Philippa Kaur

Mason, G. J. Stereotypies: A critical review. Anim. Behav. 41, 1015–1037 (1991).
Google Scholar 
Cussen, V. A. & Mench, J. A. The relationship between personality dimensions and resiliency to environmental stress in orange-winged Amazon parrots (Amazona amazonica), as indicated by the development of abnormal behaviors. PLoS ONE 10, 1–11 (2015).
Google Scholar 
Clubb, R. & Mason, G. Captivity effects on wide-ranging carnivores. Nature 425, 473–474 (2003).ADS 
CAS 
PubMed 

Google Scholar 
Shepherdson, D., Lewis, K. D., Carlstead, K., Bauman, J. & Perrin, N. Individual and environmental factors associated with stereotypic behavior and fecal glucocorticoid metabolite levels in zoo housed polar bears. Appl. Anim. Behav. Sci. 147, 268–277 (2013).
Google Scholar 
Miller, L. J., Bettinger, T. & Mellen, J. The reduction of stereotypic pacing in tigers (Panthera tigris) by obstructing the view of neighbouring individuals. Anim. Welf. 17, 255–258 (2008).CAS 

Google Scholar 
Bachmann, I., Bernasconi, P., Herrmann, R., Weishaupt, M. A. & Stauffacher, M. Behavioural and physiological responses to an acute stressor in crib-biting and control horses. Appl. Anim. Behav. Sci. 82, 297–311 (2003).
Google Scholar 
Ahola, M. K., Vapalahti, K. & Lohi, H. Early weaning increases aggression and stereotypic behaviour in cats. Sci. Rep. 7, 10412 (2017).ADS 
PubMed 
PubMed Central 

Google Scholar 
Salonen, M. et al. Prevalence, comorbidity, and breed differences in canine anxiety in 13,700 Finnish pet dogs. Sci. Rep. 10, 2962 (2020).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Garner, J. P. Stereotypies and other abnormal repetitive behaviors: Potential impact on validity, reliability, and replicability of scientific outcomes. ILAR J. 46, 106–117 (2005).CAS 
PubMed 

Google Scholar 
Tynes, V. V. & Sinn, L. Abnormal repetitive behaviors in dogs and cats. A guide for practitioners. Vet. Clin. North Am. Small Anim. Pract. 44, 543–564 (2014).PubMed 

Google Scholar 
Luescher, A. U. Diagnosis and management of compulsive disorders in dogs and cats. Vet. Clin. North Am. Small Anim. Pract. 33, 253–267 (2003).PubMed 

Google Scholar 
Mason, G., Clubb, R., Latham, N. & Vickery, S. Why and how should we use environmental enrichment to tackle stereotypic behaviour?. Appl. Anim. Behav. Sci. 102, 163–188 (2007).
Google Scholar 
Overall, K. L. & Dunham, A. E. Clinical features and outcome in dogs and cats with obsessive-compulsive disorder: 126 Cases (1989–2000). J. Am. Vet. Med. Assoc. 221, 1445–1452 (2002).PubMed 

Google Scholar 
Tiira, K. et al. Environmental effects on compulsive tail chasing in dogs. PLoS One 7, e41684 (2012).Mason, G. & Rushen, J. Stereotypic Animal Behaviour: Fundamentals and Applications to Welfare 2nd edn. (CABI Publishing, 2006).
Google Scholar 
Moon-Fanelli, A. A., Dodman, N. H., Famula, T. R. & Cottam, N. Characteristics of compulsive tail chasing and associated risk factors in Bull Terriers. J. Am. Vet. Med. Assoc. 238, 883–889 (2011).PubMed 

Google Scholar 
Hewson, C. J., Luescher, U. A. & Ball, R. O. Measuring change in the behavioural severity of canine compulsive disorder: The construct validity of categories of change derived from two rating scales. Appl. Anim. Behav. Sci. 60, 55–68 (1998).
Google Scholar 
Vandeleest, J. J., McCowan, B. & Capitanio, J. P. Early rearing interacts with temperament and housing to influence the risk for motor stereotypy in rhesus monkeys (Macaca mulatta). Appl. Anim. Behav. Sci. 132, 81–89 (2011).PubMed 
PubMed Central 

Google Scholar 
Tang, R. et al. Candidate genes and functional noncoding variants identified in a canine model of obsessive-compulsive disorder. Genome Biol. 15, 25 (2014).
Google Scholar 
Dodman, N. H. et al. A canine chromosome 7 locus confers compulsive disorder susceptibility. Mol. Psychiatry 15, 8–10 (2010).CAS 
PubMed 

Google Scholar 
Jeppesen, L. L., Heller, K. E. & Bildsøe, M. Stereotypies in female farm mink (Mustela vison) may be genetically transmitted and associated with higher fertility due to effects on body weight. Appl. Anim. Behav. Sci. 86, 137–143 (2004).
Google Scholar 
Noh, H. J. et al. Integrating evolutionary and regulatory information with a multispecies approach implicates genes and pathways in obsessive-compulsive disorder. Nat. Commun. 8, 1–13 (2017).CAS 

Google Scholar 
Koran, L. M. Quality of life in obsessive-compulsive disorder. Psychiatr. Clin. North Am. 23, 509–517 (2000).ADS 
CAS 
PubMed 

Google Scholar 
Murray, C. J. & Lopez, A. D. The Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability from Diseases, Injuries, and Risk Factors in 1990 and Projected to 2020 (Harvard School of Public Health, 1996).
Google Scholar 
Calzà, J. et al. Altered cortico-striatal functional connectivity during resting state in obsessive-compulsive disorder. Front. Psychiatry 10, 319 (2019).PubMed 
PubMed Central 

Google Scholar 
Brem, S., Grünblatt, E., Drechsler, R., Riederer, P. & Walitza, S. The neurobiological link between OCD and ADHD. ADHD Atten. Deficit Hyperact. Disord. 6, 175–202 (2014).
Google Scholar 
Stein, D. J., Dodman, N. H., Borchelt, P. & Hollander, E. Behavioral disorders in veterinary practice: Relevance to psychiatry. Compr. Psychiatry 35, 275–285 (1994).CAS 
PubMed 

Google Scholar 
Overall, K. L. Natural animal models of human psychiatric conditions: Assessment of mechanism and validity. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 24, 727–776 (2000).CAS 

Google Scholar 
Flament, M. F. et al. Obsessive compulsive disorder in adolescence: An epidemiological study. J. Am. Acad. Child Adolesc. Psychiatry 27, 764–771 (1988).CAS 
PubMed 

Google Scholar 
Nestadt, G. et al. A family study of obsessive-compulsive disorder. Arch. Gen. Psychiatry 57, 358–363 (2000).CAS 
PubMed 

Google Scholar 
Protopopova, A., Hall, N. J. & Wynne, C. D. L. Association between increased behavioral persistence and stereotypy in the pet dog. Behav. Processes 106, 77–81 (2014).PubMed 

Google Scholar 
Valerius, G., Lumpp, A., Kuelz, A. K., Freyer, T. & Voderholzer, U. Reversal learning as a neuropsychological indicator for the neuropathology of obsessive compulsive disorder? A behavioral study. J. Neuropsychiatry Clin. Neurosci. 20, 210–218 (2008).PubMed 

Google Scholar 
Snyder, H. R., Kaiser, R. H., Warren, S. L. & Heller, W. Obsessive-compulsive disorder is associated with broad impairments in executive function: A meta-analysis. Clin. Psychol. Sci. 3, 301–330 (2015).PubMed 

Google Scholar 
Ogata, N. et al. Brain structural abnormalities in Doberman pinschers with canine compulsive disorder. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 45, 1–6 (2013).
Google Scholar 
Norman, L. J. et al. Structural and functional brain abnormalities in attention-deficit/hyperactivity disorder and obsessive-compulsive disorder: A comparative meta-analysis. JAMA Psychiat. 73, 815–825 (2016).
Google Scholar 
Yalcin, E., Ilcol, Y. O. & Batmaz, H. Serum lipid concentrations in dogs with tail chasing. J. Small Anim. Pract. 50, 133–135 (2009).CAS 
PubMed 

Google Scholar 
Vermeire, S. et al. Serotonin 2A receptor, serotonin transporter and dopamine transporter alterations in dogs with compulsive behaviour as a promising model for human obsessive-compulsive disorder. Psychiatry Res. 201, 78–87 (2012).CAS 
PubMed 

Google Scholar 
Moon-Fanelli, A. A. & Dodman, N. H. Description and development of compulsive tail chasing in terriers and response to clomipramine treatment. J. Am. Vet. Med. Assoc. 212, 1252–1257 (1998).CAS 
PubMed 

Google Scholar 
Irimajiri, M. et al. Randomized, controlled clinical trial of the efficacy of fluoxetine for treatment of compulsive disorders in dogs. J. Am. Vet. Med. Assoc. 235, 705–709 (2009).CAS 
PubMed 

Google Scholar 
Walsh, B. R. A critical review of the evidence for the equivalence of canine and human compulsions. Appl. Anim. Behav. Sci. 234, 105166 (2021).
Google Scholar 
Wright, H. F., Mills, D. S. & Pollux, P. M. J. Development and validation of a psychometric tool for assessing impulsivity in the domestic dog (Canis familiaris). Int. J. Comp. Psychol. 24, 210–225 (2011).
Google Scholar 
Dinwoodie, I. R., Dwyer, B., Zottola, V., Gleason, D. & Dodman, N. H. Demographics and comorbidity of behavior problems in dogs. J. Vet. Behav. 32, 62–71 (2019).
Google Scholar 
Sulkama, S. et al. Canine hyperactivity, impulsivity, and inattention share similar demographic risk factors and behavioural comorbidities with human ADHD. Transl. Psychiatry 11, 501 (2021).PubMed 
PubMed Central 

Google Scholar 
Kooij, J. J. S. et al. Updated European Consensus Statement on diagnosis and treatment of adult ADHD. Eur. Psychiatry 56, 14–34 (2019).CAS 
PubMed 

Google Scholar 
Nakao, T., Okada, K. & Kanba, S. Neurobiological model of obsessive-compulsive disorder: Evidence from recent neuropsychological and neuroimaging findings. Psychiatry Clin. Neurosci. 68, 587–605 (2014).PubMed 

Google Scholar 
Milad, M. R. & Rauch, S. L. Obsessive-compulsive disorder: Beyond segregated cortico-striatal pathways. Trends Cogn. Sci. 16, 43–51 (2012).PubMed 

Google Scholar 
Hollander, E. Managing aggressive behavior in patients with obsessive-compulsive disorder and borderline personality disorder. J. Clin. Psychiatry 60, 38–44 (1999).PubMed 

Google Scholar 
Marsden, M. D. & Wood-Gush, D. G. M. The use of space by group-housed sheep. Appl. Anim. Behav. Sci. 15, 178 (1986).
Google Scholar 
Burn, C. C. A vicious cycle: A cross-sectional study of canine tail-chasing and human responses to it, using a free video-sharing website. PLoS ONE 6, e26553 (2011).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Stubbs, B. et al. An examination of the anxiolytic effects of exercise for people with anxiety and stress-related disorders: A meta-analysis. Psychiatry Res. 249, 102–108 (2017).PubMed 

Google Scholar 
Schneider, B. M., Dodman, N. H. & Maranda, L. Use of memantine in treatment of canine compulsive disorders. J. Vet. Behav. Clin. Appl. Res. 4, 118–126 (2009).
Google Scholar 
Mihevc, S. P. & Majdic, G. Canine cognitive dysfunction and Alzheimer’s disease-two facets of the same disease?. Front. Neurosci. 13, 604 (2019).
Google Scholar 
Delorme, R. et al. Admixture analysis of age at onset in obsessive-compulsive disorder. Psychol. Med. 35, 237–243 (2005).PubMed 

Google Scholar 
Flaisher-Grinberg, S. et al. Ovarian hormones modulate ‘compulsive’ lever-pressing in female rats. Horm. Behav. 55, 356–365 (2009).CAS 
PubMed 

Google Scholar 
Fernández-Guasti, A., Agrati, D., Reyes, R. & Ferreira, A. Ovarian steroids counteract serotonergic drugs actions in an animal model of obsessive-compulsive disorder. Psychoneuroendocrinology 31, 924–934 (2006).PubMed 

Google Scholar 
Col, R., Day, C. & Phillips, C. J. C. An epidemiological analysis of dog behavior problems presented to an Australian behavior clinic, with associated risk factors. J. Vet. Behav. Clin. Appl. Res. 15, 1–11 (2016).
Google Scholar 
Rusbridge, C. Neurological diseases of the Cavalier King Charles spaniel. J. Small Anim. Pract. 46, 265–272 (2005).CAS 
PubMed 

Google Scholar 
Wrzosek, M., Płonek, M., Nicpoń, J., Cizinauskas, S. & Pakozdy, A. Retrospective multicenter evaluation of the ‘fly-catching syndrome’ in 24 dogs: EEG, BAER, MRI, CSF findings and response to antiepileptic and antidepressant treatment. Epilepsy Behav. 53, 184–189 (2015).PubMed 

Google Scholar 
Cao, X. et al. Balancing selection on CDH2 may be related to the behavioral features of the Belgian malinois. PLoS ONE 9, e110075 (2014).ADS 
PubMed 
PubMed Central 

Google Scholar 
Moon-Fanelli, A. A., Dodman, N. H. & Cottam, N. Blanket and flank sucking in Doberman Pinschers. J. Am. Vet. Med. Assoc. 231, 907–912 (2007).PubMed 

Google Scholar 
Tiira, K. & Lohi, H. Reliability and validity of a questionnaire survey in canine anxiety research. Appl. Anim. Behav. Sci. 155, 82–92 (2014).
Google Scholar 
Puurunen, J. et al. Inadequate socialisation, inactivity, and urban living environment are associated with social fearfulness in pet dogs. Sci. Rep. 10, 3527 (2020).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hakanen, E. et al. Active and social life is associated with lower non-social fearfulness in pet dogs. Sci. Rep. 10, 1–13 (2020).
Google Scholar 
Mikkola, S. et al. Aggressive behaviour is affected by demographic, environmental and behavioural factors in purebred dogs. Sci. Rep. 11, 9433 (2021).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hejjas, K. et al. Association of polymorphisms in the dopamine D4 receptor gene and the activity-impulsivity endophenotype in dogs. Anim. Genet. 38, 629–633 (2007).CAS 
PubMed 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. (2019).Hastie, T. gam: Generalized Additive Models. (2018).Robinson, D. & Hayes, A. broom: Convert Statistical Analysis Objects into Tidy Tibbles. https://cran.r-project.org/package=broom (2018).Wickham, H., François, R., Lionel, H. & Müller, K. dplyr: A Grammar of Data Manipulation. https://cran.r-project.org/package=dplyr (2019).Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).MATH 

Google Scholar 
Fox, J. & Weisberg, S. An R Companion to Applied Regression (Sage Publications, 2011).
Google Scholar 
Robin, X. et al. pROC: An open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinform. 12, 77 (2011).
Google Scholar 
Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means. https://cran.r-project.org/package=emmeans (2019).Fox, J. Effect Displays in R for Generalised Linear Models. J. Stat. Softw. 8, 1–27 (2003).
Google Scholar 
Goto, A., Arata, S., Kiyokawa, Y., Takeuchi, Y. & Mori, Y. Risk factors for canine tail chasing behaviour in Japan. Vet. J. 192, 445–448 (2012).PubMed 

Google Scholar  More

Andersson, M. Sexual selection (Princeton University Press, 2019).
Google Scholar 
Davy, A. J. & Smith, H. Life-history variation and environment. In Plant Population Ecology (eds Davy, A. J., Hutchings, M. J. & Watkinson, A. R.) 1–22. 28th Symposium of the British Ecological Society, Sussex, 1987 (Blackwell, 1988).Wilson, K. L., De Gisi, J., Cahill, C. L., Barker, O. E. & Post, J. R. Life-history variation along environmental and harvest clines of a northern freshwater fish: plasticity and adaptation. J. Anim. Ecol. 88, 717–733 (2019).PubMed 

Google Scholar 
Laiolo, P. & Obeso, J. R. Life-history responses to the altitudinal gradient. In High Mountain Conservation in a Changing World (eds Catalan, J. et al.) 253–283 (Springer, 2017).
Google Scholar 
Schwarz, R. & Meiri, S. The fast-slow life-history continuum in insular lizards: a comparison between species with invariant and variable clutch sizes. J. Biogeogr. 44, 2808–2815 (2017).
Google Scholar 
Holm, S. et al. Size-related life-history traits in geometrid moths: a comparison of a temperate and a tropical community. Ecol. Entomol. 44, 711–716 (2019).
Google Scholar 
Ferguson, G. W. & Fox, S. F. Annual variation of survival advantage of large juvenile side-blotched lizards, Uta stansburiana: Its causes and evolutionary significance. Evolution 38, 342–349 (1984).PubMed 

Google Scholar 
Madsen, T., Ujvari, B., Shine, R. & Olsson, M. Rain, rats and pythons: Climate-driven population dynamics of predators and prey in tropical Australia. Austral Ecol. 31, 30–37 (2006).
Google Scholar 
Brown, G. P. & Shine, R. Rain, prey and predators: climatically driven shifts in frog abundance modify reproductive allometry in a tropical snake. Oecologia 154, 361–368 (2007).ADS 
PubMed 

Google Scholar 
James, C. & Shine, R. Life-history strategies of Australian lizards: a comparison between the tropics and the temperate zone. Oecologia 75, 307–316 (1988).ADS 
PubMed 

Google Scholar 
Mesquita, D. O. et al. Life-history patterns of lizards of the world. Am. Nat. 187, 689–705 (2016).PubMed 

Google Scholar 
Meiri, S. et al. The global diversity and distribution of lizard clutch sizes. Glob. Ecol. Biogeogr. 29, 1515–1530 (2020).
Google Scholar 
Andrews, R. M. Growth rate in island and mainland anoline lizards. Copeia 1976, 477–482 (1976).
Google Scholar 
Jessop, T. S. et al. Maximum body size among insular Komodo dragon populations covaries with large prey density. Oikos 112, 422–429 (2006).
Google Scholar 
Van Buskirk, J. & Crowder, L. B. Life-history variation in marine turtles. Copeia 1994, 66–81 (1994).
Google Scholar 
Broderick, A. C., Godley, B. J. & Hays, G. C. Trophic status drives interannual variability in nesting numbers of marine turtles. Proc. R. Soc. B 268, 1481–1487 (2001).CAS 
PubMed 
PubMed Central 

Google Scholar 
Broderick, A. C., Glen, F., Godley, B. J. & Hays, G. C. Variation in reproductive output of marine turtles. J. Exp. Mar. Biol. Ecol. 288, 95–109 (2003).
Google Scholar 
Pike, D. A. Climate influences the global distribution of sea turtle nesting. Glob. Ecol. Biogeogr. 22, 555–566 (2013).
Google Scholar 
Ujvari, B., Shine, R., Luiselli, L. & Madsen, T. Climate-induced reaction norms for life-history traits in pythons. Ecology 92, 1858–1864 (2011).PubMed 

Google Scholar 
Shine, R., Shine, T. G., Brown, G. P. & Goiran, C. Life history traits of the sea snake Emydocephalus annulatus, based on a 17-yr study. Coral Reefs 39, 1407–1414 (2020).
Google Scholar 
Shine, R., Brown, G. P. & Goiran, C. Population dynamics of the sea snake Emydocephalus annulatus (Elapidae, Hydrophiinae). Sci. Rep. 11, 20701 (2021). ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Goiran, C., Dubey, S. & Shine, R. Effects of season, sex and body size on the feeding ecology of turtle-headed sea snakes (Emydocephalus annulatus) on IndoPacific inshore coral reefs. Coral Reefs 32, 527–538 (2013).ADS 

Google Scholar 
Ineich, I. & Laboute, P. Les Serpents Marins de Nouvelle-Calédonie (IRD éditions, 2002).Udyawer, V., Goiran, C. & Shine, R. Peaceful coexistence between people and deadly wildlife: Why are recreational users of the ocean so rarely bitten by sea snakes? People Nat. 3, 335–346 (2021).
Google Scholar 
Goiran, C., Brown, G. P. & Shine, R. The behaviour of sea snakes (Emydocephalus annulatus) shifts with the tides. Sci. Rep. 10, 1–8 (2020).
Google Scholar 
Lukoschek, V. & Shine, R. Sea snakes rarely venture far from home. Ecol. Evol. 2, 1113–1121 (2012).PubMed 
PubMed Central 

Google Scholar 
Shine, R., Goiran, C., Shine, T., Fauvel, T. & Brischoux, F. Phenotypic divergence between seasnake (Emydocephalus annulatus) populations from adjacent bays of the New Caledonian lagoon. Biol. J. Linn. Soc. 107, 824–832 (2012).
Google Scholar 
Avolio, C., Shine, R. & Pile, A. J. The adaptive significance of sexually dimorphic scale rugosity in sea snakes. Am. Nat. 167, 728–738 (2006).PubMed 

Google Scholar 
White, G. C. & Burnham, K. P. Program MARK: Survival estimation from populations of marked animals. Bird Study 46, S120–S139 (1999).
Google Scholar 
Russell, B. C., Anderson, G. R. V. & Talbot, F. H. Seasonality and recruitment of coral reef fishes. Mar. Freshw. Res. 28, 521–528 (1977).
Google Scholar 
Shine, R., Bonnet, X., Elphick, M. J. & Barrott, E. G. A novel foraging mode in snakes: browsing by the sea snake Emydocephalus annulatus (Serpentes, Hydrophiidae). Funct. Ecol. 18, 16–24 (2004).
Google Scholar 
Calow, P. Adaptive aspects of energy allocation. In Fish Energetics (eds Tytler, P. & Calow, P.) 13–31 (Springer, 1985).
Google Scholar 
Lenormand, T. Gene flow and the limits to natural selection. Trends Ecol. Evol. 17, 183–189 (2002).
Google Scholar 
Bronikowski, A. M. Experimental evidence for the adaptive evolution of growth rate in the garter snake Thamnophis elegans. Evolution 54, 1760–1767 (2000).CAS 
PubMed 

Google Scholar 
Cook, T. R., Bonnet, X., Fauvel, T., Shine, R. & Brischoux, F. Foraging behaviour and energy budgets of sea snakes from New Caledonia: Insights from implanted data-loggers. J. Zool. 298, 82–93 (2016).
Google Scholar 
Bonnet, X., Brischoux, F., Briand, M. & Shine, R. Plasticity matches phenotype to local conditions despite genetic homogeneity across 13 snake populations. Proc. R. Soc. B 288, 20202916 (2021).PubMed 
PubMed Central 

Google Scholar 
Lukoschek, V., Waycott, M. & Marsh, H. Phylogeography of the olive sea snake, Aipysurus laevis (Hydrophiinae) indicates Pleistocene range expansion around northern Australia but low contemporary gene flow. Mol. Ecol. 16, 3406–3422 (2007).CAS 
PubMed 

Google Scholar 
Nitschke, C. R., Hourston, M., Udyawer, V. & Sanders, K. L. Rates of population differentiation and speciation are decoupled in sea snakes. Biol. Lett. 14, 20180563 (2018).PubMed 
PubMed Central 

Google Scholar 
Heatwole, H., Grech, A., Monahan, J. F., King, S. & Marsh, H. Thermal biology of sea snakes and sea kraits. Integr. Comp. Biol. 52, 257–273 (2012).PubMed 

Google Scholar 
Brischoux, F., Rolland, V., Bonnet, X., Caillaud, M. & Shine, R. Effects of oceanic salinity on body condition in sea snakes. Integr. Comp. Biol. 52, 235–244 (2012).PubMed 

Google Scholar 
Bonnet, X. et al. Spatial variation in age structure among populations of a colonial marine snake: the influence of ectothermy. J. Anim. Ecol. 84, 925–933 (2015).PubMed 

Google Scholar 
Heatwole, H. Sea Snakes 2nd edn. (Krieger Publishing, 1999).
Google Scholar 
Blouin-Demers, G. & Weatherhead, P. J. Thermal ecology of black rat snakes (Elaphe obsoleta) in a thermally challenging environment. Ecology 82, 3025–3043 (2001).
Google Scholar 
Goiran, C., Brown, G. P. & Shine, R. Niche partitioning within a population of sea snakes is constrained by ambient thermal homogeneity and small prey size. Biol. J. Linn. Soc. 129, 644–651 (2020).
Google Scholar 
Lowe, J. R. et al. Regional versus latitudinal variation in the life-history traits and demographic rates of a reef fish, Centropyge bispinosa, in the Coral Sea and Great Barrier Reef Marine Parks, Australia. J. Fish Biol. 99, 1602–1612. https://doi.org/10.1111/jfb.14865 (2021).PubMed 

Google Scholar 
Gust, N., Choat, J. & Ackerman, J. Demographic plasticity in tropical reef fishes. Mar. Biol. 140, 1039–1051 (2002).
Google Scholar 
Kingsford, M. J., Welch, D. & O’Callaghan, M. Latitudinal and cross-shelf patterns of size, age, growth, and mortality of a tropical damselfish Acanthochromis polyacanthus on the Great Barrier Reef. Diversity 11, 67 (2019).
Google Scholar  More

Alerstam, T., Hedenström, A. & Åkesson, S. Long‐distance migration: evolution and determinants. Oikos 103, 247–260 (2003).Article 

Google Scholar 
Newton, I. The migration ecology of birds (Elsevier, London, 2008).Putman, N. F. et al. An inherited magnetic map guides ocean navigation in juvenile Pacific salmon. Curr. Biol. 24, 446–450 (2014).CAS 
Article 

Google Scholar 
Jesmer, B. R. et al. Is ungulate migration culturally transmitted? Evidence of social learning from translocated animals. Science 361, 1023–1025 (2018).ADS 
CAS 
Article 

Google Scholar 
Milner-Gulland, E. J., Fryxell, J. M. & Sinclair, A. R. (Eds.) Animal migration: a synthesis (Oxford University Press, New York, 2011).Conradt, L. & Roper, T. J. Consensus decision making in animals. Trends Ecol. Evol. 20, 449–456 (2005).Article 

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

Google Scholar 
Vansteelant, W. M. G., Kekkonen, J. & Byholm, P. Wind conditions and geography shape the first outbound migration of juvenile honey buzzards and their distribution across sub-Saharan Africa. Proc. R. Soc. B 284, 20170387 (2017).Article 

Google Scholar 
Flack, A., Nagy, M., Fiedler, W., Couzin, I. D. & Wikelski, M. From local collective behavior to global migratory patterns in white storks. Science 360, 911–914 (2018).ADS 
CAS 
Article 

Google Scholar 
Chernetsov, N., Berthold, P. & Querner, U. Migratory orientation of first-year white storks (Ciconia ciconia): inherited information and social interactions. J. Exp. Biol. 207, 937–943 (2004).Article 

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

Google Scholar 
Whiten, A. Cultural evolution in animals. Annu. Rev. Ecol. Evol. Syst. 50, 27–48 (2019).Article 

Google Scholar 
Whitehead, H. & Rendell, L. The Cultural Lives of Whales and Dolphins (Chicago University Press, Chicago, 2015).Franks, N. R. & Richardson, T. Teaching in tandem-running ants. Nature 439, 153–153 (2006).ADS 
CAS 
Article 

Google Scholar 
Thornton, A. & McAuliffe, K. Teaching in wild meerkats. Science 313, 227–229 (2006).ADS 
CAS 
Article 

Google Scholar 
Cramp, S. (Ed.) The birds of the Western Palearctic. Vol. IV. Terns to woodpeckers (Oxford University Press, New York, 1985).Méndez, V. et al. Paternal effects in the initiation of migratory behaviour in birds. Sci. Rep. 11, 2782 (2021).ADS 
Article 

Google Scholar 
Olson, V. A., Liker, A., Freckleton, R. P. & Székely, T. Parental conflict in birds: comparative analyses of offspring development, ecology and mating opportunities. Proc. R. Soc. B 275, 301–307 (2008).CAS 
Article 

Google Scholar 
Ledwoń, M. & Neubauer, G. Offspring desertion and parental care in the Whiskered Tern Chlidonias hybrida. Ibis 159, 860–872 (2017).Article 

Google Scholar 
Arnqvist, G. & Rowe, L. Sexual conflict (Princeton University Press, New York, 2005).Goodenough, K. S. & Patton, R. T. Satellite telemetry reveals strong fidelity to migration routes and wintering grounds for the gull-billed tern (Gelochelidon nilotica). Waterbirds 42, 400–410 (2019).Article 

Google Scholar 
Gu, Z. et al. Climate-driven flyway changes and memory-based long-distance migration. Nature 591, 259–264 (2021).ADS 
CAS 
Article 

Google Scholar 
Baert, J. M. et al. Resource predictability drives interannual variation in migratory behavior in a long-lived bird. Behav. Ecol. arab132, https://doi.org/10.1093/beheco/arab132 (2021).Papageorgiou, D. & Farine, D. R. Group size and composition influence collective movement in a highly social terrestrial bird. eLife 9, e59902 (2020).CAS 
Article 

Google Scholar 
Caro, T. M. & Hauser, M. D. Is there teaching in nonhuman animals? Q. Rev. Biol. 67, 151–174 (1992).CAS 
Article 

Google Scholar 
Thornton, A. & Raihani, N. J. The evolution of teaching. Anim. Behav. 75, 1823–1836 (2008).Article 

Google Scholar 
Riedman, M. L. The evolution of alloparental care and adoption in mammals and birds. Q. Rev. Biol. 57, 405–435 (1982).Article 

Google Scholar 
Sheppard, C. E. et al. Decoupling of genetic and cultural inheritance in a wild mammal. Curr. Biol. 28, 1846–1850 (2018).CAS 
Article 

Google Scholar 
Åkesson, S. & Helm, B. Endogenous programs and flexibility in bird migration. Front. Ecol. Evol. 8, 1–20 (2020).Article 

Google Scholar 
Sasaki, T. & Biro, D. Cumulative culture can emerge from collective intelligence in animal groups. Nat. Commun. 8, 1–6 (2017).ADS 
Article 

Google Scholar 
Whiten, A., Ayala, F. J., Feldman, M. W. & Laland, K. N. The extension of biology through culture. Proc. Natl Acad. Sci. USA 114, 7775–7781 (2017).CAS 
Article 

Google Scholar 
Aplin, L. M. Culture and cultural evolution in birds: a review of the evidence. Anim. Behav. 147, 179–187 (2019).Article 

Google Scholar 
Laland, K. N., Toyokawa, W. & Oudman, T. Animal learning as a source of developmental bias. Evol. Dev. 22, 126–142 (2020).Article 

Google Scholar 
Sergio, F. et al. Individual improvements and selective mortality shape lifelong migratory performance. Nature 515, 410–413 (2014).ADS 
CAS 
Article 

Google Scholar 
Guttal, V. & Couzin, I. D. Social interactions, information use, and the evolution of collective migration. Proc. Natl Acad. Sci. USA 107, 16172–16177 (2010).ADS 
CAS 
Article 

Google Scholar 
Oudman, T. et al. Young birds switch but old birds lead: how barnacle geese adjust migratory habits to environmental change. Front. Ecol. Evol. 7, 106–120 (2020).Article 

Google Scholar 
Pearson, R. G. et al. Life history and spatial traits predict extinction risk due to climate change. Nat. Clim. Chang 4, 217–221 (2014).ADS 
Article 

Google Scholar 
Vickery, J. A. The decline of Afro-Palaearctic migrants and an assessment of potential causes. Ibis 156, 1–22 (2014).Article 

Google Scholar 
Thaxter, C. B. et al. A trial of three harness attachment methods and their suitability for long-term use on Lesser Black-backed Gulls and Great Skuas. Ringing Migr. 29, 65–76 (2014).Article 

Google Scholar 
Byholm, P., Beal, M., Isaksson, N., Lötberg, U. & Åkesson, S. Data from: paternal transmission of migration knowledge in a long-distance bird migrant. Movebank Data Repos. https://doi.org/10.5441/001/1.352qf1cv (2022).Article 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing, Vienna, 2020). https://www.R-project.org/. More

Whittaker, R. H. Vegetation of the Siskiyou mountains, Oregon and California. Ecol. Monogr. 30, 279–338 (1960).
Google Scholar 
Wilson, R. J., Thomas, C. D., Fox, R., Roy, D. B. & Kunin, W. E. Spatial patterns in species distributions reveal biodiversity change. Nature 432, 393–396 (2004).CAS 
PubMed 

Google Scholar 
Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).CAS 
PubMed 

Google Scholar 
Ings, T. C. et al. Ecological networks—beyond food webs. J. Anim. Ecol. 78, 253–269 (2009).PubMed 

Google Scholar 
Dunne, J. A. & Williams, R. J. Cascading extinctions and community collapse in model food webs. Philos. Trans. R. Soc. Lond. B: Biol. Sci. 364, 1711–1723 (2009).
Google Scholar 
Leclère, D. et al. Bending the curve of terrestrial biodiversity needs an integrated strategy. Nature 585, 551–556 (2020).PubMed 

Google Scholar 
Vellend, M. The Theory of Ecological Communities Vol. 57 229 (Princeton University Press, 2016).Altermatt, F. Diversity in riverine metacommunities: a network perspective. Aquat. Ecol. 47, 365–377 (2013).
Google Scholar 
Peterson, E. E. et al. Modelling dendritic ecological networks in space: an integrated network perspective. Ecol. Lett. 16, 707–719 (2013).PubMed 

Google Scholar 
Tonkin, J. D. et al. The role of dispersal in river network metacommunities: patterns, processes, and pathways. Freshw. Biol. 63, 141–163 (2018).
Google Scholar 
Muneepeerakul, R. et al. Neutral metacommunity models predict fish diversity patterns in Mississippi-Missouri basin. Nature 453, 220–222 (2008).CAS 
PubMed 

Google Scholar 
Besemer, K. et al. Headwaters are critical reservoirs of microbial diversity for fluvial networks. Proc. Biol. Sci. 280, 20131760 (2013).PubMed 
PubMed Central 

Google Scholar 
Finn, D. S., Bonada, N., Múrria, C. & Hughes, J. M. Small but mighty: headwaters are vital to stream network biodiversity at two levels of organization. J. North Am. Benthol. Soc. 30, 963–980 (2011).
Google Scholar 
Altermatt, F., Seymour, M. & Martinez, N. River network properties shape α-diversity and community similarity patterns of aquatic insect communities across major drainage basins. J. Biogeogr. 40, 2249–2260 (2013).
Google Scholar 
Harvey, E., Gounand, I., Fronhofer, E. A. & Altermatt, F. Disturbance reverses classic biodiversity predictions in river-like landscapes. Proc. R. Soc. B: Biol. Sci. 285, 20182441 (2018).
Google Scholar 
Tylianakis, J. M., Laliberté, E., Nielsen, A. & Bascompte, J. Conservation of species interaction networks. Biol. Conserv. 143, 2270–2279 (2010).
Google Scholar 
Thompson, R. M. et al. Food webs: reconciling the structure and function of biodiversity. Trends Ecol. Evol. 27, 689–697 (2012).PubMed 

Google Scholar 
Woodward, G. & Hildrew, A. G. Food web structure in riverine landscapes. Freshw. Biol. 47, 777–798 (2002).
Google Scholar 
Williams, R. J. & Martinez, N. D. Limits to trophic levels and omnivory in complex food webs: theory and data. Am. Nat. 163, 458–468 (2004).PubMed 

Google Scholar 
Thompson, R. M. & Townsend, C. R. The effect of seasonal variation on the community structure and food-web attributes of two streams: implications for food-web science. Oikos 87, 75–88 (1999).
Google Scholar 
Wood, S. A., Russell, R., Hanson, D., Williams, R. J. & Dunne, J. A. Effects of spatial scale of sampling on food web structure. Ecol. Evol. 5, 3769–3782 (2015).PubMed 
PubMed Central 

Google Scholar 
Tylianakis, J. M. & Morris, R. J. Ecological networks across environmental gradients. Annu. Rev. Ecol., Evolution, Syst. 48, 25–48 (2017).
Google Scholar 
Romanuk, T. N. et al. The structure of food webs along river networks. Ecography 29, 3–10 (2006).
Google Scholar 
Olivier, P. et al. Exploring the temporal variability of a food web using long‐term biomonitoring data. Ecography 42, 2107–2121 (2019).
Google Scholar 
Poisot, T., Canard, E., Mouillot, D., Mouquet, N. & Gravel, D. The dissimilarity of species interaction networks. Ecol. Lett. 15, 1353–1361 (2012).PubMed 

Google Scholar 
Delmas, E. et al. Analysing ecological networks of species interactions. Biol. Rev. Camb. Philos. Soc. https://doi.org/10.1111/brv.12433 (2018).Article 
PubMed 

Google Scholar 
Tavares-Cromar, A. F. & Williams, D. D. The importance of temporal resolution in food web analysis: Evidence from a detritus-based stream. Ecol. Monogr. 66, 91–113 (1996).
Google Scholar 
Poisot, T., Stouffer, D. B. & Gravel, D. Beyond species: why ecological interaction networks vary through space and time. Oikos 124, 243–251 (2015).
Google Scholar 
Thomsen, P. F. & Willerslev, E. Environmental DNA—an emerging tool in conservation for monitoring past and present biodiversity. Biol. Conserv. 183, 4–18 (2015).
Google Scholar 
Deiner, K., Fronhofer, E. A., Mächler, E., Walser, J.-C. & Altermatt, F. Environmental DNA reveals that rivers are conveyer belts of biodiversity information. Nat. Commun. 7, 12544 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Dunne, J. A. In Ecological Networks: Linking Structure and Dynamics (eds. Pascual, J. A. & Dunne, J. A.) 27–86 (University Press, 2006).Neff, F. et al. Changes in plant-herbivore network structure and robustness along land-use intensity gradients in grasslands and forests. Sci Adv 7, eabf3985 (2021).O’Connor, M. J. et al. Unveiling the food webs of tetrapods across Europe through the prism of the Eltonian niche. J. Biogeogr. 47, 181–192 (2020).
Google Scholar 
Pellissier, L. et al. Comparing species interaction networks along environmental gradients. Biol. Rev. Camb. Philos. Soc. 93, 785–800 (2018).PubMed 

Google Scholar 
Saravia, L. A. et al. Ecological network assembly: how the regional metaweb influences local food webs. BioRxiv, https://doi.org/10.1101/340430 (2021).Blackman, R. C. et al. Mapping biodiversity hotspots of fish communities in subtropical streams through environmental DNA. Sci. Rep. 4, e65352 (2021).
Google Scholar 
Baselga, A. & Orme, C. D. L. betapart: an R package for the study of beta diversity: Betapart package. Methods Ecol. Evol. 3, 808–812 (2012).
Google Scholar 
Seymour, M. et al. Executing multi-taxa eDNA ecological assessment via traditional metrics and interactive networks. Sci. Total Environ. 729, 138801 (2020).CAS 
PubMed 

Google Scholar 
D’Alessandro, S. & Mariani, S. Sifting environmental DNA metabarcoding data sets for rapid reconstruction of marine food webs. Fish Fish 22, 822–833 (2021).
Google Scholar 
Zhang, Y. et al. Holistic pelagic biodiversity monitoring of the Black Sea via eDNA metabarcoding approach: From bacteria to marine mammals. Environ. Int. 135, 105307 (2020).PubMed 

Google Scholar 
Altermatt, F. et al. Uncovering the complete biodiversity structure in spatial networks: the example of riverine systems. Oikos 129, 607–618 (2020).
Google Scholar 
Widder, S. et al. Fluvial network organization imprints on microbial co-occurrence networks. Proc. Natl Acad. Sci. USA 111, 12799–12804 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
Seymour, M. et al. Environmental DNA provides higher resolution assessment of riverine biodiversity and ecosystem function via spatio-temporal nestedness and turnover partitioning. Commun. Biol. 4, 512 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
Mächler, E. et al. Assessing different components of diversity across a river network using eDNA. Environ. DNA 1, 290–301 (2019).
Google Scholar 
Peralta-Maraver, I., López-Rodríguez, M. J. & de Figueroa, J. M. T. Structure, dynamics and stability of a Mediterranean river food web. Mar. Freshw. Res. 68, 484–495 (2017).
Google Scholar 
Woodward, G. et al. Ecological networks in a changing climate. Ecol. Netw. 42, 71–138 (2010).
Google Scholar 
Kondoh, M., Kato, S. & Sakato, Y. Food webs are built up with nested subwebs. Ecology 91, 3123–3130 (2010).PubMed 

Google Scholar 
Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J. R. & Cushing, C. E. The River Continuum Concept. Can. J. Fish. Aquat. Sci. 37, 130–137 (1980).
Google Scholar 
Power, M. E. & Dietrich, W. E. Food webs in river networks. Ecol. Res. https://doi.org/10.1046/j.0912-3814.2002.00503.x (2002).Montoya, D., Yallop, M. L. & Memmott, J. Functional group diversity increases with modularity in complex food webs. Nat. Commun. 6, 7379 (2015).CAS 
PubMed 

Google Scholar 
Gravel, D., Albouy, C. & Thuiller, W. The meaning of functional trait composition of food webs for ecosystem functioning. Philos. Trans. R. Soc. Lond. B: Biol. Sci. 371, 20150268 (2016).Ruppert, K. M., Kline, R. J. & Rahman, M. S. Past, present, and future perspectives of environmental DNA (eDNA) metabarcoding: a systematic review in methods, monitoring, and applications of global eDNA. Glob. Ecol. Conserv. 17, e00547 (2019).
Google Scholar 
Carraro, L., Mächler, E., Wüthrich, R. & Altermatt, F. Environmental DNA allows upscaling spatial patterns of biodiversity in freshwater ecosystems. Nat. Commun. 11, 3585 (2020).PubMed 
PubMed Central 

Google Scholar 
Barnes, M. A. & Turner, C. R. The ecology of environmental DNA and implications for conservation genetics. Conserv. Genet. 17, 1–17 (2016).CAS 

Google Scholar 
Bista, I. et al. Annual time-series analysis of aqueous eDNA reveals ecologically relevant dynamics of lake ecosystem biodiversity. Nat. Commun. 8, 14087 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Erickson, R. A., Merkes, C. M., Jackson, C. A., Goforth, R. R. & Amberg, J. J. Seasonal trends in eDNA detection and occupancy of bigheaded carps. J. Gt. Lakes Res. 43, 762–770 (2017).
Google Scholar 
Troth, C. R., Sweet, M. J., Nightingale, J. & Burian, A. Seasonality, DNA degradation and spatial heterogeneity as drivers of eDNA detection dynamics. Sci. Total Environ. 768, 144466 (2021).CAS 
PubMed 

Google Scholar 
Thalinger, B. et al. The effect of activity, energy use, and species identity on environmental DNA shedding of freshwater fish. Front. Ecol. Evolution 9, 73 (2021).
Google Scholar 
Kelly, R. P., Port, J. A., Yamahara, K. M. & Crowder, L. B. Using environmental DNA to census marine fishes in a large mesocosm. PLoS ONE 9, e86175 (2014).PubMed 
PubMed Central 

Google Scholar 
Leray, M. et al. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Front. Zool. 10, 34 (2013).PubMed 
PubMed Central 

Google Scholar 
Geller, J., Meyer, C., Parker, M. & Hawk, H. Redesign of PCR primers for mitochondrial cytochrome c oxidase subunit I for marine invertebrates and application in all-taxa biotic surveys. Mol. Ecol. Resour. 13, 851–861 (2013).CAS 
PubMed 

Google Scholar 
Liu, C. M. et al. BactQuant: An enhanced broad-coverage bacterial quantitative real-time PCR assay. BMC Microbiol. 12, 56 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
Mansfeldt, C. et al. Microbial community shifts in streams receiving treated wastewater effluent. Sci. Total Environ. 709, 135727 (2020).CAS 
PubMed 

Google Scholar 
Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).CAS 
PubMed 

Google Scholar 
Andrews, S. FASTQC A Quality Control tool for High Throughput Sequence Data (Babraham Institute, 2015).Magoč, T. & Salzberg, S. L. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957–2963 (2011).PubMed 
PubMed Central 

Google Scholar 
Hänfling, B. et al. Environmental DNA metabarcoding of lake fish communities reflects long-term data from established survey methods. Mol. Ecol. 25, 3101–3119 (2016).PubMed 

Google Scholar 
Csárdi, G. & Nepusz, T. The igraph software package for complex network research. Int. J. Complex Syst. 1695, 1–9 (2006).
Google Scholar 
Oksanen, J. et al. vegan: Community Ecology Package 2.5-6. https://CRAN.Rproject.org/package=vegan (2019).Tachet, H., Bournaud, M., Richoux, P. & Usseglio-Polatera, P. Invertébrés d’eau douce—systématique, biologie, écologie (CNRS Editions, 2010).Schmidt-Kloiber, A. & Hering, D. www.freshwaterecology.info—an online tool that unifies, standardises and codifies more than 20,000 European freshwater organisms and their ecological preferences. Ecol. Indic. 53, 271–282 (2015).Newton, R. J., Jones, S. E., Eiler, A., McMahon, K. D. & Bertilsson, S. A guide to the natural history of freshwater lake bacteria. Microbiol. Mol. Biol. Rev. 75, 14–49 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
Fortuna, M. A. et al. Nestedness versus modularity in ecological networks: two sides of the same coin? J. Anim. Ecol. 79, 811–817 (2010).PubMed 

Google Scholar 
Johnson, S., Domínguez-García, V., Donetti, L. & Muñoz, M. A. Trophic coherence determines food-web stability. Proc. Natl Acad. Sci. USA 111, 17923–17928 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
Wootton, K. L. Omnivory and stability in freshwater habitats: Does theory match reality? Freshw. Biol. 62, 821–832 (2017).
Google Scholar 
Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: tests in linear mixed effects models. J. Stat. Softw., Artic. 82, 1–26 (2017).
Google Scholar 
Lenth, R. V. Estimated Marginal Means, aka Least-Squares Means [R package emmeans version 1.6.1] (2021).RStudio Team RStudio: Integrated development for R. RStudio, PBC, Boston, MA. R version 4.0.4 Retrieved from http://www.rstudio.com/ (2021) More

This is the first study analyzing mandible shape in both mink species and, together with a previous study on their cranial shape38, it has revealed how small morphological differences in highly similar species can lead to substantial biomechanical differences (see breakdown below). As with cranial shape, mandible shape in minks is influenced by the complex interaction of size and sexual dimorphism both at the inter- and intraspecific levels. However, while in cranial shape both species had divergent shape allometries and parallel interspecific sexual allometries, the opposite was true for mandible shape.Differences in mandible shape between European and American mink were summarized by PC1 (Fig. 2, Fig. S1) and can be mainly related to muscle size and jaw biomechanics (i.e., in-levers and out-levers). The relatively taller and slightly wider coronoid process of European minks suggests a relatively larger temporalis muscle, while the anteriorly expanded masseteric fossa of American mink is indicative of a relatively larger masseter complex17,22,25. The relatively enlarged angular process of European mink provides a larger attachment area for the superficial masseter, with both mink species having a distinctive fossa on the lateral side of the angular process where this muscle attaches. This angular fossa is not present in European polecats (Gálvez-López, pers. obs.), part of the sister clade to European mink41.Regarding jaw biomechanics, the particular morphology of the American mink illustrates the compromise between maximizing both bite force efficiency and increased gape. The MAs for all masticatory muscles were higher in European mink due to their relatively longer in-levers (and also shorter out-levers if measured on PC1 configurations), with the exception of the MA of the deep masseter which was considerably higher in American mink (Table S2; Fig. 1D). These findings indicate that American mink exhibit features that allow them to produce larger forces at wide gape, which is particularly useful for holding and killing terrestrial vertebrates22,42. In agreement with this, a short moment arm of the superficial masseter (as observed in American mink) has been associated with increased gape in other mammals43. It is also worth noting that low MAs for the posterior temporalis and superficial masseter have also been associated with fish capture, as they indicate a relatively longer mandible relative to the muscle in-levers, which in turn allows the mouth to close faster when trying to catch elusive prey underwater21. In contrast, the characteristic features of European mink are indicative of stronger bites at the carnassials, which would allow them to cut through relatively tougher tissues and also to crush harder objects (e.g. shells of aquatic prey). Favoring carnassial over anterior bites could also be advantageous to feeding on fish. Mink catch fish underwater by grabbing them by the fins or back with their anterior teeth, and then dragging them to the surface where they are processed using cheek (carnassial) bites (Gálvez-López, pers. obs.).In our previous study on cranial shape in mink38, morphological differences between both species indicated relatively larger muscle volumes overall in the American mink (temporalis: more developed sagittal and nuchal crests, narrower braincase; masseter: longer and more curved zygomatic arches, larger infratemporal fossa), which suggested that bite forces both at the anterior dentition and at the carnassials were larger in this species. However, when combined with the MA results from this study on mandible shape, the relationship between muscle volume and force production becomes less straightforward. In the case of the European mink, the relatively smaller temporalis has a larger attachment site on the mandible (i.e., a broader and taller coronoid) and becomes more efficient (i.e., has higher MAs) due to the relatively longer in-lever. Similarly, in the American mink the effective length of the superficial masseter is increased by the marked curvature of the zygomatic arches, which mitigates the dorsal displacement of the angular process. However, the efficiency of the relatively larger temporalis is diminished by a smaller coronoid (i.e., reduced attachment area and shorter in-levers). The remaining differences in cranial morphology align with differences in mandible shape. Namely, the relatively broader zygomatic arches of the European mink support a strong superficial masseter, while the larger infratemporal fossae of American mink account for their enlarged deep masseter. On a final note, another finding common to both cranial and mandible shape was the relatively larger crushing dentition of American mink.Thus, after combining the results of cranial and mandible shape, it appears that, while the characteristic features of European mink indeed allow stronger carnassial bites, American mink present morphological indicators of both strong killing bites at wide gapes and powerful carnassial bites with a marked crushing component.The allometric effect on mandible size common to both species was represented by PC2 (Fig. 2, Fig. S3), which complements the common allometric trend recovered for both mink species in cranial shape38. The relative expansion of the masseteric fossa and the angular process with increasing size suggests that larger mink present a larger masseter complex. However, most of the allometric shape changes are related to muscle in-levers and out-levers. With increasing size, the length of both the out-lever at the anterior teeth and the in-levers of its related muscles (anterior temporalis, deep masseter) increases (Table S2), but the in-levers scale faster than the out-lever (Table S2). Thus, the mechanical advantages of both muscles at the anterior teeth also increase with size (Table S2), indicating that larger mink have markedly stronger and more efficient killing bites (particularly true for the deep masseter, which also becomes larger with size). This, together with their relatively larger anterior dentition (both in the mandible and the cranium) and taller anterior corpus, can be related to feeding on larger prey as size increases (i.e., stronger bites to perforate tougher skulls and hold onto stronger struggling prey, which would also require more robust teeth and corpora to resist the stresses placed on them). Similar features have been described for felids18, which also kill prey in this way22,32.Note, however, that one of the shape changes along PC2 does not accurately reflect the common allometric pattern: the lever arm of the superficial masseter, which slightly decreases along PC2 (Fig. 2; Table S2) and results in a decrease of the mechanical advantage of the superficial masseter and hence bite force at the carnassials along this axis (Table S2). In contrast, this lever arm significantly increases with size in the original specimens (Table S2), in agreement with the common allometric trend in cranial shape suggesting stronger bites at all teeth with increasing size38. A likely explanation for this phenomenon is that the common allometric trend is being confounded with interspecific shape differences, as American mink have significantly shorter superficial masseter in-levers than European mink (Fig. 1F; Table S2) yet their males are significantly larger than all other specimens (Fig. 1A). As mentioned above, the relative decrease in MA might reflect the trade-off between producing strong bite forces at the anterior teeth and having a wider gape to capture larger prey43, both of which are heavily supported by other morphological features in this common allometric trend.Sexual dimorphism in mandible shape was significant both within each species, and when grouping sexes from both species together. In her study of Palearctic mustelids, Romaniuk28 also found evidence for interspecific sexual dimorphism in mandible shape, but within species it was only significant for the Siberian weasel (Mustela sibirica). The different results for the European mink in that study might be related to its smaller sample. Note, however, that Hernández-Romero et al.40 did not find evidence for sexual dimorphism in mandible shape within Neotropical otters (Lontra longicaudis) even though their sample sizes were equivalent to those in the present study.Overall, the results of the present study reveal that mandible shape differences between males and females are the consequence of a complex interaction between sex and size at both inter- and intraspecific levels. For instance, each sex in each species has a mandible shape significantly different from each other (Table 1), but allometric shape changes within each of them are similar (except maybe female American mink; Fig. S5A). Additionally, while trajectory analysis indicates that the degree of sexual dimorphism in mandible shape is similar within each species, the specific differences between sexes are different in each species (i.e., same magnitude, different orientation; Table 2, Fig. S5B). While at the interspecific level, male and female mandible shapes change differently with increasing size even though the change per unit size is similar in both sexes (Tables 1, 2; Fig. S5C,D), and some of the allometric changes are common to both species and sexes (see section above; PC2 in Fig. 2). Finally, another set of shape changes related to sexual dimorphism and common to both species are those related to sexual dimorphism in mandible size, illustrated by PC3 (Figs. 2, Fig. S4).Shape changes related to sexual dimorphism in size are represented along PC3 and can be related to an overall increase in bite force (i.e., at all teeth), as higher scores on this axis correspond to increased muscle attachment areas and longer in-levers (taller and wider coronoid, anteriorly expanded masseteric fossa, ventrally expanded angular process), shorter out-levers (particularly at the anterior teeth), and a more robust corpus (dorsoventrally and mediolaterally expanded). This interpretation of shape changes along PC3 is supported by the results of the ANOVAs on the lever arms and MAs measured on the PC3 configurations (Table S2). These variables were only related to sex and size, with female mink having longer out-levers and male mink presenting longer in-levers and higher MAs, while out-levers decreased with increasing size and in-levers and MAs increased in both sexes (no significant interaction between sex and size indicates parallel allometric trajectories in both sexes). This trend is consistent with the common sexual allometry described for cranial shape, which suggested that larger males have bigger masticatory muscles than smaller females and thus produce higher bite forces38. Additionally, even though the relative length of the toothrow decreases, the size of the canine markedly increases and there is no change in molar size or the relative proportions in its shearing and crushing regions. Although this might be interpreted as reinforcing the canines to cope with killing larger prey while maintaining an otherwise similar dietary regime20, it is worth noting that larger canines have been long described as a feature of sexual size dimorphism in mustelids19,44,45.In terms of interspecific differences in sexual allometry, with increasing size the following shape changes were observed in females but not in males (Fig. S5C): a dorsoventrally more robust corpus, a ventral expansion of the angular process, longer in-levers for all masticatory muscles, larger incisors, and an increase in the shearing portion of m1 relative to the crushing portion. Most of these shape changes are similar to those described for PC3, which suggests that the female interspecific allometry bridges the bite force gap caused by sexual dimorphism in size. The changes to the female dentition suggest a shift in diet from crushing tough food items (e.g. aquatic invertebrates) towards slicing meat, which makes sense since these changes occur simultaneously with the common allometric trend (related to improved capabilities for killing larger vertebrate prey). However, as noted earlier, the increased shearing component is also advantageous for a piscivorous diet. Shape changes in male mandibles not observed in females seem to emphasize the common allometric trend (i.e., stronger killing bite at larger gapes) (Fig. S5D): a wider coronoid process for more muscle attachment, a dorsally displaced angular process to allow wider gapes, and mediolateral expansion of the corpus to increase its strength. Regarding their dentition, the opposite trend to females was observed (i.e., slightly smaller anterior teeth and a longer crushing molar portion), suggesting a larger durophagous component in the diet of larger males.As expected, variation in mandible shape could be linked to potential dietary differences between European and American mink, and also between sexes. In summary, the results of the present study show that:

American mink are better equipped for preying on terrestrial vertebrates, as they can achieve relatively larger gapes and their mandibles are able to produce larger forces during the killing bite (i.e., at the anterior teeth and with an open mouth).

European mink, on the other hand, can produce relatively stronger bites at the carnassials, suggesting that they rely more on tougher prey and/or fish.

Regardless of species and sex, morphological features in larger mink demonstrate increased capabilities for feeding on larger terrestrial prey (stronger killing bites and more robust anterior teeth and corpora to resist the stresses caused by struggling prey).

Due to their larger size, male mink of both species have stronger bites than females at both the anterior teeth and the carnassials. However, with increasing size, females bridge the gap by developing relatively stronger bites overall while shifting their diet from tougher or harder prey (probably aquatic invertebrates) towards less mechanically demanding food items (e.g. terrestrial vertebrates and/or fish). In contrast, increasing size in males leads to even more specialization towards feeding on larger terrestrial prey while tough items become more relevant in their diets (probably crushing bones of small prey).

These findings confirm our original predictions based on previous results on cranial shape differences, but do they agree with observed dietary preferences in minks? Diet studies in American mink are numerous, and provide a wide picture of seasonal and regional variation8,11 as well as intraspecific dietary competition6,7,12. However, studies on European mink diet are scarcer9,14, particularly those comparing the sexes13. Additionally, a few studies have compared diets of sympatric European and American mink10,15. All these studies can be summarized as: A, male American mink favor medium-sized mammals and birds usually heavier than themselves; B, female American mink favor aquatic prey, but are displaced towards small mammals and birds when seasonal changes in prey availability shift the males’ diet towards aquatic prey; C, European mink favor aquatic prey, particularly fish and crayfish; but D, they are displaced towards amphibians and small mammals when sympatric with American mink. From these, our results on mandible shape variation support A and somewhat B and C, but provide no information on the interspecific competition scenario or on potential seasonal or local dietary differences. Additionally, there is no information on size-related dietary changes in either species that could validate our findings on sexual allometry in mandible shape. Thus, while mandible shape is very useful for identifying broad dietary indicators even between highly similar species, its ability to provide accurate information on their potential prey is limited.As a final note on mink diets, our previous study on cranial shape38, suggested a gradient in muscle force (and potential dietary range) from female European mink to male American mink. Based on those results and studies on social interactions between and within species35,46, we hypothesized that competition between both mink species could be displacing female European mink towards narrower and poorer diets, which could affect their survivability and ability to successfully reproduce. Fortunately, the results of the present study not only propose that there might be less overlap in diets between species and sexes than suggested by dietary studies7,10,13,15, but also indicate that dietary competition seems to be higher for small terrestrial vertebrates, not aquatic prey (on which female European mink are particularly well equipped to feed). More

Alves, J. A. et al. Costs, benefits, and fitness consequences of different migratory strategies. Ecology 94(1), 11–17 (2013).PubMed 

Google Scholar 
Alexander, R. M. When is migration worthwhile for animals that walk, swim or fly?. J. Avian Biol. 29(4), 387–394 (1998).
Google Scholar 
Wikelski, M. et al. Costs of migration in free-flying songbirds. Nature 423, 704 (2003).ADS 
CAS 
PubMed 

Google Scholar 
Alerstam, T., Hedenström, A. & Åkesson, S. Long-distance migration: evolution and determinants. Oikos 103(2), 247–260 (2003).
Google Scholar 
Alerstam, T. Optimal bird migration revisited. J. Ornithol. 152, 5–23 (2011).
Google Scholar 
Hedenstrom, A. & Alerstam, T. Optimum fuel loads in migratory birds: Distinguishing between time and energy minimization. J. Theor. Biol. 189, 227–234 (1997).ADS 
CAS 
PubMed 

Google Scholar 
Åkesson, S. & Helm, B. Endogenous programs and flexibility in bird migration. Front. Ecol. Evol. 8, 78 (2020).
Google Scholar 
Jiguet, F. et al. Desert crossing strategies of migrant songbirds vary between and within species. Sci. Rep. 9(1), 20248 (2019).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Senner, N. R., Morbey, Y. E. & Sandercock, B. K. Editorial: Flexibility in the migration strategies of animals. Front. Ecol. Evol. 8, 111 (2020).
Google Scholar 
Mellone, U., López-López, P., Limiñana, R., Piasevoli, G. & Urios, V. The trans-equatorial loop migration system of Eleonora’s falcon: Differences in migration patterns between age classes, regions and seasons. J. Avian Biol. 44, 417–426 (2013).
Google Scholar 
Chevallier, D. et al. Influence of weather conditions on the flight of migrating black storks. Proc. Biol. Sci. 277(1695), 2755–2764 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Verhelst, B., Jansen, J. & Vansteelant, W. South West Georgia: An important bottleneck for raptor migration during autumn. Ardea 99, 137–146 (2011).
Google Scholar 
Klaassen, R. H. G., Strandberg, R., Hake, M. & Alerstam, T. Flexibility in daily travel routines causes regional variation in bird migration speed. Behav. Ecol. Sociobiol. 62(9), 1427–1432 (2008).
Google Scholar 
Alerstam, T. Detours in bird migration. J. Theor. Biol. 209(3), 319–331 (2001).ADS 
CAS 
PubMed 

Google Scholar 
Alerstam, T. & Hedenström, A. The development of bird migration theory. J. Avian Biol. 29(4), 343–369 (1998).
Google Scholar 
Liechti, F., Klaassen, M. & Bruderer, B. Predicting migratory flight altitudes by physiological migration models. Auk 117, 205–214 (2000).
Google Scholar 
Senner, N. R. et al. High-altitude shorebird migration in the absence of topographical barriers: Avoiding high air temperatures and searching for profitable winds. Proc. Biol. Sci. 2018, 285 (1881).
Google Scholar 
Norevik, G., Akesson, S., Andersson, A., Backman, J. & Hedenstrom, A. Flight altitude dynamics of migrating European nightjars across regions and seasons. J. Exp. Biol. 224(20), jeb242836 (2021).PubMed 
PubMed Central 

Google Scholar 
Hadjikyriakou, T. G., Nwankwo, E. C., Virani, M. Z. & Kirschel, A. N. G. Habitat availability influences migration speed, refueling patterns and seasonal flyways of a fly-and-forage migrant. Mov. Ecol. 8, 10 (2020).PubMed 
PubMed Central 

Google Scholar 
Strandberg, R., Klaassen, R. H. G., Olofsson, P. & Alerstam, T. Daily travel schedules of adult Eurasian Hobbies Falco subbuteo—Variability in flight hours and migration speed along the route. Ardea 97(3), 287–295 (2009).
Google Scholar 
Strandberg, R. & Alerstam, T. The strategy of fly-and-forage migration, illustrated for the osprey (Pandion haliaetus). Behav. Ecol. Sociobiol. 61(12), 1865–1875 (2007).
Google Scholar 
McKinnon, E. A. & Love, O. P. Ten years tracking the migrations of small landbirds: Lessons learned in the golden age of bio-logging. Auk 135(4), 834–856 (2018).
Google Scholar 
Backman, J. et al. Actogram analysis of free-flying migratory birds: New perspectives based on acceleration logging. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 203(6–7), 543–564 (2017).PubMed 
PubMed Central 

Google Scholar 
Evens, R., Beenaerts, N., Witters, N. & Artois, T. Study on the foraging behaviour of the European nightjar Caprimulgus europaeus reveals the need for a change in conservation strategy in Belgium. J. Avian Biol. 48(9), 1238–1245 (2017).
Google Scholar 
Evens, R. et al. Lunar synchronization of daily activity patterns in a crepuscular avian insectivore. Ecol. Evol. 10(14), 7106–7116 (2020).PubMed 
PubMed Central 

Google Scholar 
Liechti, F. et al. Miniaturized multi-sensor loggers provide new insight into year-round flight behaviour of small trans-Sahara avian migrants. Mov. Ecol. 6, 19 (2018).PubMed 
PubMed Central 

Google Scholar 
Liechti, F., Witvliet, W., Weber, R. & Bachler, E. First evidence of a 200-day non-stop flight in a bird. Nat. Commun. 4, 2554 (2013).ADS 
PubMed 

Google Scholar 
Dhanjal-Adams, K. L. PAMLr: Suite of functions for manipulating pressure, activity, magnetism and light data in R. (2020).Lisovski, S. et al. Light-level geolocator analyses: A user’s guide. J. Anim. Ecol. 89(1), 221–236 (2020).PubMed 

Google Scholar 
Lisovski, S. et al. Geolocation by light: Accuracy and precision affected by environmental factors. Methods Ecol. Evol. 3(3), 603–612 (2012).
Google Scholar 
Wotherspoon, S., Sumner, M., Lisovski, S. SGAT-Package: Solar/Satellite Geolocation for Animal Tracking. (2021). R package version 0.1.3. GitHub Repository.Bauer, R. RchivalTag: Analyzing Archival Tagging Data. R package version 0.1.2. (2020).Sjöberg, S. et al. Barometer logging reveals new dimensions of individual songbird migration. J. Avian Biol. 49(9), e01821 (2018).
Google Scholar 
Evens, R. et al. Migratory pathways, stopover zones and wintering destinations of Western European Nightjars Caprimulgus europaeus. Ibis 159(3), 680–686 (2017).
Google Scholar 
Becker, J. J. et al. Global bathymetry and elevation data at 30 arc seconds resolution: SRTM30_PLUS. Mar. Geodesy 32(4), 355–371 (2009).
Google Scholar 
Ricketts, T. H. Terrestrial Ecoregions of North America: A Conservation Assessment (Island Press, 1999).
Google Scholar 
Olson, D. M. et al. Terrestrial ecoregions of the world: A new map of life on earth. Bioscience 51(11), 933–938 (2001).
Google Scholar 
QGIS-Development-Team: QGIS Geographic Information System. Open Source Geospatial Foundation (2021).Vansteelant, W. M. G., Gangoso, L., Bouten, W., Viana, D. S. & Figuerola, J. Adaptive drift and barrier-avoidance by a fly-forage migrant along a climate-driven flyway. Mov. Ecol. 9(1), 37 (2021).PubMed 
PubMed Central 

Google Scholar 
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9(2), 378–400 (2017).
Google Scholar 
Hartig, F. DHARMa: Residual Diagnostics for Hierarchical Multi-Level/Mixed) Regression Models. R package version 0.3.3.0. (2020).Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.5.1. (2020).Akesson, S., Bianco, G. & Hedenstrom, A. Negotiating an ecological barrier: Crossing the Sahara in relation to winds by common swifts. Philos. Trans. R. Soc. Lond. B Biol. Sci. 371(1704), 20150393 (2016).PubMed 
PubMed Central 

Google Scholar 
Strandberg, R., Klaassen, R. H. G., Hake, M., Olofsson, P. & Alerstam, T. Converging migration routes of Eurasian Hobbies Falco subbuteo crossing the African equatorial rain forest. Proc. R. Soc. B 276, 727–733 (2009).PubMed 

Google Scholar 
Rodriguez-Ruiz, J. et al. Disentangling migratory routes and wintering grounds of Iberian near-threatened European Rollers Coracias garrulus. PLoS ONE 9(12), e115615 (2014).ADS 
PubMed 
PubMed Central 

Google Scholar 
Vickery, J. A. et al. The decline of Afro-Palaearctic migrants and an assessment of potential causes. Ibis 156, 1–22 (2014).
Google Scholar 
Evens, R. et al. Proximity of breeding and foraging areas affects foraging effort of a crepuscular, insectivorous bird. Sci. Rep. 8(1), 3008 (2018).ADS 
PubMed 
PubMed Central 

Google Scholar 
Conring, C. M., Brautigam, K., Grisham, B. A., Collins, D. P. & Conway, W. C. Identifying the migratory strategy of the Lower Colorado River Valley population of Greater Sandhill Cranes. Avian Conserv. Ecol. 14(1), 11 (2019).
Google Scholar 
Imlay, T. L., Saldanha, S. & Taylor, P. D. The fall migratory movements of Bank Swallows, Riparia riparia: Fly-and-forage migration?. Avian Conserv. Ecol. 15(1), 2 (2020).
Google Scholar 
Piersma, T. Hop, skip, or jump? Constraints on migration of arctic waders by feeding, fattening, and flight speed. Limosa 60, 185–194 (1987).
Google Scholar 
Warnock, N. Stopping vs. staging: The difference between a hop and a jump. J. Avian Biol. 41(6), 621–626 (2010).
Google Scholar 
Gomez, C. et al. Fuel loads acquired at a stopover site influence the pace of intercontinental migration in a boreal songbird. Sci. Rep. 7(1), 3405 (2017).ADS 
PubMed 
PubMed Central 

Google Scholar 
Tottrup, A. P. et al. The annual cycle of a trans-equatorial Eurasian-African passerine migrant: different spatio-temporal strategies for autumn and spring migration. Proc. Biol. Sci. 279(1730), 1008–1016 (2012).PubMed 

Google Scholar 
Lisovski, S. et al. Inherent limits of light-level geolocation may lead to over-interpretation. Curr. Biol. 28(3), R99–R100 (2018).CAS 
PubMed 

Google Scholar 
Buler, J. J., Moore, F. R. & Woltmann, S. A multi-scale examination of stopover habitat use by birds. Ecology 88(7), 1789–1802 (2007).PubMed 

Google Scholar 
Loon, A. V. et al. Migratory stopover timing is predicted by breeding latitude, not habitat quality, in a long-distance migratory songbird. J. Ornithol. 158(3), 745–752 (2017).
Google Scholar 
Norevik, G. et al. Wind-associated detours promote seasonal migratory connectivity in a flapping flying long-distance avian migrant. J. Anim. Ecol. 89(2), 635–646 (2020).PubMed 

Google Scholar 
Norevik, G., Åkesson, S. & Hedenström, A. Migration strategies and annual space-use in an Afro-Palaearctic aerial insectivore—The European nightjar Caprimulgus europaeus. J. Avian Biol. 48(5), 738–747 (2017).
Google Scholar 
Cresswell, B. & Edwards, D. Geolocators reveal wintering areas of European Nightjar (Caprimulgus europaeus). Bird Study 60(1), 77–86 (2013).
Google Scholar 
Jacobsen, L. B. et al. Annual spatiotemporal migration schedules in three larger insectivorous birds: European nightjar, common swift and common cuckoo. Anim. Biotelem. 5(1), 1–11 (2017).
Google Scholar 
Liechti, F. & Bruderer, B. The relevance of wind for optimal migration theory. J. Avian Biol. 29(4), 561–568 (1998).
Google Scholar 
Schmaljohann, H., Bruderer, B. & Liechti, F. Sustained bird flights occur at temperatures far beyond expected limits. Anim. Behav. 76(4), 1133–1138 (2008).
Google Scholar 
Schmaljohann, H., Liechti, F. & Bruderer, B. Trans-Sahara migrants select flight altitudes to minimize energy costs rather than water loss. Behav. Ecol. Sociobiol. 63(11), 1609–1619 (2009).
Google Scholar 
Sjöberg, S. et al. Extreme altitudes during diurnal flights in a nocturnal songbird migrant. Science 372, 646–648 (2021).ADS 
PubMed 

Google Scholar 
Bruderer, B., Peter, D. & Korner-Nievergelt, F. Vertical distribution of bird migration between the Baltic Sea and the Sahara. J. Ornithol. 159(2), 315–336 (2018).
Google Scholar  More

Global patterns of ARG distributionWe used a set of 4572 metagenomic samples to illustrate the global patterns of ARG distribution (Supplementary Data 1). These samples were collected from six types of habitats: air, aquatic, terrestrial, engineered, humans and other hosts (Fig. 1a and Supplementary Data 1). From these samples, we identified a total of 2561 ARGs that conferred resistance to 24 drug classes of antibiotics based on the Comprehensive Antibiotic Research Database (CARD). Of these, 2401 were genes conferring resistance to only one drug class, and 160 conferred resistances to multiple drug classes (Supplementary Data 2). Twenty-five ARGs were found in more than 75% samples, however, the frequency of most ARGs (2313/2561) were More

Barton, N. Evolutionary biology. The geometry of adaptation. Nature 395, 751–752. https://doi.org/10.1038/27338 (1998).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Otto, S. P. & Lenormand, T. Resolving the paradox of sex and recombination. Nat. Rev. Genet. 3, 252–261. https://doi.org/10.1038/nrg761 (2002).CAS 
Article 
PubMed 

Google Scholar 
Becks, L. & Agrawal, A. F. Higher rates of sex evolve in spatially heterogeneous environments. Nature 468, 89–92. https://doi.org/10.1038/nature09449 (2010).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359, 80–83. https://doi.org/10.1126/science.aan8048 (2018).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Thompson, D. M. & van Woesik, R. Corals escape bleaching in regions that recently and historically experienced frequent thermal stress. Proc. Biol. Sci. 276, 2893–2901. https://doi.org/10.1098/rspb.2009.0591 (2009).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Pandolfi, J. M., Connolly, S. R., Marshall, D. J. & Cohen, A. L. Projecting coral reef futures under global warming and ocean acidification. Science 333, 418–422. https://doi.org/10.1126/science.1204794 (2011).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Sully, S., Burkepile, D. E., Donovan, M. K., Hodgson, G. & van Woesik, R. A global analysis of coral bleaching over the past two decades. Nat. Commun. 10, 1264. https://doi.org/10.1038/s41467-019-09238-2 (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Yund, P. O. How severe is sperm limitation in natural populations of marine free-spawners?. Trends Ecol. Evol. 15, 10–13 (2000).CAS 
Article 

Google Scholar 
Levitan, D. R. & Petersen, C. Sperm limitation in the sea. Trend Ecol. Evol. 10, 228–231 (1995).CAS 
Article 

Google Scholar 
Baird, A., Guest, J. & Willis, B. Systematic and biogeographical patterns in the reproductive biology of scleractinian corals. Annu. Rev. Ecol. Evol. Syst. 40, 551–571. https://doi.org/10.1146/Annurev.Ecolsys.110308.120220 (2009).Article 

Google Scholar 
Wei, N. V. et al. Reproductive isolation among Acropora species (Scleractinia: Acroporidae) in a marginal coral assemblage. Zool. Stud. 51, 85–92 (2012).
Google Scholar 
Kitanobo, S., Isomura, N., Fukami, H., Iwao, K. & Morita, M. The reef-building coral Acropora conditionally hybridize under sperm limitation. Biol. Lett. 12, 20160511. https://doi.org/10.1098/rsbl.2016.0511 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Mercier, A. & Hamel, J.-F. Synchronized breeding events in sympatric marine invertebrates: Role of behavior and fine temporal windows in maintaining reproductive isolation. Behav. Ecol. Sociobiol. 64, 1749–1765 (2010).Article 

Google Scholar 
Levitan, D. R. et al. Mechanisms of reproductive isolation among sympatric broadcast-spawning corals of the Montastraea annularis species complex. Evolution 58, 308–323 (2004).Article 

Google Scholar 
Willis, B. L., Babcock, R. C., Harrison, P. L. & Wallace, C. C. Experimental hybridization and breeding incompatibilities within the mating systems of mass spawning reef corals. Coral Reefs 16, S53–S65 (1997).Article 

Google Scholar 
Nozawa, Y., Isomura, N. & Fukami, H. Influence of sperm dilution and gamete contact time on the fertilization rate of scleractinian corals. Coral Reefs 34, 1199–1206. https://doi.org/10.1007/s00338-015-1338-3 (2015).ADS 
Article 

Google Scholar 
Oliver, J. & Babcock, R. Aspects of the fertilization ecology of broadcast spawning corals: Sperm dilution effects and in situ measurements of fertilization. Biol. Bull. 183, 409–417. https://doi.org/10.2307/1542017 (1992).CAS 
Article 
PubMed 

Google Scholar 
Coma, R. & Lasker, H. R. Small-scale heterogeneity of fertilization success in a broadcast spawning octocoral. J. Exp. Mar. Biol. Ecol. 214, 107–120. https://doi.org/10.1016/S0022-0981(97)00017-8 (1997).Article 

Google Scholar 
Teo, A. & Todd, P. A. Simulating the effects of colony density and intercolonial distance on fertilisation success in broadcast spawning scleractinian corals. Coral Reefs 37, 891–900. https://doi.org/10.1007/s00338-018-1715-9 (2018).ADS 
Article 

Google Scholar 
Marshall, D. J. In situ measures of spawning synchrony and fertilization success in an intertidal, free-spawning invertebrate. Mar. Ecol. Prog. Ser. 236, 113–119 (2002).ADS 
Article 

Google Scholar 
Babcock, R. C., Mundy, C. N. & Whitehead, D. Sperm diffusion-models and in-situ confirmation of long-distance fertilization in the free-spawning asteroid Acanthaster planci. Biol. Bull. 186, 17–28 (1994).CAS 
Article 

Google Scholar 
Omori, M., Fukami, H., Kobinata, H. & Hatta, M. Significant drop of fertilization of Acropora corals in 1999. An after-effect of heavy coral bleaching?. Limnol. Oceanogr. 46, 704–706. https://doi.org/10.4319/lo.2001.46.3.0704 (2001).ADS 
Article 

Google Scholar 
Levitan, D. R., Fogarty, N. D., Jara, J., Lotterhos, K. E. & Knowlton, N. Genetic, spatial, and temporal components of precise spawning synchrony in reef building corals of the Montastraea annularis species complex. Evolution 65, 1254–1270. https://doi.org/10.1111/j.1558-5646.2011.01235.x (2011).Article 
PubMed 

Google Scholar 
Fukami, H., Omori, M., Shimoike, K., Hayashibara, T. & Hatta, M. Ecological and genetic aspects of reproductive isolation by different spawning times in Acropora corals. Mar. Biol. 142, 679–684. https://doi.org/10.1007/S00227-002-1001-8 (2003).Article 

Google Scholar 
Morita, M. et al. Reproductive strategies in the intercrossing corals Acropora donei and A. tenuis to prevent hybridization. Coral Reefs 38, 1211–1223. https://doi.org/10.1007/s00338-019-01839-z (2019).ADS 
Article 

Google Scholar 
Shinzato, C. et al. Development of novel, cross-species microsatellite markers for Acropora corals using next-generation sequencing technology. Front. Mar. Sci. 1, 11 (2014).Article 

Google Scholar 
R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2020).Albright, R. & Mason, B. Projected near-future levels of temperature and pCO2 reduce coral fertilization success. PLoS One 8, e56468. https://doi.org/10.1371/journal.pone.0056468 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Iguchi, A., Morita, M., Nakajima, Y., Nishikawa, A. & Miller, D. In vitro fertilization efficiency in coral Acropora digitifera. Zygote 17, 225–227. https://doi.org/10.1017/S096719940900519X (2009).Article 
PubMed 

Google Scholar 
Morita, M. et al. Eggs regulate sperm flagellar motility initiation, chemotaxis and inhibition in the coral Acropora digitifera, A. gemmifera and A. tenuis. J. Exp. Biol. 209, 4574–4579. https://doi.org/10.1242/jeb.02500 (2006).CAS 
Article 
PubMed 

Google Scholar 
Chan, W. Y., Hoffmann, A. A. & van Oppen, M. J. H. Hybridization as a conservation management tool. Conserv. Lett. https://doi.org/10.1111/conl.12652 (2019).Article 

Google Scholar  More