. Carcasses with mainly intact as well as fully removed muscle tissue have been documented c.f.13. However, the reports by Stringell et al.4 suggest that not only the blubber tissue is targeted, but that there may also be some individual behavioural variation.
The findings and the resulting parameters described here are in line with wound patterns reported in earlier publications from other areas1,6,7,13. This shows that the documented wound patterns make a reliable set of parameters when assessing harbour porpoises carcasses potentially predated by a grey seal and should be used in future assessments.
As a complementary tool to the suggested parameters, corresponding to porpoises, we developed a decision tree with the aim of supporting a standardised and information-based decision-making process. Despite an accuracy in decision-making of 96% when using our data set, the example in Fig. 5 illustrates the limitations of such static tools when it comes to judging more complex cases. Furthermore, when comparing the suggestion given by the tree with the one made by the experts, in only 50% of unmatched cases, a rather precautionary judgement was made, bearing the risk of an overestimation of case numbers. Therefore, we recommend using the suggested tree only as an informational tool in supporting decision-making and final judgments should always be made by the responsible expert based on all available information.
In addition to cases for which the attack of a grey seal directly led to the death of the animal, interestingly, it seems not unusual that porpoises escape this predator. Several observations have been described in the literature5,6,13,24 and nine cases were documented in German waters (Figs. 1, 2). In order to be able to verify the origin of recorded teeth marks in porpoise skin, it is crucial to record marks in detail including their pattern, location and inter-teeth distances. Using the latter, for example, interactions with dolphins can potentially be excluded. Although there has been the odd case of a severely injured seal showing comparable lesions to what is associated with grey seal predation14, such high rates of escape cases as described for porpoises have not been reported.
Despite the co-occurrence of porpoises and grey seals in the Baltic, no case of grey seal predation on a porpoise can be confirmed by the presented results. It remains unclear whether grey seals in this area of the Baltic just don’t prey on porpoises or whether other factors like differences in behaviour (e.g. primary area of predation further offshore) are involved.
Some of the observed behaviour of grey seals when catching a porpoise can be directly linked to the detected lesions. For example, Stringell et al.4 as well as Bouveroux et al.7 described the grey seal acting as an ambush predator and attacking the porpoise from below using its jaws to catch and retain the prey. Lesions starting in the throat area (parameter 3) combined with parallel multifocal puncture lesions (parameter 6) resemble what would be expected as the result of such an attack.
Despite a lower rate of variability in detected wound patterns in porpoise carcasses, care should be applied when assessing lesions, as there is always the chance of other factors being involved. Therefore, if possible, a combination of data sources (necropsy results, genetic detection of predator DNA, indicators at the stranding site, eye witness reports, etc.) should be used in a systematic evaluation.
Future research should focus on continuing thorough investigations of stranded marine mammal carcasses in order to further update and refine the suggested set of parameters. Additionally, results of current as well as retrospective analysis of stranding data should be used to support an evaluation of the ecological relevance of this behaviour. More

1.
Mucina, L. & Rutherford, M. C. The Vegetation of South Africa, Lesotho and Swaziland (South African National Biodiversity Institute, Pretoria, 2006).
Google Scholar 
2.
van Zinderen Bakker, E. M. The evolution of late Quaternary paleoclimates of Southern Africa. Palaeoecol. Afr. 9, 160–202 (1976).
Google Scholar 

3.
Cockcroft, M. J., Wilkinson, M. J. & Tyson, P. D. The application of a present-day climatic model to the late Quaternary in southern Africa. Clim. Change 10, 161–181 (1987).
ADS  Google Scholar 

4.
Chase, B. M. & Meadows, M. E. Late Quaternary dynamics of southern Africa’s winter rainfall zone. Earth Sci. Rev. 84(3), 103–138 (2007).
ADS  Google Scholar 

5.
Bistinas, I., Harrison, S. P., Prentice, I. C. & Pereira, J. M. C. Causal relationships vs. emergent patterns in the global controls of fire frequency. Biogeosciences 11, 5087–5101 (2014).
ADS  Google Scholar 

6.
Hoetzel, S., Dupont, L., Schefuß, E., Rommerskirchen, F. & Wefer, G. The role of fire in Miocene to Pliocene C 4 grassland and ecosystem evolution. Nat. Geosci. 6(12), 1027–1030 (2013).
ADS  CAS  Google Scholar 

7.
Bond, W. J., Woodward, F. I. & Midgley, G. F. The global distribution of ecosystems in a world without fire. New Phytol. 165(2), 525–538 (2005).
CAS  PubMed  Google Scholar 

8.
Ripley, B. et al. Fire ecology of C3 and C4 grasses depends on evolutionary history and frequency of burning but not photosynthetic type. Ecology 96(10), 2679–2691 (2015).
PubMed  Google Scholar 

9.
Pinto, H., Sharwood, R. E., Tissue, D. T. & Ghannoum, O. Photosynthesis of C3, C3–C4, and C4 grasses at glacial CO2. J. Exp. Bot. 65(13), 3669–3681 (2014).
PubMed  PubMed Central  Google Scholar 

10.
Roth-Nebelsick, A. & Konrad, W. Habitat responses of fossil plant species to palaeoclimate—possible interference with CO2?. Palaeogeogr. Palaeoclimatol. Palaeoecol. 467, 277–286 (2017).
Google Scholar 

11.
Ehleringer, J. R., Cerling, T. E. & Helliker, B. R. C4 photosynthesis, atmospheric CO2, and climate. Oecologia 112(3), 285–299 (1997).
ADS  PubMed  Google Scholar 

12.
Edwards, E. J., Osborne, C. P., Strömberg, C. A., Smith, S. A. & C4 Grasses Consortium. The origins of C4 grasslands: integrating evolutionary and ecosystem science. Science 328(5978), 587–591 (2010).
CAS  PubMed  Google Scholar 

13.
Hönisch, B., Hemming, N. G., Archer, D., Siddall, M. & McManus, J. F. Atmospheric carbondioxide concentration across the mid-Pleistocene transition. Science 324(5934), 1551–1554 (2009).
ADS  PubMed  Google Scholar 

14.
Yan, Y. et al. Two-million-year-old snapshots of atmospheric gases from Antarctic ice. Nature 574(7780), 663–666 (2019).
ADS  CAS  PubMed  Google Scholar 

15.
Faith, J. T., Rowan, J. & Du, A. Early hominins evolved within non-analog ecosystems. Proc. Natl. Acad. Sci. 116(43), 21478–21483 (2019).
ADS  CAS  PubMed  Google Scholar 

16.
Sealy, J., Naidoo, N., Hare, V. J., Brunton, S. & Faith, J. T. Climate and ecology of the palaeo-Agulhas Plain from stable carbon and oxygen isotopes in bovid tooth enamel from Nelson Bay Cave, South Africa. Quat. Sci. Rev. 235, 105974 (2019).
Google Scholar 

17.
Horwitz, L. K. & Chazan, M. Past and present at Wonderwerk Cave (Northern Cape Province, South Africa). Afr. Archaeol. Rev. 32(4), 595–612 (2015).
Google Scholar 

18.
Ecker, M. et al. The palaeoecological context of the Oldowan-Acheulean in southern Africa. Nat. Ecol. Evol. 2(7), 1080–1086 (2018).
PubMed  Google Scholar 

19.
Matmon, A. et al. New chronology for the southern Kalahari Group sediments with implications for sediment-cycle dynamics and early hominin occupation. Quat. Res. 84(1), 118–132 (2015).
Google Scholar 

20.
Vainer, S., Erel, Y. & Matmon, A. Provenance and depositional environments of Quaternary sediments in the southern Kalahari Basin. Chem. Geol. 476, 352–369 (2018).
ADS  CAS  Google Scholar 

21.
Prentice, I. C. et al. Modeling fire and the terrestrial carbon balance. Glob. Biogeochem. Cycles 25(3), 2–13 (2011).
Google Scholar 

22.
Braconnot, P. et al. Results of PMIP2 coupled simulations of the Mid-Holocene and Last Glacial Maximum-Part 1: experiments and large-scale features. Clim. Past 3(2), 261–277 (2007).
Google Scholar 

23.
Kelley, D. I. et al. A comprehensive benchmarking system for evaluating global vegetation models. Biogeosciences 10(5), 3313–3340 (2013).
ADS  Google Scholar 

24.
Chazan, M. et al. Archaeology, paleoenvironment and chronology of the early middle stone age component of Wonderwerk cave in the interior of southern Africa. J. Palaeolithic Archaeol. https://doi.org/10.1007/s41982-020-00051-8 (2020).
Article  Google Scholar 

25.
Lee-Thorp, J. A. & Beaumont, P. B. Vegetation and seasonality shifts during the late Quaternary deduced from 13C/12C ratios of grazers at Equus Cave, South Africa. Quat. Res. 43, 426–432 (1995).
Google Scholar 

26.
Vogel, J. C. The geographical distribution of Kranz species in southern Africa. South Afr. J. Sci. 75, 209–215 (1978).
Google Scholar 

27.
Zhou, H., Helliker, B. R., Huber, M., Dicks, A. & Akçay, E. C4 photosynthesis and climate through the lens of optimality. Proc. Natl. Acad. Sci. 115(47), 12057–12062 (2018).
CAS  PubMed  Google Scholar 

28.
Rubin, F., Palmer, A. R. & Tyson, C. Patterns of endemism within the Karoo National Park, South Africa. Bothalia 31(1), 117–133 (2001).
Google Scholar 

29.
Walker, S. J., Lukich, V. & Chazan, M. Kathu townlands: a high density earlier stone age locality in the interior of South Africa. PLoS ONE 9(7), e103436 (2014).
ADS  PubMed  PubMed Central  Google Scholar 

30.
Lee-Thorp, J. A., Sponheimer, M. & Luyt, J. Tracking changing environments using stable carbon isotopes in fossil tooth enamel: an example from the South African hominin sites. J. Hum. Evol. 53(5), 595–601 (2007).
PubMed  Google Scholar 

31.
Codron, D., Brink, J. S., Rossouw, L. & Clauss, M. The evolution of ecological specialization in southern African ungulates: competition- or physical environmental turnover?. Oikos 117, 344–353 (2008).
Google Scholar 

32.
Plummer, T. W. et al. The environmental context of Oldowan hominin activities at Kanjera South, Kenya. In Interdisciplinary approaches to the Oldowan (eds Hovers, E. & Braun, D. R.) 149–160 (Springer, Berlin, 2009).
Google Scholar 

33.
Cerling, T. E. et al. Dietary changes of large herbivores in the Turkana Basin, Kenya from 4 to 1 Ma. Proc. Natl. Acad. Sci. 112(37), 11467–11472 (2015).
ADS  CAS  PubMed  Google Scholar 

34.
Harris, I., Osborn, T. J., Jones, P. & Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data. https://doi.org/10.1038/s41597-020-0453-3 (2020).
Article  PubMed  PubMed Central  Google Scholar 

35.
Sitch, S. et al. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob. Change Biol. 9(2), 161–185 (2003).
ADS  Google Scholar 

36.
Thonicke, K. et al. The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: results from a process-based model. Biogeosciences 7(6), 1991–2011 (2010).
ADS  CAS  Google Scholar 

37.
Haxeltine, A. & Prentice, I. C. BIOME3: an equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types. Glob. Biogeochem. Cycles 10(4), 693–709 (1996).
ADS  CAS  Google Scholar 

38.
Haxeltine, A. & Prentice, I. C. A general model for the light-use efficiency of primary production. Funct. Ecol. 10, 551–561 (1996).
Google Scholar 

39.
Farquhar, G. D., Von Caemmerer, S. & Berry, J. A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 plants. Planta 149, 78–90 (1980).
CAS  PubMed  PubMed Central  Google Scholar 

40.
Farquhar, G. D. & Von Caemmerer, S. Modelling of photosynthetic response to environmental conditions. In Physiological Plant Ecology II: Water Relations and Carbon Assimilation (eds Nobel, P. S. et al.) 549–587 (Springer, Berlin, 1982).
Google Scholar 

41.
Monteith, J. L. A reinterpretation of stomatal responses to humidity. Plant Cell Environ. 18, 357–364 (1995).
Google Scholar 

42.
Rothermel, R. C. A Mathematical Model for Predicting Fire Spread in Wildland Fuels (Vol. 115). Intermountain Forest and Range Experiment Station, Forest Service, US Department of Agriculture (1972).

43.
Sato, H., Kelley, D. I., Mayor, S. J., Cowling S. A., Calvo, M. M. & Prentice, I. C. Fire and low CO2 opened dry corridors in South America during the Last Glacial Maximum. Under Review for Nature Geosciences: NGS-2019–07–01558B (2020).

44.
Prentice, I. C., Harrison, S. P. & Bartlein, P. J. Global vegetation and terrestrial carbon cycle changes after the last ice age. New Phytol. 189(4), 988–998 (2011).
CAS  PubMed  Google Scholar  More

Cohort and data description
In order to examine seasonal changes of human molecular data, we leveraged the power of longitudinal multiomics data from profiling of 105 individuals (55 women and 50 men) with ages ranging from 25 to 75 years old (Fig. 1a; Supplementary Table 1). This cohort was generally healthy and well characterized for glucose dysregulation using annual oral glucose tolerance tests (OGTTs), insulin resistance measuring steady-state plasma glucose (SSPG), fasting glucose and hemoglobin A1c (HbA1c; an indicator of the average level of blood glucose over the past 100 days)19 as well as quarterly sample collections with measurements of transcriptomes (from peripheral blood mononuclear cells), proteome and metabolome from plasma, targeted cytokine and growth factor assays using serum. Nasal and gut microbiomes were analyzed using 16S rRNA sequencing providing information at the genus level and host exome sequencing was performed once from PBMCs (Fig. 1b). Moreover, 51 clinical laboratory tests were acquired on each visit and they were aligned to the meteorological data (e.g. air temperature), pollen counts (e.g. mold spores, grass pollens, tree pollens, weed pollens) and airborne fungi from the San Francisco bay area. In total, there were 902 visits (average across different types of omes‘) from which samples were drawn over up to 4 years (see “Methods”). The sample collections were generally evenly distributed throughout the year (Fig. 1b). Nearly all individuals lived in the San Francisco Bay Area with the exception of three individuals who lived in Southern California and frequented the Bay area (Supplementary Data 1). Participants in our study were well characterized for steady-state plasma glucose (SSPG) using the modified insulin suppression test20, in which 31 participants were insulin sensitive (SSPG  0.05, Supplementary Table 5, Supplementary Fig. 10). In our analysis we used subject ID as a random effect to account for different numbers of samples per subject. On the other hand, physical activity measured in total metabolic equivalent of task (MET) is significantly different between the IR and the IS groups in February, May, June, and August (P-value = 0.01787, Supplementary Fig. 11). However, a post-hoc analysis of all the omics features that were identified to be significantly different between the IR and the IS groups, are not associated with the physical activity. More

1.
United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects 2019—Data Booklet (ST/ESA/ SER.A/377), (2019). https://population.un.org/wpp/Publications/Files/WPP2019_DataBooklet.pdf
2.
Pimentel, D. & Burgess, M. Environmental and economic costs of the application of pesticides primarily in the United States. In Integrated Pest Management: Innovation-Development Process (eds Peshin, R. & Dhawan, A. K.) 47–71 (Springer, Dordrecht, 2014). https://doi.org/10.1007/978-1-4020-8992-3_4
Google Scholar 

3.
Devine, G. J. & Furlong, M. J. Insecticide use: Contexts and ecological consequences. Agric. Hum. Values 24(3), 281–306. https://doi.org/10.1007/s10460-007-9067-z (2007).
Article  Google Scholar 

4.
Sanchis, V. & Bourguet, D. Bacillus thuringiensis: Applications in agriculture and insect resistance management. A review. Agron. Sustain. Dev. 28(1), 11–20. https://doi.org/10.1051/agro:2007054 (2008).
Article  Google Scholar 

5.
WHO report. WHO specifications and evaluations for public health pesticides: Bacillus thuringiensis subspecies israelensis strain AM65-52. (World Health Organization, Geneva, 2007).

6.
Rizzati, V., Briand, O., Guillou, H. & Gamet-Payrastre, L. Effects of pesticide mixtures in human and animal models: An update of the recent literature. Chem. Biol. Interact. 254, 231–246. https://doi.org/10.1016/j.cbi.2016.06.003 (2016).
Article  PubMed  CAS  Google Scholar 

7.
Lacey, L. A. et al. Insect pathogens as biological control agents: Back to the future. J. Invertebr. Pathol. 132, 1–41. https://doi.org/10.1016/j.jip.2015.07.009 (2015).
Article  PubMed  CAS  Google Scholar 

8.
Adang, M. J., Crickmore, N. & Jurat-Fuentes, J. L. Diversity of Bacillus thuringiensis Crystal Toxins and Mechanism of Action. Adv. Insect Physiol. 47, 39–87. https://doi.org/10.1016/B978-0-12-800197-4.00002-6 (2014).
Article  Google Scholar 

9.
Crickmore, N. Bacillus thuringiensis toxin classification. In Bacillus thuringiensis and Lysinibacillus sphaericus. (eds Fiuza, L.M. et al.) ISBN 978-3-319-56677-1, 41-52, (Spinger, Cham, 2017).

10.
WHO report. Guideline specification for bacterial larvicides for public health use. WHO document WHO/CDS/CPC/WHOPES/99.2 (World Health Organization, Geneva, 1999).

11.
Bravo, A., Pacheco, S., Gomez, I., Garcia-Gomez B., Onofre, J., Soberon, M. Insecticidal Proteins from Bacillus thuringiensis and their Mechanism of Action. In Bacillus thuringiensis and Lysinibacillus sphaericus (eds Fiuza, L.M. et al.) ISBN 978-3-319-56677-1, 53–66, (Spinger, Cham, 2017).

12.
Palma, L., Muñoz, D., Berry, C., Murillo, J. & Caballero, P. Bacillus thuringiensis toxins: An overview of their biocidal activity. Toxins 6(12), 3296–3325. https://doi.org/10.3390/toxins6123296 (2014).
Article  PubMed  PubMed Central  CAS  Google Scholar 

13.
Ben-Dov, E. et al. Extended screening by PCR for seven cry-group genes from field-collected strains of Bacillus thuringiensis. Appl. Environ. Microb. 63(12), 4883–4890. https://doi.org/10.1128/aem.63.12.4883-4890.1997 (1997).
CAS  Google Scholar 

14.
Berry, C. et al. Complete sequence and organization of pBtoxis, the toxin-coding plasmid of Bacillus thuringiensis subsp. israelensis. Appl. Environ. Microbiol. 68(10), 5082–5095. https://doi.org/10.1128/aem.68.10.5082-5095.2002 (2002).
Article  PubMed  PubMed Central  CAS  Google Scholar 

15.
Bravo, A., Gill, S. S. & Soberon, M. Mode of action of Bacillus thuringiensis Cry and Cyt toxins and their potential for insect control. Toxicon 49, 423–435. https://doi.org/10.1016/j.toxicon.2006.11.022 (2007).
Article  PubMed  CAS  Google Scholar 

16.
Wei, J. et al. Activation of Bt protoxin Cry1Ac in resistant and susceptible cotton bollworm. PLoS ONE 11(6), e0156560. https://doi.org/10.1371/journal.pone.0156560 (2016).
Article  PubMed  PubMed Central  CAS  Google Scholar 

17.
Bravo, A., Likitvivatanavong, S., Gill, S. S. & Soberon, M. Bacillus thuringiensis: A story of a successful bioinsecticide. Insect Biochem. Mol. Biol. 41(7), 423–431. https://doi.org/10.1016/j.ibmb.2011.02.006 (2011).
Article  PubMed  PubMed Central  CAS  Google Scholar 

18.
Caccia, S. et al. Midgut microbiota and host immunocompetence underlie Bacillus thuringiensis killing mechanism. Proc. Natl. Acad. Sci. USA 113(34), 9486–9491. https://doi.org/10.1073/pnas.1521741113 (2016).
Article  PubMed  CAS  Google Scholar 

19.
Glare, T.R., O’Callaghan, M. Bacillus thuringiensis: Biology, Ecology and Safety. ISBN: 9780471496304, 350, (Wiley, New York, 2000).

20.
Rubio-Infante, N. & Moreno-Fierros, L. An overview of the safety and biological effects of Bacillus thuringiensis Cry toxins in mammals. J. Appl. Toxicol. 36, 630–648. https://doi.org/10.1002/jat.3252 (2016).
Article  PubMed  CAS  Google Scholar 

21.
EFSA Panel on Biological Hazards (BIOHAZ). Risks for public health related to the presence of Bacillus cereus and other Bacillus spp. including Bacillus thuringiensis in foodstuffs. EFSA J. https://doi.org/10.2903/j.efsa.2016.4524 (2016).
Article  Google Scholar 

22.
Amichot, M., Curty, C., Benguettat-Magliano, O., Gallet, A. & Wajnberg, E. Side effects of Bacillus thuringiensis var. kurstaki on the hymenopterous parasitic wasp Trichogramma chilonis. Environ. Sci. Pollut. Res. Int. 23, 3097–3103. https://doi.org/10.1007/s11356-015-5830-7 (2016).
Article  PubMed  CAS  Google Scholar 

23.
Renzi, M. T. et al. Chronic toxicity and physiological changes induced in the honey bee by the exposure to fipronil and Bacillus thuringiensis spores alone or combined. Ecotoxicol. Environ. Saf. 127, 205–213. https://doi.org/10.1016/j.ecoenv.2016.01.028 (2016).
Article  PubMed  CAS  Google Scholar 

24.
Caquet, T., Roucaute, M., Le Goff, P. & Lagadic, L. Effects of repeated field applications of two formulations of Bacillus thuringiensis var. israelensis on non-target saltmarsh invertebrates in Atlantic coastal wetlands. Ecotoxicol. Environ. Saf. 74, 1122–1130. https://doi.org/10.1016/j.ecoenv.2011.04.028 (2011).
Article  PubMed  CAS  Google Scholar 

25.
Duguma, D. et al. Microbial communities and nutrient dynamics in experimental microcosms are altered after the application of a high dose of Bti. J. Appl. Ecol. 52, 763–773. https://doi.org/10.1111/1365-2664.12422 (2015).
Article  CAS  Google Scholar 

26.
Venter, H. J. & Bøhn, T. Interactions between Bt crops and aquatic ecosystems: A review. Environ. Toxicol. Chem. 35(12), 2891–2902. https://doi.org/10.1002/etc.3583 (2016).
Article  PubMed  CAS  Google Scholar 

27.
van Frankenhuyzen, K. Specificity and cross-order activity of Bacillus thuringiensis pesticidal proteins. In Bacillus thuringiensis and Lysinibacillus sphaericus (eds Fiuza, L.M. et al.) ISBN 978-3-319-56677-1, 127–172, (Springer, Cham, 2017).

28.
Bizzarri, M. F. & Bishop, A. H. The ecology of Bacillus thuringiensis on the phylloplane: Colonization from soil, plasmid transfer, and interaction with larvae of Pieris brassicae. Microb. Ecol. 56(1), 133–139. https://doi.org/10.1007/s00248-007-9331-1 (2008).
Article  PubMed  CAS  Google Scholar 

29.
Raymond, B., Wyres, K. L., Sheppard, S. K., Ellis, R. J. & Bonsall, M. B. Environmental factors determining the epidemiology and population genetic structure of the Bacillus cereus group in the field. PLoS Pathog. 6(5), e1000905. https://doi.org/10.1371/journal.ppat.1000905 (2010).
Article  PubMed  PubMed Central  CAS  Google Scholar 

30.
Hendriksen, N. B. & Hansen, B. M. Long-term survival and germination of Bacillus thuringiensis var. kurstaki in a field trial. Can. J. Microbiol. 48(3), 256–261. https://doi.org/10.1139/w02-009 (2002).
Article  PubMed  CAS  Google Scholar 

31.
Hung, T. P. et al. Persistence of detectable insecticidal proteins from Bacillus thuringiensis (Cry) and toxicity after adsorption on contrasting soils. Environ. Pollut. 208, 318–325. https://doi.org/10.1016/j.envpol.2015.09.046 (2016).
Article  PubMed  CAS  Google Scholar 

32.
Hung, T. P. et al. Fate of insecticidal Bacillus thuringiensis Cry protein in soil: Differences between purified toxin and biopesticide formulation. Pest Manag. Sci. 72, 2247–2253. https://doi.org/10.1002/ps.4262 (2016).
Article  PubMed  CAS  Google Scholar 

33.
Enger, K. S. et al. Evaluating the long-term persistence of Bacillus spores on common surfaces. Microb. Biotechnol. 11(6), 1048–1059. https://doi.org/10.1111/1751-7915.13267 (2018).
Article  PubMed  PubMed Central  CAS  Google Scholar 

34.
Couch, T.L. Industrial fermentation and formulation of entomopathogenic bacteria. In Entomopathogenic Bacteria: From Laboratory to Field Application (eds Charles, J.-F. et al.) ISBN 978-90-481-5542-2, 297–316.43, (Springer, Dordrecht, 2000).

35.
Brar, S. K., Verma, M., Tyagi, R. D. & Valéro, J. R. Recent advances in downstream processing and formulations of Bacillus thuringiensis based biopesticides. Process Biochem. 41(2), 323–342. https://doi.org/10.1016/j.procbio.2005.07.015 (2006).
Article  CAS  Google Scholar 

36.
Setlow, P. Spore resistance properties. Microbiol. Spectr. 2(5), TBS-0003-2012. https://doi.org/10.1128/microbiolspec.TBS-0003-2012 (2014).
Article  CAS  Google Scholar 

37.
European Food Safety Authority. Conclusion on the peer review of the pesticide risk assessment of the active substance Bacillus thuringiensis subsp. Kurstaki (strains ABTS 351, PB 54, SA 11, SA 12, EG 2348). EFSA J. 10(2), 2540. https://doi.org/10.2903/j.efsa.2012.2540 (2012).
Article  CAS  Google Scholar 

38.
Bächli, G. TaxoDros: The database on Taxonomy of Drosophilidae: Database 2020/1.https://www.taxodros.uzh.ch. (1999–2020).

39.
Tennessen, J. M. & Thummel, C. S. Coordinating growth and maturation—Insights from Drosophila. Curr. Biol. 21(18), R750–R757. https://doi.org/10.1016/j.cub.2011.06.033 (2011).
Article  PubMed  PubMed Central  CAS  Google Scholar 

40.
Benz, G. & Perron, J. M. The toxic action of Bacillus thuringiensis “exotoxin” on Drosophila reared in yeast-containing and yeast-free media. Experientia 23(10), 871–872 (1967).
PubMed  CAS  Google Scholar 

41.
Saadoun, I., Al-Moman, F., Obeidat, M., Meqdam, M. & Elbetieha, A. Assessment of toxic potential of local Jordanian Bacillus thuringiensis strains on Drosophila melanogaster and Culex sp. (Diptera). J. Appl. Microbiol. 90, 866–872. https://doi.org/10.1046/j.1365-2672.2001.01315.x (2001).
Article  PubMed  CAS  Google Scholar 

42.
Khyami-Horani, H. Toxicity of Bacillus thuringiensis and B. sphaericus to laboratory populations of Drosophila melanogaster (Diptera: Drosophilidae). J. Basic Microbiol. 42(2), 105–110. https://doi.org/10.1002/1521-4028(200205)42:23.0.CO;2-S (2002). 
Article  PubMed  Google Scholar 

43.
Obeidat, M. Toxicity of local Bacillus thuringiensis isolates against Drosophila melanogaster. WJAS 4(2), 161–167 (2008).
Google Scholar 

44.
Obeidat, M., Khymani-Horani, H. & Al-Momani, F. Toxicity of Bacillus thuringiensis β-exotoxins and δ-endotoxins to Drosophila melanogaster, Ephestia kuhniella and human erythrocytes. Afr. J. Biotechnol. 11(46), 10504–10512 (2012).
Google Scholar 

45.
Cossentine, J., Robertson, M. & Xu, D. Biological activity of Bacillus thuringiensis in Drosophila suzukii (Diptera: Drosophilidae). J. Econ. Entomol. 109(3), 1–8. https://doi.org/10.1093/jee/tow062 (2016).
Article  CAS  Google Scholar 

46.
Biganski, S., Jehle, J. A. & Kleepies, R. G. Bacillus thuringiensis serovar israelensis has no effect on Drosophila suzukii Matsumura. J. Appl. Entomol. 142, 33–36. https://doi.org/10.1111/jen.12415 (2017).
Google Scholar 

47.
Haller, S., Romeis, J. X. R. & Meissle, M. Effects of purified or plant-produced Cry proteins on Drosophila melanogaster (Diptera: Drosophilidae) larvae. Sci. Rep. 7(1), 11172. https://doi.org/10.1038/s41598-017-10801-4 (2017).
ADS  Article  PubMed  PubMed Central  CAS  Google Scholar 

48.
Benado, M. & Brncic, D. An eight-year phenological study of a local drosophilid community in Central Chile. J. Zool. Syst. Evol. Res. 32, 51–63. https://doi.org/10.1111/j.1439-0469.1994.tb00470.x (1994).
Article  Google Scholar 

49.
Nunney, L. The colonization of oranges by the cosmopolitan Drosophila. Oecologia 108, 552–561. https://www.jstor.org/stable/4221451 (1996).
ADS  PubMed  Google Scholar 

50.
Mitsui, H. & Kimura, M. T. Coexistence of drosophilid flies: Aggregation, patch size diversity and parasitism. Ecol. Res. 15, 93–100.  https://doi.org/10.1046/j.1440-1703.2000.00328.x (2000).
Google Scholar 

51.
Withers, P. & Allemand, R. Les drosophiles de la région Rhône-Alpes (Diptera, Drosophilidae). Bull. Soc. Entomol. Fr. 117(4), 473–482. https://www.persee.fr/doc/bsef_0037-928x_2012_num_117_4_3076 (2012).
Google Scholar 

52.
Stevens, T., Song, S., Bruning, J. B., Choo, A. & Baxter, S. W. Expressing a moth abcc2 gene in transgenic Drosophila causes susceptibility to Bt Cry1Ac without requiring a cadherin-like protein receptor. Insect Biochem. Mol. Biol. 80, 61–70. https://doi.org/10.1016/j.ibmb.2016.11.008 (2017).
Article  PubMed  CAS  Google Scholar 

53.
George, Z., Crickmore, N. Bacillus thuringiensis applications in agriculture. In Bacillus thuringiensis Biotechnology (ed Sansinenea, E.) 392, (Springer, Dordrecht, 2012).

54.
Nepoux, V., Haag, C. R. & Kawecki, T. J. Effects of inbreeding on aversive learning in Drosophila. J. Evol. Biol. 23, 2333–2345. https://doi.org/10.1111/j.1420-9101.2010.02094.x (2010).
Article  PubMed  CAS  Google Scholar 

55.
Vantaux, A., Ouattarra, I., Lefèvre, T. & Dabiré, K. R. Effects of larvicidal and larval nutritional stresses on Anopheles gambiae development, survival and competence for Plasmodium falciparum. Parasite. Vector. 9, 226. https://doi.org/10.1186/s13071-016-1514-5 (2016).
Article  CAS  Google Scholar 

56.
Moret, Y. & Schmid-Hempel, P. Survival for immunity: The price of immune system activation for bumblebee workers. Science 290(5494), 1166–1168. https://doi.org/10.1126/science.290.5494.1166 (2000).
ADS  Article  PubMed  CAS  Google Scholar 

57.
Kutzer, M. A. & Armitage, S. A. O. The effect of diet and time after bacterial infection on fecundity, resistance, and tolerance in Drosophila melanogaster. Ecol. Evol. 6(13), 4229–4242. https://doi.org/10.1002/ece3.2185 (2016).
Article  PubMed  PubMed Central  Google Scholar 

58.
Andersen, L. H., Kristensen, T. N., Loeschcke, V., Toft, S. & Mayntz, D. Protein and carbohydrate composition of larval food affects tolerance to thermal stress and desiccation in adult Drosophila melanogaster. J. Insect Physiol. 56, 336–340. https://doi.org/10.1016/j.jinsphys.2009.11.006 (2010).
Article  PubMed  CAS  Google Scholar 

59.
Rion, S. & Kawecki, T. J. Evolutionary biology of starvation resistance: What we have learned from Drosophila. J. Evol. Biol. 20(5), 1655–1664. https://doi.org/10.1111/j.1420-9101.2007.01405.x (2007).
Article  PubMed  CAS  Google Scholar 

60.
Burger, J. M. S., Buechel, S. D. & Kawecki, T. J. Dietary restriction affects lifespan but not cognitive aging in Drosophila melanogaster. Aging Cell 9, 327–335. https://doi.org/10.1111/j.1474-9726.2010.00560.x (2010).
Article  PubMed  CAS  Google Scholar 

61.
Khazaeli, A. A. & Curtsinger, J. W. Genetic analysis of extended lifespan in Drosophila melanogaster III. On the relationship between artificially selected and wild stocks. Genetica 109, 245–253. https://doi.org/10.1023/a:1017569318401 (2000).
Article  PubMed  CAS  Google Scholar 

62.
Atkinson, W. & Shorrocks, B. Breeding site specificity in the domestic species of Drosophila. Oecologia 29(3), 223–232. https://www.jstor.org/stable/4215461 (1977).
ADS  PubMed  CAS  Google Scholar 

63.
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. https://doi.org/10.1603/IPM10010 (2011).
Article  Google Scholar 

64.
Delbac, L. et al. Drosophila suzukii est-elle une menace pour la vigne?. Phytoma 679, 16–21 (2014).
Google Scholar 

65.
Poyet, M. et al. Invasive host for invasive pest: When the Asiatic cherry fly (Drosophila suzukii) meets the American black cherry (Prunus serotine) in Europe. Agric. For. Entomol. 16(3), 251–259. https://doi.org/10.1111/afe.12052 (2014).
Article  Google Scholar 

66.
Poulin, B., Lefebvre, G. & Paz, L. Red flag for green spray: Adverse trophic effects of Bti on breeding birds. J. Appl. Ecol. 47, 884–889. https://doi.org/10.1111/j.1365-2664.2010.01821.x (2010).
Article  Google Scholar 

67.
Zeigler, D.R. Bacillus genetic stock center catalog of strains, 7th edition. Part 2: Bacillus thuringiensis and Bacillus cereus. http://www.bgsc.org/_catalogs/Catpart2.pdf (1999).

68.
Gonzales, J. M. Jr., Brown, B. J. & Carlton, B. C. Transfer of Bacillus thuringiensis plasmids coding for δ-endotoxin among strains of B. thuringiensis and B. cereus. Proc. Natl Acad. Sci. USA 79, 6951–6955. https://doi.org/10.1073/pnas.79.22.6951 (1982).
ADS  Article  Google Scholar 

69.
Santos, M., Borash, D. J., Joshi, A., Bounlutay, N. & Mueller, L. D. Density-dependent natural selection in Drosophila: Evolution of growth rate and body size. Evolution 51(2), 420–432. https://doi.org/10.2307/2411114 (1997).
Article  PubMed  Google Scholar 

70.
Bradberry, S. M., Proudfoot, A. T. & Vale, J. A. Glyphosate poisoning. Toxicol. Rev. 23(3), 159–167. https://doi.org/10.2165/00139709-200423030-00003 (2004).
Article  PubMed  CAS  Google Scholar 

71.
R Development Core Team. R: A language and environment for statistical computing. ISBN 3-900051-07-0 https://www.R-project.org (R Foundation for Statistical Computing, Vienna, 2008).

72.
Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).
Google Scholar 

73.
Kosmidis I. brglm: Bias Reduction in Binary-Response Generalized Linear Models. R package version 0.6.1, https://www.ucl.ac.uk/~ucakiko/software.html, (2017).

74.
Horton, T., Bretz, F. & Westfall, P. Simultaneous inference in general parametric models. Biometrical J. 50(3), 346–363. https://doi.org/10.1002/bimj.200810425 (2008).
MathSciNet  Article  Google Scholar 

75.
Therneau, T.M., Grambsch, P.M. Modeling Survival Data: Extending The Cox Model. ISBN 0-387-98784-3 (Springer, New York, 2000).

76.
Therneau, T.M. coxme: Mixed Effects Cox Models. R package version 2.2-5. https://CRAN.R-project.org/package=coxme (2015). More