Ecology

1.DeBach, P. & Rosen, D. Biological Control by Natural Enemies (Cambridge University Press, 1991).
Google Scholar 
2.Naranjo, S. E., Ellsworth, P. C. & Frisvold, G. B. Economic value of biological control in integrated pest management of managed plant systems. Annu. Rev. Entomol. 60, 621–645 (2015).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
3.Walker, J. T. S., Suckling, D. M. & Wearing, C. H. Past, present, and future of integrated control of apple pests: The New Zealand experience. Annu. Rev. Entomol. 62, 231–248 (2017).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
4.van Lenteren, J. C., Bale, J., Bigler, F., Hokkanen, H. M. T. & Loomans, A. J. M. Assessing risks of releasing exotic biological control agents of arthropod pests. Annu. Rev. Entomol. 51, 609–634 (2006).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
5.Bale, J. S., van Lenteren, J. C. & Bigler, F. Biological control and sustainable food production. Phil. Trans. R. Soc. Lond. B 363, 761–776 (2008).Article 
CAS 

Google Scholar 
6.Sheppard, A. W. et al. A global review of risk-benefit-cost analysis for the introduction of classical biological control agents against weeds: A crisis in the making?. Biocontrol News Inf. 24, 91N-108N (2003).
Google Scholar 
7.Barratt, B. I. P., Blossey, B. & Hokkanen, H. M. Post-release evaluation of non-target effects of biological control agents. In Environmental Impact of Invertebrates for Biological Control of Arthropods: Methods and Risk Assessment (eds Bigler, F. et al.) 166–186 (CABI Publishing, 2006).Chapter 

Google Scholar 
8.Barratt, B. I. P., Moeed, A. & Malone, L. A. Biosafety assessment protocols for new organisms in New Zealand: Can they apply internationally to emerging technologies?. Environ. Impact Assess. Rev. 26, 339–358 (2006).Article 

Google Scholar 
9.Klassen, W. & Curtis, C. F. History of the sterile insect technique. In Sterile Insect Technique: Principles and Practice in Area-Wide Integrated Pest Management (eds Dyck, V. A. et al.) 3–38 (Springer, 2021).
Google Scholar 
10.Hendrichs, J., Kenmore, P., Robinson, A. S. & Vreyson, M. J. B. Area-wide integrated pest management (AW-IPM): principles, practice and prospects. In Area-Wide Control of Insect Pests (eds Vreysen, M. J. B. et al.) 3–34 (Springer, 2007).
Google Scholar 
11.Knipling, E. F. Possibilities of insect control or eradication through the use of sexually sterile males. J. Econ. Entomol. 48, 459–462 (1955).Article 

Google Scholar 
12.Brockerhoff, E. G., Liebhold, A. M., Richardson, B. & Suckling, D. M. Eradication of invasive forest insects: Concepts, methods, costs and benefits. NZ J. For. Sci. 40, S117–S135 (2010).
Google Scholar 
13.Suckling, D. M., Tobin, P. C., McCullough, D. G. & Herms, D. A. Combining tactics to exploit Allee effects for eradication of alien insect populations. J. Econ. Entomol. 105, 1–13 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
14.Hendrichs, J., Enkerlin, W. R. & Pereira, R. Invasive insect pests: challenges and the role of the sterile insect technique in their prevention, containment, and eradication. In Sterile Insect Technique: Principles and Practice in Area-Wide Integrated Pest Management 885–922 (Springer, 2021).Chapter 

Google Scholar 
15.Nagel, P. & Peveling, R. Environment and the sterile insect technique. In Sterile Insect Technique: Principles and Practice in Area-Wide Integrated Pest Management (eds Dyck, V. A. et al.) 499–519 (Springer, 2021).
Google Scholar 
16.Knipling, E. F. The Basic Principles of Insect Population Suppression and Management (U.S. Department of Agriculture, 1979).
Google Scholar 
17.Barclay, H. J. Models for pest control: Complementary effects of periodic releases of sterile pests and parasitoids. Theor. Popul. Biol. 32, 76–89 (1987).Article 

Google Scholar 
18.Soller, M. & Lanzrein, B. Polydnavirus and venom of the egg-larval parasitoid Chelonus inanitus (Braconidae) induce developmental arrest in the prepupa of its host Spodoptera littoralis (Noctuidae). J. Insect Physiol. 42, 471–481 (1996).Article 
CAS 

Google Scholar 
19.Tillinger, N. A., Hoch, G. & Schopf, A. Effects of parasitoid associated factors of the endoparasitoid Glyptapanteles liparidis (Hymenoptera: Braconidae). Eur. J. Entomol. 101, 243–249 (2004).Article 

Google Scholar 
20.Tunçbilek, A. S., Canpolat, U. & Ayvaz, A. Effects of gamma radiation on suitability of stored cereal pest eggs and the reproductive capability of the egg parasitoid Trichogramma evanescens (Trichogrammatidae: Hymenoptera). Biocontrol Sci. Techn. 19, 179–191 (2009).Article 

Google Scholar 
21.Lynch, L. D. et al. Insect biological control and non-target effects: a European perspective. In Evaluating Indirect Ecological Effects of Biological Control (eds Wajnberg, E. et al.) 99–126 (Springer, 2001).
Google Scholar 
22.van Lenteren, J. C. V. et al. Environmental risk assessment of exotic natural enemies used in inundative biological control. Biocontrol 48, 3–38 (2003).Article 

Google Scholar 
23.Horrocks, K. J., Avila, G. A., Holwell, G. I. & Suckling, D. M. Integrating sterile insect technique with the release of sterile classical biocontrol agents for eradication: Is the Kamikaze Wasp Technique feasible?. Biocontrol 65, 257–271 (2020).Article 

Google Scholar 
24.Welsh, T. J., Stringer, L. D., Caldwell, R., Carpenter, J. E. & Suckling, D. M. Irradiation biology of male brown marmorated stink bugs: Is there scope for the sterile insect technique?. Int. J. Radiat. Biol. 93, 1357–1363 (2017).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
25.Suckling, D. M. et al. The competitive mating of irradiated brown marmorated stink bugs, Halyomorpha halys, for the sterile insect technique. Insects 10, 411 (2019).PubMed Central 
Article 

Google Scholar 
26.Larivière, M.-C. Fauna of New Zealand (Manaaki Whenua Press, 1995).
Google Scholar 
27.Martin, N. A. Green vegetable bug – Nezara viridula. Interesting insects and other invertebrates. New Zealand arthropod factsheet number 47 https://nzacfactsheets.landcareresearch.co.nz/factsheet/InterestingInsects/Green-vegetable-bug—Nezara-viridula.html (2018). Accessed 16 Sept 2020.28.Powell, J. E. & Shepard, M. Biology of Australian and United States strains of Trissolcus basalis, a parasitoid of the green vegetable bug Nezara viridula. Austr. Ecol. 7, 181–186 (1982).Article 

Google Scholar 
29.Cantón-Ramos, J. M. & Callejón-Ferre, Á. J. Raising Trissolcus basalis for the biological control of Nezara viridula in greenhouses of Almería (Spain). Afr. J. Agric. Res. 5, 3207–3212 (2010).
Google Scholar 
30.Loch, A. D. & Walter, G. H. Mating behavior of Trissolcus basalis (Wollaston) (Hymenoptera: Scelionidae): Potential for outbreeding in a predominantly inbreeding species. J. Insect Behav. 11, 2 (2002).
Google Scholar 
31.Johns, H. F. & Cunningham, J. R. The interaction of single beams of x and gamma rays with a scattering medium. In The Physics of Radiology 349–350 (Charles C Thomas, 1983).
Google Scholar 
32.Bin, F., Vinson, S. B., Strand, M. R., Colazza, S. & Jones, W. A. Source of an egg kairomone for Trissolcus basalis, a parasitoid of Nezara viridula. Physiol. Entomol. 18, 7–15 (1993).Article 

Google Scholar 
33.Mahmoud, A. M. A. & Lim, U. T. Evaluation of cold-stored eggs of Dolycoris baccarum (Hemiptera: Pentatomidae) for parasitization by Trissolcus nigripedius (Hymenoptera: Scelionidae). Biol. Control 43, 287–293 (2007).Article 

Google Scholar 
34.Haye, T. et al. Fundamental host range of Trissolcus japonicus in Europe. J. Pest Sci. 93, 171–182 (2020).Article 

Google Scholar 
35.Cusumano, A. et al. First extensive characterization of the venom gland from an egg parasitoid: Structure, transcriptome and functional role. J. Insect Physiol. 107, 68–80 (2018).PubMed 
Article 
CAS 

Google Scholar 
36.Bundy, C. S. & McPherson, R. M. Morphological examination of stink bug (Heteroptera: Pentatomidae) eggs on cotton and soybeans, with a key to genera. Ann. Entomol. Soc. Am. 93, 616–624 (2000).Article 

Google Scholar 
37.Favetti, B. M., Butnariu, A. R. & Doetzer, A. K. Storage of Euschistus heros eggs (Fabricius) (Hemiptera: Pentatomidae) in liquid nitrogen for parasitization by Telenomus podisi Ashmead (Hymenoptera: Platygastridae). Neotrop. Entomol. 43, 291–293 (2014).PubMed 
Article 
CAS 

Google Scholar 
38.Kazmer, D. J. & Luck, R. F. Field tests of the size-fitness hypothesis in the egg parasitoid Trichogramma pretiosum. Ecology 76, 412–425 (1995).Article 

Google Scholar 
39.Wickham, H. Ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).MATH 
Book 

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

Google Scholar 
41.Chapman, T., Miyatake, T., Smith, H. K. & Partridge, L. Interactions of mating, egg production and death rates in females of the Mediterranean fruit fly, Ceratitis capitata. Proc. R. Soc. Lond. B 265, 1879–1894 (1998).Article 
CAS 

Google Scholar 
42.Grosch, D. S. & Sullivan, R. L. The quantitative aspects of permanent and temporary sterility induced in female Habrobracon by x-rays and β radiation. Radiat. Res. 1, 294–320 (1954).ADS 
PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
43.Colazza, S. & Wajnberg, E. Effects of host egg mass size on sex ratio and oviposition sequence of Trissolcus basalis (Hymenoptera: Scelionidae). Environ. Entomol. 27, 329–336 (1998).Article 

Google Scholar 
44.Rosi, M. C., Isidoro, N., Colazza, S. & Bin, F. Source of the host marking pheromone in the egg parasitoid Trissolcus basalis (Hymenoptera: Scelionidae). J. Insect Physiol. 47, 989–995 (2001).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
45.Abram, P. K., Brodeur, J., Burte, V. & Boivin, G. Parasitoid-induced host egg abortion: An underappreciated component of biological control services provided by egg parasitoids. Biol. Control 98, 52–60 (2016).Article 

Google Scholar 
46.Kuske, S. et al. Dispersal and persistence of mass released Trichogramma brassicae (Hymenoptera: Trichogrammatidae) in non-target habitats. Biol. Control 27, 181–193 (2003).Article 

Google Scholar 
47.Draz, K. A., Tabikha, R. M., El-Aw, M. A. & Darwish, H. F. Impact of gamma radiation doses on sperm competitiveness, fecundity and morphometric characters of peach fruit fly Bactrocera zonata (Saunders) (Diptera: Tephiritidae). J. Radiat. Res. Appl. Sci. 9, 352–362 (2016).Article 
CAS 

Google Scholar 
48.Ali, A., Rashid, M. A., Huang, Q. Y. & Lei, C.-L. Effect of UV-A radiation as an environmental stress on the development, longevity, and reproduction of the oriental armyworm, Mythimna separata (Lepidoptera: Noctuidae). Environ. Sci. Pollut. Res. 23, 17002–17007 (2016).Article 
CAS 

Google Scholar 
49.Liebhold, A. M. et al. Eradication of invading insect populations: From concepts to applications. Annu. Rev. Entomol. 61, 335–352 (2016).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
50.Tobin, P. C. et al. Determinants of successful arthropod eradication programs. Biol. Invasions 16, 401–414 (2014).Article 

Google Scholar 
51.Pluess, T. et al. Which factors affect the success or failure of eradication campaigns against alien species?. PLoS ONE 7, e48157 (2012).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
52.Colunga-Garcia, M., Magarey, R. A., Haack, R. A., Gage, S. H. & Qi, J. Enhancing early detection of exotic pests in agricultural and forest ecosystems using an urban-gradient framework. Ecol. Appl. 20, 303–310 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
53.Myers, J. H., Savoie, A. & van Randen, E. Eradication and pest management. Annu. Rev. Entomol. 43, 471–491 (1998).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
54.Lance, D. R. & McInnis, D. O. Biological basis of the sterile insect technique. In Sterile Insect Technique: Principles and Practice in Area-Wide Integrated Pest Management (eds Dyck, V. A. et al.) 69–94 (Springer, 2021).
Google Scholar 
55.Godfray, H. C. J. Oviposition behaviour. In Parasitoids: Behavioural and Evolutionary Ecology Vol. 67 83–150 (Princeton University Press, 1994).Chapter 

Google Scholar 
56.Ravuiwasa, K. T., Lu, K.-H., Shen, T.-C. & Hwang, S.-Y. Effects of irradiation on Planococcus minor (Hemiptera: Pseudococcidae). J. Econ. Entomol. 102, 1774–1780 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
57.Bloem, S., Bloem, K. A. & Knight, A. L. Oviposition by sterile codling moths, Cydia pomonella (Lepidoptera: Tortricidae) and control of wild populations with combined releases of sterile moths and egg parasitoids. J. Entomol. Soc. 95, 99–109 (1998).
Google Scholar 
58.Hasaballah, A. I. Impact of gamma irradiation on the development and reproduction of Culex pipiens (Diptera; Culicidae). Int. J. Radiat. Biol. 94, 844–849 (2018).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
59.Sagarra, L. A., Vincent, C. & Stewart, R. K. Body size as an indicator of parasitoid quality in male and female Anagyrus kamali (Hymenoptera: Encyrtidae). Bull. Entomol. Res. 91, 363–367 (2001).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
60.Bertin, A., Pavinato, V. A. C. & Parra, J. R. P. Effects of intraspecific hybridization on the fitness of the egg parasitoid Trichogramma galloi. Biocontrol 63, 555–563 (2018).Article 

Google Scholar 
61.Bloem, S., Bloem, K. A., Carpenter, J. E. & Calkins, C. O. Inherited sterility in codling moth (Lepidoptera: Tortricidae): Effect of substerilizing doses of radiation on insect fecundity, fertility, and control. Ann. Entomol. Soc. Am. 92, 222–229 (1999).Article 

Google Scholar 
62.Bloem, S., Carpenter, J. E. & Hofmeyr, J. H. Radiation biology and inherited sterility in false codling moth (Lepidoptera:Tortricidae). J. Econ. Entomol. 96, 1724–1731 (2003).PubMed 
Article 
PubMed Central 

Google Scholar 
63.El-Kholy, E. M. S. Biological and biochemical effects of vitamin ‘c’ on the normal and irradiated mediterranean fruit fly, Ceratitis capitata (wied). J. Radiat. Res. Appl. Sci. 2, 197–212 (2009).
Google Scholar 
64.Rempoulakis, P., Castro, R., Nemny-Lavy, E. & Nestel, D. Effects of radiation on the fertility of the Ethiopian fruit fly, Dacus ciliatus. Entomol. Exp. Appl. 155, 117–122 (2015).Article 

Google Scholar 
65.Würgler, F. E. & Lütolf, H.-U. Radiosensitivity of oocytes of Drosophila I. sensitivity of class-a oocytes of triploid and diploid females. Int. J. Radiat. Biol. 21, 455–463 (1972).
Google Scholar 
66.Field, S. A. Patch exploitation, patch-leaving and pre-emptive patch defence in the parasitoid wasp Trissolcus basalis (Insecta: Scelionidae). Ethology 104, 323–338 (1998).Article 

Google Scholar 
67.Sked, S. L. & Calvin, D. D. Temporal synchrony between Macrocentrus cingulum (Hymenoptera: Braconidae) with its preferred host, Ostrinia nubilalis (Lepidoptera: Crambidae). Environ. Entomol. 34, 344–352 (2005).Article 

Google Scholar 
68.Jiang, N., Zhou, G., Overholt, W. A., Muchugu, E. & Schulthess, F. The temporal correlation and spatial synchrony in the stemborer and parasitoid system of Coast Kenya with climate effects. Ann. Soc. Entomol. Fr. 42, 381–387 (2006).Article 

Google Scholar 
69.Whitten, M. & Mahon, R. Misconceptions and constraints. In Sterile Insect Technique: Principles and Practice in Area-Wide Integrated Pest Management (eds Dyck, V. A. et al.) 601–626 (Springer, 2021).
Google Scholar 
70.Lee, Y. J. & Ducoff, H. S. Radiation-enhanced resistance to oxygen: A possible relationship to radiation-enhanced longevity. Mech. Ageing Dev. 27, 101–109 (1984).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
71.Suckling, D. M., Wee, S. L. & Pedley, R. Assessing competitive fitness of irradiated painted apple moth Teia anartoides (Lepidoptera: Lymantriidae). N.Z. Plant Prot. 57, 171–176 (2004).
Google Scholar 
72.Wee, S. L. et al. Effects of substerilizing doses of gamma radiation on adult longevity and level of inherited sterility in Teia anartoides (Lepidoptera: Lymantriidae). J. Econ. Entomol. 98, 732–738 (2005).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
73.Vilca Mallqui, K. S., Vieira, J. L., Guedes, R. N. C. & Gontijo, L. M. Azadirachtin-induced hormesis mediating shift in fecundity-longevity trade-off in the Mexican bean weevil (Chrysomelidae: Bruchinae). J. Econ. Entomol. 107, 860–866 (2014).Article 

Google Scholar 
74.Monroy Kuhn, J. M. & Korb, J. Editorial overview: Social insects: Aging and the re-shaping of the fecundity/longevity trade-off with sociality. Curr. Opin. Insect Sci. 16, 7–10 (2016).
Google Scholar 
75.Blacher, P., Huggins, T. J. & Bourke, A. F. G. Evolution of ageing, costs of reproduction and the fecundity–longevity trade-off in eusocial insects. Proc. R. Soc. B-Biol. Sci. 284, 20170380 (2017).Article 

Google Scholar 
76.Flatt, T. Survival costs of reproduction in Drosophila. Exp. Gerontol. 46, 369–375 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
77.Vogt, E. & Nechols, J. R. The influence of host deprivation and host source on the reproductive biology and longevity of the squash bug egg parasitoid Gryon penssylvanicum (Ashmead) (Hymenoptera: Scelionidae). Biol. Control 3, 148–154 (1993).Article 

Google Scholar 
78.Ramesh, B. & Manickavasagam, S. Tradeoff between longevity and fecundity in relation to host availability in a thelytokous oophagous parasitoid, Trichogramma brasiliensis Ashmead (Trichogrammatidae: Hymenoptera). Int. J. Trop. Insect Sci. 23, 207–210 (2003).Article 

Google Scholar 
79.Gurr, G. M. & Kvedaras, O. L. Synergizing biological control: scope for sterile insect technique, induced plant defences and cultural techniques to enhance natural enemy impact. Biol. Control 52, 198–207 (2010).Article 

Google Scholar 
80.Knipling, E. F. Principles of Insect Parasitism Analyzed from New Perspectives: Practical Implications for Regulating Insect Populations by Biological Means (United States Department of Agriculture, 1992).
Google Scholar 
81.Orozco, D., Domínguez, J., Reyes, J., Villaseñor, A. & Gutiérrez, J. M. SIT and biological control of Anastrepha fruit flies in Mexico. in Proceedings of the 6th International Fruit Fly Symposium 245–249 (Isteg Scientific Publications, 2002).82.Wong, T. T. Y., Ramadan, M. M., Herr, J. C. & McInnis, D. O. Suppression of a Mediterranean fruit fly (Diptera: Tephritidae) population with concurrent parasitoid and sterile fly releases in Kula, Maui, Hawaii. J. Econ. Entomol. 85, 1671–1681 (1992).Article 

Google Scholar 
83.Cossentine, J. E. & Jensen, L. B. M. Releases of Trichogramma platneri (Hymenoptera: Trichogrammatidae) in apple orchards under a sterile codling moth release program. Biol. Control 18, 179–186 (2000).Article 

Google Scholar 
84.Carpenter, J. E., Bloem, S. & Hofmeyr, J. H. Acceptability and suitability of eggs of false codling moth (Lepidoptera: Tortricidae) from irradiated parents to parasitism by Trichogrammatoidea cryptophlebiae (Hymenoptera: Trichogrammatidae). Biol. Control 30, 351–359 (2004).Article 

Google Scholar 
85.Carpenter, J. E., Bloem, S. & Hofmeyr, J. H. Area-wide control tactics for the false codling moth Thaumatotibia leucotreta in South Africa: a potential invasive species. In Area-Wide Control of Insect Pests (eds Vreysen, M. J. B. et al.) 351–359 (Springer, 2007).
Google Scholar 
86.Faúndez, E. I. & Rider, D. A. The brown marmorated stink bug Halyomorpha halys (Stål, 1855) (Heteroptera: Pentatomidae) in Chile. Arquivos Entomol. 17, 305–307 (2017).
Google Scholar 
87.Kriticos, D. J. et al. The potential global distribution of the brown marmorated stink bug, Halyomorpha halys, a critical threat to plant biosecurity. J. Pest Sci. 90, 1033–1043 (2017).Article 

Google Scholar 
88.Kiwifruit Vine Health. KVH information sheet: BMSB risk update January 2019 (Kiwifruit Vine Health, 2019).89.Vandervoet, T. F., Bellamy, D. E., Anderson, D. & MacLellan, R. Trapping for early detection of the brown marmorated stink bug, Halyomorpha halys New Zealand. N.Z. Plant Prot. 72, 36–43 (2019).
Google Scholar 
90.Laing, K., Belton, D. & Taylor, J. Decision on releasing Trissolcus japonicus from containment. (Environmental Protection Authority, 2018).91.Charles, J. G. et al. Experimental assessment of the biosafety of Trissolcus japonicus in New Zealand, prior to the anticipated arrival of the invasive pest Halyomorpha halys. Biocontrol 64, 367–379 (2019).Article 
CAS 

Google Scholar  More

1.Blackburn, T. M. & Duncan, R. P. Establishment patterns of exotic birds are constrained by non-random patterns in introduction. J. Biogeogr. 28, 927–939 (2001).Article 

Google Scholar 
2.Long, J. L. Introduced Mammals of the World: Their History, Distribution and Abundance (CABI Publishing, 2003).Book 

Google Scholar 
3.Stuwe, M. & Scribner, K. T. Low genetic variability in reintroduced alpine ibex (Capra ibex ibex) populations. J. Mammal. 70, 370–373 (1989).Article 

Google Scholar 
4.Allendorf, F. W. & Lundquist, L. L. Introduction: Population biology, evolution, and control of invasive species. Conserv. Biol. 17, 24–30 (2003).Article 

Google Scholar 
5.Frankham, R. Genetics and extinction. Biol. Conserv. 126, 131–140 (2005).Article 

Google Scholar 
6.Michael Reed, J. et al. Emerging issues in population viability analysis. Conserv. Biol. 16, 7–19 (2002).Article 

Google Scholar 
7.Carpio, A. J. et al. Hunting as a source of alien species: A European review. Biol. Invasions 19, 1197–1211 (2017).Article 

Google Scholar 
8.Linnell, J. D. C. & Zachos, F. E. Status and distribution patterns of European ungulates: genetics, population history and conservation. In Ungulate Management in Europe: Problems and Practices (eds Putman, R. et al.) 12–53 (Cambridge University Press, 2011).Chapter 

Google Scholar 
9.Šprem, N., Gančević, P., Safner, T., Jerina, K. & Cassinello, J. Barbary sheep (Ammotragus lervia, Pallas 1777). In Handbook of the Mammals of Europe (eds Hackländer, K. & Zachos, F. E.) (Springer, 2021).
Google Scholar 
10.Cassinello, J. Ammotragus lervia: A review on systematics, biology, ecology and distribution. Ann. Zool. Fennici 35, 149–162 (1998).
Google Scholar 
11.Cassinello, J. Ammotragus lervia (aoudad). Invasive species compendium. http://www.cabi.org/isc (2015).12.Bounaceur, F., Benamor, N., Bissaad, F. Z., Abdi, A. & Aulagnier, S. Is there a future for the last populations of aoudad (Ammotragus lervia) in northern Algeria?. Pak. J. Zool. 48, 1727–1731 (2016).
Google Scholar 
13.Cassinello, J. et al. Ammotragus lervia. The IUCN Red List of Threatened Species. www.iucnredlist.org (2008).14.Lazarus, M. et al. Barbary sheep tissues as bioindicators of radionuclide and stabile element contamination in Croatia: Exposure assessment for consumers. Environ. Sci. Pollut. Res. 26, 14521–14533 (2019).CAS 
Article 

Google Scholar 
15.Mori, E., Mazza, G., Saggiomo, L., Sommese, A. & Esattore, B. Strangers coming from the Sahara: An update of the worldwide distribution, potential impacts and conservation opportunities of alien aoudad. Ann. Zool. Fennici 54, 373–386 (2017).Article 

Google Scholar 
16.Gančević, P., Šprem, N. & Jerina, K. Space use and activity patterns of introduced Barbary sheep (Ammotragus lervia) in Southern Dinarides, Croatia in Abstract book of 6th World Congress on Mountain Ungulates and 5th International Symposium on Mouflon (ed. Hadjisterkotis, E.) 41 (2016).17.Bartoš, L., Kotrba, R. & Pintíř, J. Ungulates and their management in the Czech Republic. In European Ungulates and their Management in the 21st Century (eds Apollonio, M. et al.) 243–261 (Cambridge University Press, 2010).
Google Scholar 
18.Cassinello, J., Serrano, E., Calabuig, G. & Pérez, J. M. Range expansion of an exotic ungulate (Ammotragus lervia) in southern Spain: Ecological and conservation concerns. Biodivers. Conserv. 13, 851–866 (2004).Article 

Google Scholar 
19.Anadón, J. D., Pérez-García, J. M., Pérez, I., Royo, J. & Sánchez-Zapata, J. A. Disentangling the effects of habitat, connectivity and interspecific competition in the range expansion of exotic and native ungulates. Landsc. Ecol. 33, 597–608 (2018).Article 

Google Scholar 
20.Cassinello, J. Misconception and mismanagement of invasive species: The paradoxical case of an alien ungulate in Spain. Conserv. Lett. 11, e12440. https://doi.org/10.1111/conl.12440 (2018).Article 

Google Scholar 
21.Prentis, P. J., Wilson, J. R. U., Dormontt, E. E., Richardson, D. M. & Lowe, A. J. Adaptive evolution in invasive species. Trends Plant Sci. 13, 288–294 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
22.Derouiche, L. et al. Deep mitochondrial DNA phylogeographic divergence in the threatened aoudad Ammotragus lervia (Bovidae, Caprini). Gene 739, 144510. https://doi.org/10.1016/j.gene.2020.144510 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
23.Selkoe, K. A. & Toonen, R. J. Microsatellites for ecologists: A practical guide to using and evaluating microsatellite markers. Ecol. Lett. 9, 615–629 (2006).PubMed 
Article 
PubMed Central 

Google Scholar 
24.Fernando, P., Vidya, T. N. C., Rajapakse, C., Dangolla, A. & Melnick, D. J. Reliable noninvasive genotyping: Fantasy or reality?. J. Hered. 94, 115–123 (2003).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
25.Cassinello, J. Ammotragus free-ranging population in the south-east of Spain: A necessary first account. Biodivers. Conserv. 9, 887–900 (2000).Article 

Google Scholar 
26.Moravčíková, N. et al. Identification of genetic families based on mitochondrial D-loop sequence in population of the Tatra chamois (Rupicapra rupicapra tatrica). Biologia 75, 121–128 (2019).Article 
CAS 

Google Scholar 
27.Cassinello, J. Ammotragus lervia Aoudad (Barbary Sheep, Arui). In Mammals of Africa. Volume VI: Pigs, Hippopotamuses, Chevrotain, Giraffes, Deer and Bovids (eds Kingdon, J. & Hoffmann, M.) 595–599 (Bloomsbury Publishing, 2013).
Google Scholar 
28.Nei, M., Maruyama, T. & Chakraborty, R. The bottleneck effect and genetic variability in populations. Evolution 29, 1–10 (1975).PubMed 
Article 
PubMed Central 

Google Scholar 
29.Šprem, N. & Buzan, E. The genetic impact of chamois management in the dinarides. J. Wildl. Manag. 80, 783–793 (2016).Article 

Google Scholar 
30.Pascual-Rico, R. et al. Ecological niche overlap between co-occurring native and exotic ungulates: Insights for a conservation conflict. Biol. Invasions 22, 2497–2508 (2020).Article 

Google Scholar 
31.Dlugosch, K. M. & Parker, I. M. Founding events in species invasions: Genetic variation, adaptive evolution, and the role of multiple introductions. Mol. Ecol. 17, 431–449 (2008).CAS 
PubMed 
Article 

Google Scholar 
32.Beja-Pereira, A. et al. Twenty polymorphic microsatellites in two of North Africa’s most threatened ungulates: Gazella dorcas and Ammotragus lervia (Bovidae; Artiodactyla). Mol. Ecol. Notes 4, 452–455 (2004).CAS 
Article 

Google Scholar 
33.Schuelke, M. An economic method for the fluorescent labeling of PCR fragments. Nat. Biotechnol. 18, 233–234 (2000).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
34.Mereu, P., Palici di Suni, M., Manca, L. & Masala, B. Complete nucleotide mtDNA sequence of Barbary sheep (Ammotragus lervia). DNA Seq. 19, 241–245 (2008).CAS 
PubMed 
Article 

Google Scholar 
35.Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
36.Rozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol. Biol. Evol. 34, 3299–3302 (2017).CAS 
PubMed 
Article 

Google Scholar 
37.Bandelt, H.-J., Forster, P. & Rohl, A. Median-joining networks for inferring intraspecific phylogenies. Mol. Biol. Evol. 16, 37–48 (1999).CAS 
Article 

Google Scholar 
38.Leigh, J. W. & Bryant, D. POPART: Full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116 (2015).Article 

Google Scholar 
39.van Oosterhout, C., Hutchinson, W. F., Wills, D. P. M. & Shipley, P. MICROCHECKER: Software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes 4, 535–538 (2004).Article 
CAS 

Google Scholar 
40.Dempster, A. P., Laird, N. M. & Rubin, D. B. Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B 39, 1–22 (1977).MathSciNet 
MATH 

Google Scholar 
41.Chapuis, M.-P. & Estoup, A. Microsatellite null alleles and estimation of population differentiation. Mol. Biol. Evol. 24, 621–631 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
42.Kalinowski, S. T., Taper, M. L. & Marshall, T. C. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol. Ecol. 16, 1099–1106 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
43.Belkhir K, Borsa P, Goudet, J., Chikhi, L. & Bonhomme, F. Genetix 4.05, logiciel sous Windows TM pour la genetique des populations. Available at: http://www.genetix.univ-montp2.fr/genetix/genetix.htm (2004)44.Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370 (1984).CAS 

Google Scholar 
45.Rousset, F. GENEPOP’007: A complete re-implementation of the GENEPOP software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
46.Kalinowski, S. T. Counting alleles with rarefaction: Private alleles and hierarchical sampling designs. Conserv. Genet. 5, 539–543 (2004).CAS 
Article 

Google Scholar 
47.Waples, R. S. A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci. Conserv. Genet. 7, 167–184 (2006).Article 

Google Scholar 
48.Do, C. et al. NeEstimator v2: Re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Mol. Ecol. Resour. 14, 209–214 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
49.Waples, R. S. & Do, C. Linkage disequilibrium estimates of contemporary Ne using highly variable genetic markers: A largely untapped resource for applied conservation and evolution. Evol. Appl. 3, 244–262 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
50.Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
51.Earl, D. A. & vonHoldt, B. M. STRUCTURE HARVESTER: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361 (2012).Article 

Google Scholar 
52.Jakobsson, M. & Rosenberg, N. A. CLUMPP: A cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23, 1801–1806 (2007).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
53.Rosenberg, N. A. DISTRUCT: A program for the graphical display of population structure. Mol. Ecol. Notes 4, 137–138 (2004).Article 

Google Scholar  More

Our study extends the known geographic area used by salmon during their migration in the North Atlantic Ocean and Barents Sea as reported by earlier studies based on conventional tagging and sampling surveys15,16,20. An extended use of the North Atlantic Ocean and Barents Sea was also suggested in recent studies using archival tags12,23,24,25,26,28, but these studies have concentrated on single populations or been restricted by low sample sizes. The present study indicated that multiple individuals from the Norwegian and Danish populations survived to migrate northward from their home river and reached latitudes as high as 80° N. This is to our knowledge the furthest north any Atlantic salmon has ever been recorded, extending previously assumed northern limits8,30. These results confirm that the foraging areas of Atlantic salmon currently extend to more northerly latitudes than previously thought. For populations in Denmark and Norway, the marine distribution is probably limited by the northern boundary of Atlantic currents. In contrast, the populations from Iceland, Ireland and Spain did not travel as far north, but instead crossed the main North Atlantic current and migrated towards southern Greenland, indicating a difference in ocean distribution for these populations. The less directed migration displayed by most of the North American salmon tagged at Greenland was likely due to these fish already being present at their assumed main ocean feeding grounds at the west coast of Greenland15 when tagged.Despite the fact that salmon from different areas used different migration routes and ocean areas, they consistently migrated to and aggregated in assumed highly productive areas at the boundaries between large-scale frontal water masses where branches of the North Atlantic current lie adjacent to cold polar waters31. In these areas, previous analyses demonstrated frequent diving activity by tagged individuals28. The duration and diving profile of these dives suggested foraging behaviour, rather than predator escape, because the dives were U-shaped, typically lasted a few hours, and diving depths were related to the depth of the mixed layer during the different seasons28. Thus, the increased diving frequency is most likely an indication of increased feeding activity, emphasizing the importance of these productive regions as feeding areas for Atlantic salmon. In contrast to Atlantic salmon from the other areas, the two northernmost populations displayed a high diving frequency close to the shore immediately after sea entrance, as also shown by Hedger et al.28. These rivers are located closer to the frontal water masses, and these fish may have started extensive feeding earlier in their sea migration. This assumption is further supported by a study of Norwegian post-smolts, where the northernmost populations were feeding more extensively just after leaving their rivers than fish from southern populations32. Thus, the northern populations may benefit from a shorter migration route to the main feeding areas for salmon. However, given that many kelts are in poor condition when they enter the sea, it is likely that tagged fish from all populations were feeding pelagically in the first weeks at sea during the transit away from the coast when prey were available.Migration from the rivers to the assumed foraging areas (i.e., the most distant areas they migrated to) was fast and direct for individuals from southern populations, while salmon from the northern Norway did not display similar direct migration routes. Our results are similar to those reported by an earlier study26 on the same North-Western Norwegian population as in the present study, and are likely related to the greater proximity to ocean frontal areas and rich food resources.The results in the present study may have been influenced by the relatively large size of the tag compared to the size of the fish. Hedger et al.33 assessed tagging effects of PSATs on post-spawned Atlantic salmon by comparing their behaviour with salmon tagged with much smaller archival tags. They found that the overall depth distribution, ocean migration routes based on temperature recordings and return rates did not differ between salmon tagged with PSATs and smaller archival tags and concluded that PSATs are suitable for use in researching large-scale migratory behaviour of adult salmon at sea. However, salmon with PSATs dived less frequently and to slightly shallower depths33. Based on this, we believe the conclusions of the present study are valid despite potential tagging effects, but the diving depths and frequencies might be underestimated compared to non-tagged fish.Diet data from adult salmon in the ocean are limited but show that salmon feed on a variety of prey taxa. Typically, herring (Clupea harengus), sand eels (Ammodytes spp.), capelin (Mallotus villosus) and myctophids dominate as fish prey, while euphausiids and amphipods often dominate as crustacean prey34,35,36. Although there exist some data of adult herring and capelin during parts of the year, there is limited information on the spatial and temporal distribution of crustaceans in these ocean areas, and it is therefore difficult to relate the salmon diving behaviour to availability of all their main prey items. However, salmon appeared to be able to forage on prey far below the surface, indicated by the frequent dives, and salmon at sea have also previously been shown to feed on the mesopelagic community37,38. Hedger et al.28 found that the diving depth increased with the depth of the mixed layer and hypothesised that stratification affected the aggregation of prey and thereby the salmon diving behaviour. They also showed that when the stratification disappeared during the dark winter months, the salmon dived less but their dives were deeper. Nevertheless, the possibilities to feed at different depths28, expand the foraging niche of salmon compared to feeding merely near the surface.Dadswell et al.11 published the “merry-go-round hypothesis”, which implies that both first-time migrants and previous spawners from all salmon populations enter the North Atlantic Subpolar Gyres and move counter clockwise within these gyres until returning to their natal rivers. Although the full migration from river outrun to return was not followed in the present study (most tags popped off half-way into the migration), and some individuals indicated a counter clockwise migration pattern, most of the populations and individuals in this study clearly did not follow the North Atlantic Subpolar Gyres during the first months at sea. Therefore, most of our data did not support the merry-go-round hypothesis. However, some individuals from northern Norway seemed to follow the currents to a larger extent than individuals from other populations during the first months at sea. Previous studies on Atlantic salmon from Canada also documented that adults migrated either independently or against prevailing currents while at sea, indicating that the horizontal movement of adults are primarily governed by other factors12,24.Due to the size limit of the pop-up-tags, we primarily tracked large post-spawned individuals that are more mobile than smaller first-time migrants. Although some studies have shown that first-time migrants can be found in the same areas as post-spawners from the same populations8,30 is not known to which extent the migration pattern and distribution of post-spawners represent the same migration pattern of first-time migrants. Due to a larger body size, it is possible that the migration of post-spawners depends to a lesser degree on ocean currents and gyres than do the movements of first-time migrants, especially in the first part of the migration. For example, we observed that the Irish and Spanish post-spawned individuals all crossed the main North Atlantic current towards Greenlandic waters. However, Irish and other southern European post-smolts have frequently been captured in the Norwegian Sea20, indicating that some of these individuals migrate and follow the main ocean current in a northward direction. It is possible that many of these post-smolts later migrate southwest towards Greenland and feed in these waters as maiden salmon before they return to rivers. This corresponds to the observation that it is mostly large (two sea-winter) southern European salmon (including Irish individuals) that are found in the southern Greenland feeding areas20. Therefore, it might be that the post-spawned salmon from these populations return to their primary feeding areas where they were feeding as maiden salmon from their first sea migration, and not necessarily to the same area as they started their feeding migration as post-smolts.Populations differed in their ocean distribution, but the distribution also overlapped to some degree between or among populations, with more overlap between geographically proximate than distant populations. Some populations never overlapped in geographical distribution during the study. The populations from Ireland and Spain did not overlap with the Norwegian and Danish salmon, but there was a small spatial overlap between the Irish salmon and the North American salmon tagged at Greenland, although area use by these populations did not overlap in time. It is known that populations from North America and Europe largely use different parts of the North Atlantic, with more North American salmon in the western part and more European salmon in the eastern part of the ocean although they have been shown to mix at the feeding grounds at the Faroes and at Greenland12,15,16,18,20. For the Spanish population, it should be noted that tagged individuals were followed for a relatively short period, and a larger sample size over a longer period might have shown some overlap with the northern European populations, based on the initial northward direction of two individuals. At the same time as populations differed in their ocean distribution, there were also relatively large within-population differences in migration routes and geographic distribution. Individual differences in migration routes and ocean distribution of salmon from the same population, even within the same year, were also shown by Strøm et al.12,26. Collectively, these results imply that salmon from different populations will experience highly different ecological conditions, potentially contributing to between-and within-population variation in growth and survival. Since our data are limited by a varying number of individuals among the studied populations, and restricted mainly to post-spawned salmon, our results represent a minimum overlap among the populations so the actual overlap may be larger. Nevertheless, this strongly indicates a varying degree of geographical separation in ocean feeding areas. Thus, geographically close populations will to a larger extent be influenced by similar conditions in the ocean than more distant populations.The study was carried out over several years, with not all sites having tagging undertaken in the same years. There is a possibility that geographic area use and overlap among populations may vary among years, according to variation in environmental conditions among years29. However, data from multiple years for some populations suggest consistent population specific migration routes and area use among years, indicating that the principal patterns are stable over time for particular salmon populations.The differing distributions of salmon from particular populations in different oceanic regions might simply be a function of distance to appropriate feeding grounds from the different home rivers, with individuals from the different rivers mainly adapted to seek the closest feeding areas. The route selection during the migration might in addition be a result of each individuals’ opportunistic behaviour and which food resources and environmental conditions they encounter along the journey. As discussed above, the experience and learning during the first ocean migration might also impact individuals’ route choice and area use. Salmon from southern populations used more southern ocean areas, and hence stayed in warmer water, than salmon from the northern populations. We cannot rule out that salmon from different populations have different temperature preferences due to different thermal selection regimes in their home rivers, but similar to a previous study29, we suggest that the differences in thermal habitat among populations utilising different areas at sea are mainly driven by availability of prey fields. There is generally little support for the hypothesis that variation in salmonid growth rates reflects thermal adaptations to their home stream39.Despite the variation in migration patterns among and within populations, most individuals seemed to migrate to distant ocean frontal areas. This suggests that climate change may have greater impact on populations originating further south, because the distances and time required to travel to feeding areas will increase if the boundary between Atlantic and Arctic waters move northward because of ocean warming. Our study has shown that several populations are able to migrate over large distances, but the capacity for populations to adapt to an increased migration distance is unknown. Given increased migration time, especially for southern populations, the time available for accumulating important energy reserves will likely be reduced. In addition, increased water temperatures in the North Atlantic may also increase the energy expenditure that the individual fish spend per unit of distance when migrating from their home rivers towards the feeding areas. This may affect all populations to some degree, and may contribute to an additional burden for Atlantic salmon populations that are already in a poor state. This will also add to the hypothesized negative effect of climate change in freshwater for the southern populations, where temperatures will have a greater likelihood of reaching to growth inhibiting levels compared to more northern populations39.Taking advantage of the development of electronic tags, we have shown an extended use of the North Atlantic Ocean by Atlantic salmon, including the Barents Sea, which contrasts to the earlier strong focus on feeding areas at the Faroes, West Greenland and in the Norwegian Sea in previous studies. These results expand the knowledge on the marine foraging and habitat niche of Atlantic salmon, in terms of geography, migration behaviour and thermal niche. The existence of feeding areas at the boundaries between Atlantic and Arctic surface currents suggests that salmon have a strong link to Arctic oceanic frontal systems. We have further shown that salmon from different populations may migrate to different ocean frontal areas in the North Atlantic Ocean and Barents Sea and therefore be impacted by different ecological conditions that may contribute to within-population variation in growth and survival. We also conclude that climate induced changes in oceanographic conditions, which will likely alter the location of and distance to polar frontal feeding areas, may have region-specific influences on the length and cost of the Atlantic feeding migrations, particularly affecting the southern populations most. As the polar oceans get warmer and current patterns shift, changes in the location and productivity of high latitude fronts will become evident. As migration distances become longer, or more variable, and the time accumulating energy is reduced, the variation in the marine survival and productivity of different populations are likely to become more marked. Combined, our results help to shed light on important ecological process that shape Atlantic salmon population dynamics within most of its distribution area. More

1.Hotez, P. J. et al. An unfolding tragedy of chagas disease in North America. PLoS Negl. Trop. Dis. 7(10), e2300. https://doi.org/10.1371/journal.pntd.0002300 (2013) (PMID: 24205411).Article 
PubMed 
PubMed Central 

Google Scholar 
2.Hotez, P. J., Bottazzi, M. E., Franco-Paredes, C., Ault, S. K. & Periago, M. R. The neglected tropical diseases of Latin America and the Caribbean: A review of disease burden and distribution and a roadmap for control and elimination. PLoS Negl. Trop. Dis. 2(9), e300. https://doi.org/10.1371/journal.pntd.0000300 (2008) (PMID: 18820747).Article 
PubMed 
PubMed Central 

Google Scholar 
3.Lee, B. Y., Bacon, K. M., Bottazzi, M. E. & Hotez, P. J. Global economic burden of Chagas disease: A computational simulation model. Lancet Infect. Dis. 13(4), 342–348. https://doi.org/10.1016/S1473-3099(13)70002-1 (2013) (PMID: 23395248).Article 
PubMed 
PubMed Central 

Google Scholar 
4.WHO. Chagas disease in Latin America: An epidemiological update based on 2010 estimates. Wkly. Epidemiol. Rec. 90(6), 33–43 (2015) (PMID: 25671846).
Google Scholar 
5.Pena-Garcia, V. H., Gomez-Palacio, A. M., Triana-Chavez, O. & Mejia-Jaramillo, A. M. Eco-epidemiology of Chagas disease in an endemic area of Colombia: Risk factor estimation, Trypanosoma cruzi characterization and identification of blood-meal sources in bugs. Am. J. Trop. Med. Hyg. 91(6), 1116–1124. https://doi.org/10.4269/ajtmh.14-0112 (2014) (PMID: 25331808).Article 
PubMed 
PubMed Central 

Google Scholar 
6.Mejia-Jaramillo, A. M. et al. Genotyping of Trypanosoma cruzi in a hyper-endemic area of Colombia reveals an overlap among domestic and sylvatic cycles of Chagas disease. Parasit. Vectors. 7, 108. https://doi.org/10.1186/1756-3305-7-108 (2014) (PMID: 24656115).Article 
PubMed 
PubMed Central 

Google Scholar 
7.Dib, J. C., Agudelo, L. A. & Velez, I. D. Prevalencia de patologías tropicales y factores de riesgo en la comunidad indígena de Bunkwimake, Sierra Nevada de Santa Marta. DUAZARY. 3(1), 38–44 (2006).
Google Scholar 
8.Parra-Henao, G. et al. In search of congenital Chagas disease in the Sierra Nevada de Santa Marta, Colombia. Am. J. Trop. Med. Hyg. 101(3), 482–483. https://doi.org/10.4269/ajtmh.19-0110 (2019) (PMID: 31264558).Article 
PubMed 
PubMed Central 

Google Scholar 
9.Guhl, F., Aguilera, G., Pinto, N. & Vergara, D. Actualización de la distribución geográfica y ecoepidemiología de la fauna de triatominos (Reduviidae: Triatominae) en Colombia. Biomedica. 27(Suppl 1), 143–162 (2007) (PMID: 18154255).Article 

Google Scholar 
10.Parra-Henao, G., Suarez-Escudero, L. C. & Gonzalez-Caro, S. Potential distribution of Chagas disease vectors (Hemiptera, Reduviidae, Triatominae) in Colombia, based on Ecological Niche Modeling. J. Trop. Med. 2016, 1439090. https://doi.org/10.1155/2016/1439090 (2016) (PMID: 28115946).Article 
PubMed 
PubMed Central 

Google Scholar 
11.Rodriguez-Mongui, E., Cantillo-Barraza, O., Prieto-Alvarado, F. E. & Cucunuba, Z. M. Heterogeneity of Trypanosoma cruzi infection rates in vectors and animal reservoirs in Colombia: A systematic review and meta-analysis. Parasit. Vectors. 12(1), 308. https://doi.org/10.1186/s13071-019-3541-5 (2019) (PMID: 31221188).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
12.Dib, J., Barnabe, C., Tibayrenc, M. & Triana, O. Incrimination of Eratyrus cuspidatus (Stal) in the transmission of Chagas’ disease by molecular epidemiology analysis of Trypanosoma cruzi isolates from a geographically restricted area in the north of Colombia. Acta Trop. 111(3), 237–242. https://doi.org/10.1016/j.actatropica.2009.05.004 (2009) (PMID: 19442641).Article 
PubMed 

Google Scholar 
13.Parra Henao, G., Angulo, V., Jaramillo, N. & Restrepo, M. Triatominos (Hemiptera: Reduviidae) de ka Sierra Nevada de Santa Marta, Colombia. Aspectos epidemiológicos, entomológicos y de distribución. Rev. CES Med. 23(1), 17–26 (2009).
Google Scholar 
14.Hernandez, C. et al. Untangling the transmission dynamics of primary and secondary vectors of Trypanosoma cruzi in Colombia: Parasite infection, feeding sources and discrete typing units. Parasit. Vectors. 9(1), 620. https://doi.org/10.1186/s13071-016-1907-5 (2016) (PMID: 27903288).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
15.Cantillo-Barraza, O., Chaverra, D., Marcet, P., Arboleda-Sanchez, S. & Triana-Chavez, O. Trypanosoma cruzi transmission in a Colombian Caribbean region suggests that secondary vectors play an important epidemiological role. Parasit. Vectors. 7, 381. https://doi.org/10.1186/1756-3305-7-381 (2014) (PMID: 25141852).Article 
PubMed 
PubMed Central 

Google Scholar 
16.Weiss, B. & Aksoy, S. Microbiome influences on insect host vector competence. Trends Parasitol. 27(11), 514–522. https://doi.org/10.1016/j.pt.2011.05.001 (2011) (PMID: 21697014).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
17.Azambuja, P., Garcia, E. S. & Ratcliffe, N. A. Gut microbiota and parasite transmission by insect vectors. Trends Parasitol. 21(12), 568–572 (2005) (PMID: 16226491).Article 

Google Scholar 
18.Dumonteil, E. et al. Interactions among Triatoma sanguisuga blood feeding sources, gut microbiota and Trypanosoma cruzi diversity in southern Louisiana. Mol Ecol. 29(19), 3747–3761 (2020).Article 

Google Scholar 
19.Zingales, B. et al. A new consensus for Trypanosoma cruzi intraspecific nomenclature: Second revision meeting recommends TcI to TcVI. Mem. Inst. Oswaldo Cruz. 104(7), 1051–1054 (2009) (PMID: 20027478).CAS 
Article 

Google Scholar 
20.Zingales, B. et al. The revised Trypanosoma cruzi subspecific nomenclature: Rationale, epidemiological relevance and research applications. Infect. Genet. Evol. 12(2), 240–253. https://doi.org/10.1016/j.meegid.2011.12.009 (2012) (PMID: 22226704).Article 
PubMed 

Google Scholar 
21.Tibayrenc, M. & Ayala, F. J. The population genetics of Trypanosoma cruzi revisited in the light of the predominant clonal evolution model. Acta Trop. 151, 156–165. https://doi.org/10.1016/j.actatropica.2015.05.006 (2015) (PMID: 26188332).Article 
PubMed 
PubMed Central 

Google Scholar 
22.Majeau, A., Murphy, L., Herrera, C. & Dumonteil, E. Assessing Trypanosoma cruzi parasite diversity through comparative genomics: Implications for disease epidemiology and diagnostics. Pathogens. 10, 212. https://doi.org/10.3390/pathogens10020212 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
23.Flores-Ferrer, A., Marcou, O., Waleckx, E., Dumonteil, E. & Gourbière, S. Evolutionary ecology of Chagas disease; what do we know and what do we need?. Evol. Appl. 11(4), 470–487. https://doi.org/10.1111/eva.12582 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
24.Tibayrenc, M., Kjellberg, F. & Ayala, F. J. A clonal theory of parasitic protozoa: The population structures of Entamoeba, Giardia, Leishmania, Naegleria, Plasmodium, Trichomonas, and Trypanosoma and their medical and taxonomical consequences. Proc. Natl. Acad. Sci. USA 87, 2414–2418 (1990).ADS 
CAS 
Article 

Google Scholar 
25.Berry, A. S. F. et al. Sexual reproduction in a natural Trypanosoma cruzi population. PLoS Negl. Trop. Dis. 13(5), e0007392. https://doi.org/10.1371/journal.pntd.0007392 (2019) (PMID: 31107905).Article 
PubMed 
PubMed Central 

Google Scholar 
26.Schwabl, P. et al. Meiotic sex in Chagas disease parasite Trypanosoma cruzi. Nat. Commun. 10(1), 3972. https://doi.org/10.1038/s41467-019-11771-z (2019) (PMID: 31481692).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
27.Falla, A. et al. Haplotype identification within Trypanosoma cruzi I in Colombian isolates from several reservoirs, vectors and humans. Acta Trop. 110(1), 15–21 (2009) (PMID: 19135020).CAS 
Article 

Google Scholar 
28.Cura, C. I. et al. Trypanosoma cruzi I genotypes in different geographical regions and transmission cycles based on a microsatellite motif of the intergenic spacer of spliced-leader genes. Int. J. Parasitol. 40(14), 1599–1607. https://doi.org/10.1016/j.ijpara.2010.06.006 (2010) (PMID: 20670628).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
29.Rodriguez, I. B. et al. Transmission dynamics of Trypanosoma cruzi determined by low-stringency single primer polymerase chain reaction and southern blot analyses in four indigenous communities of the Sierra Nevada de Santa Marta, Colombia. Am. J. Trop. Med. Hyg. 81(3), 396–403 (2009) (PMID: 19706903).CAS 
Article 

Google Scholar 
30.Waleckx, E., Gourbière, S. & Dumonteil, E. Intrusive triatomines and the challenge of adapting vector control practices. Mem. Inst. Oswaldo Cruz. 110(3), 324–338 (2015).CAS 
Article 

Google Scholar 
31.Dumonteil, E. et al. Detailed ecological associations of triatomines revealed by metabarcoding and next-generation sequencing: Implications for triatomine behavior and Trypanosoma cruzi transmission cycles. Sci. Rep. 8(1), 4140. https://doi.org/10.1038/s41598-018-22455-x (2018) (PMID: 29515202).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
32.Dumonteil, E. et al. Interactions among Triatoma sanguisuga blood feeding sources, gut microbiota and Trypanosoma cruzi diversity in southern Louisiana. Mol. Ecol. https://doi.org/10.1111/mec.15582 (2020) (PMID: 32749727).Article 
PubMed 

Google Scholar 
33.O’Connor, O., Bosseno, M. F., Barnabe, C., Douzery, E. J. & Breniere, S. F. Genetic clustering of Trypanosoma cruzi I lineage evidenced by intergenic miniexon gene sequencing. Infect. Genet. Evol. 7(5), 587–593. https://doi.org/10.1016/j.meegid.2007.05.003 (2007) (PMID: 17553755).CAS 
Article 
PubMed 

Google Scholar 
34.Villanueva-Lizama, L., Teh-Poot, C., Majeau, A., Herrera, C. & Dumonteil, E. Molecular genotyping of Trypanosoma cruzi by next-generation sequencing of the mini-exon gene reveals infections with multiple parasite DTUs in Chagasic patients from Yucatan, Mexico. J. Inf. Dis. 219(12), 1980–1988 (2019).CAS 
Article 

Google Scholar 
35.Parra-Henao, G., Angulo, V. M., Osorio, L. & Jaramillo, O. N. Geographic distribution and ecology of Triatoma dimidiata (Hemiptera: Reduviidae) in Colombia. J. Med. Entomol. 53(1), 122–129. https://doi.org/10.1093/jme/tjv163 (2016) (PMID: 26487247).Article 
PubMed 

Google Scholar 
36.Angulo, V. M., Esteban, L. & Luna, K. P. Attalea butyracea proximas a las viviendas como posible fuente de infestacion domiciliaria por Rhodnius prolixus (Hemiptera: Reduviidae) en los Llanos Orientales de Colombia. Biomedica. 32(2), 277–285. https://doi.org/10.1590/S0120-41572012000300016 (2012) (PMID: 23242302).Article 
PubMed 

Google Scholar 
37.Feliciangeli, M. D., Sanchez-Martin, M., Marrero, R., Davies, C. & Dujardin, J. P. Morphometric evidence for a possible role of Rhodnius prolixus from palm trees in house re-infestation in the State of Barinas (Venezuela). Acta Trop. 101(2), 169–177. https://doi.org/10.1016/j.actatropica.2006.12.010 (2007) (PMID: 17306204).Article 
PubMed 

Google Scholar 
38.Fitzpatrick, S., Feliciangeli, M. D., Sanchez-Martin, M. J., Monteiro, F. A. & Miles, M. A. Molecular genetics reveal that silvatic Rhodnius prolixus do colonise rural houses. PLoS Negl. Trop. Dis. 2(4), e210. https://doi.org/10.1371/journal.pntd.0000210 (2008) (PMID: 18382605).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
39.Lopez, G. & Moreno, J. Genetic variability and differentiation between populations of Rhodnius prolixus and R. pallescens, vectors of Chagas’ disease in Colombia. Mem. Inst. Oswaldo Cruz. 90, 353–357 (1995).CAS 
Article 

Google Scholar 
40.Dumonteil, E. et al. Detailed ecological associations of triatomines revealed by metabarcoding based on next-generation sequencing: linking triatomine behavioral ecology and Trypanosoma cruzi transmission cycles. Sci. Rep. 8(1), 4140. https://doi.org/10.1038/s41598-018-22455-x (2018).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
41.Hernández-Andrade, A., Moo-Millan, J., Cigarroa-Toledo, N., Ramos-Ligonio, A., Herrera, C., Bucheton, B., et al. Metabarcoding: A powerful yet still underestimated approach for the comprehensive study of vector-borne pathogen transmission cycles and their dynamics. in Vector-Borne Diseases: Recent Developments in Epidemiology and Control (ed. Claborn, D.) 1–6. (Intechopen, 2020). https://doi.org/10.5772/intechopen.8311042.Flores-Ferrer, A., Waleckx, E., Rascalou, G., Dumonteil, E. & Gourbière, S. Trypanosoma cruzi transmission dynamics in a synanthropic and domesticated host community. PLoS Negl. Trop. Dis. 13(12), e0007902. https://doi.org/10.1371/journal.pntd.0007902 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
43.Llewellyn, M. S. et al. Genome-scale multilocus microsatellite typing of Trypanosoma cruzi discrete typing unit I reveals phylogeographic structure and specific genotypes linked to human infection. PLoS Pathog. 5(5), e1000410. https://doi.org/10.1371/journal.ppat.1000410 (2009) (PMID: 19412340).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
44.Herrera, C. et al. Genetic variability and phylogenetic relationships within Trypanosoma cruzi I isolated in Colombia based on Miniexon Gene Sequences. J. Parasitol. Res. https://doi.org/10.1155/2009/897364 (2009) (PMID: 20798881).Article 
PubMed 

Google Scholar 
45.Zumaya-Estrada, F. A. et al. North American import? Charting the origins of an enigmatic Trypanosoma cruzi domestic genotype. Parasit. Vectors. 5, 226. https://doi.org/10.1186/1756-3305-5-226 (2012) (PMID: 23050833).Article 
PubMed 
PubMed Central 

Google Scholar 
46.Montoya-Porras, L. M., Omar, T. C., Alzate, J. F., Moreno-Herrera, C. X. & Cadavid-Restrepo, G. E. 16S rRNA gene amplicon sequencing reveals dominance of Actinobacteria in Rhodnius pallescens compared to Triatoma maculata midgut microbiota in natural populations of vector insects from Colombia. Acta Trop. 178, 327–332. https://doi.org/10.1016/j.actatropica.2017.11.004 (2018) (PMID: 29154947).CAS 
Article 
PubMed 

Google Scholar 
47.Kieran, T. J. et al. Regional biogeography of microbiota composition in the Chagas disease vector Rhodnius pallescens. Parasit. Vectors. 12(1), 504. https://doi.org/10.1186/s13071-019-3761-8 (2019) (PMID: 31665056).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
48.Rodriguez-Ruano, S. M. et al. Microbiomes of North American Triatominae: The grounds for Chagas Disease epidemiology. Front. Microbiol. 9, 1167. https://doi.org/10.3389/fmicb.2018.01167 (2018) (PMID: 29951039).Article 
PubMed 
PubMed Central 

Google Scholar 
49.Eichler, S. & Schaub, G. A. Development of symbionts in triatomine bugs and the effects of infections with trypanosomatids. Exp. Parasitol. 100(1), 17–27 (2002).CAS 
Article 

Google Scholar 
50.Waltmann, A. et al. Hindgut microbiota in laboratory-reared and wild Triatoma infestans. PLoS Negl. Trop. Dis. 13(5), e0007383. https://doi.org/10.1371/journal.pntd.0007383 (2019) (PMID: 31059501).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
51.Herren, J. K. et al. A microsporidian impairs Plasmodium falciparum transmission in Anopheles arabiensis mosquitoes. Nat. Commun. 11(1), 2187. https://doi.org/10.1038/s41467-020-16121-y (2020) (PMID: 32366903).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
52.Moreira, L. A. et al. A Wolbachia symbiont in Aedes aegypti limits infection with dengue, Chikungunya, and Plasmodium. Cell 139(7), 1268–1278. https://doi.org/10.1016/j.cell.2009.11.042 (2009) (PMID: 20064373).Article 
PubMed 

Google Scholar 
53.Angulo, V. M. & Esteban, L. Nueva trampa para la captura de triatominos en habitats silvestres y peridomesticos. Biomedica. 31(2), 264–268. https://doi.org/10.1590/S0120-41572011000200015 (2011) (PMID: 22159544).Article 
PubMed 

Google Scholar 
54.Lent, H. & Wygodzinsky, P. Revision of Triatominae (Hemiptera: Reduviidae), and their significance as vectors of Chagas’ disease. Bull. Am. Mus. Nat. His. 163, 123–520 (1979).
Google Scholar 
55.Monteiro, F. A. et al. Molecular phylogeography of the Amazonian Chagas disease vectors Rhodnius prolixus and R. robustus. Mol. Ecol. 12(4), 997–1006. https://doi.org/10.1046/j.1365-294x.2003.01802.x (2003) (PMID: 12753218).CAS 
Article 
PubMed 

Google Scholar 
56.Baker, G. C., Smith, J. J. & Cowan, D. A. Review and reanalysis of domain-specific 16s primers. J. Microbiol. Meth. 55, 541–555 (2003).CAS 
Article 

Google Scholar 
57.Heuer, H., Krsek, M., Baker, P., Smalla, K. & Wellington, E. M. Analysis of actinomycete communities by specific amplification of genes encoding 16S rRNA and gel-electrophoretic separation in denaturing gradients. Appl. Environ. Microbiol. 63(8), 3233–3241 (1997).CAS 
Article 

Google Scholar 
58.Souto, R. P., Fernandes, O., Macedo, A. M., Campbell, D. A. & Zingales, B. DNA markers define two major phylogenetic lineages of Trypanosoma cruzi. Mol. Biochem. Parasitol. 83(2), 141–152 (1996) (PMID: 9027747).CAS 
Article 

Google Scholar 
59.Majeau, A., Herrera, C. & Dumonteil, E. An improved approach to Trypanosoma cruzi molecular genotyping by next-generation sequencing of the mini-exon gene. Methods Mol. Biol. 1955, 47–60 (2019).CAS 
Article 

Google Scholar 
60.Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27(16), 2194–2200. https://doi.org/10.1093/bioinformatics/btr381 (2011) (PMID: 21700674).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
61.Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. arXiv preprint. (arXiv:1207.3907 [q-bio.GN]), 1–9. https://arxiv.org/abs/1207.3907v2 (2012).62.Dhariwal, A. et al. MicrobiomeAnalyst: A web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Res. 45(W1), W180–W188. https://doi.org/10.1093/nar/gkx295 (2017) (PMID: 28449106).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
63.Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2—Approximately maximum-likelihood trees for large alignments. PLoS ONE 5(3), e9490. https://doi.org/10.1371/journal.pone.0009490 (2010) (PMID: 20224823).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
64.Bouckaert, R. et al. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLoS Comput Biol. 15(4), e1006650. https://doi.org/10.1371/journal.pcbi.1006650 (2019) (PMID: 30958812).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
65.Torres-Silva, C. F. et al. Assessment of genetic mutation frequency induced by oxidative stress in Trypanosoma cruzi. Genet Mol Biol. 41(2), 466–474. https://doi.org/10.1590/1678-4685-GMB-2017-0281 (2018) (PMID: 30088612).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
66.Hammer, Ø., Harper, D. A. T. & Ryan, P. D. PAST: Paleontological statistics software package for education and data analysis. Palaeontol. Electron. 4(1), 9 (2001).
Google Scholar 
67.Cole, J. R. et al. Ribosomal Database Project: Data and tools for high throughput rRNA analysis. Nucleic Acids Res. 42(Database issue), D633–D642. https://doi.org/10.1093/nar/gkt1244 (2014) (PMID: 24288368).CAS 
Article 
PubMed 

Google Scholar  More

Mapping kelp persistenceThe study area for this analysis encompasses the region where Macrocystis pyrifera is the dominant canopy kelp species in the Northeast Pacific Ocean. The region extends from Año Nuevo Island in the north (latitude ~37.1°), California, USA, to Punta Prieta in the south (latitude ~27°), Baja California Sur, Mexico. We mapped the distribution of giant kelp canopy and characterized persistence using a 30-m resolution satellite-based time series covering our entire study area27. These data provide quarterly estimates of kelp canopy area across the study region from 1984 to 2018. We estimated giant kelp canopy from three Landsat sensors: Landsat 5 Thematic Mapper (1984–2011), Landsat 7 Enhanced Thematic Mapper+ (1999–present), and Landsat 8 Operational Land Imager (2013–present). We downloaded all imagery as atmospherically corrected Landsat Collection 1 Level-2 products. Each Landsat sensor has a pixel resolution of 30 × 30 m and a repeat time of 16 days (8 days when two Landsat sensors were operational). Since Landsat imagery can be obscured by cloud cover, we obtained a clear estimate of kelp areas ~16 times per year from 1984 to 2018 (mean = 16.2, std = 4.1). The repeated observations across the time series avoid missing kelp canopy due to physical processes such as tides and currents. Multiple Landsat passes over seasonal timescales are successful at mitigating the effect of tide and tidal currents on Landsat kelp canopy detection27.While the pixel resolution of Landsat sensors is 30 × 30 m, we were able to observe the presence and density of kelp canopy on subpixel scales using a fully automation procedure. We first masked all land areas using a global 30 m resolution digital elevation model (asterweb.jpl.nasa. gov/gdem.asp) and classified the remaining pixels as seawater, cloud, or kelp canopy using a binary decision tree classifier trained on a diverse array of pixels within the study region27. We then used Multiple Endmember Spectral Mixture Analysis39 to model each pixel as the linear combination of seawater and kelp canopy. This method can accurately obtain kelp canopy presence as long as kelp canopy covers ~13% of a 30 m pixel. These methods were validated using 15 years of monthly kelp canopy surveys by the Santa Barbara Coastal Long Term Ecological Research project at two sites in Southern California. We filtered errors of commission (such as free-floating kelp paddies) by removing any pixels classified as kelp canopy in More

1.Zalasiewicz, J., Williams, M., Haywood, A. & Ellis, M. The Anthropocene: a new epoch of geological time? Phil. Trans. A Math. Phys. Eng. Sci. 369, 835–841 (2011).
Google Scholar 
2.Ellis, E., Maslin, M. A., Boivin, N. & Bauer, A. Involve social scientists in defining the Anthropocene. Nature 540, 192–193 (2016).Article 

Google Scholar 
3.Ruddiman, W. F. The Anthropogenic greenhouse era began thousands of years ago. Clim. Change 61, 261–293 (2003).CAS 
Article 

Google Scholar 
4.Crutzen, P. J. Geology of mankind. Nature 415, 23 (2002).CAS 
PubMed 
Article 

Google Scholar 
5.Gallery, R. E. in Ecology and the Environment (ed. Monson, R. K.) 247–272 (Springer, 2014).6.Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).CAS 
PubMed 
Article 

Google Scholar 
7.Dinerstein, E. et al. An ecoregion-based approach to protecting half the terrestrial realm. BioScience 67, 534–545 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
8.Malhi, Y., Gardner, T. A., Goldsmith, G. R., Silman, M. R. & Zelazowski, P. Tropical forests in the Anthropocene. Annu. Rev. Environ. Resour. 39, 125–159 (2014).Article 

Google Scholar 
9.Staal, A. et al. Hysteresis of tropical forests in the 21st century. Nat. Commun. 11, 4978 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
10.Lenton, T. M. et al. Climate tipping points—too risky to bet against. Nature 575, 592–595 (2019).CAS 
PubMed 
Article 

Google Scholar 
11.Zalasiewicz, J. et al. The Working Group on the Anthropocene: summary of evidence and interim recommendations. Anthropocene 19, 55–60 (2017).Article 

Google Scholar 
12.Syvitski, J. et al. Extraordinary human energy consumption and resultant geological impacts beginning around 1950 CE initiated the proposed Anthropocene Epoch. Commun. Earth Environ. https://doi.org/10.1038/s43247-020-00029-y (2020).13.Ruddiman, W. F. Three flaws in defining a formal ‘Anthropocene’. Prog. Phys. Geogr. Earth Environ. https://doi.org/10.1177/0309133318783142 (2018).14.Smith, B. D. & Zeder, M. A. The onset of the Anthropocene. Anthropocene 4, 8–13 (2013).Article 

Google Scholar 
15.Roberts, P., Boivin, N. & Kaplan, J. O. Finding the Anthropocene in tropical forests. Anthropocene 23, 5–16 (2018).Article 

Google Scholar 
16.Boivin, N. L. et al. Ecological consequences of human niche construction: examining long-term anthropogenic shaping of global species distributions. Proc. Natl Acad. Sci. USA 113, 6388–6396 (2016).CAS 
PubMed 
Article 

Google Scholar 
17.Stephens, L. et al. Archaeological assessment reveals Earth’s early transformation through land use. Science 365, 897–902 (2019).CAS 
PubMed 
Article 

Google Scholar 
18.Crosby, A. W. The Columbian Exchange: Biological and Cultural Consequences of 1492 (Greenwood Publishing Group, 1972).19.Lewis, S. L. & Maslin, M. A. Defining the anthropocene. Nature 519, 171–180 (2015).CAS 
PubMed 
Article 

Google Scholar 
20.Denevan, W. M. Estimating the Aboriginal population of Latin America in 1492: methodological synthesis. Publ. Ser. Conf. Lat. Am. Geogr. 5, 125–132 (1976).
Google Scholar 
21.Koch, A., Brierley, C., Maslin, M. M. & Lewis, S. L. Earth system impacts of the European arrival and Great Dying in the Americas after 1492. Quat. Sci. Rev. 207, 13–36 (2019).Article 

Google Scholar 
22.Denevan, W. M. The Native Population of the Americas in 1492 (Univ. Wisconsin Press, 1992).23.Denevan, W. M. After 1492: nature rebounds. Geogr. Rev. 106, 381–398 (2016).Article 

Google Scholar 
24.Iriarte, J. et al. Fire-free land use in pre-1492 Amazonian savannas. Proc. Natl Acad. Sci. USA 109, 6473–6478 (2012).CAS 
PubMed 
Article 

Google Scholar 
25.Nevle, R. J., Bird, D. K., Ruddiman, W. F. & Dull, R. A. Neotropical human–landscape interactions, fire, and atmospheric CO2 during European conquest. Holocene 21, 853–864 (2011).Article 

Google Scholar 
26.Power, M. J. et al. Climatic control of the biomass-burning decline in the Americas after ad 1500. Holocene 23, 3–13 (2013).Article 

Google Scholar 
27.Mann, C. C. Uncovering the New World Columbus Created (Knopf Publishing Group, 2011).28.Hung, H.-C. et al. Ancient jades map 3,000 years of prehistoric exchange in Southeast Asia. Proc. Natl Acad. Sci. USA 104, 19745–19750 (2007).CAS 
PubMed 
Article 

Google Scholar 
29.Newson, L. A. Conquest and Pestilence in the Early Spanish Philippines (Univ. Hawaii Press, 2009).30.Amano, N., Bankoff, G., Findley, D. M., Barretto-Tesoro, G. & Roberts, P. Archaeological and historical insights into the ecological impacts of pre-colonial and colonial introductions into the Philippine Archipelago. Holocene 31, 313–330 (2021).Article 

Google Scholar 
31.Acabado, S. B. in Irrigated Taro (Colocasia esculenta) in the Indo-Pacific (Senri Ethnological Studies 78) (eds Spriggs, M. et al.) 285–305 (National Museum of Ethnology, 2012).32.Junker, L. L. Raiding, Trading, and Feasting: The Political Economy of Philippine Chiefdoms (Ateneo de Manila Univ. Press, 2000).33.Amano, N., Piper, P. J., Hung, H.-C. & Bellwood, P. Introduced domestic animals in the Neolithic and Metal Age of the Philippines: evidence from Nagsabaran, Northern Luzon. J. Isl. Coast. Archaeol. 8, 317–335 (2013).Article 

Google Scholar 
34.Williams, J. W. et al. The Neotoma Paleoecology Database, a multiproxy, international, community-curated data resource. Quat. Res. 89, 156–177 (2018).Article 

Google Scholar 
35.Boivin, N. & Crowther, A. Mobilizing the past to shape a better Anthropocene. Nat. Ecol. Evol. 5, 273–284 (2021).PubMed 
Article 

Google Scholar 
36.Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth: a new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. BioScience 51, 933–938 (2001).Article 

Google Scholar 
37.Berrio, J. C., Hooghiemstra, H., Behling, H., Botero, P. & Van der Borg, K. Late-Quaternary savanna history of the Colombian Llanos Orientales from Lagunas Chenevo and Mozambique: a transect synthesis. Holocene 12, 35–48 (2002).
Google Scholar 
38.Berrío, J. C., Hooghiemstra, H., Marchant, R. & Rangel, O. Late-glacial and Holocene history of the dry forest area in the south Colombian Cauca Valley. J. Quat. Sci. 17, 667–682 (2002).Article 

Google Scholar 
39.Mayle, F. E., Burbridge, R. & Killeen, T. J. Millennial-scale dynamics of southern Amazonian rain forests. Science 290, 2291–2294 (2000).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
40.Flantua, S. G. A. et al. Climate variability and human impact in South America during the last 2000 years: synthesis and perspectives from pollen records. Climate 12, 483–523 (2016).
Google Scholar 
41.Polissar, P. J. et al. Solar modulation of Little Ice Age climate in the tropical Andes. Proc. Natl Acad. Sci. USA 103, 8937–8942 (2006).CAS 
PubMed 
Article 

Google Scholar 
42.Maezumi, S. Y. et al. The legacy of 4,500 years of polyculture agroforestry in the eastern Amazon. Nat. Plants 4, 540–547 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
43.Leyden, B. W. et al. in The Managed Mosaic: Ancient Maya Agriculture and Resource Use (ed. Fedick, S. L.) (Univ. Utah Press, 1996).44.Dodson, J. R. & Intoh, M. Prehistory and palaeoecology of Yap, Federated States of Micronesia. Quat. Int. 59, 17–26 (1999).Article 

Google Scholar 
45.Athens, J. S. & Ward, J. V. Holocene vegetation, savanna origins and human settlement of Guam. Rec. Aust. Mus. Suppl. 29, 15–30 (2004).Article 

Google Scholar 
46.Levin, M. J. & Ayres, W. S. Managed agroforests, swiddening, and the introduction of pigs in Pohnpei, Micronesia: phytolith evidence from an anthropogenic landscape. Quat. Int. 434, 70–77 (2017).Article 

Google Scholar 
47.Chen, S.-H. et al. Late Holocene paleoenvironmental changes in subtropical Taiwan inferred from pollen and diatoms in lake sediments. J. Paleolimnol. 41, 315–327 (2009).Article 

Google Scholar 
48.Stevenson, J., Siringan, F., Finn, J. A. N., Madulid, D. & Heijnis, H. Paoay Lake, northern Luzon, the Philippines: a record of Holocene environmental change. Glob. Change Biol. 16, 1672–1688 (2010).Article 

Google Scholar 
49.Wigboldus, J. S. A History of the Minahasa c. 1615–1680. Archipel 34, 63–101 (1987).Article 

Google Scholar 
50.United States Office of the Chief of Naval Operations. West Caroline Islands (Office of the Chief of Naval Operations, Navy Department, 1943).51.De Souza, J. G. et al. Climate change and cultural resilience in late pre-Columbian Amazonia. Nat. Ecol. Evol. 3, 1007–1017 (2019).PubMed 
Article 

Google Scholar 
52.Leal, C. Landscapes of Freedom: Building a Postemancipation Society in the Rainforests of Western Colombia (Univ. Arizona Press, 2018).53.Block, D. Mission Culture on the Upper Amazon: Native Tradition, Jesuit Enterprise & Secular Policy in Moxos, 1660–1880 (Univ. Nebraska Press, 1994).54.Callaghan, R. & Fitzpatrick, S. M. On the relative isolation of a Micronesian archipelago during the historic period: the Palau case-study. Int. J. Nautical Archaeol. 36, 353–364 (2007).Article 

Google Scholar 
55.Da Silva, C. M. The miracle of the Brazilian Cerrados as a juggernaut: soil, science, and national culture. Hispanic Issues Ser. 24, 98–116 (2019).
Google Scholar 
56.Goldberg, W. M. The Geography, Nature and History of the Tropical Pacific and Its Islands (Springer, 2017).57.Schwaller, R. C. Contested conquests: African maroons and the incomplete conquest of Hispaniola, 1519–1620. Americas 75, 609–638 (2018).Article 

Google Scholar 
58.Acabado, S. B. et al. The short history of the Ifugao rice terraces: a local response to the Spanish conquest. J. Field Archaeol. 44, 195–214 (2019).Article 

Google Scholar 
59.Iriarte, J. et al. The origins of Amazonian landscapes: plant cultivation, domestication and the spread of food production in tropical South America. Quat. Sci. Rev. 248, 106582 (2020).Article 

Google Scholar 
60.Staver, A. C., Archibald, S. & Levin, S. A. The global extent and determinants of savanna and forest as alternative biome states. Science 334, 230–232 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
61.Graham, N. R., Gruner, D. S., Lim, J. Y. & Gillespie, R. G. Island ecology and evolution: challenges in the Anthropocene. Environ. Conserv. 44, 323–335 (2017).Article 

Google Scholar 
62.Roos, C. I. Scale in the study of Indigenous burning. Nat. Sustain. 3, 898–899 (2020).Article 

Google Scholar 
63.Lu, Z., Liu, Z., Zhu, J. & Cobb, K. M. A review of paleo El Niño-Southern Oscillation. Atmosphere https://doi.org/10.3390/atmos9040130 (2018).64.Shi, F., Li, J. & Wilson, R. J. A tree-ring reconstruction of the South Asian summer monsoon index over the past millennium. Sci. Rep. 4, 6739 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
65.Newton, A., Thunell, R. & Stott, L. Climate and hydrographic variability in the Indo-Pacific Warm Pool during the last millennium. Geophys. Res. Lett. https://doi.org/10.1029/2006gl027234 (2006).66.Chepstow-Lusty, A. & Winfield, M. Inca agroforestry: lessons from the past. Ambio 29, 322–328 (2000).Article 

Google Scholar 
67.Nunn, P. Environmental catastrophe in the Pacific Islands around A.D. 1300. Geoarchaeology 15, 715–740 (2000).Article 

Google Scholar 
68.Robinson, M. et al. Uncoupling human and climate drivers of late Holocene vegetation change in southern Brazil. Sci. Rep. 8, 7800 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
69.Green, W. A. The New World and the rise of European capitalist hegemony: some historiographical perspectives. Itinerario 10, 53–68 (1986).Article 

Google Scholar 
70.Wolf, E. R. Europe and the People Without History (Univ. California Press, 2010).71.Castilla-Beltrán, A. et al. Columbus’ footprint in Hispaniola: a paleoenvironmental record of indigenous and colonial impacts on the landscape of the central Cibao Valley, northern Dominican Republic. Anthropocene 22, 66–80 (2018).Article 

Google Scholar 
72.Goman, M. & Byrne, R.A 5000-year record of agriculture and tropical forest clearance in the Tuxtlas, Veracruz, Mexico. Holocene 8, 83–89 (1998).Article 

Google Scholar 
73.Francis, X. & Hezel, S. J. Disease in Micronesia: a historical survey. Pac. Health Dialogue 16, 11–25 (2010).
Google Scholar 
74.Jones, J. G. Pollen Evidence of Prehistoric Forest Modification and Maya Cultivation in Belize. PhD thesis, Texas A&M Univ. (1991).75.Rojas, M., Arias, P. A., Flores-Aqueveque, V., Seth, A. & Vuille, M. The South American monsoon variability over the last millennium in climate models. Climate 12, 1681–1691 (2016).
Google Scholar 
76.Rosenthal, Y., Linsley, B. K. & Oppo, D. W.Pacific ocean heat content during the past 10,000 years. Science 342, 617–621 (2013).CAS 
PubMed 
Article 

Google Scholar 
77.Blois, J. L., Williams, J. W., Grimm, E. C., Jackson, S. T. & Graham, R. W. A methodological framework for assessing and reducing temporal uncertainty in paleovegetation mapping from late-Quaternary pollen records. Quat. Sci. Rev. 30, 1926–1939 (2011).Article 

Google Scholar 
78.Flantua, S. G. A., Blaauw, M. & Hooghiemstra, H. Geochronological database and classification system for age uncertainties in Neotropical pollen records. Climate 12, 387–414 (2016).
Google Scholar 
79.Marchant, R. et al. Pollen-based biome reconstructions for Latin America at 0, 6000 and 18 000 radiocarbon years ago. Climate 5, 725–767 (2009).
Google Scholar 
80.Juggins, S. rioja: Analysis of Quaternary Science Data. R package version 0.9-21. https://cran.r-project.org/package=rioja (2014)..81.R Core Development Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013).82.Hamilton, R., Penny, D. & Hall, T. L. Forest, fire & monsoon: investigating the long-term threshold dynamics of south-east Asia’s seasonally dry tropical forests. Quat. Sci. Rev. https://doi.org/10.1016/j.quascirev.2020.106334 (2020).83.Bhagwat, S. A., Nogué, S. & Willis, K. J. Resilience of an ancient tropical forest landscape to 7500 years of environmental change. Biol. Conserv. 153, 108–117 (2012).Article 

Google Scholar 
84.Blarquez, O. et al. paleofire: an R package to analyse sedimentary charcoal records from the Global Charcoal Database to reconstruct past biomass burning. Comput. Geosci. 72, 255–261 (2014).Article 

Google Scholar 
85.Rohatgi, A. WebPlotDigitizer v4.2 https://automeris.io/WebPlotDigitizer (2019).86.Blaauw, M. & Christen, J. A.Flexible paleoclimate age–depth models using an autoregressive gamma process. Bayesian Anal. 6, 457–474 (2011).Article 

Google Scholar 
87.Plumpton, H., Whitney, B. & Mayle, F. Ecosystem turnover in palaeoecological records: the sensitivity of pollen and phytolith proxies to detecting vegetation change in southwestern Amazonia. Holocene 29, 1720–1730 (2019).Article 

Google Scholar 
88.Simpson, G. L. Modelling palaeoecological time series using generalised additive models. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2018.00149 (2018).89.Wood, S. N. Thin plate regression splines. J. R. Stat. Soc. Ser. B Stat. Methodol. 65, 95–114 (2003).Article 

Google Scholar 
90.Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. Ser. B Stat. Methodol. 73, 3–36 (2011).Article 

Google Scholar 
91.Dowle, M. et al. data.table: Extension of ‘data.frame’. R package version 0.9-21. https://cran.r-project.org/web/packages/data.table (2018).92.Wickham, H. & Bryan, J. readxl: Read Excel Files. R package version 1.3.1. https://CRAN.R-project.org/package=readxl (2019).93.Doeppers, D. F. The development of Philippine cities before 1900. J. Asian Stud. 31, 769–792 (1972).Article 

Google Scholar 
94.Dobyns, H. F. Disease transfer at contact. Annu. Rev. Anthropol. 22, 273–291 (1993).Article 

Google Scholar 
95.Watts, W. A. & Bradbury, J. P. Paleoecological studies at Lake Patzcuaro on the west-central Mexican Plateau and at Chalco in the Basin of Mexico. Quat. Res. 17, 56–70 (1982).Article 

Google Scholar 
96.Van Hengstum, P. J. et al. The intertropical convergence zone modulates intense hurricane strikes on the western North Atlantic margin. Sci. Rep. 6, 21728 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
97.Crausbay, S. D., Martin, P. H., Kelly, E. F. & McGlone, M. Tropical montane vegetation dynamics near the upper cloud belt strongly associated with a shifting ITCZ and fire. J. Ecol. 103, 891–903 (2015).Article 

Google Scholar 
98.Kelly, T. J. et al. The vegetation history of an Amazonian domed peatland. Palaeogeogr. Palaeoclimatol. Palaeoecol. 468, 129–141 (2017).Article 

Google Scholar 
99.Carson, J. F. et al. Environmental impact of geometric earthwork construction in pre-Columbian Amazonia. Proc. Natl Acad. Sci. USA 111, 10497–10502 (2014).CAS 
PubMed 
Article 

Google Scholar 
100.Berrio, J. C., Hooghiemstra, H., Behling, H. & van der Borg, K. Late Holocene history of savanna gallery forest from Carimagua area, Colombia. Rev. Palaeobot. Palynol. 111, 295–308 (2000).CAS 
PubMed 
Article 

Google Scholar 
101.Ledru, M.-P. Late quaternary environmental and climatic changes in central Brazil. Quat. Res. 39, 90–98 (1993).Article 

Google Scholar 
102.Ledru, M.-P., Behling, H., Fournier, M., Martin, L. & Servant, M. Localisation de la forêt d’Araucaria du Brésil au cours de l’Holocène. Implications paléoclimatiques. C. R. Acad. Sci. Paris 317, 517–521 (1994).
Google Scholar 
103.Behling, H. A high resolution Holocene pollen record from Lago do Pires, SE Brazil: vegetation, climate and fire history. J. Paleolimnol. 14, 253–268 (1995).Article 

Google Scholar 
104.Behling, H. Late Quaternary vegetation, climate and fire history from the tropical mountain region of Morro de Itapeva, SE Brazil. Palaeogeogr. Palaeoclimatol. Palaeoecol. 129, 407–422 (1997).Article 

Google Scholar 
105.Behling, H., Hooghiemstra, H. & Negret, A. J. Holocene history of the Chocó rain forest from Laguna Piusbi, southern Pacific lowlands of Colombia. Quat. Res. 50, 300–308 (1998).Article 

Google Scholar 
106.Vélez, M. I. et al. Late Holocene environmental history of southern Chocó region, Pacific Colombia; sediment, diatom and pollen analysis of core El Caimito. Palaeogeogr. Palaoclimatol. Palaeoecol. 173, 197–214 (2001).Article 

Google Scholar 
107.Vélez, M. I., Berrío, J. C., Hooghiemstra, H., Metcalfe, S. & Marchant, R. Palaeoenvironmental changes during the last ca. 8590 calibrated yr (7800 radiocarbon yr) in the dry forest ecosystem of the Patía Valley, Southern Colombian Andes: a multiproxy approach. Palaeogeogr. Palaeoclimatol. Palaeoecol. 216, 279–302 (2005).Article 

Google Scholar 
108.Behling, H., Negret, A. J. & Hooghiemstra, H. Late Quaternary vegetational and climatic change in the Popayán region, southern Colombian Andes. J. Quat. Sci. 13, 43–53 (1998).Article 

Google Scholar 
109.Wille, M., Hooghiemstra, H., Behling, H., van der Borg, K. & Negret, A. J. Environmental change in the Colombian subandean forest belt from 8 pollen records: the last 50 kyr. Veg. Hist. Archaeobot. 10, 61–77 (2001).Article 

Google Scholar 
110.Epping, I. Environmental Change in the Colombian Upper Forest Belt. MSc thesis, Univ. Amsterdam (2009).111.Niemann, H. & Behling, H. Late Pleistocene and Holocene environmental change inferred from the Cocha Caranga sediment and soil records in the southeastern Ecuadorian Andes. Palaeogeogr. Palaeoclimatol. Palaeoecol. 276, 1–14 (2009).Article 

Google Scholar 
112.Graf, K. in Pollendiagramme aus den Anden, eine Synthese zur Klimageschichte und Vegetationsentwicklung Seit der letzten Eiszeit. Vol. 34 (Univ. Zurich, 1992).113.Kuhry, P., Salomons, J. B., Riezebos, P. A. & Van der Hammen, T. in Studies on Tropical Andean Ecosystems/Estudios de Ecosistemas Tropandinos: La Cordillera Central Colombiana Transecto Parque Los Nevados (eds van der Hammen, T. et al.) 227–261 (Cramer, 1983).114.Velásquez-R, C. A. & Hooghiemstra, H. Pollen-based 17-kyr forest dynamics and climate change from the Western Cordillera of Colombia; no-analogue associations and temporarily lost biomes. Rev. Palaeobot. Palynol. 194, 38–49 (2013).Article 

Google Scholar 
115.Rull, V., Salgado-Labouriau, M.-L., Schubert, C. & Valastro, S. Jr. Late Holocene temperature depression in the Venezuelan Andes: palynological evidence. Palaeogeogr. Palaeoclimatol. Palaeoecol. 60, 109–121 (1987).Article 

Google Scholar 
116.Van der Hammen, T. Palinología de la región de “Laguna de los Bobos”: historia de su clima, vegetación y agricultura durante los últimos 5.000 años. Revista de la Academia Colombiana de Ciencias Exactas. Físicas Nat. 11, 359–361 (1962).
Google Scholar 
117.Wang, L. C. et al. Late Holocene environmental reconstructions and their implications on flood events, typhoon, and agricultural activities in NE Taiwan. Climate 10, 1857–1869 (2014).CAS 

Google Scholar 
118.Dam, R. A. C., Fluin, J., Suparan, P. & van der Kaars, S. Palaeoenvironmental developments in the Lake Tondano area (N. Sulawesi, Indonesia) since 33,000 yr B.P. Palaeogeogr. Palaeoclimatol. Palaeoecol. 171, 147–183 (2001).Article 

Google Scholar 
119.Suparan, P., Dam, R. A. C., van der Kaars, S. & Wong, T. E. Late Quaternary tropical lowland environments on Halmahera, Indonesia. Palaeogeogr. Palaeoclimatol. Palaeoecol. 171, 229–258 (2001).Article 

Google Scholar 
120.Athens, J. S. & Ward, J. V. Holocene Paleoenvironmental Investigations on Ngerekebesang, Koror, South Babeldaob, and Peleliu Islands, Palau (International Archaeological Research Institute, 2002).121.Athens, J. S. & Ward, J. V. Palau Compact Road Archaeological Investigations, Babeldaob Island, Republic of Palau. Phase I: Intensive Archaeological Survey. Volume IV: Holocene Paleoenvironment and Landscape Change (International Archaeological Research Institute, 2005). More

ParticipantsThe sample consisted of 36 participants (Mage = 22.72, SDage = 1.91), which were recruited during the autumn semester at the Saint-Charles cafeteria of the University Paul Valery, France. All participants completed an informed consent form and reported being right-handed, had normal or corrected-to-normal visual acuity, and normal motricity. We chose a sample composed exclusively of women due to the existence of differences between men and women in the use of SR26. The aim was also to avoid a possible effect of sexism (e.g., men might not use the SR because it is a woman)27,28. The sample size was determined with G*Power29. A hypothesized effect size of − 0.43 was chosen, based on a previous study23; a corresponding power analysis (effect size r = − 0.43, α = 0.05, power = 0.80) resulted in an estimation of 32 participants. The final sample size (36) was chosen to meet methodological needs. The study was conducted according to the Declaration of Helsinki and were reviewed and approved by the Scientific and Ethics Committee of Epsylon Laboratory EA4556, University Paul Valéry of Montpellier.Materials and stimuliA schematic representation of the experimental design is presented in Fig. 1 left-hand side. Three, rectangular tables were placed some distance apart from each other. In the real action task, toilet tissue rolls (either 16 or 8) were positioned in rows on Table A, with each row containing four rolls (e.g., for eight rolls, there were two rows of four rolls). The aim was to use objects that can be grasped with hands and light enough to limit the impact of the weight. Participants were asked to move the rolls from Table A to Table B and to put them into containers disposed on Table B. There were two containers (height: 30 cm, width: 55 cm, depth: 35 cm) in order to avoid interference between the participant and the SR during the real action task. A beeper was placed on Table C. Participants had to press on this beeper to ask for help from the SR. For all participants, the SR was a 23-year-old woman student who sat on a chair 2 m from Table A. The distances AB and AC were 2 m and 3.5 m, respectively.Figure 1Schematic representation of the design used in Experiments 1 and 2.Full size imageThe decision task (Fig. 2) was computer-based, and developed with OpenSesame software30. Participants were seated at a table located 3 m from Table A, in front of a monitor and keyboard (screen size: 14-inch; distance participant-screen: 75 cm; distance participant-keyboard: 30 cm). Photographs showing a quantity of 4 (Q4), 8 (Q8), 12 (Q12), 16 (Q16), 20 (Q20), and 24 (Q24) rolls were displayed on the screen.Figure 2Experimental design for decision task in Experiment 1 and 2.Full size imagePersonality traits were assessed by a self-report questionnaire: the Big Five Inventory (BFI)31 translated and validated in a French population32. This questionnaire is based on the “Big Five”, the five dimensions consensual model of adult personality33. The Big Five dimensions are: Conscientiousness, Agreeableness, Neuroticism, Openness to experience, and Extraversion.ProcedureParticipants were informed that the experiment was composed of four phases. In the first phase they would be asked to fill out the BFI. In a second phase called the real action task, they would have to move different quantities of rolls with their hands, or with the help of a SR. In the third phase, the decision task, they could decide to use the SR or not depending on the actions performed in the second phase. Finally, they were told that in the last, fourth, phase they would be asked to move different quantities of rolls depending on the choices they had made in the decision task (third phase). Here, the aim was to raise the participant’s awareness of the impact and importance of the decision task, but this fourth phase was never actually done.After the BFI completion, participants began phase two. Here, they were asked to physically move rolls from Table A at normal speed (i.e., without any time constraint) and place them in the container on Table B. This scenario was designed to reflect a real action task of storing purchases after returning from the supermarket. The experimenter asked participants to perform four trials: two in the Hands condition (quantities 8 and 16), and two in the SR condition (quantities 8 and 16). In the Hands condition, participants had to move all the rolls from Table A to Table B and only two at a time. Once the task was completed, they had to return to Table A. In the SR condition, participants had to move all rolls with the help of the SR. Here, they had to move from Table A, go to Table C to press the beeper (which sounded instantly), then return to Table A and move rolls with their hands, two at a time, to the container on Table B. Simultaneously, the co-actor got up from her chair and went to Table A to help participants to move the rolls. The co-actor also moved two rolls at a time, in synchrony with participants. Thus, participants and the co-actor moved four rolls, at the same time, with their hands. When the task was completed, participants had to go back to Table A, then Table C, press the beeper a second time, and finally return to Table A. The variables Quantity of rolls (8 vs. 16) and Condition (Hands vs. SR) were counterbalanced between participants, leading to the four following orders: (1) Hands/Q8, SR/Q16, Hands/Q16, SR/Q8, (2) Hands/Q16, SR/Q8, Hands/Q8, SR/Q16, (3), SR/Q8, Hands/Q16, SR/Q16, Hands/Q8, (4) SR/Q16, Hands/Q8, SR/Q8, Hands/Q16.As mentioned above, decision task (third phase) was computer based. Each trial began with a white fixation cue presented in the center of a black screen displayed for 1500 ms. The fixation cue was immediately followed by a photograph showing a quantity of rolls (Q4 vs. Q8 vs. Q12 vs. Q16 vs. Q20 vs. Q24) displayed for 3000 ms on the screen. Participants had to evaluate 20 times each Quantity of Rolls (6 Quantity of Rolls × 20 Blocks), making a total of 120 photographs to be evaluated. They were asked to respond as rapidly as they could before the photograph disappeared from the screen. In case they did not respond to a trial in the allotted time, the trial was presented later in its corresponding block. Participants were asked to press the ‘a’ key with their left index finger, or the ‘p’ key with their right index finger if they considered being faster to move the rolls with the SR or by hands. The response assigned to each key was counterbalanced across participants and the quantity of rolls was fully randomized. Response times and decisions were collected for each of the 120 photographs. Participants were informed that after the decision task, the software would randomly choose 12 photographs, and in a second real action task (i.e., fourth phase), they would have to move these quantities of rolls depending on the choices they had previously made. Moreover, they were informed that the SR was at their complete disposal and they were invited to choose its use according to their own estimate. In fact, once the decision task was over, they were informed that they would not have to complete the fourth phase. Upon recruitment, they were told that the experiment would take 40 min (i.e., enough time to also complete the fourth phase). However, the actual duration of the experiment was 30 min (the time to complete the BFI, the real action task and the decision task).ResultsRaw responses were converted to a binary response, based on the participant’s choice (0 for Hands, 1 for SR). These data were then fitted locally using the ModelFree software package34, giving a point of subjective equality (PSE-SR) for each participant. Specifically, the PSE-SR indicates the quantity of rolls for which the participant considered the use of their hands, or the SR as equivalent. After a visual inspection of the psychometric curve, data of four participants were excluded from the analysis because these participants had particularly flat curve (i.e., slope = 0). Then, we used the Shapiro test to test the normality of distributions of all dependent variables. PSE-SR, Neuroticism, Openness to experience, Conscientiousness, and Extraversion were identified to be normally distributed (all W [0.940, 0.979], and p [0.070, 0.78]), while Agreeableness was not (W = 0.933, p = 0.048). Hence, the use of parametric statistical tests was proscribed, and the analysis of the correlation matrix was performed with the Spearman non-parametric method.Correlations matrix between the five personality factors, and the PSE-SR score are given in Table 1, which highlights a correlation between Extraversion and PSE-SR (Fig. 3). Data were also examined by estimating Bayes factors comparing fit under the null hypothesis (PSE-SR is not a function of personality trait), and the alternative hypothesis (PSE-SR is a function of personality trait). Bayes factors were, respectively, BF01 = 3.481 for Neuroticism, and BF01 = 3.728 for Conscientiousness. These results confirm the null hypothesis, as Bayes factors are above three35. Bayes factors were, respectively, BF01 = 1.550 for Openness to experience, and BF01 = 1.117 for Agreeableness. As these results do not support either the null nor the alternative hypothesis, a multiple regression was conducted to test whether Extraversion, Agreeableness, and Openness to experience predicted PSE-SR.Table 1 Spearman correlation coefficients for PSE-SR and personality factors, and among personality factors for Experiment 1.Full size tableFigure 3Correlation between Extraversion and PSE-SR found in Experiment 1.Full size imageThe multiple regression showed that these three factors explain a significant amount of variance in the value of PSE-SR, F(3,31) = 5.087, p = 0.006, R2Adjusted = 0.283. Specifically, Agreeableness (β =  − 0.141, t =  − 0.882, p = 0.385, 95% CI = [− 0.258, 0.103]), and Openness to experience (β =  − 0.159, t =  − 1.023, p = 0.314, 95% CI = [− 0.237, 0.079]) did not significantly predict the value of PSE-SR. However, Extraversion did (β =  − 0.480, t =  − 2.958, p = 0.006, 95% CI = [− 0.402, − 0.073]).DiscussionThe key finding of Experiment 1 is the significant negative linear relationship between Extraversion and PSE-SR. This result supports our hypothesis, and shows that participants’ Extraversion level predicts the use of the SR. The more participants are extraverted, the more they perceive the SR as a benefit. This is consistent with the work of Amirkhan et al.23, which shows that extraverts seek help much more quickly than introverts. They also extend the results obtained by Schnall et al.13 and Doerffeld et al.12, namely that there are individual differences in how the benefits of a SR are perceived: the more participants are extraverted, the more they tend to incorporate SR as a benefit into their economy of action. However, a new question arises: does Extraversion only influence how people perceive the benefits of SR, or does it extend to other external resources? To investigate this question, we replicated the second experiment reported in Osiurak et al.25 (i.e. we replaced the SR with a tool) and added the BFI. More

1.Holway, D. A., Lach, L., Suarez, A. V., Tsutsui, N. D. & Case, T. J. The cause and consequences of ant invasions. Annu. Rev. Ecol. Systemat. 33, 181–233 (2002).Article 

Google Scholar 
2.Moller, H. Lessons for invasion theory from social insects. Biol. Conserv. 78, 125–142 (1996).Article 

Google Scholar 
3.Hoffmann, B. D. & Saul, W. C. Yellow crazy ant (Anoplolepis gracilipes) invasions within undisturbed mainland Australian habitats: no support for biotic resistance hypothesis. Biol. Invasions 12, 3093–3108 (2010).Article 

Google Scholar 
4.Human, K. G. & Gordon, D. M. Exploitation and interference competition between the invasive Argentine ant, Linepithema humile, and native ant species. Oecologia 105, 405–412 (1996).ADS 
PubMed 
Article 

Google Scholar 
5.Walker, K. L. Impact of the little fire ant, Wasmannia auropunctata, on native forest ants in Gabon. Biotropica 38, 666–673 (2006).Article 

Google Scholar 
6.Cole, F. R., Medeiros, A. C., Loope, L. L. & Zuehlke, W. W. Effects of the Argentine ant on arthropod fauna of Hawaiian high-elevation shrubland. Ecology 73, 1313–1322 (1992).Article 

Google Scholar 
7.Porter, S. D. & Savignano, D. A. Invasion of polygyne fire ants decimates native ants and disrupts arthropod community. Ecology 71, 2095–2106 (1990).Article 

Google Scholar 
8.Feare, C. Ants take over from rats on Bird Island, Seychelles. Bird Conserv. Int. 9, 95–96 (1999).Article 

Google Scholar 
9.Laakkonen, J., Fisher, R. N. & Case, T. J. Effect of land cover, habitat fragmentation, and ant colonies on the distribution and abundance of shrews in southern California. J. Anim. Ecol. 70, 776–788 (2001).Article 

Google Scholar 
10.Wojcik, D. P. et al. Red imported fire ants: impact on biodiversity. Am. Entomol. 47, 16–23 (2001).Article 

Google Scholar 
11.O’Dowd, D. J., Green, P. T. & Lake, P. S. Invasional ‘meltdown’ on an oceanic island. Ecol. Lett. 6, 812–817 (2003).Article 

Google Scholar 
12.Ness, J. H. & Bronstein, J. L. The effects of invasive ants on prospective ant mutualists. Biol. Invasions 6, 445–461 (2004).Article 

Google Scholar 
13.Buczkowski, G. & Bennett, G. Seasonal polydomy in a polygynous supercolony of the odorous house ant, Tapinoma sessile. Ecol. Entomol. 33, 780–788 (2008).
Google Scholar 
14.Menke, S. B., Fisher, R. N., Jetz, W. & Holway, D. A. Biotic and abiotic controls of Argentine ant invasion success at local and landscape scales. Ecology 88, 3164–3173 (2007).CAS 
PubMed 
Article 

Google Scholar 
15.Roura-Pascual, N. et al. Relative roles of climatic suitability and anthropogenic influence in determining the pattern of spread in a global invader. Proc. Natl. Acad. Sci. USA 108, 220–225 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
16.Bos, M. M., Tylianakis, J. M., Steffan-Dewenter, I. & Tsharntke, T. The invasive yellow crazy ant and the decline of forest ant diversity in Indonesian cacao agroforests. Biol. Invasions 10, 1399–1409 (2008).Article 

Google Scholar 
17.Human, K. G., Weiss, S., Weiss, A., Sandler, B. & Gordon, D. M. Effects of abiotic factors on the distribution and activity of the invasive Argentine ant (Hymenoptera: Formicidae). Environ. Entomol. 27, 822–833 (1998).Article 

Google Scholar 
18.Suarez, A. V., Holway, D. A. & Case, T. J. Patterns of spread in biological invasions dominated by long-distance jump dispersal: insights from Argentine ants. Proc. Natl. Acad. Sci. USA 98, 1095–1100 (2001).ADS 
CAS 
PubMed 
Article 

Google Scholar 
19.Ito, F., Asfiya, W. & Kojima, J. I. Discovery of independent-founding solitary queens in the yellow crazy ant Anoplolepis gracilipes in East Java, Indonesia (Hymenoptera: Formicidae). Entomol. Sci. 19, 312–314 (2016).Article 

Google Scholar 
20.Lee, C. C., Lin, C. Y., Hsu, H. W. & Yang, C. C. S. Complete genome sequences of two novel dicistroviruses detected in yellow crazy ants (Anoplolepis gracilipes). Arch. Virol. 165, 2715–2719 (2020).CAS 
PubMed 
Article 

Google Scholar 
21.Wetterer, J. K. Worldwide distribution and potential spread of the long-legged ant, Anoplolepis gracilipes (Hymenoptera: Formicidae). Sociobiology 45, 77–97 (2005).
Google Scholar 
22.Abbott, K. L., Greaves, S. N. J., Ritchie, P. A. & Lester, P. J. Behaviourally and genetically distinct populations of an invasive ant provide insight into invasion history and impacts on a tropical ant community. Biol. Invasions 9, 453–463 (2007).Article 

Google Scholar 
23.Haines, I. H., Haines, J. B. & Cherrett, J. M. The impact and control of the crazy ant, Anoplolepis Longipes (Jerd.), in the Seychelles. In Exotic ants. Biology, impact and control of introduced species (ed. Williams, D. F.) 206–218 (Westview Press, 1994).
Google Scholar 
24.Gerlach, J. Impact of the invasive ant Anoplolepis gracilipes on Bird Island, Seychelles. J. Insect Conserv. 8, 15–25 (2004).Article 

Google Scholar 
25.Hill, M., Holm, K., Vel, T., Shah, N. J. & Matyot, P. Impact of the introduced yellow crazy ant Anoplolepis gracilipes on Bird Island, Seychelles. Biodivers. Conserv. 12, 1969–1984 (2003).Article 

Google Scholar 
26.Hoffmann, B. D., Auina, S. & Stanley, M. C. Targeted research to improve invasive species management: yellow crazy ant Anoplolepis gracilipes in Samoa. PLoS ONE 9, e95301 (2014).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
27.Kaiser-Bunbury, C. N., Cuthbert, H., Fox, R., Birch, D. & Bunburry, N. Invasion of yellow crazy ant Anoplolepis gracilipes in a Seychelles UNESCO palm forest. NeoBiota 22, 43–57 (2014).Article 

Google Scholar 
28.Wheeler, W. M. Ants of Formosa and the Philippines. Bull. Am. Mus. Nat. Hist. 26, 333–345 (1909).
Google Scholar 
29.Hsu, P. C. The study of habitats distribution of exotic invasive ants in Taiwan by using bait traps. Master dissertation, National Changhua University of Education (2013) (In Chinese).30.Tseng, H. H. The ant community structure at Kenting National Park in Taiwan. Master dissertation, National Changhua University of Education (2013) (In Chinese).31.Hsu, J. W. & Shih, H. T. Diversity of Taiwanese Brackish crabs genus Ptychognathus Stimpson, 1858 (Crustacea: Brachyura: Varunidae) based on DNA barcodes, with descriptions of two new species. Zool. Stud. 59, 59 (2020).CAS 

Google Scholar 
32.Li, J. J., Shih, H. T. & Ng, P. K. Three new species and two new records of Parasesarma De Man, 1895 (Crustacea: Brachyura: Sesarmidae) from Taiwan and the Philippines from morphological and molecular evidence. Zool. Stud. 58, 40 (2019).CAS 

Google Scholar 
33.Li, J. J., Hsu, J. W., Ng, N. K. & Shih, H. T. Eight new records of crabs (Decapoda, Brachyura: Sesarmidae, Varunidae) from the coasts of Taiwan. Crustaceana 92, 1207–1230 (2019).Article 

Google Scholar 
34.Li, J. J., Shih, H. T. & Ng, P. K. The Taiwanese and Philippine species of the terrestrial crabs Bresedium Serène and Soh, 1970 and Sesarmops Serène and Soh, 1970 (Crustacea: Decapoda: Brachyura), with descriptions of two new species. Zool. Stud. 59, 16 (2020).CAS 

Google Scholar 
35.Liu, H. C. Report on the survey of ecological resources of land crab in Kenting National Park 2019–2020. Consultancy Report to Kenting National Park Headquarters, p. 155 (2020) (In Chinese).36.Ng, P. K., Li, J. J. & Shih, H. T. What is Sesarmops impressus (H. Milne Edwards, 1837) (Crustacea: Brachyura: Sesarmidae)?. Zool. Stud. 59, 27 (2020).CAS 

Google Scholar 
37.Shih, H. T., Hsu, J. W., Li, J. J., Ng, N. K. & Lee, J. H. The identities of three species of Parahelice Sakai, Türkay & Yang, 2006 (Crustacea: Brachyura: Varunidae) from the western Pacific, based on morphological and molecular evidence. Zootaxa 4728, 249–265 (2020).Article 

Google Scholar 
38.Liu, H. C. Biodiversity and population abundance of the land crab fauna both at Houwan and Hsiangchiaowan-Shadao areas of the Kenting National Park. Consultancy Report to Kenting National Park Headquarters, p. 102 (2016) (In Chinese)39.Lin, C. C., Chang, T. W., Chen, H. W., Shih, C. H. & Hsu, P. C. Development of liquid bait with unique bait station for control of Dolichoderus thoracicus (Hymenoptera: Formicidae). J. Econ. Entomol. 110, 1685–1692 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
40.Haines, I. H. & Haines, J. B. Colony structure, seasonality and food requirements of the crazy ant, Anoplolepis longipes (Jerd.), in the Seychelles. Ecol. Entomol. 3, 109–118 (1978).Article 

Google Scholar 
41.Ho, P. H. Land crabs at coastal forests in Kenting National Park, p. 47 (Kenting National Park Headquarters, 2003) (In Chinese).42.Tung, G. S., Chang, T. P. & Liu, H. C. Monitor and comparison of terrestrial crab communities in the virgin and restoration tropical coastal forests in Kenting National Park. J. Natl. Park 23, 21–30 (2013).
Google Scholar 
43.National Land Survey and Mapping Center (NLSC). The Second National Land-Use Survey (Ministry of Interior, 2008).44.ESRI. ArcGIS Desktop: Release 10 (Environmental Systems Research Institute, 2011).45.R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2018. Available online: https://www.R-project.org/, accessed 20 December 2018.46.Lester, P. J. & Tavite, A. Long-legged ants, Anoplolepis gracilipes (Hymenoptera: Formicidae), have invaded Tokelau, changing composition and dynamics of ant and invertebrate communities. Pac. Sci. 58, 391–401 (2004).Article 

Google Scholar 
47.Liu, H. C. & Jeng, M. S. Some reproductive aspects of Gecarcoidea lalandii (Brachyura: Gecarcinidae) in Taiwan. Zool. Stud. 46, 347–354 (2007).
Google Scholar 
48.Su, C. Y., Li, J. J., Wu, H. J. & Chiu, Y. W. An investigation of diversity and reproduction of land crab fauna in Houwan. J. Natl. Park 26, 49–57 (2014).
Google Scholar 
49.Baumgartner, N. R. II. & Ryan, S. D. Interaction of red crabs with yellow crazy ants during migration on Christmas Island. Math. Biosci. 330, 108486 (2020).MathSciNet 
PubMed 
MATH 
Article 

Google Scholar 
50.Hicks, J. W. The breeding behaviour and migrations of the terrestrial crab Gecarcoidea natalis (Decapoda: Brachyura). Aust. J. Zool. 33, 127–142 (1985).Article 

Google Scholar 
51.Green, P. T., O’Dowd, D. J. & Lake, P. S. Alien ant invasion and ecosystem collapse on Christmas Island, Indian Ocean. Aliens 9, 2–4 (1999).
Google Scholar 
52.Li, J. J. & Chiu, Y. W. An atlas of land crabs on Hengchun Peninsula 2.0, p. 136 (National Museum of Marine Biology and Aquarium, 2019) (In Chinese).53.Liu, H. C. Land crab resource survey and management plan in Kenting National Park. Consultancy Report to Kenting National Park Headquarters, p. 88 (2010) (In Chinese).54.Achury, R., Chacón de Ulloa, P., Arcila, Á. & Suarez, A. V. Habitat disturbance modifies dominance, coexistence, and competitive interactions in tropical ant communities. Ecol. Entomol. 45, 1247–1262 (2020).Article 

Google Scholar 
55.Lessard, J. P. & Buddle, C. M. The effects of urbanization on ant assemblages (Hymenoptera: Formicidae) associated with the Molson Nature Reserve, Quebec. Can. Entomol. 137, 215–225 (2005).Article 

Google Scholar 
56.Mauda, E. V., Joseph, G. S., Seymour, C. L., Munyai, T. C. & Foord, S. H. Changes in landuse alter ant diversity, assemblage composition and dominant functional groups in African savannas. Biodivers. Conserv. 27, 947–965 (2018).Article 

Google Scholar 
57.Bacon, S. J., Aebi, A., Calanca, P. & Bacher, S. Quarantine arthropod invasions in Europe: the role of climate, hosts and propagule pressure. Divers. Distrib. 20, 84–94 (2014).Article 

Google Scholar 
58.Tschinkel, W. R. Distribution of the fire ants Solenopsis invicta and S. geminata (Hymenoptera: Formicidae) in Northern Florida in relation to habitat and disturbance. Ann. Entomol. Soc. Am. 81, 76–81 (1988).Article 

Google Scholar 
59.Pyšek, P. et al. Disentangling the role of environmental and human pressure on biological invasions across Europe. Proc. Natl. Acad. Sci. USA 107, 12157–12162 (2010).ADS 
PubMed 
Article 

Google Scholar 
60.Rizali, A. et al. Ant communities on small tropical islands: effects of island size and isolation are obscured by habitat disturbance and ‘tramp’ ant species. J. Biogeogr. 37, 229–236 (2010).Article 

Google Scholar 
61.Rao, N. S., Veeresh, G. K. & Viraktamath, C. A. Dispersal and spread of crazy ant Anoplolepis longipes (Jerdon)(Hymenoptera: Formicidae). Environ. Ecol. 9, 682–686 (1991).
Google Scholar 
62.Gordon, D. M., Moses, L., Falkovitz-Halpern, M. & Wong, E. H. Effect of weather on infestation of buildings by the invasive Argentine ant, Linepithema humile (Hymenoptera: Formicidae). Am. Midl. Nat. 146, 321–328 (2001).Article 

Google Scholar 
63.Menke, S. B. & Holway, D. A. Abiotic factors control invasion by Argentine ants at the community scale. J. Anim. Ecol 75, 368–376 (2006).PubMed 
Article 

Google Scholar 
64.Hsu, P. W. et al. Ant crickets (Orthoptera: Myrmecophilidae) associated with the invasive yellow crazy ant Anoplolepis gracilipes (Hymenoptera: Formicidae): evidence for cryptic species and potential co-introduction with hosts. Myrmecol. News 30, 103–129 (2020).
Google Scholar 
65.Rao, N. S. & Veeresh, G. K. Nesting and foraging habits of crazy ant Anoplolepis longipes (Jerdon) (Hymenoptera: Formicidae). Environ. Ecol. 9, 670–677 (1991).
Google Scholar 
66.Vonshak, M. & Gordon, D. M. Intermediate disturbance promotes invasive ant abundance. Biol. Conserv. 186, 359–367 (2015).Article 

Google Scholar 
67.Yodzis, P. How rare is omnivory?. Ecology 65, 321–323 (1984).Article 

Google Scholar 
68.Linquist, E. S. et al. Land crabs as key drivers in tropical coastal forest recruitment. Biol. Rev. 84, 203–223 (2009).Article 

Google Scholar 
69.Koch, V. & Wolff, M. Energy budget and ecological role of mangrove epibenthos in the Caeté estuary, North Brazil. Mar. Ecol. Prog. Ser. 228, 119–130 (2002).ADS 
Article 

Google Scholar  More