Ecology

1.Lambin, E. F. et al. The causes of land-use and land-cover change: Moving beyond the myths. Glob. Environ. Chang. 11, 261–269 (2001).Article 

Google Scholar 
2.Lawler, J. J. et al. Projected land-use change impacts on ecosystem services in the United States. Proc. Natl. Acad. Sci. USA 111, 7492–7497 (2014).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
3.Bongaarts, J. IPBES, 2019. Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services. Population and Development Review vol. 45 (2019).4.Pardini, R. OBSOLETE: Fragmentation and habitat loss. Ref. Modul. Earth Syst. Environ. Sci. 2, 10–11. https://doi.org/10.1016/b978-0-12-409548-9.09824-9 (2018).Article 

Google Scholar 
5.Anthony, B. & Wasambo, J. Human-wildlife conflict study report. Human Wildl. Confl. Stud. Rep. 2, 55 (2009).
Google Scholar 
6.Fahrig, L. Effects of habitat fragmentation on biodiversity. Annu. Rev. Ecol. Evol. Syst. 34, 487–515 (2003).Article 

Google Scholar 
7.Collinge, S. K. Ecological consequences of habitat fragmentation: Implications for landscape architecture and planning. Landsc. Urban Plan. 36, 59–77 (1996).Article 

Google Scholar 
8.Pierri-Daunt, A. B. & Tanaka, M. O. Assessing habitat fragmentation on marine epifaunal macroinvertebrate communities: An experimental approach. Landsc. Ecol. 29, 17–28 (2014).Article 

Google Scholar 
9.Fahrig, L. et al. Is habitat fragmentation bad for biodiversity?. Biol. Conserv. 230, 179–186 (2019).Article 

Google Scholar 
10.Bustamante, R. O., Serey, I. A. & Pickett, S. T. A. Forest fragmentation, plant regeneration and invasion processes across edges in Central Chile. In How Landscapes Change Ecological Studies (Analysis and Synthesis), 162 (eds Bradshaw, G. A. & Marquet, P. A.) 145–160 (Springer, 2003).
Google Scholar 
11.Chaplin-Kramer, R. et al. Degradation in carbon stocks near tropical forest edges. Nat. Commun. 6, 1–6 (2015).Article 
CAS 

Google Scholar 
12.Betts, M. G. et al. Global forest loss disproportionately erodes biodiversity in intact landscapes. Nature 547, 441–444 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
13.Symes, W. S., Edwards, D. P., Miettinen, J., Rheindt, F. E. & Carrasco, L. R. Combined impacts of deforestation and wildlife trade on tropical biodiversity are severely underestimated. Nat. Commun. 9, 20 (2018).ADS 
Article 
CAS 

Google Scholar 
14.Singh, S. et al. Modeling the spatial dynamics of deforestation and fragmentation using multi-layer perceptron neural network and landscape fragmentation tool. Ecol. Eng. 99, 543–551 (2017).Article 

Google Scholar 
15.Bustamante, R. O. & Simonetti, J. A. Is Pinus radiata invading the native vegetation in Central Chile? Demographic responses in a fragmented forest. Biol. Invas. 7, 243–249 (2005).Article 

Google Scholar 
16.Ripple, W. J. et al. Extinction risk is most acute for the world’s largest and smallest vertebrates. Proc. Natl. Acad. Sci. USA 114, 10678–10683 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
17.Cardillo, M. et al. Evolution: Multiple causes of high extinction risk in large mammal species. Science (80–) 309, 1239–1241 (2005).ADS 
CAS 
Article 

Google Scholar 
18.Woodroffe, R., Thirgood, S. & Rabinowitz, A. People and Wildlife: Conflict or Coexistence (Cambridge University Press, 2005).Book 

Google Scholar 
19.Goswami, V. R. et al. Community-managed forests and wildlife-friendly agriculture play a subsidiary but not substitutive role to protected areas for the endangered Asian elephant. Biol. Conserv. 177, 74–81 (2014).Article 

Google Scholar 
20.Wittemyer, G., Elsen, P., Bean, W. T., Burton, A. C. O. & Brashares, J. S. Accelerated human population growth at protected area edges. Science (80–) 321, 123–126 (2008).ADS 
CAS 
Article 

Google Scholar 
21.Shaffer, L. J., Khadka, K. K., Van Den Hoek, J. & Naithani, K. J. Human-elephant conflict: A review of current management strategies and future directions. Front. Ecol. Evol. 6, 58 (2019).Article 

Google Scholar 
22.Desai, A. A. & Riddle, H. S. Human–Elephant Conflict in Asia. (2015).23.Thouless, C. R. et al. African elephant status report 2016: An update from the African elephant database. Occasional paper series of the IUCN Species Survival Commission. IUCN Species Survical Commun. 4, 309 (2016).
Google Scholar 
24.Leimgruber, P. et al. Fragmentation of Asia’s remaining wildlands: Implications for Asian elephant conservation. Anim. Conserv. 6, 347–359 (2003).Article 

Google Scholar 
25.Koirala, R. K., Raubenheimer, D., Aryal, A., Pathak, M. L. & Ji, W. Feeding preferences of the Asian elephant (Elephas maximus) in Nepal. BMC Ecol. 16, 1–9 (2016).Article 

Google Scholar 
26.Sukumar, R. A brief review of the status, distribution and biology of wild Asian elephants Elephas maximus. Int. Zoo Yearb. 40, 1–8 (2006).Article 

Google Scholar 
27.Baskaran, N. Ranging and Resource Use by Asian elephant in Nilgiri Biosphere Reserve Southern India. (1998).28.Branco, P. S. et al. Determinants of elephant foraging behaviour in a coupled human-natural system: Is brown the new green?. J. Anim. Ecol. 88, 780–792 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
29.Fernando, P. et al. Ranging behavior of the Asian elephant in Sri Lanka. Mamm. Biol. 73, 2–13 (2008).Article 

Google Scholar 
30.Naha, D. et al. Landscape predictors of human–leopard conflicts within multi-use areas of the Himalayan region. Sci. Rep. 10, 20 (2020).Article 
CAS 

Google Scholar 
31.DNPWC. The Elephant Conservation Action Plan for Nepal. (2009).32.Ram, A. K. Status distribution and habitat use by Asian elephants in Nepal. (2020).33.ten Velde, P. A Status Report of Nepal’s Wild Elephant Population. (1997).34.Ram, A. K. et al. Patterns and determinants of Elephant attacks on humans in Nepal. Ecol. Evol. 11, 11639–11650. https://doi.org/10.1002/ece3.7796 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
35.Wikramanayake, E. et al. Designing a conservation landscape for tigers in human-dominated environments. Conserv. Biol. 18, 839–844 (2004).Article 

Google Scholar 
36.Smith, J. L. D. & Mishra, H. R. Status and distribution of Asian elephants in Central Nepal. Oryx 26, 10–14 (1992).Article 

Google Scholar 
37.Shrestha, M. N., Shrestha, K. . & Dhakal, T. R. Hatti byabasthapan yojana tarujma pratibedan (Report on Planning for Elephant Management). Kathmandu: Janchbujh kendra bibhag raj durbar (Department Investigation Center, Nepali Royal Palace (in Nepali version). (HMGN palace investigation centre, Principal Secretariat of His Majesty King, Royal Palace, Kathmandu, Nepal (in Nepali version), 1985).38.Kharel, F. R. The challenge of managing domesticated Asian elephants in Nepal. in Giants on our Hands (Proceedings of the international workshop on the domesticated Asian elehant) 103–103 (FAO Regional Office for Asia and the Pacific of United Nations, Maliwan Mansion Phra Atit Road, Bangkok 10200 Thailand, 2002).39.Gee, E. P. Report on a Survey of Rhinoceros Area of Nepal, prepared for the survival service commission of the International Union for the Conservation of Nature and Natural resources. (1959).40.MoFSC. Strategy and Action Plan 2015–2025 for Terai Arc landscape, Nepal. (2015).41.Subedi, N. et al. Progress Report on Faunal Biodiversity Assessment in Chure Range of Nepal. (President Chure-Terai Madhesh Conservation Development Board and National Trust for Nature Conservation, Khumaltar, Lalitpur, 2021).42.DFRS. State of Nepal’s Forests. Forest Resource Assessment (FRA) Nepal, Department of Forest Research and Survey (DFRS). Kathmandu, Nepal. (Ministry of Forest and Soil Conservation, Nepal, 2015). 978-9937-8896-3-6.43.Reddy, C. S. et al. Assessment and monitoring of deforestation and forest fragmentation in South Asia since the 1930s. Glob. Planet. Change 161, 132–148 (2018).ADS 
Article 

Google Scholar 
44.Reddy, S. C. et al. Quantifying nationwide land cover and historical changes in forests of Nepal (1930–2014): Implications on forest fragmentation. Biodivers. Conserv. 27, 91–107 (2018).Article 

Google Scholar 
45.Aulestia, M. J. S. Understanding land use and land cover dynamics in the Chure region of Nepal: Integrating physiographic, socio-economic and policy drivers. (2019).46.Laurie, A. The Ecology and Behaviour of the Greater One-Horned Rhinoceros, a dissertation submitted to the University of Cambridge for the degree of Doctor of Philosophy. Behaviour (1978).47.Rimal, S., Adhikari, H. & Tripathi, S. Habitat suitability and threat analysis of Greater One-horned Rhinoceros Rhinoceros unicornis Linnaeus, 1758 (Mammalia: Perissodactyla: Rhinocerotidae) in Rautahat District, Nepal. J. Threat. Taxa 10, 11999–12007 (2018).Article 

Google Scholar 
48.Peh, K. S. H. Invasive species in Southeast Asia: The knowledge so far. Biodivers. Conserv. 19, 1083–1099 (2010).Article 

Google Scholar 
49.Lamichhane, B. R. et al. Using interviews and biological sign surveys to infer seasonal use of forested and agricultural portions of a human-dominated landscape by Asian elephants in Nepal. Ethol. Ecol. Evol. 30, 331–347 (2018).Article 

Google Scholar 
50.Acharya, K. P., Paudel, P. K., Neupane, P. R. & Köhl, M. Human-wildlife conflicts in Nepal: Patterns of human fatalities and injuries caused by large mammals. PLoS One 11, 1–18 (2016).
Google Scholar 
51.Carter, N. H., Shrestha, B. K., Karki, J. B., Pradhan, N. M. B. & Liu, J. Coexistence between wildlife and humans at fine spatial scales. Proc. Natl. Acad. Sci. USA 109, 15360–15365 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
52.Choudhury, A. Human-Elephant conflicts in northeast India. Hum. Dimens. Wildl. 9, 261–270 (2004).Article 

Google Scholar 
53.Reddy, C. S., Sreelekshmi, S., Jha, C. S. & Dadhwal, V. K. National assessment of forest fragmentation in India: Landscape indices as measures of the effects of fragmentation and forest cover change. Ecol. Eng. 60, 453–464 (2013).Article 

Google Scholar 
54.Puyravaud, J. P. Standardizing the calculation of the annual rate of deforestation. For. Ecol. Manag. 177, 593–596 (2003).Article 

Google Scholar 
55.Puyravaud, J. P., Gubbi, S., Poornesha, H. C. & Davidar, P. Deforestation increases frequency of incidents with elephants (Elephas maximus). Trop. Conserv. Sci. 12, 20 (2019).Article 

Google Scholar 
56.Puyravaud, J. P., Davidar, P. & Laurance, W. F. Cryptic destruction of India’s native forests. Conserv. Lett. 3, 390–394 (2010).Article 

Google Scholar 
57.Sampson, C. et al. Effects of illegal grazing and invasive Lantana camara on Asian elephant habitat use. Biol. Conserv. 220, 50–59 (2018).Article 

Google Scholar 
58.Roever, C. L., van Aarde, R. J. & Leggett, K. Functional responses in the habitat selection of a generalist mega-herbivore, the African savannah elephant. Ecography (Cop.) 35, 972–982 (2012).Article 

Google Scholar 
59.Liu, P., Wen, H., Lin, L., Liu, J. & Zhang, L. Habitat evaluation for Asian elephants (Elephas maximus) in Lincang: Conservation planning for an extremely small population of elephants in China. Biol. Conserv. 198, 113–121 (2016).Article 

Google Scholar 
60.Ripple, W. J. et al. Collapse of the world’s largest herbivores. Sci. Adv. 1, 2 (2015).Article 

Google Scholar 
61.Sukumar, R. The Asian Elephant: Ecology and Management Vol 8 254 (Cambridge University Press, 1989).
Google Scholar 
62.Desai, A. A. & Baskaran, N. Impact of human activities on the ranging behaviour of elephants in the Nilgiri biosphere Reserve, South India. Bombay Nat. Hist. Soc. 93, 25 (1996).
Google Scholar 
63.Smit, I. P. J., Grant, C. C. & Devereux, B. J. Do artificial waterholes influence the way herbivores use the landscape? Herbivore distribution patterns around rivers and artificial surface water sources in a large African savanna park. Biol. Conserv. 136, 85–99 (2007).Article 

Google Scholar 
64.Smit, I. P. J., Grant, C. C. & Whyte, I. J. Landscape-scale sexual segregation in the dry season distribution and resource utilization of elephants in Kruger National Park, South Africa: Biodiversity research. Divers. Distrib. 13, 225–236 (2007).Article 

Google Scholar 
65.Birkett, P. J., Vanak, A. T., Muggeo, V. M. R., Ferreira, S. M. & Slotow, R. Animal perception of seasonal thresholds: Changes in elephant movement in relation to rainfall patterns. PLoS One 7, 25 (2012).
Google Scholar 
66.Wilson, S., Davies, T. E., Hazarika, N. & Zimmermann, A. Understanding spatial and temporal patterns of human-elephant conflict in Assam, India. Oryx https://doi.org/10.1017/S0030605313000513 (2015).Article 

Google Scholar 
67.Neupane, D., Kunwar, S., Bohara, A. K., Risch, T. S. & Johnson, R. L. Willingness to pay for mitigating human-elephant conflict by residents of Nepal. J. Nat. Conserv. 36, 65–76 (2017).Article 

Google Scholar 
68.Neupane, D., Kwon, Y., Risch, T. S., Williams, A. C. & Johnson, R. L. Habitat use by Asian elephants: Context matters. Glob. Ecol. Conserv. 17, e00570 (2019).Article 

Google Scholar 
69.Goswami, V. R., Medhi, K., Nichols, J. D. & Oli, M. K. Mechanistic understanding of human-wildlife conflict through a novel application of dynamic occupancy models. Conserv. Biol. 29, 1100–1110 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
70.Reddy, C. S. et al. Conservation priorities of forest ecosystems: Evaluation of deforestation and degradation hotspots using geospatial techniques. Ecol. Eng. 91, 2 (2016).Article 

Google Scholar 
71.Nandy, S., Kushwaha, S. P. S. & Dadhwal, V. K. Forest degradation assessment in the upper catchment of the river Tons using remote sensing and GIS. Ecol. Indic. 11, 509–513 (2011).Article 

Google Scholar 
72.Suba, R. B. et al. Rapid expansion of oil palm is leading to human–elephant conflicts in north Kalimantan province of Indonesia. Trop. Conserv. Sci. 10, 25 (2017).Article 

Google Scholar 
73.Naha, D., Sathyakumar, S., Dash, S., Chettri, A. & Rawat, G. S. Assessment and prediction of spatial patterns of human-elephant conflicts in changing land cover scenarios of a human-dominated landscape in North Bengal. PLoS One 14, 25 (2019).
Google Scholar 
74.Laudari, H. K., Aryal, K. & Maraseni, T. A postmortem of forest policy dynamics of Nepal. Land Use Policy 91, 25 (2020).Article 

Google Scholar 
75.Gee, E. P. Report on a brief survey of the wild life resources of Nepal, including the rhinoceros. Oryx 7, 67–76 (1963).Article 

Google Scholar 
76.Kanel, K. R. & Acharya, D. P. Re-Inventing Forestry Agencies: Institutional Innovation to Support Community Forestry in Nepal. Re-Inventing Forestry Agencies: Experiences of Institutional Restructuring in Asia and the Pacific vol. 4 (FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS REGIONAL OFFICE FOR ASIA AND THE PACIFIC Bangkok, 2008, 2008).77.Dahal, G. R., Pokharel, B. K., Khanal, D. R. & Pokhrel, P. R. A framework for classifying subsistence production types of Nepal. J. For. Livelih. 15, 15–26 (2017).Article 

Google Scholar 
78.Ranjit, Y. History of forest management in Nepal: An analysis of political and economic perspective. Econ. J. Nepal 42, 12–28 (2019).Article 

Google Scholar 
79.Adhikari, J. & Dhungana, H. The state and forest resources: An historical analysis of policies affecting forest management in the Nepalese Tarai. Himal. J. Assoc. Nepal Himal. Stud. 29, 43–56 (2010).
Google Scholar 
80.Ram, A.K. & Acharya, H. Status distribution and habitat use by Asian elephants in Nepal. In A Compendium of Conservation Bulletien. 155–160 (Department of National Parks and Wildlife Conservation, Nepal, 2020).81.GoN/PCTMCDB. President Chure-Tarai Madhesh Conservation and Management Master Plan. (2017).82.Chaudhary, B. et al. Detailed Final Report Report with Major Findings (Part-I). 1–19 (2018).83.CBS. National Population Census. Central Bureau of Statistics Vol. 08, 2014 (Central Bureau of Statistics Ramshah Path, 2011).
Google Scholar 
84.Hamilton, A. C. & Radford, E. A. Identification and Conservation of Impeortant Plant Areas for Medicinal Plants in the Himalaya. Project and Workshop Report (Plantlife International, Salisbury, UK) and Ethnobotanical Society of Nepal (Kathmandu, Nepal, 2007).85.Chaudhary, R. P., Uprety, Y. & Rimal, S. K. Deforestation in Nepal: Causes, consequences, and responses. Biol. Environ. Hazards Risks Disast. 20, 20. https://doi.org/10.1016/B978-0-12-394847-2.00020-6 (2016).Article 

Google Scholar 
86.Neupane, D., Johnson, R. L. & Risch, T. S. How do land-use practices affect human–elephant conflict in Nepal?. Wildl. Biol. 17, wlb.00313 (2017).Article 

Google Scholar 
87.Acharya, K. P., Paudel, P. K., Jnawali, S. R., Neupane, P. R. & Köhl, M. Can forest fragmentation and configuration work as indicators of human–wildlife conflict? Evidences from human death and injury by wildlife attacks in Nepal. Ecol. Indic. 80, 74–83 (2017).Article 

Google Scholar 
88.DNPWC. Elephant Conservation Action Plan of Nepal (2010–2019). 1–30 (2010).89.Wilcove, D. S., McLellan, C. H. & Dobson, A. P. Habitat fragmentation in the temperate zone. In Conservation Biology 237–256 (The Science of Scarcity and Diversity, 1986).
Google Scholar 
90.FAO. State of the World’s Forests. Food and Agriculture Organization of The United Nations, Rome (2014).91.Padalia, H. et al. Assessment of historical forest cover loss and fragmentation in Asian elephant ranges in India. Environ. Monit. Assess. 191, 25 (2019).Article 

Google Scholar 
92.Sudhakar Reddy, C. et al. Quantification and monitoring of deforestation in India over eight decades (1930–2013). Biodivers. Conserv. 25, 93–116 (2016).Article 

Google Scholar 
93.Kaim, D. et al. Broad scale forest cover reconstruction from historical topographic maps. Appl. Geogr. 67, 39–48 (2016).Article 

Google Scholar 
94.Kaim, D. et al. Uncertainty in historical land-use reconstructions with topographic maps. Quaest. Geogr. 33, 55–63 (2014).Article 

Google Scholar 
95.Gorelick, N. et al. Google earth engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017).ADS 
Article 

Google Scholar 
96.Wang, Y. et al. Mapping tropical disturbed forests using multi-decadal 30 m optical satellite imagery. Remote Sens. Environ. 221, 474–488 (2019).ADS 
Article 

Google Scholar 
97.Huang, H. et al. Mapping major land cover dynamics in Beijing using all Landsat images in Google Earth Engine. Remote Sens. Environ. 202, 166–176 (2017).ADS 
Article 

Google Scholar 
98.Midekisa, A. et al. Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing. PLoS One 12, 1–15 (2017).
Google Scholar 
99.Zurqani, H. A., Post, C. J., Mikhailova, E. A., Schlautman, M. A. & Sharp, J. L. Geospatial analysis of land use change in the Savannah River Basin using Google Earth Engine. Int. J. Appl. Earth Obs. Geoinf. 69, 175–185 (2018).ADS 
Article 

Google Scholar 
100.Rodriguez-Galiano, V. F., Ghimire, B., Rogan, J., Chica-Olmo, M. & Rigol-Sanchez, J. P. An assessment of the effectiveness of a random forest classifier for land-cover classification. ISPRS J. Photogramm. Remote Sens. 67, 93–104 (2012).ADS 
Article 

Google Scholar 
101.ESRI. ArcGIS Desktop105 (ESRI, 2016).
Google Scholar 
102.Elkie, P., Rempel, R. & Carr, A. Patch Analyst User’s Manual. Ont. Min. Natur. Resour. Northwest Sci. & Technol. Thunder Bay, Ont. TM-002, 16. (1999).103.Vogt, P. et al. Mapping spatial patterns with morphological image processing. Landsc. Ecol. 22, 171–177 (2007).Article 

Google Scholar 
104.Dutta, K., Sudhakar Reddy, C., Sharma, S. & Jha, C. S. Quantification and monitoring of forest cover changes in Agasthyamalai Biosphere Reserve, Western Ghats, India (1920–2012). Curr. Sci. 110, 508–520 (2016).Article 

Google Scholar 
105.Shapiro, A. C., Aguilar-Amuchastegui, N., Hostert, P. & Bastin, J. F. Using fragmentation to assess degradation of forest edges in Democratic Republic of Congo. Carbon Balance Manag. 11, 25 (2016).Article 
CAS 

Google Scholar  More

1.Northrup, J. M., Rivers, J. W., Yang, Z. & Betts, M. G. Synergistic effects of climate and land-use change influence broad-scale avian population declines. Glob. Change Biol. 25, 1561–1575 (2019).Article 

Google Scholar 
2.Thackeray, S. J. et al. Trophic level asynchrony in rates of phenological change for marine, freshwater and terrestrial environments. Glob. Change Biol. 16, 3304–3313 (2011).Article 

Google Scholar 
3.González-Ortegón, E., Blasco, J., Vay, L. L. & Giménez, L. A multiple stressor approach to study the toxicity and sub-lethal effects of pharmaceutical compounds on the larval development of a marine invertebrate. J. Hazard. Mater. 263, 233–238 (2013).PubMed 
Article 
CAS 

Google Scholar 
4.Byrne, M. & Przeslawski, R. Multistressor impacts of warming and acidification of the ocean on marine invertebrates’ life histories. Integr. Comp. Biol. 53, 582–596 (2013).CAS 
PubMed 
Article 

Google Scholar 
5.Keeling, R. F., Kärtzinger, A. & Gruber, N. Ocean deoxygenation in a warming world. Annu. Rev. Mar. Sci. 2, 199–229 (2010).Article 

Google Scholar 
6.Crain, C. M., Kroeker, K. & Halpern, B. S. Interactive and cumulative effects of multiple human stressors in marine systems. Ecol. Lett. 11, 1304–1315 (2008).PubMed 
Article 

Google Scholar 
7.Griffen, B., Belgrad, B. A., Cannizzo, Z. J., Knotts, E. R. & Hancock, E. R. Rethinking our approach to multiple stressor studies in marine environments. Mar. Ecol. Prog. Ser. 543, 273–281 (2016).Article 

Google Scholar 
8.Gunderson, A., Armstrong, E. & Stillman, J. Multiple stressors in a changing world: the need for an improved perspective on physiological responses to the dynamic marine environment. Annu. Rev. Mar. Sci. 8, 357–378 (2016).Article 

Google Scholar 
9.Orr, J. A. et al. Towards a unified study of multiple stressors: divisions and common goals across research disciplines. Proc. R. Soc. B. 287, 20200421 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
10.Piggott, J. J., Townsend, C. R. & Matthaei, C. D. Climate warming and agricultural stressors interact to determine stream macroinvertebrate community dynamics. Glob. Change Biol. 21, 1887–1906 (2015).Article 

Google Scholar 
11.Tekin, E. et al. Using a newly introduced framework to measure ecological stressor interactions. Ecol. Lett. 23, 1391–1403 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
12.Côté, I. M., Darling, E. S. & Brown, C. J. Interactions among ecosystem stressors and their importance in conservation. Proc. R. Soc. B: Biol. Sci. 283, 20152592 (2016).Article 

Google Scholar 
13.Breitburg, D. L. et al. In Successes, Limitations, and Frontiers in Ecosystem Science (eds. Pace, M. L. & Groffman, P. M.) Ch. 17 (Springer, 1998).14.Sinclair, B. J., Ferguson, L. V., Salehipour-shirazi, G. & MacMillan, H. A. Cross-tolerance and cross-talk in the cold: relating low temperatures to desiccation and immune stress in insects. Integr. Comp. Biol. 53, 545–556 (2013).PubMed 
Article 
PubMed Central 

Google Scholar 
15.Vinebrooke, D. et al. Impacts of multiple stressors on biodiversity and ecosystem functioning: the role of species co-tolerance. Oikos 104, 451–457 (2004).Article 

Google Scholar 
16.Boyd, P. W. et al. Experimental strategies to assess the biological ramifications of multiple drivers of global ocean change—A review. Glob. Change Biol. 24, 2239–2261 (2018).Article 

Google Scholar 
17.De Laender, F. Community- and ecosystem-level effects of multiple environmental change drivers: beyond null model testing. Glob. Change Biol. 24, 5021–5030 (2018).Article 

Google Scholar 
18.Borer, E. T. et al. Finding generality in ecology: a model for globally distributed experiments. Meth. Ecol. Evol. 5, 65–73 (2014).Article 

Google Scholar 
19.Fraser, L. H. et al. Coordinated distributed experiments: an emerging tool for testing global hypotheses in ecology and environmental science. Front. Ecol. Environ. 11, 147–155 (2013).Article 

Google Scholar 
20.Dunham, A. E. & Beaupre, S. J. In Experimental Ecology: Issues and Perspectives (eds Resetarits, W. & Bernardo, J.) Ch. 2 (Oxford Univ. Press, 1998).21.Morin, P. J. In Experimental Ecology: Issues and Perspectives (eds Resetarits, W. & Bernardo, J.) Ch. 3 (Oxford Univ. Press, 1998).22.Moran, E. V., Hartig, F. & Bell, D. M. Intraspecific trait variation across scales: implications for understanding global change responses. Glob. Change Biol. 22, 137–150 (2016).Article 

Google Scholar 
23.Violle, C., Reich, P. B., Pacala, S. W., Enquist, B. J. & Kattge, J. The emergence and promise of functional biogeography. Proc. Natl Acad. Sci. USA 111, 13690–13696 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
24.Carter, H. A., Ceballos-Osuna, L., Miller, N. A. & Stillman, J. H. Impact of ocean acidification on metabolism and energetics during early life stages of the intertidal porcelain crab Petrolisthes cinctipes. J. Exp. Biol. 216, 1412–1422 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
25.Appelbaum, S. L., Pan, T. C. F., Hedgecock, D. & Manahan, D. T. Separating the nature and nurture of the allocation of energy in response to global change. Integr. Comp. Biol. 54, 284–295 (2014).Article 

Google Scholar 
26.Barner, A. K. et al. Generality in multispecies responses to ocean acidification revealed through multiple hypothesis testing. Glob. Change Biol. 24, 4464–4477 (2018).Article 

Google Scholar 
27.Spitzner, F., Giménez, L., Meth, R., Harzsch, S. & Torres, G. Unmasking intraspecific variation in offspring responses to multiple environmental drivers. Mar. Biol. 166, 112 (2019).Article 
CAS 

Google Scholar 
28.Torres, G., Thomas, D. N., Whiteley, N. M., Wilcockson, D. & Giménez, L. Maternal and cohort effects modulate offspring responses to multiple stressors. Proc. R. Soc. B 287, 20200492 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
29.Blanquart, F., Kaltz, O., Nuismer, S. L. & Gandon, S. A practical guide to measuring local adaptation. Ecol. Lett. 16, 1195–1205 (2013).30.Bolnick, D. I. et al. Why intraspecific trait variation matters in community ecology. Trends Ecol. Evol. 26, 183–192 (2011).PubMed 
PubMed Central 
Article 

Google Scholar 
31.Coleman, R. et al. A continental scale evaluation of the role of limpet grazing on rocky shores. Oecologia 147, 556–564 (2006).PubMed 
Article 

Google Scholar 
32.Hewitt, J. E., Thrush, S. F., Dayton, P. K. & Bonsdorff, E. The effect of spatial and temporal heterogeneity on the design and analysis of empirical studies of scale‐dependent systems. Am. Nat. 169, 398–408 (2007).PubMed 
Article 

Google Scholar 
33.Levin, S. A. The problem of pattern and scale in ecology. Ecology 73, 1943–1967 (1992).Article 

Google Scholar 
34.Wiens, J. A. Spatial scaling in ecology. Funct. Ecol. 3, 385–397 (1989).Article 

Google Scholar 
35.Benedetti-Cecchi, L. Variance in ecological consumer-resource interactions. Nature 407, 370–374 (2000).CAS 
PubMed 
Article 

Google Scholar 
36.Schäfer, R. B. & Piggott, J. J. Advancing understanding and prediction in multiple stressor research through a mechanistic basis for null models. Glob. Change Biol. 24, 1817–1826 (2018).Article 

Google Scholar 
37.Hastie, T, Tibshirani, R. & Friedman, J. The Elements of Statistical Learning (Springer, 2009).38.Garfinkel, A., Shevtsov, J. & Guo, Y. Modelling Life (Springer, 2017).39.Durrant, H. M. S., Clark, G. F., Dworjanyn, S. A., Byrne, M. & Johnston, E. L. Seasonal variation in the effects of ocean warming and acidification on a native bryozoan, Celleporaria nodulosa. Mar. Biol. 160, 1903–1911 (2013).Article 

Google Scholar 
40.Jensen, G. C., McDonald, P. S. & David, A. A. East meets west: competitive interactions between green crab Carcinus maenas, and native and introduced shore crab Hemigrapsus spp. Mar. Ecol. Prog. Ser. 225, 251–262 (2002).Article 

Google Scholar 
41.Jungblut, S., Beermann, J., Boos, K., Saborowski, R. & Hagen, W. Population development of the invasive crab Hemigrapsus sanguineus (De Haan, 1853) and its potential native competitor Carcinus maenas (Linnaeus, 1758) at Helgoland (North Sea) between 2009 and 2014. Aquat. Inv. 12, 85–96 (2017).Article 

Google Scholar 
42.Fischer, E. M. & Schär, C. Consistent geographical patterns of changes in high-impact European heatwaves. Nat. Geosci. 3, 398 (2010).CAS 
Article 

Google Scholar 
43.Christidis, N., Jones, G. S. & Stott, P. A. Dramatically increasing chance of extremely hot summers since the 2003 European heatwave. Nat. Clim. Change 5, 46–50 (2015).Article 

Google Scholar 
44.Hobday, A. J. et al. A hierarchical approach to defining marine heatwaves. Progr. Oceanogr. 141, 227–238 (2016).Article 

Google Scholar 
45.Arias-Ortiz, A. et al. A marine heatwave drives massive losses from the world’s largest seagrass carbon stocks. Nat. Clim. Change 8, 338–344 (2018).CAS 
Article 

Google Scholar 
46.Smale, D. A. et al. Marine heatwaves threaten global biodiversity and the provision of ecosystem services. Nat. Clim. Change 9, 306–312 (2019).Article 

Google Scholar 
47.Giraldo-Ospina, A., Kendrick, G. A. & Hovey, R. K. Depth moderates loss of marine foundation species after an extreme marine heatwave: could deep temperate reefs act as a refuge? Proc. R. Soc. B 287, 20200709 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
48.Pandori, L. L. M. & Sorte, C. J. B. The weakest link: sensitivity to climate extremes across life stages of marine invertebrates. Oikos 128, 621–629 (2019).Article 

Google Scholar 
49.Tilman, D. Competition and biodiversity in spatially structured habitats. Ecology 75, 2–16 (1994).Article 

Google Scholar 
50.Gouvêa, L. P. et al. Interactive effects of marine heatwaves and eutrophication on the ecophysiology of a widespread and ecologically important macroalga. Limnol. Oceanogr. 62, 2056–2075 (2017).Article 
CAS 

Google Scholar 
51.Hayashida, H., Matear, R. J. & Strutton, P. G. Background nutrient concentration determines phytoplankton bloom response to marine heatwaves. Glob. Change Biol. 26, 4800–4811 (2020).Article 

Google Scholar 
52.Von Biela, V. R. et al. Extreme reduction in nutritional value of a key forage fish during the Pacific marine heatwave of 2014-2016. Mar. Ecol. Prog. Ser. 613, 171–182 (2019).Article 

Google Scholar 
53.Dawirs, R. R., Püschel, C. & Schorn, F. Temperature and growth in Carcinus maenas L. (Decapoda: Portunidae) larvae reared in the laboratory from hatching through metamorphosis. J. Exp. Mar. Biol. Ecol. 100, 47–74 (1986).Article 

Google Scholar 
54.Torres, G. & Giménez, L. Temperature modulates compensatory responses to food limitation at metamorphosis in a marine invertebrate. Funct. Ecol. 34, 1564–1576 (2020).Article 

Google Scholar 
55.Roman, J. O. E. & Palumbi, S. R. A global invader at home: population structure of the green crab, Carcinus maenas, in Europe. Mol. Ecol. 13, 2891–2898 (2004).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
56.Zeng, C., Rotllant, G., Gimenez, L. & Romano, N. In The Natural History of Crustacea: Developmental Biology and Larval Ecology (eds Anger, K., Harzsch, S. & Thiel, M.) Vol. 7, Ch. 7 (Oxford Univ. Press, 2020).57.Nougué, O., Svendsen, N., Jabbour-Zahab, R., Lenormand, T. & Chevin, L.-M. The ontogeny of tolerance curves: habitat quality vs. acclimation in a stressful environment. J. Anim. Ecol. 85, 1625–1635 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
58.Seuront, L., Nicastro, K. R., Zardi, G. I. & Goberville, E. Decreased thermal tolerance under recurrent heat stress conditions explains summer mass mortality of the blue mussel Mytilus edulis. Sci. Rep. 9, 17498 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
59.Enriquez-Urzelai, U. et al. Ontogenetic reduction in thermal tolerance is not alleviated by earlier developmental acclimation in Rana temporaria. Oecologia 189, 385–394 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
60.Epifanio, C. E., Dittel, A. I., Park, S., Schwalm, S. & Fouts, A. Early life history of Hemigrapsus sanguineus, a non-indigenous crab in the Middle Atlantic Bight (USA). Mar. Ecol. Prog. Ser. 170, 231–238 (1998).Article 

Google Scholar 
61.Karlsson, R., Obst, M. & Berggren, M. Analysis of potential distribution and impacts for two species of alien crabs in Northern Europe. Biol. Inv. 21, 3109–3119 (2019).Article 

Google Scholar 
62.Sulkin, S., Blanco, A., Chan, J. & Bryant, M. Effects of limiting access to prey on development of first zoeal stage of the brachyuran crabs Cancer magister and Hemigrapsus oregonensis. Mar. Biol. 131, 515–521 (1998).Article 

Google Scholar 
63.Warton, D. I. & Hui, F. K. C. The arcsine is asinine: the analysis of proportions in ecology. Ecology 92, 3–10 (2011).PubMed 
Article 

Google Scholar 
64.Bolker, B. M. et al. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol. Evol. 24, 127–135 (2009).Article 

Google Scholar 
65.Zuur, A., Ieno, E. N., Walker, N., Savaliev, A. A. & Smith, G. M. Mixed Effect Models and Extensions in Ecology with R (Springer, 2009).66.R core team. R: a language and environment for statistical computing. R Foundation for Statistical Computing https://www.R-project.org/ (2017).67.Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. and R Core Team. nlme: linear and nonlinear mixed effects models. R package version 3.1-137. (2018).68.Giménez, L. & Torres, G. Effect of simulated heatwaves on larval performance of two marine invertebrates. PANGAEA https://doi.org/10.1594/PANGAEA.934715 (2021). More

1.Hamann, M., Jessop, T., Limpus, C. & Whittier, J. Interactions among endocrinology, seasonal reproductive cycles and the nesting biology of the female green sea turtle. Mar. Biol. 140, 823–830 (2002).CAS 
Article 

Google Scholar 
2.Chaloupka, M. et al. Encouraging outlook for recovery of a once severely exploited marine megaherbivore. Glob. Ecol. Biogeogr. 17, 297–304 (2007).Article 

Google Scholar 
3.Kitayama, C. et al. Infection by and molecular features of Learedius learedi (Digenea: Schistosomatoidea) in green sea turtles (Chelonia mydas) on the Ogasawara islands, Japan. J Parasitol. 105(4), 533–538 (2019).Article 

Google Scholar 
4.Kondo, S., Morimoto, Y., Sato, T. & Suganuma, H. Factors affecting the long-term population dynamics of green turtles (Chelonia mydas) in Ogasawara, Japan: Influence of natural and artificial production of hatchlings and harvest pressure. Chelonian Conserv. Biol. 16, 83–92 (2017).Article 

Google Scholar 
5.Hatase, H., Sato, K., Yamaguchi, M., Takahashi, K. & Tsukamoto, K. Individual variation in feeding habitat use by adult female green sea turtles (Chelonia mydas): Are they obligately neritic herbivores? Oecologia 149, 52–64 (2006).ADS 
Article 

Google Scholar 
6.Nishizawa, H. et al. Composition of green turtle feeding aggregations along the Japanese archipelago: Implications for changes in composition with current flow. Mar. Biol. 160(10), 2671–2685 (2013).Article 

Google Scholar 
7.Wood, J. R. & Wood, F. E. Reproductive biology of captive green sea turtles (Chelonia mydas). Am. Zool. 20, 499–505 (1980).Article 

Google Scholar 
8.Ulrich, G. F. & Parkes, A. S. The green sea turtle (Chelonia mydas): Further observations on breeding in captivity. J. Zool. 185(2), 237–251 (1978).Article 

Google Scholar 
9.Gist, D. H. & Congdon, J. D. Oviductal sperm storage as a reproductive tactic of turtles. J. Exp. Zool. 282, 526–534 (1998).CAS 
Article 

Google Scholar 
10.Gist, D. H. & Jones, J. M. Sperm storage within the oviduct of turtles. J. Morphol. 199, 379–384 (1989).Article 

Google Scholar 
11.Holt, W. V. Mechanisms of sperm storage in the female reproductive tract: An interspecies comparison. Reprod. Domest. Anim. 46, 68–74 (2011).Article 

Google Scholar 
12.Orr, T. J. & Brennan, P. L. R. Sperm storage: Distinguishing selective processes and evaluating criteria. Trends Ecol. Evol. 30, 261–272 (2015).Article 

Google Scholar 
13.Blackburn, D. G. Structure, function, and evolution of the oviducts of squamate reptiles, with special reference to viviparity and placentation. J. Exp. Zool. 282, 560–617 (1998).CAS 
Article 

Google Scholar 
14.Matsuzaki, M. & Sasanami, T. Sperm storage in the female reproductive tract: A conserved reproductive strategy for better fertilization success. In Avian Reproduction. Advances in Experimental Medicine and Biology Vol. 1001 (ed. Sasanami, T.) 173–186 (Springer, 2017).
Google Scholar 
15.Girling, J. E. The reptilian oviduct: A review of structure and function and directions for future research. J. Exp. Zool. 293, 141–170 (2002).Article 

Google Scholar 
16.Almeida-Santos, S. M. & Salomão, M. G. Long-term sperm storage in the female Neotropical Rattlesnake Crotalus durissus terrificus (Viperidae: Crotalinae). Jpn. J. Herpetol. 17, 46–52 (1997).Article 

Google Scholar 
17.Sever, D. M. & Hopkins, W. A. Oviductal sperm storage in the ground skink Scincella laterale Holbrook (Reptilia: Scincidae). J. Exp. Biol. 301, 599–611 (2004).
Google Scholar 
18.Bakst, M. R. Fate of fluorescent stained sperm following insemination: New light on oviducal sperm transport and storage in the turkey. Biol. Reprod. 50, 987–992 (1994).CAS 
Article 

Google Scholar 
19.Sasanami, T., Matsuzaki, M., Mizushima, S. & Hiyama, G. Sperm storage in the female reproductive tract in birds. J. Reprod. Dev. 59, 334–338 (2013).Article 

Google Scholar 
20.Palmer, B. D. & Guillette, L. J. Jr. Histology and functional morphology of the female reproductive tract of the tortoise Gopherus polyphemus. Am. J. Anat. 183, 200–211 (1988).CAS 
Article 

Google Scholar 
21.Xiangkun, H. et al. Seasonal changes of sperm storage and correlative structures in male and female soft-shelled turtles, Trionyx sinensis. Anim. Reprod. Sci. 108, 435–445 (2008).Article 

Google Scholar 
22.Seminoff, J. A. The IUCN Red List of Threatened Species 2004: e.T4615A11037468. https://doi.org/10.2305/IUCN.UK.2004.RLTS.T4615A11037468.en (2004)23.Bjorndal, K. A. & Jackson, J. B. C. Roles of sea turtles in marine ecosystems: Reconstructing the past. In The Biology of Sea Turtles Vol. 2 (eds Lutz, P. L. et al.) 259–273 (CRC Press, 2003).
Google Scholar 
24.Gist, D. H., Bagwill, A., Lance, V., Sever, D. M. & Elsey, R. M. Sperm storage in the oviduct of the American alligator. J. Exp. Zool. 309, 581–587 (2008).Article 

Google Scholar 
25.Gist, D. H. & Fischer, E. N. Fine structure of the sperm storage tubules in the box turtle oviduct. J. Reprod. Fertil. 97, 463–468 (1993).CAS 
Article 

Google Scholar 
26.Chen, S. et al. Sperm storage and spermatozoa interaction with epithelial cells in oviduct of Chinese soft-shelled turtle, Pelodiscus sinensis. Ecol. Evol. 5, 3023–3030 (2015).Article 

Google Scholar 
27.Miller, J. D. Reproduction in sea turtles. In The Biology of Sea Turtles (eds Lutz, P. L. & Musick, J. A.) 51–81 (CRC Press, 1997).
Google Scholar 
28.Pearse, D. E. & Avise, J. C. Turtle mating systems: Behavior, sperm storage, and genetic paternity. J. Hered. 92, 206–211 (2001).CAS 
Article 

Google Scholar 
29.Pearse, D. E., Janzen, F. J. & Avise, J. C. Genetic markers substantiate long-term storage and utilization of sperm by female painted turtles. Heredity 86, 378–384 (2001).CAS 
Article 

Google Scholar 
30.Sarkar, S., Sarkar, N. & Maiti, B. Oviductal sperm storage structure and their changes during the seasonal (dissociated) reproductive cycle in the soft-shelled turtle Lissemys punctata punctata. J. Exp. Zool. A Comp. Exp. Biol. 295, 83–91 (2003).PubMed 

Google Scholar 
31.Bagwill, A., Sever, D. M. & Elsey, R. M. Seasonal variation of the oviduct of the American alligator, Alligator mississippiensis (Reptilia: Crocodylia). J. Morphol. 270, 702–713 (2009).Article 

Google Scholar 
32.Han, X. et al. Ultrastructure of anterior uterus of the oviduct and the stored sperm in female soft-shelled turtle, Trionyx sinensis. Anat. Rec. 291, 335–351 (2008).Article 

Google Scholar 
33.Nogueira, K. O. P. C., Araújo, V. A., Sartori, S. S. R. & Neves, C. A. Phagocytosis of spermatozoa by epithelial cells in the vagina of the lizard Hemidactylus mabouia (Reptilia, Squamata). Micron 42, 377–380 (2011).Article 

Google Scholar  More

Phototactic behaviourThe optimization results of the proposed behavioural setup allowed the phototactic behaviour of the studied D. magna clone and the effects of FK treatment on this behaviour to be monitored and quantified. Furthermore, the effects of the FKs were evident only upon light exposure, were more apparent after a short (5 min) acclimation to light and were tightly regulated by the light intensity. The above-mentioned factors agree with previous studies, which found a marked positive phototactism of clone P132,8528 and that the effects of the FKs become consistent after 5 min of light exposure28. Moreover, it has also been reported that light intensity controls anti-predatory defences in Daphnia29.The effects of the pharmacological treatments were consistent for GABAergic and muscarinic cholinergic compounds across two or three identical non-consecutive experiments performed over more than one year. Consistency of the toxicological results and, in particular, of the behavioural responses should be compulsory in toxicological studies to increase the credibility and robustness of the findings30,31. Agonists of these two neurotransmitter receptors (DZP, PILO) and the antagonist of the GABA receptor (PICRO) affected the induction of the phototactic behavioural changes (i.e., interfered with fish recognition). The receptor agonists DZP and PILO counteracted the negative phototactism evoked by the FKs, whereas PICRO enhanced the effect of the FKs, increasing the negative phototactism. None of the three applied substances when applied alone induced anti-predatory fish phototactic behaviour, indicating that these compounds interfered with the FK sensorial pathway. Alternatively, the muscarinic cholinergic antagonist SCOP interfered with phototaxis itself, almost completely abolishing the positive phototactic behaviour of the studied clone under both control and FK conditions. This indicates that the muscarinic cholinergic signalling pathway could potentially be a major regulator of anti-predatory fish phototactic behaviour. In D. pulex and D. galeata, the formation of neck teeth or helmets in response to predatory kairomones released by invertebrate predators has been related to a series of biological reactions that involve kairomone perception and neuronal signals, which are converted into endocrine signals and subsequently induce changes in the expression of morphogenetic factors32,33. We previously showed that DZP, PILO, PICRO and SCOP were neuroactive in D. magna, affecting sensitization and/or habituation motile responses to repetitive light stimuli34; thus, it is likely that these compounds disrupted neurological signalling pathways related to the phototactism shifts caused by FK perception or to the phototaxis itself.Little is known about how phototaxis is neuronally coded. In D. pulex, both in silico and experimental works have shown that histaminergic neurons may mediate phototactic responses to UV irradiation12. By using histamine immunohistochemistry, the previous authors labelled putative photoreceptors in the compound eye and neuronal projections from these cells to the brain. The D. pulex genome also has a putative Drosophila orthologue of histidine decarboxylase (the rate-limiting biosynthetic enzyme for histamine), as well as two putative histamine-gated chloride channels (hclA and hclB orthologues). Exposure of D. magna to cimetidine, an H2 receptor antagonist known to block both hclA and hclB in D. melanogaster, inhibited the negative phototactic responses of these orthologues to UV irradiation. In another study, it was found that short-day photoperiods induced a significant increase in light-avoidance behaviours relative to controls and increased glutamate signalling, which is a critical pathway in arthropod light-avoidance behaviour35. It has also been reported that a group of serotonergic cells located in the protocerebrum probably control phototactic behaviour16. Notably, the perception of predatory kairomones and neuronal and cellular wiring is largely unknown in Daphnia2. For example, the receptors that detect invertebrate cues from Notonecta in D. longicephala were shown to be located on the first antennae, from which neurites extend into the deutocerebrum of the brain. However, key olfactory neuronal structures, such as olfactory glomeruli in the deutocerebrum, were not found2.Our results obtained for DZP, an agonist of the GABAA receptor, agree with those of Weiss et al.11, who found that co-exposure to FKs and exogenous GABA ameliorated life history changes to FKs in a D. pulex clone, whereas co-exposure with the GABAA antagonist PICRO did not have any effect. The ineffectiveness of PICRO on the modulation of FK effects in D. pulex found by Weiss et al.11 might indicate species differences resulting from different receptor amino acid sequences. For example, GABAA receptor subtypes with a single amino acid replacement make the Drosophila GABAA receptor PICRO-insensitive36. Indeed, in crustaceans, lobster GABAA receptors were also found to be insensitive to PICRO37. There is also the possibility that FK-mediated changes in phototactic behaviour and life history traits may be controlled by different mechanisms6.Reported information on the modulatory effects of cholinergic compounds on anti-predatory defences in Daphnia is limited to invertebrate predatory cues, which, according to previous studies, should be regulated by neurological mechanisms distinct from those of fish2,11. Our results showed that the neurological cholinergic mechanisms that modulate induced defence responses against invertebrate predators or that mimic these responses are also able to do the same for fish predation but in the opposite way. Physostigmine and carbaryl, which are acetylcholinesterase inhibitors that increase acetylcholine receptor activity, enhanced and mimicked, respectively, the morphogenetic effects of invertebrate kairomones in several Daphnia species11,21,23. Conversely, atropine, which is a muscarinic acetylcholine receptor (AChR) inhibitor like SCOP, diminished neck tooth formation in D. pulex11,21. In our study, SCOP alone abolished the positive phototactism of the studied clone, which mimicked the effects of the FKs. Conversely, PILO, which is a muscarine AChR agonist, ameliorates the phototactic responses to FKs.The nicotinic AChR agonists (NICO, IMI) and antagonist (MEC) only marginally affected the phototactic responses to the FKs. This indicates that muscarinic cholinergic signalling but not nicotinic signalling is involved in phototaxis/phototactic behaviour. It is therefore possible that both FK and SCOP treatment, through inhibition of muscarinic cholinesterase receptor activity, diminished the positive phototaxis of the studied clone, and PILO activation of these receptors ameliorated the effects of the FKs. In insects, neurons that connect olfactory inputs to higher-order brain areas that coordinate behavioural responses are thought to be under cholinergic control38.In general, GABA is known to have inhibitory functions. It has been proposed that the continuous activation of the GABAergic neuronal pathway by endogenous GABA without predatory cues prevents life history shifts11, which in our case would be the transition from positive to negative phototaxis. FKs and PICRO relieve inhibition, which can be re-established by the experimental application of GABAA receptor agonists such as DZP or GABA itself. Our results and those of Weiss et al.11 agree with the previous argument.Equi-effective mixtures of the tested agonists and antagonists had similar effects on D. magna responses to FKs as the single mixture compound treatments did, indicating that the joint effects of agonists and antagonists of the GABAergic and cholinergic signalling pathways can act cooperatively and probably independently, modulating the effects of FKs. This is in line with other findings that showed that key ecophysiological responses in Daphnia are regulated by several signalling receptor pathways, which likely ensures more robust control. This is the case for the storage lipid dynamics associated with moulting and reproduction39.The involvement of additional neurotransmitter signalling pathways, such as the serotonergic pathway, can also be taken into consideration despite being less consistent. Agonists of the serotonin receptor (such as serotonin) or treatments that increase serotonin levels (such as fluoxetine) ameliorated the effects of the FKs in only one experiment, but treatments that decreased serotonin, such as PCPA, increased the effects of the FKs in two out of the three experiments. Previously, we reported that serotonin activity in the brains of D. magna increased with algae food levels, and thus, the effects of fluoxetine on the enhancement of brain serotonin levels could only be observed under limited food conditions24. This indicates that the high levels of food used in our experiments probably prevented fluoxetine from increasing the already high serotonin levels in the central nervous system. Interestingly, inducible fish kairomone changes in phototactic behaviour in Daphnia increased with food level40, which is probably related to high levels of serotonin. On the other hand, the effects of PCPA, which decreases serotonin concentrations26, are unlikely to be modulated by food since this drug inhibits tryptophan hydrolase, the serotonin synthesis rate-limiting enzyme in D. magna41. This is apparently the case in our study.Neurophysiological stimulation experiments with dopaminergic/adrenergic agonists and antagonists were inconclusive since in only one out of two experiments the dopaminergic agonist APO diminish negative phototaxis after FK exposure. We also did not find any effects from the glutamatergic agonists and antagonists on phototactism. This could be related to the low stability of dopaminergic compounds in water and the reported small effects of glutaminergic compounds on the Daphnia motile response to light34.Consistent failure of the tested antihistaminergic drugs to modulate phototactism to visible light disagrees with previous findings that discovered that these drugs affected phototactism but at much higher doses12.Metabolomic changesThe study of metabolomic changes across the treatments that modulated FK-mediated phototactic changes or altered phototaxis provided further experimental evidence of the involvement of key neurological signalling metabolic pathways. Caution must be exercised, however, since the studied receptor agonist and antagonist drugs do not change the neurotransmitters or their related metabolites. Nevertheless, little is known about how these drugs may affect the Daphnia neuronal metabolome. The cholinergic neurotransmitter system is one of the most important systems that plays a pivotal role in learning and memory in animal species, including D. magna34,42. Whole-body concentrations of acetylcholine decreased in females exposed to FKs and those exposed to SCOP and increased in those exposed to the agonists PILO and DZP. Thus, it is possible to establish a direct link between the decreased levels of acetylcholine and decreased positive phototactism in the studied clone. The results obtained for the GABAergic and serotonergic signalling pathways were less convincing, as FKs alone did not consistently affect the levels of GABA and serotonin. However, co-exposure to FK and the GABAA receptor agonist DZP increased endogenous GABA levels, which is in line with the results reported by Weiss et al.11, who also found that the addition of exogenous GABA ameliorated FK effects. Interestingly, the summarized results depicted in Fig. 4 showed that serotonin levels dereased upon exposure to SCOP, PICRO and PILO but PILO also increase the levels of the serotonin degradation metabolite 5-HIAA. This may indicate that PILO may affect the turnover rather than the levls of serotionin.Previous findings have reported altered responses to light in D. magna individuals lacking serotonin16. Therefore, it is possible to establish a link between the observed marked negative phototactism of females exposed to SCOP and low levels of serotonin.Dopaminergic- and adrenergic-related metabolites deserve special attention, although there is only evidence that dopamine is involved in the proliferation and structural formation of morphological defences in Daphnia for invertebrate kairomones22. In some invertebrates, adrenergic signalling is considered to be absent, and the analogous functions are performed by octopamine43. In our study, fish kairomones and SCOP decreased the levels of dopamine and octopamine, whereas females co-treated with the agonists DZP and PILO and FKs showed relatively high levels of dopamine. In the insect Drosophila melanogaster, which shares many gene signalling pathways with Daphnia44, individuals deficient in dopamine show reduced positive phototactism45. Unfortunately, it is not possible to know whether the observed changes in DA in the whole bodies of D. magna indicate that DA is less used or used in excess. Figure 4 indicates that FK and SCOP reduced both DA and its intermediary metabolite L-DOPA. SCOP also increased the DA degradation metabolite 3-MT and two norepinephrine metabolites/neurotransmitters (NOEM, EPPY) that ultimately depend on DA. This means that FK decreased DA probably decreasing its intermediary metabolite L-DOPA, whereas SCOP decreased DA to a greater extent decreasing its intermediary L-DOPA but also increasing its turnover rate. Our neurophysiological stimulation experiments with dopaminergic active compounds are also not conclusive. This suggests that further research is needed to study the involvement of dopaminergic signalling in the response to fish. Existing studies on adrenergic signalling in daphnids indicated that β-blockers such as propranolol diminish the heart rate46 and motile responses to light27, which are related to the known role of adrenergic signalling that regulates blood pressure47 and other fight-or-flight responses to stress48. Future research is needed to elucidate the involvement of OCT, EPPY and NORM in the phototactic response of D. magna to FKs.In summary, this study provides consistent results that muscarinic cholinergic and GABAergic receptor agonists and antagonists are able to ameliorate or enhance, respectively, the phototactic response of adult females from the studied D. magna clone to FKs. Furthermore, inhibition of the muscarinic acetylcholine receptor by SCOP induced the phototactic response to fish kairomones. This may indicate that muscarinic cholinergic antagonists changed phototaxis, whereas muscarinic cholinergic agonists and GABAergic agonists and antagonists changed the perception of FKs. Serotonergic agonists and antagonists were also able to diminish and increase FK effects, respectively, but only in half of the trials performed. The fact that we could not observe effects from the remaining neuroactive agents (i.e., dopaminergic, histaminergic, glutamatergic) could simply be because they are not relevant for predator-induced anti-phototaxis. The study of neurotransmitters and their related metabolite changes allowed us to identify acetylcholine and GABA as putative key metabolites associated with the observed phototactic modulatory effects of FK and cholinergic and GABAergic compounds. Increased and decreased levels of dopamine in the whole bodies of D. magna were related to positive and negative phototactic behaviours, respectively, but could not be related to neurophysiological studies with the tested dopaminergic drugs. More

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript. More

1.Mcguire, A. D. et al. Sensitivity of the carbon cycle in the Arctic to climate change. Ecol. Monogr. 79, 523–555 (2009). Details Arctic changes under RCP scenarios using a multi-model approach forecasting vegetation offsets of some carbon emissions.
Google Scholar 
2.Brandt, J. P. The extent of the North American boreal zone. Environ. Rev. 17, 101–161 (2009).
Google Scholar 
3.Chadburn, S. et al. Carbon stocks and fluxes in the high latitudes: using site-level data to evaluate Earth system models. Biogeosciences 14, 5143–5169 (2017).CAS 

Google Scholar 
4.Karjalainen, O. et al. Data descriptor: circumpolar permafrost maps and geohazard indices for near-future infrastructure risk assessments. Sci. Data 6, 190037 (2019).
Google Scholar 
5.Hjort, J. et al. Degrading permafrost puts Arctic infrastructure at risk by mid-century. Nat. Commun. 9, 5147 (2018).CAS 

Google Scholar 
6.Abramov, A., Vishnivetskaya, T. & Rivkina, E. Are permafrost microorganisms as old as permafrost? FEMS Microbiol. Ecol. 97, fiaa260 (2021).CAS 

Google Scholar 
7.Ricketts, M. P. et al. The effects of warming and soil chemistry on bacterial community structure in Arctic tundra soils. Soil Biol. Biochem. 148, 107882 (2020).CAS 

Google Scholar 
8.Hultman, J. et al. Multi-omics of permafrost, active layer and thermokarst bog soil microbiomes. Nature 521, 208–212 (2015).CAS 

Google Scholar 
9.Turetsky, M. R. et al. Carbon release through abrupt permafrost thaw. Nat. Geosci. 13, 138–143 (2020). Seminal paper that identifies abrupt permafrost thaw as an important mechanism in rapid Arctic change.CAS 

Google Scholar 
10.Nikrad, M. P., Kerkhof, L. J. & Aggblom, M. M. The subzero microbiome: microbial activity in frozen and thawing soils. FEMS Microbiol. Ecol. 92, fiw081 (2016).
Google Scholar 
11.Turetsky, M. R. et al. Permafrost collapse is accelerating carbon release. Nature 569, 32–24 (2019).CAS 

Google Scholar 
12.Wild, B. et al. Rivers across the Siberian Arctic unearth the patterns of carbon release from thawing permafrost. Proc. Natl Acad. Sci. USA 116, 10280–10285 (2019).CAS 

Google Scholar 
13.Anthony, K. W. et al. 21st-century modeled permafrost carbon emissions accelerated by abrupt thaw beneath lakes. Nat. Commun. 9, 3262 (2018).
Google Scholar 
14.Schaefer, K., Lantuit, H., Romanovsky, V. E., Schuur, E. A. G. & Witt, R. The impact of the permafrost carbon feedback on global climate. Environ. Res. Lett. 9, 085003 (2014).CAS 

Google Scholar 
15.Hong, E., Perkins, R. & Trainor, S. Thaw settlement hazard of permafrost related to climate warming in Alaska. Arctic 67, 93–103 (2014).
Google Scholar 
16.Trofimenko, Y. V., Evgenev, G. I. & Shashina, E. V. Functional loss risks of highways in permafrost areas due to climate change. Procedia Eng. 189, 258–264 (2017).
Google Scholar 
17.Wurzbacher, C., Nilsson, R. H., Rautio, M. & Peura, S. Poorly known microbial taxa dominate the microbiome of permafrost thaw ponds. ISME J. 11, 1938–1941 (2017).
Google Scholar 
18.Emerson, J. B. et al. Host-linked soil viral ecology along a permafrost thaw gradient. Nat. Microbiol. 3, 870–880 (2018).CAS 

Google Scholar 
19.Gross, M. Permafrost thaw releases problems. Curr. Biol. 29, R39–R41 (2019).CAS 

Google Scholar 
20.Walsh, M. G., De Smalen, A. W. & Mor, S. M. Climatic influence on anthrax suitability in warming northern latitudes. Sci. Rep. 8, 9269 (2018).
Google Scholar 
21.Zolkos, S. et al. Mercury export from Arctic great rivers. Environ. Sci. Technol. 54, 4140–4148 (2020).CAS 

Google Scholar 
22.Ewing, S. A. et al. Uranium isotopes and dissolved organic carbon in loess permafrost: modeling the age of ancient ice. Geochim. Cosmochim. Acta 152, 143–165 (2015).CAS 

Google Scholar 
23.Eriksson, M. On Weapons Plutonium in the Arctic Environment (Thule, Greenland). PhD thesis, Lund Univ. (2002).24.Colgan, W. et al. The abandoned ice sheet base at Camp Century, Greenland, in a warming climate. Geophys. Res. Lett. 43, 8091–8096 (2016).
Google Scholar 
25.Anisimov, O., Kokorev, V. & Zhiltcova, Y. Arctic ecosystems and their services under changing climate: predictive-modeling assessment. Geogr. Rev. 107, 108–124 (2017).
Google Scholar 
26.Pelletier, M., Allard, M. & Levesque, E. Ecosystem changes across a gradient of permafrost degradation in subarctic Québec (Tasiapik Valley, Nunavik, Canada). Arct. Sci. 5, 1–26 (2019).
Google Scholar 
27.Perryman, C. R. et al. Heavy metals in the Arctic: distribution and enrichment of five metals in Alaskan soils. PLoS ONE 15, e0233297 (2020).CAS 

Google Scholar 
28.Gilichinsky, D. A. & Rivkina, E. M. Permafrost microbiology. Encycl. Earth Sci. Ser. 6, 726–732 (1995). Details the (at the time) emergent field of permafrost microbiology, extremophilic species and future prospects for emergent microbes.
Google Scholar 
29.Steven, B., Léveillé, R., Pollard, W. H. & Whyte, L. G. Microbial ecology and biodiversity in permafrost. Extremophiles 10, 259–267 (2006).
Google Scholar 
30.Voigt, C. et al. Warming of subarctic tundra increases emissions of all three important greenhouse gases—carbon dioxide, methane, and nitrous oxide. Glob. Change Biol. 23, 3121–3138 (2017).
Google Scholar 
31.Mackelprang, R., Saleska, S. R., Jacobsen, C. S., Jansson, J. K. & Taş, N. Permafrost meta-omics and climate change. Annu. Rev. Earth Planet. Sci. 44, 439–462 (2016).CAS 

Google Scholar 
32.Graham, D. E. et al. Microbes in thawing permafrost: the unknown variable in the climate change equation. ISME J. 6, 709–712 (2012).CAS 

Google Scholar 
33.Abbott, B. W. et al. Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire: an expert assessment. Environ. Res. Lett. 11, 034014 (2016).
Google Scholar 
34.Ren, J. et al. Biomagnification of persistent organic pollutants along a high-altitude aquatic food chain in the Tibetan Plateau: processes and mechanisms. Environ. Pollut. https://doi.org/10.1016/j.envpol.2016.10.019 (2016).35.Dean, J. F. et al. Abundant pre-industrial carbon detected in Canadian Arctic headwaters: implications for the permafrost carbon feedback. Environ. Res. Lett. 13, 34024 (2018).
Google Scholar 
36.Jeffries, M. O., Overland, J. E. & Perovich, D. K. The Arctic shifts to a new normal. Phys. Today 66, 35–40 (2013).
Google Scholar 
37.El-Sayed, A. & Kamel, M. Future threat from the past. Environ. Sci. Pollut. Res. https://doi.org/10.1007/s11356-020-11234-9 (2020).38.Houwenhuyse, S., Macke, E., Reyserhove, L., Bulteel, L. & Decaestecker, E. Back to the future in a petri dish: origin and impact of resurrected microbes in natural populations. Evol. Appl. 11, 29–41 (2018).
Google Scholar 
39.Miner, K. R. et al. Organochlorine pollutants within a polythermal glacier in the Interior Eastern Alaska Range. Water 10, 1157 (2018).
Google Scholar 
40.Li, F. et al. Arctic sea-ice loss intensifies aerosol transport to the Tibetan Plateau. Nat. Clim. Change 10, 1037–1044 (2020).CAS 

Google Scholar 
41.Eriksson, M., Lindahl, P., Roos, P., Dahlgaard, H. & Holm, E. U, Pu, and Am nuclear signatures of the thule hydrogen bomb debris. Environ. Sci. Technol. 42, 4717–4722 (2008).CAS 

Google Scholar 
42.Lind, O. C. et al. Characterization of U/Pu particles originating from the nuclear weapon accidents at Palomares, Spain, 1966 and Thule, Greenland, 1968. Sci. Total Environ. 376, 294–305 (2007).CAS 

Google Scholar 
43.Slemmons, K. E. H., Saros, J. E. & Simon, K. The influence of glacial meltwater on alpine aquatic ecosystems: a review. Environ. Sci. Process. Impacts 15, 1794 (2013).CAS 

Google Scholar 
44.Bidleman, T. F., Jantunen, L. M., Kurt-Karakus, P. B. & Wong, F. Chiral persistent organic pollutants as tracers of atmospheric sources and fate: review and prospects for investigating climate change influences. Atmos. Pollut. Res. 3, 371–382 (2012).CAS 

Google Scholar 
45.Chen, M. et al. Release of perfluoroalkyl substances from melting glacier of the Tibetan Plateau: insights into the impact of global warming on the cycling of emerging pollutants. J. Geophys. Res. Atmos. 124, 7442–7456 (2019).
Google Scholar 
46.Goodman, S. & Kertysova, K. The Nuclearisation of the Russian Arctic: New Reactors, New Risks (European Leadership Network, 2020); https://www.europeanleadershipnetwork.org/wp-content/uploads/2020/06/The-nuclearisation-of-the-Russian-Arctic-2.pdf47.Byrne, S. et al. Persistent organochlorine pesticide exposure related to a formerly used defense site on St. Lawrence Island, Alaska: data from sentinel fish and human sera. Toxicol. Environ. Health 78, 37–54 (2015).
Google Scholar 
48.The National Academies of Sciences Understanding and Responding to Global Health Security Risks from Microbial Threats in the Arctic (National Academies Press, 2020); https://doi.org/10.17226/2588749.Edwards, A. et al. Microbial genomics amidst the Arctic crisis. Microb. Genom. 6, e000375 (2020). Catalogues known genomic diversity, evolution dynamics and environment of Arctic microbes.
Google Scholar 
50.Botnen, S. S., Mundra, S., Kauserud, H. & Eidesen, P. B. Glacier retreat in the high Arctic: opportunity or threat for ectomycorrhizal diversity? FEMS Microbiol. Ecol. https://doi.org/10.1093/femsec/fiaa171 (2020).51.Schuur, E. A. G. et al. Climate change and the permafrost carbon feedback. Nature 520, 171–179 (2015).CAS 

Google Scholar 
52.Ward, C. P., Nalven, S. G., Crump, B. C., Kling, G. W. & Cory, R. M. Photochemical alteration of organic carbon draining permafrost soils shifts microbial metabolic pathways and stimulates respiration. Nat. Commun. 8, 772 (2017).
Google Scholar 
53.Taş, N. et al. Landscape topography structures the soil microbiome in Arctic polygonal tundra. Nat. Commun. 9, 777 (2018).
Google Scholar 
54.Price, P. B. Microbial genesis, life and death in glacial ice. Can. J. Microbiol. 55, 1–11 (2009).CAS 

Google Scholar 
55.Niederberger, T. D. et al. Microbial characterization of a subzero, hypersaline methane seep in the Canadian high Arctic. ISME J. 4, 1326–1339 (2010).CAS 

Google Scholar 
56.Malavin, S., Shmakova, L., Claverie, J. M. & Rivkina, E. Frozen Zoo: a collection of permafrost samples containing viable protists and their viruses. Biodivers. Data J. 8, e51586 (2020).
Google Scholar 
57.Gilichinsky, D., Rivkina, E., Shcherbakova, V., Laurinavichuis, K. & Tiedje, J. Supercooled water brines within permafrost—an unknown ecological niche for microorganisms: a model for astrobiology. Astrobiology 3, 331–341 (2003).CAS 

Google Scholar 
58.Legendre, M. et al. Thirty-thousand-year-old distant relative of giant icosahedral DNA viruses with a pandoravirus morphology. Proc. Natl Acad. Sci. USA 111, 4274–4279 (2014).CAS 

Google Scholar 
59.Legendre, M. et al. In-depth study of Mollivirus sibericum, a new 30,000-yold giant virus infecting Acanthamoeba. Proc. Natl Acad. Sci. USA 112, E5327–E5335 (2015).CAS 

Google Scholar 
60.MacKelprang, R. et al. Metagenomic analysis of a permafrost microbial community reveals a rapid response to thaw. Nature 480, 368–371 (2011). Uses deep metagenomic sequencing to map the impacts of thaw on the Arctic microbial community structure and genomics.CAS 

Google Scholar 
61.Mühlemann, B. et al. Diverse variola virus (smallpox) strains were widespread in northern Europe in the Viking age. Science 369, eaaw8977 (2020).
Google Scholar 
62.Ng, T. F. F. et al. Preservation of viral genomes in 700-y-old caribou feces from a subarctic ice patch. Proc. Natl Acad. Sci. USA 111, 16842–16847 (2014).
Google Scholar 
63.Shmakova, L. et al. A living bdelloid rotifer from 24,000-year-old Arctic permafrost. Curr. Biol. 31, PR712–R713 (2021).
Google Scholar 
64.Siliakus, M. F., van der Oost, J. & Kengen, S. W. M. Adaptations of archaeal and bacterial membranes to variations in temperature, pH and pressure. Extremophiles 21, 651–670 (2017).CAS 

Google Scholar 
65.Edwards, A. Coming in from the cold: potential microbial threats from the terrestrial cryosphere. Front. Earth Sci. 3, 12 (2015).
Google Scholar 
66.Mackelprang, R. et al. Microbial survival strategies in ancient permafrost: insights from metagenomics. ISME J. 11, 2305–2318 (2017).CAS 

Google Scholar 
67.Bale, N. J. et al. Fatty acid and hopanoid adaption to cold in the methanotroph Methylovulum psychrotolerans. Front. Microbiol. 10, 589 (2019).
Google Scholar 
68.Johnson, S. S. et al. Ancient bacteria show evidence of DNA repair. Proc. Natl Acad. Sci. USA 104, 14401–14405 (2007).CAS 

Google Scholar 
69.Ji, M. et al. Atmospheric trace gases support primary production in Antarctic desert surface soil. Nature 552, 400–403 (2017).CAS 

Google Scholar 
70.Burkert, A., Douglas, T. A., Waldrop, M. P. & Mackelprang, R. Changes in the active, dead, and dormant microbial community structure across a Pleistocene permafrost chronosequence. Appl. Environ. Microbiol. 85, e02646–18 (2019).CAS 

Google Scholar 
71.Colangelo-Lillis, J., Eicken, H., Carpenter, S. D. & Deming, J. W. Evidence for marine origin and microbial-viral habitability of subzero hypersaline aqueous inclusions within permafrost near Barrow, Alaska. FEMS Microbiol. Ecol. 92, fiw053 (2016).CAS 

Google Scholar 
72.Boetius, A., Anesio, A. M., Deming, J. W., Mikucki, J. A. & Rapp, J. Z. Microbial ecology of the cryosphere: sea ice and glacial habitats. Nat. Rev. Microbiol. 13, 677–690 (2015).CAS 

Google Scholar 
73.Zhong, Z.-P. et al. Viral ecogenomics of Arctic cryopeg brine and sea ice. mSystems https://doi.org/10.1128/mSystems.00246-20 (2020).74.Bay, S. K. et al. Trace gas oxidizers are widespread and active members of soil microbial communities. Nat. Microbiol. 6, 246–256 (2021).CAS 

Google Scholar 
75.Aslam, S. N., Huber, C., Asimakopoulos, A. G., Steinnes, E. & Mikkelsen, Ø. Trace elements and polychlorinated biphenyls (PCBs) in terrestrial compartments of Svalbard, Norwegian Arctic. Sci. Total Environ. 685, 1127–1138 (2019).CAS 

Google Scholar 
76.Winiger, P. et al. Source apportionment of circum-Arctic atmospheric black carbon from isotopes and modeling. Sci. Adv. 5, eaau8052 (2019).CAS 

Google Scholar 
77.Villa, S., Migliorati, S., Monti, G. S., Holoubek, I. & Vighi, M. Risk of POP mixtures on the Arctic food chain. Environ. Toxicol. Chem. 36, 1181–1192 (2017).CAS 

Google Scholar 
78.Ma, J., Hung, H., Tian, C. & Kallenborn, R. Revolatilization of persistent organic pollutants in the Arctic induced by climate change. Nat. Clim. Change 1, 255–260 (2011).CAS 

Google Scholar 
79.Ji, X., Abakumov, E. & Polyakov, V. Assessments of pollution status and human health risk of heavy metals in permafrost-affected soils and lichens: a case-study in Yamal Peninsula, Russia Arctic. Hum. Ecol. Risk Assess. 25, 2142–2159 (2019).CAS 

Google Scholar 
80.Mu, C. et al. Carbon and mercury export from the Arctic rivers and response to permafrost degradation. Water Res. 161, 54–60 (2019).CAS 

Google Scholar 
81.Brown, T. M., Macdonald, R. W., Muir, D. C. G. & Letcher, R. J. The distribution and trends of persistent organic pollutants and mercury in marine mammals from Canada’s eastern Arctic. Sci. Total Environ. 618, 500–517 (2018).CAS 

Google Scholar 
82.Ferrario, C., Finizio, A. & Villa, S. Legacy and emerging contaminants in meltwater of three alpine glaciers. Sci. Total Environ. 574, 350–357 (2017).CAS 

Google Scholar 
83.Miner, K. R., Bogdal, C., Pavlova, P. A., Steinlin, C. & Kreutz, K. J. Quantitative screening level assessment of human risk from PCB in glacial meltwater: Silvretta Glacier, Swiss Alps. Ecotoxicol. Environ. Saf. 166, 251–258 (2018).CAS 

Google Scholar 
84.Octaviani, M., Stemmler, I., Lammel, G. & Graf, H. F. Atmospheric transport of persistent organic pollutants to and from the Arctic under present-day and future climate. Environ. Sci. Technol. 49, 3593–3602 (2015).CAS 

Google Scholar 
85.Nielsen, S. P., Iosjpe, M. & Strand, P. Collective doses to man from dumping of radioactive waste in the Arctic seas. Sci. Total Environ. 202, 135–146 (1997).CAS 

Google Scholar 
86.Eickmeyer, D. C. et al. Interactions of polychlorinated biphenyls and organochlorine pesticides with sedimentary organic matter of retrogressive thaw slump-affected lakes in the tundra uplands adjacent to the Mackenzie Delta, NT, Canada. J. Geophys. Res. G Biogeosci. 121, 411–421 (2016).CAS 

Google Scholar 
87.St Pierre, K. A. et al. Unprecedented increases in total and methyl mercury concentrations downstream of retrogressive thaw slumps in the western Canadian Arctic. Environ. Sci. Technol. 52, 14099–14109 (2018).
Google Scholar 
88.Birnbaum, L. S. When environmental chemicals act like uncontrolled medicine. Trends Endocrinol. Metab. 24, 321–323 (2013).CAS 

Google Scholar 
89.Potapowicz, J., Szumińska, D., Szopińska, M. & Polkowska, Ż. The influence of global climate change on the environmental fate of anthropogenic pollution released from the permafrost: part I. Case study of Antarctica. Sci. Total Environ. 651, 1534–1548 (2019).CAS 

Google Scholar 
90.Kim, K.-S. et al. Associations of organochlorine pesticides and polychlorinated biphenyls in visceral vs. subcutaneous adipose tissue with type 2 diabetes and insulin resistance. Chemosphere 94, 151–157 (2014).CAS 

Google Scholar 
91.Knutsen, H. K. et al. Risk to human health related to the presence of perfluorooctane sulfonic acid and perfluorooctanoic acid in food. EFSA J. 16, e05194 (2018).
Google Scholar 
92.Iszatt, N. et al. Prenatal and postnatal exposure to persistent organic pollutants and infant growth: a pooled analysis of seven European birth cohorts. Environ. Health Perspect. 123, 730–736 (2015).CAS 

Google Scholar 
93.Nadal, M., Marquès, M., Mari, M. & Domingo, J. L. Climate change and environmental concentrations of POPs: a review. Environ. Res. 143, 177–185 (2015).CAS 

Google Scholar 
94.Toxicological Profile for Lead (Agency for Toxic Substances and Disease Registry, 2020); https://www.atsdr.cdc.gov/toxprofiles/tp13.pdf95.Toxicological Profile for Mercury (Agency for Toxic Substances and Disease Registry, 1999); https://www.atsdr.cdc.gov/ToxProfiles/tp46.pdf96.Toxicological Profile for Cadmium (Agency for Toxic Substances and Disease Registry, 2012); https://www.atsdr.cdc.gov/toxprofiles/tp5.pdf97.Halbach, K., Mikkelsen, Ø., Berg, T. & Steinnes, E. The presence of mercury and other trace metals in surface soils in the Norwegian Arctic. Chemosphere 188, 567–574 (2017).CAS 

Google Scholar 
98.Miner, K. R. et al. Legacy organochlorine pollutants in glacial watersheds: a review. Environ. Sci. Process. Impacts 19, 1474–1483 (2017).CAS 

Google Scholar 
99.Jamieson, H. E. The legacy of arsenic contamination from mining and processing refractory gold ore at Giant Mine, Yellowknife, Northwest Territories, Canada. Rev. Mineral. Geochem. 79, 533–551 (2014).
Google Scholar 
100.Tolvanen, A. et al. Mining in the Arctic environment—a review from ecological, socioeconomic and legal perspectives. J. Environ. Manag. 233, 832–844 (2019).
Google Scholar 
101.Liu, X., Jiang, S., Zhang, P. & Xu, L. Effect of recent climate change on Arctic Pb pollution: a comparative study of historical records in lake and peat sediments. Environ. Pollut. 160, 161–168 (2012).CAS 

Google Scholar 
102.Antcibor, I. et al. Trace metal distribution in pristine permafrost-affected soils of the Lena River delta and its hinterland, northern Siberia, Russia. Biogeosciences 11, 1–15 (2014).
Google Scholar 
103.Lim, A. G. et al. A revised pan-Arctic permafrost soil Hg pool based on western Siberian peat Hg and carbon observations. Biogeosciences 17, 3083–3097 (2020).CAS 

Google Scholar 
104.Schuster, P. F. et al. Permafrost stores a globally significant amount of mercury. Geophys. Res. Lett. 45, 1463–1471 (2018).CAS 

Google Scholar 
105.Schaefer, K. et al. Potential impacts of mercury released from thawing permafrost. Nat. Commun. 11, 4650 (2020). Estimates future releases of mercury from the permafrost from present to 2300, under RCP scenarios.CAS 

Google Scholar 
106.Jiskra, M. E., Sonke, J., Agnan, Y., Helmig, D. & Obrist, D. Insights from mercury stable isotopes on terrestrial-atmosphere exchange of Hg(0) in the Arctic tundra. Biogeosciences 16, 4051–4064 (2019).CAS 

Google Scholar 
107.Blais, J. M. et al. Arctic seabirds transport marine-derived contaminants. Science 309, 445 (2005).CAS 

Google Scholar 
108.Brimble, S. K. et al. High Arctic ponds receiving biotransported nutrients from a nearby seabird colony are also subject to potentially toxic loadings of arsenic, cadmium, and zinc. Environ. Toxicol. Chem. 28, 2426–2433 (2009).CAS 

Google Scholar 
109.Michelutti, N. et al. Trophic position influences the efficacy of seabirds as metal biovectors. Proc. Natl Acad. Sci. USA 107, 10543–10548 (2010).CAS 

Google Scholar 
110.Mallory, M. L. & Braune, B. M. Tracking contaminants in seabirds of Arctic Canada: temporal and spatial insights. Mar. Pollut. Bull. 64, 1475–1484 (2012).CAS 

Google Scholar 
111.Lehnherr, I. Methylmercury biogeochemistry: a review with special reference to Arctic aquatic ecosystems. Environ. Rev. 22, 229–243 (2014).CAS 

Google Scholar 
112.Steinlin, C. et al. A temperate alpine glacier as a reservoir of polychlorinated biphenyls: model results of incorporation, transport, and release. Environ. Sci. Technol. 50, 5572–5579 (2016).CAS 

Google Scholar 
113.Pavlova, P. A., Schmid, P., Zennegg, M., Bogdal, C. & Schwikowski, M. Trace analysis of hydrophobic micropollutants in aqueous samples using capillary traps. Chemosphere 106, 51–56 (2014).CAS 

Google Scholar 
114.Blais, J. M. et al. Melting glaciers: a major source of persistent organochlorines to subalpine Bow Lake in Banff National Park, Canada. Ambio 30, 410–415 (2001).CAS 

Google Scholar 
115.Lafrenière, M. J., Blais, J. M., Sharp, M. J. & Schindler, D. W. Organochlorine pesticide and polychlorinated biphenyl concentrations in snow, snowmelt, and runoff at Bow Lake, Alberta. Environ. Sci. Technol. 40, 4909–4915 (2006).
Google Scholar 
116.Elliott, J. E. et al. Factors influencing legacy pollutant accumulation in alpine osprey: biology, topography, or melting glaciers? Environ. Sci. Technol. 46, 9681–9689 (2012).CAS 

Google Scholar 
117.Walters, D. M. et al. Trophic magnification of organic chemicals: a global synthesis. Environ. Sci. Technol. 50, 4650–4658 (2016).CAS 

Google Scholar 
118.Miner, K. R., Wayant, N. & Ward, H. Preventing chemical release in hurricanes. Science 362, 166 (2018).CAS 

Google Scholar 
119.Quadroni, S. & Bettinetti, R. Health risk assessment for the consumption of fresh and preserved fish (Alosa agone) from Lago di Como (northern Italy). Environ. Res. 156, 571–578 (2017).CAS 

Google Scholar 
120.Mangano, M. C., Sarà, G. & Corsolini, S. Monitoring of persistent organic pollutants in the polar regions: knowledge gaps & gluts through evidence mapping. Chemosphere 172, 37–45 (2017).CAS 

Google Scholar 
121.Villa, S., Vighi, M., Maggi, V., Finizio, A. & Bolzacchini, E. Historical trends of organochlorine pesticides in an alpine glacier. J. Atmos. Chem. 46, 295–311 (2003).CAS 

Google Scholar 
122.Garmash, O. et al. Deposition history of polychlorinated biphenyls to the Lomonosovfonna glacier, Svalbard: a 209 congener analysis. Environ. Sci. Technol. 47, 12064–12072 (2013).CAS 

Google Scholar 
123.Bizzotto, E. C., Villa, S., Vaj, C. & Vighi, M. Comparison of glacial and non-glacial-fed streams to evaluate the loading of persistent organic pollutants through seasonal snow/ice melt. Chemosphere 74, 924–930 (2009).CAS 

Google Scholar 
124.Villa, S., Negrelli, C., Finizio, A., Flora, O. & Vighi, M. Organochlorine compounds in ice melt water from Italian alpine rivers. Ecotoxicol. Environ. Saf. 63, 84–90 (2006).CAS 

Google Scholar 
125.Miner, K. R. et al. A screening-level approach to quantifying risk from glacial release of organochlorine pollutants in the Alaskan Arctic. J. Expo. Sci. Environ. Epidemiol. 29, 293–301 (2018). Develops the first human risk assessment of glacially stored pollutants in the Arctic.
Google Scholar 
126.Czub, G. & McLachlan, M. S. A food chain model to predict the levels of lipophilic organic contaminants in humans. Environ. Toxicol. Chem. 23, 2356–2366 (2004).CAS 

Google Scholar 
127.Wang, X., Gong, P., Wang, C., Ren, J. & Yao, T. A review of current knowledge and future prospects regarding persistent organic pollutants over the Tibetan Plateau. Sci. Total Environ. 573, 139–154 (2016).CAS 

Google Scholar 
128.Desforges, J. P. et al. Predicting global killer whale population collapse from PCB pollution. Science 361, 1373–1376 (2018).CAS 

Google Scholar 
129.Macdonald, R. W. et al. Contaminants in the Canadian Arctic: 5 years of progress in understanding sources, occurrence and pathways. Sci. Total Environ. 254, 93–234 (2000).CAS 

Google Scholar 
130.Pavlova, P. A. et al. Polychlorinated biphenyls in a temperate alpine glacier: 1. Effect of percolating meltwater on their distribution in glacier ice. Environ. Sci. Technol. 49, 14085–14091 (2015).CAS 

Google Scholar 
131.Wania, F., Westgate, J. N., Technol, E. S. & Asap, A. On the mechanism of mountain cold-trapping of organic chemicals. Environ. Sci. Technol. 42, 9092–9098 (2008).CAS 

Google Scholar 
132.Strand, P. & Cooke, A. Environmental Radioactivity in the Arctic (Scientific Committee of the Environmental Radioactivity in the Arctic, 1995).133.Wright, S. M. et al. Spatial variation in the vulnerability of Norwegian Arctic counties to radiocaesium deposition. Sci. Total Environ. 202, 173–184 (1997).CAS 

Google Scholar 
134.Mitchell, P. I., León Vintró, L., Dahlgaard, H., Gascó, C. & Sánchez-Cabeza, J. A. Perturbation in the 240Pu/239Pu global fallout ratio in local sediments following the nuclear accidents at Thule (Greenland) and Palomares (Spain). Sci. Total Environ. 202, 147–153 (1997).CAS 

Google Scholar 
135.Khalturin, V. I., Rautian, T. G., Richards, P. G. & Leith, W. S. A review of nuclear testing by the Soviet Union at Novaya Zemlya, 1955–1990. Sci. Glob. Secur. 13, 1–42 (2005). Reviews the Novaya Zemlya nuclear testing site history, nuclear releases and posits environmental distribution.
Google Scholar 
136.Travkina, A. V. et al. Monitoring the environmental contamination of Kara Sea and shallow bays of Novaya Zemlya. J. Radioanal. Nucl. Chem. 311, 1673–1680 (2017).CAS 

Google Scholar 
137.Skorve, J. The environment of the nuclear test sites on Novaya Zemlya. Sci. Total Environ. 202, 167–172 (1997).CAS 

Google Scholar 
138.Sarkisov, A. A. The question of clean-up of radioactive contamination in the Arctic region. Her. Russ. Acad. Sci. 89, 7–22 (2019).
Google Scholar 
139.Pogrebov, V. B., Fokin, S. I., Galtsova, V. V. & Ivanov, G. I. Benthic communities as influenced by nuclear testing and radioactive waste disposal off Novaya Zemlya in the Russian Arctic. Mar. Pollut. Bull. 35, 333–339 (1997).CAS 

Google Scholar 
140.Miroshnikov, A. Y. et al. Radioecological investigations on the northern Novaya Zemlya Archipelago. Oceanology 57, 204–214 (2017).
Google Scholar 
141.Salbu, B. et al. Radioactive contamination from dumped nuclear waste in the Kara Sea—results from the joint Russian-Norwegian expeditions in 1992-1994. Sci. Total Environ. 202, 185–198 (1997).CAS 

Google Scholar 
142.Oughton, D. H., Børretzen, P., Salbu, B. & Tronstad, E. Mobilisation of 137Cs and 90Sr from sediments: potential sources to Arctic waters. Sci. Total Environ. 202, 155–165 (1997).CAS 

Google Scholar 
143.Faria, S. H., Weikusat, I. & Azuma, N. The microstructure of polar ice. Part I: highlights from ice core research. J. Struct. Geol. 61, 2–20 (2014).
Google Scholar 
144.Karlsson, N. B. et al. Ice-penetrating radar survey of the subsurface debris field at Camp Century, Greenland. Cold Reg. Sci. Technol. 165, 102788 (2019). The most recent ice-penetrating radar survey of Camp Century, Greenland, characterizing the location and concentration of wastes.
Google Scholar 
145.Vandecrux, B., Colgan, W. T., Solgaard, A., Steffensen, J. P. & Karlsson, N. B. Firn evolution at Camp Century, Greenland: 1966-2100. Front. Earth Sci. 9, 578978 (2021).
Google Scholar 
146.Vila, E., Hornero-Méndez, D., Azziz, G., Lareo, C. & Saravia, V. Carotenoids from heterotrophic bacteria isolated from Fildes Peninsula, King George Island, Antarctica. Biotechnol. Rep. 21, e00306 (2019).
Google Scholar 
147.Chaudhary, D. K., Kim, D. U., Kim, D. & Kim, J. Flavobacterium petrolei sp. nov., a novel psychrophilic, diesel-degrading bacterium isolated from oil-contaminated Arctic soil. Sci. Rep. 9, 4134 (2019).
Google Scholar 
148.de Gouw, J. A. et al. Daily satellite observations of methane from oil and gas production regions in the United States. Sci. Rep. 10, 1379 (2020).
Google Scholar 
149.Girardot, F. et al. Bacterial diversity on an abandoned, industrial wasteland contaminated by polychlorinated biphenyls, dioxins, furans and trace metals. Sci. Total Environ. 748, 141242 (2020).CAS 

Google Scholar 
150.Price, P. B. Microbial life in glacial ice and implications for a cold origin of life. FEMS Microbiol. Ecol. 59, 217–231 (2007).CAS 

Google Scholar 
151.Schütte, U. M. E. et al. Effect of permafrost thaw on plant and soil fungal community in a boreal forest: does fungal community change mediate plant productivity response? J. Ecol. 107, 1737–1752 (2019).
Google Scholar 
152.Jensen, P. E., Hennessy, T. W. & Kallenborn, R. Water, sanitation, pollution, and health in the Arctic. Environ. Sci. Pollut. Res. 25, 32827–32830 (2018).
Google Scholar 
153.Ewing, S. A. et al. Long-term anoxia and release of ancient, labile carbon upon thaw of Pleistocene permafrost. Geophys. Res. Lett. 42, 10730–10738 (2015).CAS 

Google Scholar 
154.Elder, C. D. et al. Seasonal sources of whole-lake CH4 and CO2 emissions from interior Alaskan thermokarst lakes. J. Geophys. Res. Biogeosci. 124, 1209–1229 (2019).CAS 

Google Scholar 
155.Jansen, E. et al. Past perspectives on the present era of abrupt Arctic climate change. Nat. Clim. Change 10, 714–721 (2020).
Google Scholar 
156.Nellier, Y.-M. et al. Mass budget in two high altitude lakes reveals their role as atmospheric PCB sinks. Sci. Total Environ. 511, 203–213 (2015).CAS 

Google Scholar 
157.Garnett, J. et al. Mechanistic insight into the uptake and fate of persistent organic pollutants in sea ice. Environ. Sci. Technol. 53, 6757–6764 (2019).CAS 

Google Scholar 
158.Kortenkamp, A. & Faust, M. Regulate to reduce chemical mixture risk. Science 361, 224–226 (2018).CAS 

Google Scholar 
159.Kirchgeorg, T. et al. Seasonal accumulation of persistent organic pollutants on a high altitude glacier in the eastern Alps. Environ. Pollut. 218, 804–812 (2016).CAS 

Google Scholar 
160.Weil, T. et al. Legal immigrants: invasion of alien microbial communities during winter occurring desert dust storms. Microbiome 5, 32 (2017).
Google Scholar 
161.Li, J. et al. Evidence for persistent organic pollutants released from melting glacier in the central Tibetan Plateau, China. Environ. Pollut. 220, 178–185 (2017).CAS 

Google Scholar 
162.Walvoord, M. A., Voss, C. I., Ebel, B. A. & Minsley, B. J. Development of perennial thaw zones in boreal hillslopes enhances potential mobilization of permafrost carbon. Environ. Res. Lett. 14, 015003 (2019).CAS 

Google Scholar 
163.Mogrovejo, D. C. et al. Prevalence of antimicrobial resistance and hemolytic phenotypes in culturable Arctic bacteria. Front. Microbiol. 11, 570 (2020).
Google Scholar 
164.Friedman, C. L. & Selin, N. E. Long-range atmospheric transport of polycyclic aromatic hydrocarbons: a global 3-D model analysis including evaluation of Arctic sources. Environ. Sci. Technol. 46, 9501–9510 (2012).CAS 

Google Scholar 
165.Myers-Smith, I. H. et al. Complexity revealed in the greening of the Arctic. Nat. Clim. Change 10, 106–117 (2020).
Google Scholar 
166.Vonk, J. E. et al. Reviews and syntheses: effects of permafrost thaw on Arctic aquatic ecosystems. Biogeosciences 12, 7129–7167 (2015).CAS 

Google Scholar 
167.MacInnis, J. J. et al. Fate and transport of perfluoroalkyl substances from snowpacks into a lake in the high Arctic of Canada. Environ. Sci. Technol. 53, 10753–10762 (2019).CAS 

Google Scholar 
168.Yeung, L. W. Y. et al. Vertical profiles, sources, and transport of PFASs in the Arctic Ocean. Environ. Sci. Technol. 51, 6735–6744 (2017).CAS 

Google Scholar 
169.Colatriano, D. et al. Genomic evidence for the degradation of terrestrial organic matter by pelagic Arctic Ocean Chloroflexi bacteria. Commun. Biol. 1, 90 (2018).
Google Scholar 
170.Commane, R. et al. Carbon dioxide sources from Alaska driven by increasing early winter respiration from Arctic tundra. Proc. Natl Acad. Sci. USA 114, 5361–5366 (2017).CAS 

Google Scholar 
171.Hartmann, M. et al. Variation of ice nucleating particles in the European Arctic over the last centuries. Geophys. Res. Lett. https://doi.org/10.1029/2019GL082311 (2019).172.Murray, B. J., Carslaw, K. S. & Field, P. R. Opinion: cloud-phase climate feedback and the importance of ice-nucleating particles. Atmos. Chem. Phys. 21, 665–679 (2021).CAS 

Google Scholar 
173.Joyce, R. E. et al. Biological ice-nucleating particles deposited year-round in subtropical precipitation. Appl. Environ. Microbiol. 85, e01567-19 (2019).
Google Scholar 
174.Yumashev, D., van Hussen, K., Gille, J. & Whiteman, G. Towards a balanced view of Arctic shipping: estimating economic impacts of emissions from increased traffic on the Northern Sea Route. Clim. Change 143, 143–155 (2017).CAS 

Google Scholar 
175.Ramage, J. et al. Population living on permafrost in the Arctic. Popul. Environ. https://doi.org/10.1007/s11111-020-00370-6 (2021).176.Bartsch, A., Pointner, G., Ingeman-Nielsen, T. & Lu, W. Towards circumpolar mapping of Arctic settlements and infrastructure based on Sentinel-1 and Sentinel-2. Remote Sens. 12, 2368 (2020).
Google Scholar 
177.Dewailly, E. Canadian Inuit and the Arctic dilemma. Oceanography 19, 88–89 (2006).
Google Scholar 
178.Plaza, C. et al. Direct observation of permafrost degradation and rapid soil carbon loss in tundra. Nat. Geosci. 12, 627–631 (2019).CAS 

Google Scholar 
179.Kashuba, E. et al. Ancient permafrost staphylococci carry antibiotic resistance genes. Microb. Ecol. Health Dis. https://doi.org/10.1080/16512235.2017.1345574 (2017).180.Dcosta, V. M. et al. Antibiotic resistance is ancient. Nature 477, 457–461 (2011).CAS 

Google Scholar 
181.Perron, G. G. et al. Functional characterization of bacteria isolated from ancient Arctic soil exposes diverse resistance mechanisms to modern antibiotics. PLoS ONE 10, e0069533 (2015).
Google Scholar 
182.Gilichinsky, D. et al. in Psychrophiles: From Biodiversity to Biotechnology (eds Margesin, R. et al.) 83–102 (Springer-Verlag, 2008).183.Forsberg, K. J. et al. The shared antibiotic resistome of soil bacteria and human pathogens. Science 337, 1107–1111 (2012).CAS 

Google Scholar 
184.Woodcroft, B. J. et al. Genome-centric view of carbon processing in thawing permafrost. Nature 560, 49–54 (2018).CAS 

Google Scholar 
185.Taubenberger, J. K. et al. Reconstruction of the 1918 influenza virus: unexpected rewards from the past. mBio 3, e00201–12 (2012).
Google Scholar 
186.Jordan, D., Tumpey, T. & Jester, B. The Deadliest Flu: The Complete Story of the Discovery and Reconstruction of the 1918 Pandemic Virus (US Center for Disease Control, 2019).187.Tumpey, T. M. et al. Characterization of the reconstructed 1918 Spanish influenza pandemic virus. Science 310, 77–80 (2005).CAS 

Google Scholar 
188.Revich, B., Tokarevich, N. & Parkinson, A. J. Climate change and zoonotic infections in the Russian Arctic. Int. J. Circumpolar Health 71, 18792 (2012).
Google Scholar 
189.Waits, A., Emelyanova, A., Oksanen, A., Abass, K. & Rautio, A. Human infectious diseases and the changing climate in the Arctic. Environ. Int. 121, 703–713 (2018).
Google Scholar 
190.Hueffer, K., Drown, D., Romanovsky, V. & Hennessy, T. Factors contributing to anthrax outbreaks in the circumpolar north. Ecohealth 17, 174–180 (2020).
Google Scholar 
191.Springer, Y. P. et al. Novel Orthopoxvirus infection in an Alaska resident. Clin. Infect. Dis. 64, 1737–1741 (2017).
Google Scholar 
192.Mackay, D. Multimedia Environmental Models (CRC Press, 2001).193.Mackay, D., Celsie, A. K. D., Powell, D. E. & Parnis, J. M. Bioconcentration, bioaccumulation, biomagnification and trophic magnification: a modelling perspective. Environ. Sci. Process. Impacts 20, 72–85 (2018).CAS 

Google Scholar 
194.Vizcaino, E., Grimalt, J. O., Fernandez-Somoano, A. & Tardon, A. Transport of persistent organic pollutants across the human placenta. Environ. Int. 65, 107–115 (2014).CAS 

Google Scholar 
195.Costa, O. et al. First-trimester maternal concentrations of polyfluoroalkyl substances and fetal growth throughout pregnancy. Environ. Int. https://doi.org/10.1016/j.envint.2019.05.024 (2019).196.Adetona, O. et al. Concentrations of select persistent organic pollutants across pregnancy trimesters in maternal and in cord serum in Trujillo, Peru. Chemosphere 91, 1426–1433 (2013).CAS 

Google Scholar 
197.Toxicological Profile for Plutonium (Agency for Toxic Substances and Disease Registry, 2010); https://www.atsdr.cdc.gov/toxprofiles/tp143.pdf198.Toxicological Profile for Cesium (Agency for Toxic Substances and Disease Registry, 2004); https://www.atsdr.cdc.gov/toxprofiles/tp157.pdf199.Serikova, S. et al. High carbon emissions from thermokarst lakes of western Siberia. Nat. Commun. 10, 1552 (2019).CAS 

Google Scholar 
200.Swingedouw, D. et al. Early warning from space for a few key tipping points in physical, biological, and social-ecological systems. Surv. Geophys. https://doi.org/10.1007/s10712-020-09604-6 (2020).201.Lewkowicz, A. G. & Way, R. G. Extremes of summer climate trigger thousands of thermokarst landslides in a high Arctic environment. Nat. Commun. 10, 1329 (2019).
Google Scholar 
202.Tank, S. E. et al. Landscape matters: predicting the biogeochemical effects of permafrost thaw on aquatic networks with a state factor approach. Permafr. Periglac. Process. https://doi.org/10.1002/ppp.2057 (2020).203.Feng, J. et al. Warming-induced permafrost thaw exacerbates tundra soil carbon decomposition mediated by microbial community. Microbiome 8, 3 (2020).
Google Scholar 
204.Stein, A. F. et al. NOAA’s HYSPLIT atmospheric transport and dispersion modeling system. Bull. Am. Meteorol. Soc. 96, 2059–2077 (2015).
Google Scholar 
205.Donald, D. B. et al. Delayed deposition of organochlorine pesticides at a temperate glacier. Environ. Sci. Technol. 33, 1794–1798 (1999).CAS 

Google Scholar 
206.Hermanson, M. H. et al. Current-use and legacy pesticide history in the Austfonna ice cap, Svalbard, Norway. Environ. Sci. Technol. 39, 8163–8169 (2005).CAS 

Google Scholar 
207.Salvadó, J. A., Sobek, A., Carrizo, D. & Gustafsson, Ö. Observation-based assessment of PBDE loads in Arctic ocean waters. Environ. Sci. Technol. 50, 2236–2245 (2016).
Google Scholar 
208.Vecchiato, M. et al. The great acceleration of fragrances and PAHs archived in an ice core from Elbrus, Caucasus. Sci. Rep. 10, 10661 (2020).CAS 

Google Scholar 
209.Miteva, V., Teacher, C., Sowers, T. & Brenchley, J. Comparison of the microbial diversity at different depths of the GISP2 Greenland ice core in relationship to deposition climates. Environ. Microbiol. 11, 640–656 (2009).CAS 

Google Scholar  More

Our measure of interest was whether females ate more of the flake items (i.e., cheated less quickly) when the male had perceptual access than when he did not. Consistent with our predictions, females ate fewer flake items in the male not visible condition (Mean = 3.6 items, SD = 3.2) than in the male visible condition (Mean = 4.5, SD = 3.1; Fig. 2A; for flake items eaten by pairs see Supplementary Fig. S1). Additionally, females tended to cheat less over rounds (Supplementary Fig. S2). Indeed, the number of flake items eaten was predicted by both conditions (LRT, X21 = 8.13, p = 0.004; Fig. 2A; Supplementary Table S1) and round (LRT, X21 = 12.46, p  More

1.Aluja, M. Fruit fly (Diptera: Tephritidae) research in Latin America: myths, realities and dreams. Soc. Entomol. Bras. 28, 565–594 (1999).Article 

Google Scholar 
2.Weldon, C. W., Yap, S. & Taylor, P. W. Desiccation resistance of wild and mass-reared Bactrocera tryoni (Diptera: Tephritidae). Bull. Entomol. Res. 103, 690–699 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
3.Weldon, C. W., Boardman, L., Marlin, D. & Terblanche, J. S. Physiological mechanisms of dehydration tolerance contribute to the invasion potential of Ceratitis capitata (Wiedemann) (Diptera: Tephritidae) relative to its less widely distributed congeners. Front. Zool. 13, 15 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
4.Weldon, C. W., Díaz-Fleischer, F. & Pérez-Staples, D. in Area-Wide Management of Fruit Fly Pests (eds. Pérez-Staples, D. et al.) 27–43 (CRC Press, 2020).5.Malacrida, A. R. et al. Globalization and fruit fly invasion and expansion: the medfly paradigm. Genetica 131, 1–9 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
6.Diamantidis, A. D., Carey, J. R., Nakas, C. T. & Papadopoulos, N. T. Ancestral populations perform better in a novel environment: domestication of Mediterranean fruit fly populations from five global regions. Biol. J. Linn. Soc. 102, 334–345 (2011).Article 

Google Scholar 
7.Diamantidis, A. D. et al. Life history evolution in a globally invading tephritid: patterns of survival and reproduction in medflies from six world regions. Biol. J. Linn. Soc. 97, 106–117 (2009).Article 

Google Scholar 
8.Papadopoulos, N. T., Plant, R. E. & Carey, J. R. From trickle to flood: the large-scale, cryptic invasion of California by tropical fruit flies. Proc. R. Soc. Biol. Sci. Ser. B 280, 20131466 (2013).Article 

Google Scholar 
9.EUPHRESCO, project FLY_DETECT. Development and implementation of early detection tools and effective management strategies for invasive non-European and other selected fruit fly species of economic importance (FLY DETECT). Final report. https://doi.org/10.5281/zenodo.3732297. (2020)10.FSA PLH Panel, (EFSA Panel on Plant Health). Pest categorisation of non-EU Tephritidae. EFSA J. 18, e05931 (2020).
Google Scholar 
11.Carey, J. R. The Mediterranean fruit fly (Ceratitis capitata). Am. Entomol. 56, 158–163 (2010).Article 

Google Scholar 
12.Gutierrez, A. P. Applied Population Ecology: A Supply-Demand Approach. (Wiley, 1996).13.Sinclair, T. R. & Seligman, N. G. Crop modeling: from infancy to maturity. Agron. J. 88, 698–704 (1996).Article 

Google Scholar 
14.Gutierrez, A. P. & Ponti, L. Eradication of invasive species: why the biology matters. Environ. Entomol. 42, 395–411 (2013).PubMed 
Article 
PubMed Central 

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

Google Scholar 
16.Neteler, M., Bowman, M. H., Landa, M. & Metz, M. GRASS GIS: a multi-purpose Open Source GIS. Environ. Model. Softw. 31, 124–130 (2012).Article 

Google Scholar 
17.Ekesi, S., Mohamed, S. & Meyer, M. D. Fruit Fly Research and Development in Africa—Towards a Sustainable Management Strategy to Improve Horticulture. (Springer, 2016).18.Vera, M. T., Rodriguez, R., Segura, D. F., Cladera, J. L. & Sutherst, R. W. Potential geographical distribution of the Mediterranean fruit fly, Ceratitis capitata (Diptera: Tephritidae), with emphasis on Argentina and Australia. Environ. Entomol. 31, 1009–1022 (2002).Article 

Google Scholar 
19.De Meyer, M., Robertson, M. P., Peterson, A. T. & Mansell, M. W. Ecological niches and potential geographical distributions of Mediterranean fruit fly (Ceratitis capitata) and Natal fruit fly (Ceratitis rosa). J. Biogeogr. 35, 270–281 (2008).Article 

Google Scholar 
20.Tuel, A. & Eltahir, E. A. B. Why is the Mediterranean a climate change hot spot? J. Clim. 33, 5829–5843 (2020).Article 

Google Scholar 
21.Gaston, K. J. Geographic range limits: achieving synthesis. Proc. R. Soc. Biol. Sci. Ser. B 276, 1395–1406 (2009).Article 

Google Scholar 
22.IPCC, Intergovernmental Panel on Climate Change. Climate change 2014: Impacts, Adaptation, and Vulnerability. Part A: global and sectoral aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. (Cambridge University Press, 2014).23.Godefroid, M., Cruaud, A., Rossi, J. P. & Rasplus, J. Y. Assessing the risk of invasion by Tephritid fruit flies: intraspecific divergence matters. PLoS ONE 10, e0135209 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
24.Ponti, L. et al. Biological invasion risk assessment of Tuta absoluta: mechanistic versus correlative methods. Biol. Invasions (in press).25.Carey, J. R., Papadopoulos, N. & Plant, R. The 30‐year debate on a multi‐billion‐dollar threat: tephritid fruit fly establishment in California. Am. Entomol. 63, 100–113 (2017).Article 

Google Scholar 
26.Gutierrez, A. P., Ponti, L. & Gilioli, G. Comments on the concept of ultra-low, cryptic tropical fruit fly populations. Proc. R. Soc. B Biol. Sci. 281, 20132825 (2014).Article 

Google Scholar 
27.McInnis, D. O. et al. Can polyphagous invasive tephritid pest populations escape detection for years under favorable climatic and host conditions? Am. Entomol. 63, 89–99 (2017).Article 

Google Scholar 
28.Barr, N. B. et al. Genetic diversity of Bactrocera dorsalis (Diptera: Tephritidae) on the Hawaiian islands: implications for an introduction pathway into California. J. Econ. Entomol. 107, 1946–1958 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
29.Davies, N., Villablanca, F. X. & Roderick, G. K. Bioinvasions of the medfly Ceratitis capitata: source estimation using DNA sequences at multiple intron loci. Genetics 153, 351–360 (1999).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
30.Meixner, M. D., McPheron, B. A., Silva, J. G., Gasparich, G. E. & Sheppard, W. S. The Mediterranean fruit fly in California: evidence for multiple introductions and persistent populations based on microsatellite and mitochondrial DNA variability. Mol. Ecol. Notes 11, 891–899 (2002).CAS 
Article 

Google Scholar 
31.Gutierrez, A. P., Ponti, L. & Cossu, Q. A. Effects of climate warming on olive and olive fly (Bactrocera oleae (Gmelin)) in California and Italy. Clim. Change 95, 195–217 (2009).Article 

Google Scholar 
32.Johnson, M. W. et al. High temperature affects olive fruit fly populations in California’s Central Valley. Calif. Agric. 65, 29–33 (2011).Article 

Google Scholar 
33.Gutierrez, A. P., Ponti, L. & Dalton, D. T. Analysis of the invasiveness of spotted wing Drosophila (Drosophila suzukii) in North America, Europe, and the Mediterranean Basin. Biol. Invasions 18, 3647–3663 (2016).Article 

Google Scholar 
34.Ponti, L., Gutierrez, A. P., Ruti, P. M. & Dell’Aquila, A. Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers. Proc. Natl Acad. Sci. USA 111, 5598–5603 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
35.Andrewartha, H. G. & Birch, L. C. The Distribution and Abundance of Animals. (The University of Chicago Press, 1954).36.Huffaker, C. B. & Messenger, P. S. Theory and Practice of Biological Control. (Academic Press, 1976).37.Palladino, P. Defining ecology: ecological theories, mathematical models, and applied biology in the 1960s and 1970s. J. Hist. Biol. 24, 223–243 (1991).Article 

Google Scholar 
38.Dormann, C. F., Fründ, J. & Schaefer, H. M. Identifying causes of patterns in ecological networks: opportunities and limitations. Annu. Rev. Ecol. Evol. Syst. 48, 559–584 (2017).Article 

Google Scholar 
39.Evans, M. R. Modelling ecological systems in a changing world. Philos. Trans. R. Soc. B Biol. Sci. 367, 181–190 (2012).Article 

Google Scholar 
40.Jørgensen, S. E., Nielsen, S. N. & Fath, B. D. Recent progress in systems ecology. Ecol. Model. 319, 112–118 (2016).Article 

Google Scholar 
41.FSA PLH Panel, (EFSA Panel on Plant Health). Pest categorisation of non-EU Tephritidae. EFSA J. 18, e05931 (2020).
Google Scholar 
42.Messenger, P. S. & van den Bosch, R. in Biological Control (ed. Huffaker, C. B.) 511 (Plenum/Rosetta Press, 1969).43.Grout, T. G. & Stoltz, K. C. Developmental rates at constant temperatures of three economically important Ceratitis spp. (Diptera: Tephritidae) from southern Africa. Environ. Entomol. 36, 1310–1317 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
44.Papanastasiou, S. A., Nestel, D., Diamantidis, A. D., Nakas, C. T. & Papadopoulos, N. T. Physiological and biological patterns of a highland and a coastal population of the European cherry fruit fly during diapause. J. Insect Physiol. 57, 83–93 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
45.Müller, H. G., Wu, S., Diamantidis, A. D., Papadopoulos, N. T. & Carey, J. R. Reproduction is adapted to survival characteristics across geographically isolated medfly populations. Proc. R. Soc. Biol. Sci. Ser. B 276, 4409–4416 (2009).Article 

Google Scholar 
46.Wang, J., Zeng, L. & Han, Z. An assessment of cold hardiness and biochemical adaptations for cold tolerance among different geographic populations of the Bactrocera dorsalis (Diptera: Tephritidae) in China. J. Insect Sci. Ludhiana 14, 292 (2014).47.Aluja, M. et al. Nonhost status of Citrus sinensis cultivar Valencia and C. paradisi cultivar Ruby Red to Mexican Anastrepha fraterculus (Diptera: Tephritidae). J. Econ. Entomol. 96, 1693–1703 (2003).PubMed 
Article 
PubMed Central 

Google Scholar 
48.Dupuis, J. R., Ruiz‐Arce, R., Barr, N. B., Thomas, D. B. & Geib, S. M. Range‐wide population genomics of the Mexican fruit fly: toward development of pathway analysis tools. Evol. Appl. 12, 1641–1660 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
49.Bennett, J. M. et al. The evolution of critical thermal limits of life on Earth. Nat. Commun. 12, 1198 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
50.Ricalde, M. P., Nava, D. E., Loeck, A. E. & Donatti, M. G. Temperature-dependent development and survival of Brazilian populations of the Mediterranean fruit fly, Ceratitis capitata, from tropical, subtropical and temperate regions. J. Insect Sci. 12, 33 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
51.Duyck, P. F. & Quilici, S. Survival and development of different life stages of three Ceratitis spp. (Diptera: Tephritidae) reared at five constant temperatures. Bull. Entomol. Res. 92, 461–469 (2002).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
52.Gutierrez, A. P. & Regev, U. The bioeconomics of tritrophic systems: applications to invasive species. Ecol. Econ. 52, 383–396 (2005).Article 

Google Scholar 
53.Gutierrez, A. P. & Ponti, L. The new world screwworm: prospective distribution and role of weather in eradication. Agric. Entomol. 16, 158–173 (2014).Article 

Google Scholar 
54.Gutierrez, A. P., Ponti, L. & Arias, P. A. Deconstructing the eradication of new world screwworm in North America: retrospective analysis and climate warming effects. Med. Vet. Entomol. 33, 282–295 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
55.Egartner, A. & Lethmayer, C. Invasive fruit flies of economic importance in Austria – monitoring activities 2016. IOBCWPRS Bull. 123, 45–49 (2017).
Google Scholar 
56.Nugnes, F., Russo, E., Viggiani, G. & Bernardo, U. First record of an invasive fruit fly belonging to Bactrocera dorsalis complex (Diptera: Tephritidae) in Europe. Insects 9, 182 (2018).PubMed Central 
Article 

Google Scholar 
57.Liebhold, A. M. et al. Eradication of invading insect populations: from concepts to applications. Annu. Rev. Entomol. 61, 335–352 (2016).58.Tobin, P. C. et al. Determinants of successful arthropod eradication programs. Biol. Invasions 16, 401–414 (2014).Article 

Google Scholar 
59.Gilbert, N., Gutierrez, A. P., Frazer, B. D. & Jones, R. E. Ecological Relationships. (W.H. Freeman and Co., 1976).60.Gutierrez, A. P. Applied Population Ecology: A Supply-Demand Approach (Wiley, 1996).61.Gutierrez, A. P. The physiological basis of ratio-dependent predator-prey theory: the metabolic pool model as a paradigm. Ecology 73, 1552–1563 (1992).Article 

Google Scholar 
62.Gutierrez, A. P., Mills, N. J., Schreiber, S. J. & Ellis, C. K. A physiologically based tritrophic perspective on bottom-up-top-down regulation of populations. Ecology 75, 2227–2242 (1994).Article 

Google Scholar 
63.Mills, N. J. & Gutierrez, A. P. in Theoretical Approaches to Biological Control (eds. Hawkins, B. A. & Cornell, V. H.) (Cambridge University Press, 1999).64.Barlow, N. D. in Theoretical Approaches to Biological Control (eds. Hawkins, B. A. & Cornell, H. V.) 43–70 (Cambridge University Press, 1999).65.Manetsch, T. J. Time-varying distributed delays and their use in aggregative models of large systems. IEEE Trans. Syst. Man Cybern. 6, 547–553 (1976).Article 

Google Scholar 
66.Buffoni, G. & Pasquali, S. Structured population dynamics: continuous size and discontinuous stage structures. J. Math. Biol. 54, 555–595 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
67.Di Cola, G., Gilioli, G. & Baumgärtner, J. in Ecological Entomology (eds. Huffaker, C. B. & Gutierrez, A. P.) (Wiley, 1999).68.Severini, M., Alilla, R., Pesolillo, S. & Baumgärtner, J. Fenologia della vite e della Lobesia botrana (Lep. Tortricidae) nella zona dei Castelli Romani. Riv. Ital. Agrometeorol. 3, 34–39 (2005).
Google Scholar 
69.Vansickle, J. Attrition in distributed delay models. IEEE Trans. Syst. Man Cybern. 7, 635–638 (1977).Article 

Google Scholar 
70.Wang, Y. H. & Gutierrez, A. P. An assessment of the use of stability analyses in population ecology. J. Anim. Ecol. 49, 435–452 (1980).Article 

Google Scholar 
71.Briére, J. F., Pracros, P., Le Roux, A. Y. & Pierre, J. S. A novel rate model of temperature-dependent development for arthropods. Environ. Entomol. 28, 22–29 (1999).Article 

Google Scholar 
72.Frazer, B. D. & Gilbert, N. Coccinellids and aphids: a quantitative study of the impact of adult ladybirds (Coleoptera: Coccinellidae) preying on field populations of pea aphids (Homoptera: Aphididae). J. Entomol. Soc. Br. Columbia 73, 33–56 (1976).
Google Scholar 
73.Gutierrez, A. P. & Baumgärtner, J. U. Multitrophic level models of predator-prey energetics: I. Age-specific energetics models—pea aphid Acyrthosiphon pisum (Homoptera: Aphididae) as an example. Can. Entomol. 116, 924–932 (1984).
Google Scholar 
74.Bieri, M., Baumgärtner, J., Bianchi, G., Delucchi, V. & von Arx, R. Development and fecundity of pea aphid (Acyrthosiphon pisum Harris) as affected by constant temperatures and by pea varieties. Mitteilungen Schweiz. Entomol. Ges. 56, 163–171 (1983).
Google Scholar 
75.Messenger, P. S. & Flitters, N. E. Effect of constant temperature environments on the egg stage of three species of Hawaiian fruit flies. Ann. Entomol. Soc. Am. 51, 109–119 (1958).Article 

Google Scholar 
76.Carey, J. R. Demography and population dynamics of the Mediterranean fruit fly. Ecol. Model. 16, 125–150 (1982).Article 

Google Scholar 
77.Muñiz, M. & Gil, A. Laboratory studies on isolated pairs of Ceratitis capitata—results obtained during the last three years in Spain. In: Cavalloro R (ed), Fruit flies of economic importance; Joint Ad-Hoc Meeting of the Commission of the European Communities and the International Organization for Biological and Integrated Control, Hamburg, West Germany, A.A. Balkema, Rotterdam, Netherlands; Boston, MA, USA, 125–128 (1984).78.Vargas, R. I., Walsh, W. A., Jang, E. B., Armstrong, J. W. & Kanehisa, D. T. Survival and development of immature stages of four Hawaiian fruit flies (Diptera: Tephritidae) reared at five constant temperatures. Ann. Entomol. Soc. Am. 89, 64–69 (1996).Article 

Google Scholar 
79.Vargas, R. I., Walsh, W. A., Kanehisa, D., Jang, E. B. & Armstrong, J. W. Demography of four Hawaiian fruit flies (Diptera: Tephritidae) reared at five constant temperatures. Ann. Entomol. Soc. Am. 90, 162–168 (1997).Article 

Google Scholar 
80.Vargas, R. I., Walsh, W. A., Kanehisa, D., Stark, J. D. & Nishida, T. Comparative demography of three Hawaiian fruit flies (Diptera:Tephritidae) at alternating temperatures. Ann. Entomol. Soc. Am. 93, 75–81 (2000).Article 

Google Scholar 
81.Delrio, G., Conti, B. & Corvetti, A. Effects of abiotic factors on Ceratitis capitata (Wied.) (Diptera: Tephritidae)—I. Egg development under constant temperatures. In Fruit Flies of Economic Importance 84. Proceedings of the CEC/IOBC “Ad-hoc Meeting” (ed. Cavalloro, R.) 133–139 (A.A. Balkema, 1984).82.Duyck, P. F., Sterlin, J. F. & Quilici, S. Survival and development of different life stages of Bactrocera zonata (Diptera: Tephritidae) reared at five constant temperatures compared to other fruit fly species. Bull. Entomol. Res. 94, 89–93 (2004).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
83.Powell, M. R. Modeling the response of the Mediterranean fruit fly (Diptera:Tephritidae) to cold treatment. J. Econ. Entomol. 96, 300–310 (2003).PubMed 
Article 
PubMed Central 

Google Scholar 
84.Shoukry, A. & Hafez, M. The biology of the Mediterranean fruit fly Ceratitis capitata. Entomol. Exp. Appl. 26, 33–39 (1979).Article 

Google Scholar 
85.Duyck, P. F., David, P. & Quilici, S. Climatic niche partitioning following successive invasions by fruit flies in La Réunion. J. Anim. Ecol. 75, 518–526 (2006).PubMed 
Article 
PubMed Central 

Google Scholar 
86.Dhillon, M. K., Singh, R., Naresh, J. S. & Sharma, H. C. The melon fruit fly, Bactrocera cucurbitae: a review of its biology and management. J. Insect Sci. Ludhiana 5, 40 (2005).CAS 

Google Scholar 
87.Messenger, P. S. & Flitters, N. E. Bioclimatic studies of three species of fruit flies in Hawaii. J. Econ. Entomol. 47, 756–765 (1954).Article 

Google Scholar 
88.Keck, C. B. Effect of temperature on development and activity of the melon fly. J. Econ. Entomol. 44, 1001–1002 (1951).Article 

Google Scholar 
89.Yang, P., Carey, J. R. & Dowell, R. V. Comparative demography of two cucurbit-attacking fruit flies, Bactrocera tau and B. cucurbitae (Diptera: Tephritidae). Ann. Entomol. Soc. Am. 87, 538–545 (1994).Article 

Google Scholar 
90.Vayssières, J. F., Carel, Y., Coubes, M. & Duyck, P. F. Development of immature stages and comparative demography of two cucurbit-attacking fruit flies in Reunion Island: Bactrocera cucurbitae and Dacus ciliatus (Diptera Tephritidae). Environ. Entomol. 37, 307–314 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
91.Huang, Y. B. & Chi, H. Age-stage, two-sex life tables of Bactrocera cucurbitae (Coquillett) (Diptera: Tephritidae) with a discussion on the problem of applying female age-specific life tables to insect populations. Insect Sci. 19, 263–273 (2012).Article 

Google Scholar 
92.Kandakoor, S. B., Chakravarthy, A. K., Rashmi, M. A. & Verghese, A. Effect of elevated carbon dioxide and temperature on biology of melon fruit fly, Bactrocera cucurbitae Coquillett (Tephritidae: Diptera). Afr. Entomol. 27, 36–42 (2019).Article 

Google Scholar 
93.Teruya, T. Effects of relative humidity during pupal development on subsequent eclosion and flight capability of the melon fly, Dacus cucurbitae Coquillett (Diptera:Tephiritidae). Appl. Entomol. Zool. 25, 521–523 (1990).Article 

Google Scholar 
94.Laskar, N. & Chatterjee, H. The effect of meteorological factors on the population dynamics of melon fly, Bactrocera cucurbitae (Coq.) (Diptera: Tephritidae) in the foot hills of Himalaya. J. Appl. Sci. Environ. Manag. 14, 53–58 (2010).95.Myers, S. W., Cancio-Martinez, E., Hallman, G. J., Fontenot, E. A. & Vreysen, M. J. B. Relative tolerance of six Bactrocera (Diptera: Tephritidae) species to phytosanitary cold treatment. J. Econ. Entomol. 109, 2341–2347 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
96.Zhou, S. H., Li, L., Zeng, B. & Fu, Y. G. Effects of short-term high-temperature conditions on oviposition and differential gene expression of Bactrocera cucurbitae (Coquillett) (Diptera: Tephritidae. Int. J. Pest Manag. 66, 332–340 (2020).Article 
CAS 

Google Scholar 
97.Vargas, R. I. et al. Area-wide suppression of the Mediterranean fruit fly, Ceratitis capitata, and the Oriental fruit fly, Bactrocera dorsalis, in Kamuela, Hawaii. J. Insect Sci. 10, 135 (2010).PubMed 
PubMed Central 
Article 

Google Scholar 
98.Vargas, R. I. & Carey, J. R. Comparative survival and demographic statistics for wild Oriental fruit fly, Mediterranean fruit fly, and melon fly (Diptera: Tephritidae) on papaya. J. Econ. Entomol. 83, 1344–1349 (1990).Article 

Google Scholar 
99.Jang, E. B., Nagata, J. T., Chan, H. T. & Laidlaw, W. G. Thermal death kinetics in eggs and larvae of Bactrocera latifrons (Diptera: Tephritidae) and comparative thermotolerance to three other tephritid fruit fly species in Hawaii. J. Econ. Entomol. 92, 684–690 (1999).Article 

Google Scholar 
100.Xie, Q., Hou, B. & Zhang, R. Thermal responses of oriental fruit fly (diptera: tephritidae) late third instars: mortality, puparial morphology, and adult emerge. J. Econ. Entomol. 101, 736–741 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
101.Armstrong, J. W., Tang, J. & Wang, S. Thermal death kinetics of Mediterranean, Malaysian, melon, and oriental fruit fly (Diptera: Tephritidae) eggs and third instars. J. Econ. Entomol. 102, 522–532 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
102.Choi, K. S., Samayoa, A. C., Hwang, S.-Y., Huang, Y.-B. & Ahn, J. J. Thermal effect on the fecundity and longevity of Bactrocera dorsalis adults and their improved oviposition model. PLOS ONE 15, e0235910 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
103.Shukla, R. P. & Prasad, V. G. Population fluctuations of the oriental fruit fly, Dacus dorsalis Hendel in relation to hosts and abiotic factors. Trop. Pest Manag. 31, 273–275 (1985).Article 

Google Scholar 
104.Hurtado, H. et al. Demography of three Mexican tephritids: Anastrepha ludens, A. obliqua and A. serpentina. Fla. Entomol. 71, 110–120 (1988).
Google Scholar 
105.Liedo, P., Carey, J. R., Celedonio, H. & Guillen, J. Size specific demography of three species of Anastrepha fruit flies. Entomol. Exp. Appl. 63, 135–142 (1992).Article 

Google Scholar 
106.Carey, J. R. et al. Biodemography of a long-lived tephritid: Reproduction and longevity in a large cohort of female Mexican fruit flies, Anastrepha ludens. Exp. Gerontol. 40, 793–800 (2005).PubMed 
PubMed Central 
Article 

Google Scholar 
107.Berrigan, D. A., Carey, J. R., Guillen, J. & Celedonio, H. Age and host effects on clutch size in the Mexican fruit fly, Anastrepha ludens. Entomol. Exp. Appl. 47, 73–80 (1988).Article 

Google Scholar 
108.Quintero‐Fong, L. et al. Demography of a genetic sexing strain of Anastrepha ludens (Diptera: Tephritidae): effects of selection based on mating performance. Agric. Entomol. 20, 1–8 (2018).Article 

Google Scholar 
109.Tejeda, M. T. et al. Reasons for success: rapid evolution for desiccation resistance and life-history changes in the polyphagous fly Anastrepha ludens. Evolution 70, 2583–2594 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
110.Darby, H. H. & Kapp, E. M. Observations on the thermal death points of Anatrepha ludens (Loew). US Dep. Agric. Tech. Bull. 400, 12445 (1933).111.Flitters, N. E. & Messenger, P. S. Effect of temperature and humidity on development and potential distribution of the Mexican fruit fly in the United States. U. S. Dep. Agric. Tech. Bull. 1330, 1–36 (1965).112.Ruane, A. C., Goldberg, R. & Chryssanthacopoulos, J. Climate forcing datasets for agricultural modeling: merged products for gap-filling and historical climate series estimation. Agric. Meteorol. 200, 233–248 (2015).Article 

Google Scholar 
113.Rienecker, M. M. et al. MERRA: NASA’s Modern-Era retrospective analysis for research and applications. J. Clim. 24, 3624–3648 (2011).Article 

Google Scholar 
114.Dell’Aquila, A. et al. Effects of seasonal cycle fluctuations in an A1B scenario over the Euro-Mediterranean region. Clim. Res. 52, 135–157 (2012).Article 

Google Scholar 
115.Artale, V. et al. An atmosphere-ocean regional climate model for the Mediterranean area: assessment of a present climate simulation. Clim. Dyn. 35, 721–740 (2010).Article 

Google Scholar 
116.Giorgi, F. & Bi, X. Updated regional precipitation and temperature changes for the 21st century from ensembles of recent AOGCM simulations. Geophys. Res. Lett. 32, L21715 (2005).Article 

Google Scholar 
117.Gualdi, S. et al. The CIRCE simulations: regional climate change projections with realistic representation of the Mediterranean sea. Bull. Am. Meteorol. Soc. 94, 65–81 (2013).Article 

Google Scholar 
118.Thrasher, B., Maurer, E. P., McKellar, C. & Duffy, P. B. Technical Note: Bias correcting climate model simulated daily temperature extremes with quantile mapping. Hydrol. Earth Syst. Sci. 16, 3309–3314 (2012).Article 

Google Scholar 
119.Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).Article 

Google Scholar 
120.Riahi, K. et al. RCP 8.5—A scenario of comparatively high greenhouse gas emissions. Clim. Change 109, 33–57 (2011).CAS 
Article 

Google Scholar 
121.Rogelj, J., Meinshausen, M. & Knutti, R. Global warming under old and new scenarios using IPCC climate sensitivity range estimates. Nat. Clim. Change 2, 248–253 (2012).Article 

Google Scholar 
122.GRASS Development Team. Geographic Resources Analysis Support System (GRASS) Software, Version 7.9.dev. (Open Source Geospatial Foundation. http://grass.osgeo.org, (2021).123.Gutierrez, A. P. & Ponti, L. in Invasive Species and Global Climate Change (eds. Ziska, L. H. & Dukes, J. S.) 271–288 (CABI Publishing, 2014).124.Ponti, L. et al. Bioeconomic analogies as a unifying paradigm for modeling agricultural systems under global change in the context of geographic information systems. Geophys. Res. Abstr. 21, 13677 (2019). EGU2019.
Google Scholar  More