Ecology

Olszewska-Guizzo, A., Fogel, A., Benjumea, D. & Tahsin, N. Sustainable Policies and Practices in Energy, Environment and Health Research 223–243 (Springer, 2022).Book 

Google Scholar 
Gascon, M. et al. Mental health benefits of long-term exposure to residential green and blue spaces: A systematic review. Int. J. Environ. Res. Public Health 12, 4354–4379. https://doi.org/10.3390/ijerph120404354 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Houlden, V., Weich, S., Porto-de-Albuquerque, J., Jarvis, S. & Rees, K. The relationship between greenspace and the mental wellbeing of adults: A systematic review. PLoS ONE 13, 3000 (2018).Article 

Google Scholar 
Hung, S.-H. & Chang, C.-Y. Health benefits of evidence-based biophilic-designed environments: A review. J. People Plants Env. 24, 1–16 (2021).Article 

Google Scholar 
Berman, M. G., Jonides, J. & Kaplan, S. The cognitive benefits of interacting with nature. Psychol. Sci. 19, 1207–1212. https://doi.org/10.1111/j.1467-9280.2008.02225.x (2008).Article 
PubMed 

Google Scholar 
Kaplan, S. Meditation, restoration, and the management of mental fatigue. Environ. Behav. 33, 480–506. https://doi.org/10.1177/00139160121973106 (2001).Article 

Google Scholar 
Ulrich, R. S. et al. Stress recovery during exposure to natural and urban environments. J. Environ. Psychol. 11, 201–230 (1991).Article 

Google Scholar 
Kellert, S. R. & Wilson, E. O. The Biophilia Hypothesis (Island Press, 1993).
Google Scholar 
Stack, K. & Shultis, J. Implications of attention restoration theory for leisure planners and managers. Leisure/Loisir 37, 1–16 (2013).Article 

Google Scholar 
Steel, Z. et al. The global prevalence of common mental disorders: A systematic review and meta-analysis 1980–2013. Int. J. Epidemiol. 43, 476–493. https://doi.org/10.1093/ije/dyu038 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Mueller, D. P. The current status of urban-rural differences in psychiatric disorder. An emerging trend for depression. J. Nerv. Ment. Dis. 169, 18–27 (1981).Article 
CAS 
PubMed 

Google Scholar 
Peen, J., Schoevers, R. A., Beekman, A. T. & Dekker, J. The current status of urban-rural differences in psychiatric disorders. Acta Psychiatr. Scand. 121, 84–93. https://doi.org/10.1111/j.1600-0447.2009.01438.x (2010).Article 
CAS 
PubMed 

Google Scholar 
Taylor, L. & Hochuli, D. F. Defining greenspace: Multiple uses across multiple disciplines. Landsc. Urban Plan. 158, 25–38 (2017).Article 

Google Scholar 
en K Staats, H. Restorative Environments The Oxford Handbook of Environmental and Conservation Psychology 445th edn. (Oxford University Press, 2012).
Google Scholar 
Wood, L., Hooper, P., Foster, S. & Bull, F. Public green spaces and positive mental health–investigating the relationship between access, quantity and types of parks and mental wellbeing. Health Place 48, 63–71 (2017).Article 
PubMed 

Google Scholar 
Tsunetsugu, Y. et al. Physiological and psychological effects of viewing urban forest landscapes assessed by multiple measurements. Landsc. Urban Plan. 113, 90–93 (2013).Article 

Google Scholar 
Gidlow, C. J. et al. Where to put your best foot forward: Psycho-physiological responses to walking in natural and urban environments. J. Environ. Psychol. 45, 22–29 (2016).Article 

Google Scholar 
Lee, J. Experimental study on the health benefits of garden landscape. Int. J. Environ. Res. Public Health 14, 829 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Fuller, R. A., Irvine, K. N., Devine-Wright, P., Warren, P. H. & Gaston, K. J. Psychological benefits of greenspace increase with biodiversity. Biol. Lett. 3, 390–394 (2007).Article 
PubMed 
PubMed Central 

Google Scholar 
Thompson, C. W., Aspinall, P. & Bell, S. Innovative Approaches to Researching Landscape and Health: Open Space: People Space 2 (Routledge, 2010).Book 

Google Scholar 
Tsutsumi, M., Nogaki, H., Shimizu, Y., Stone, T. E. & Kobayashi, T. Individual reactions to viewing preferred video representations of the natural environment: A comparison of mental and physical reactions. Jpn. J. Nurs. Sci. 14, 3–12 (2017).Article 
PubMed 

Google Scholar 
Grazuleviciene, R. et al. Tracking restoration of park and urban street settings in coronary artery disease patients. Int. J. Environ. Res. Public Health 13, 550 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Bostancı, S. H. In New Approaches to Spatial Planning and Design (ed Murat Özyavuz) Ch. 32, 435–451 (Peter Lang, 2019).Daniel, T. C. Measuring Landscape Esthetics: The Scenic Beauty Estimation Method, vol. 167 (Department of Agriculture, Forest Service, Rocky Mountain Forest and Range…, 1976).Bacon, W. R. In (eds Elsner G. H. et al) Technical Coordinators. Proceedings of our national landscape: A conference on applied techniques for analysis and management of the visual resource [Incline Village, Nev., April 23–25, 1979]. Gen. Tech. Rep. PSW-GTR-35. Berkeley, CA. Pacific Southwest Forest and Range Exp. Stn., Forest Service, US Department of Agriculture 660–665 (1979).Gavrilidis, A. A., Ciocănea, C. M., Niţă, M. R., Onose, D. A. & Năstase, I. I. Urban landscape quality index—planning tool for evaluating urban landscapes and improving the quality of life. Procedia Environ. Sci. 32, 155–167. https://doi.org/10.1016/j.proenv.2016.03.020 (2016).Article 

Google Scholar 
Knobel, P. et al. Development of the urban green space quality assessment tool (RECITAL). Urban For. Urban Green. 57, 126895 (2021).Article 

Google Scholar 
Bacon, W. R. & Dell, J. National Forest Landscape Management (Forest Service, US Department of Agriculture, 1973).Kaplan, R., Kaplan, S. & Ryan, R. With People in Mind: Design and Management of Everyday Nature (Island Press, 1998).
Google Scholar 
Smardon, R., Palmer, J. & Felleman, J. P. Foundations for Visual Project Analysis (Wiley, 1986).
Google Scholar 
Jung, C. G. Man and His Symbols Garden City (Doubleday and Co, 1964).
Google Scholar 
Olszewska, A., Marques, P. F., Ryan, R. L. & Barbosa, F. What makes a landscape contemplative?. Env. Plan. B Urban Anal. City Sci. 45, 7–25. https://doi.org/10.1177/0265813516660716 (2016).Article 

Google Scholar 
Tarkka, I. M. & Hallett, M. Cortical topography of premotor and motor potentials preceding self-paced, voluntary movement of dominant and non-dominant hands. Electroencephalogr. Clin. Neurophysiol. 75, 36–43 (1990).Article 
CAS 
PubMed 

Google Scholar 
Olszewska-Guizzo, A., Paiva, T. O. & Barbosa, F. Effects of 3D contemplative landscape videos on brain activity in a passive exposure EEG experiment. Front. Psychiatry 9, 317. https://doi.org/10.3389/fpsyt.2018.00317 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Bradley, M. M. & Lang, P. J. Measuring emotion: The self-assessment manikin and the semantic differential. J. Behav. Ther. Exp. Psychiatry 25, 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 (1994).Article 
CAS 
PubMed 

Google Scholar 
Beck, A. T., Steer, R. A. & Brown, G. K. Beck depression inventory-II. San Antonio 78, 490–498 (1996).
Google Scholar 
Ferree, T. C., Luu, P., Russell, G. S. & Tucker, D. M. Scalp electrode impedance, infection risk, and EEG data quality. Clin. Neurophysiol. 112, 536–544. https://doi.org/10.1016/S1388-2457(00)00533-2 (2001).Article 
CAS 
PubMed 

Google Scholar 
Stroganova, T. A. & Orekhova, E. V. EEG and infant states. Infant EEG Event-Relat. Potentials 251, 280 (2007).
Google Scholar 
Cacioppo, J. T., Tassinary, L. G. & Berntson, G. Handbook of Psychophysiology (Cambridge University Press, 2007).
Google Scholar 
Ulrich, R. S. Natural versus urban scenes: Some psychophysiological effects. Environ. Behav. 13, 523–556 (1981).Article 

Google Scholar 
Choi, Y., Kim, M. & Chun, C. Measurement of occupants’ stress based on electroencephalograms (EEG) in twelve combined environments. Build. Environ. 88, 65–72 (2015).Article 

Google Scholar 
Gorji, M. A. H., Davanloo, A. A. & Heidarigorji, A. M. The efficacy of relaxation training on stress, anxiety, and pain perception in hemodialysis patients. Indian J. Nephrol. 24, 356 (2014).Article 

Google Scholar 
Cahn, B. R. & Polich, J. Meditation states and traits: EEG, ERP, and neuroimaging studies. Psychol. Bull. 132, 180 (2006).Article 
PubMed 

Google Scholar 
Gruzelier, J. A theory of alpha/theta neurofeedback, creative performance enhancement, long distance functional connectivity and psychological integration. Cogn. Process. 10, 101–109 (2009).Article 

Google Scholar 
Vecchiato, G. et al. Neurophysiological correlates of embodiment and motivational factors during the perception of virtual architectural environments. Cogn. Process. 16, 425–429 (2015).Article 
PubMed 

Google Scholar 
Lagopoulos, J. et al. Increased theta and alpha EEG activity during nondirective meditation. J. Altern. Complement. Med. 15, 1187–1192 (2009).Article 
PubMed 

Google Scholar 
Wascher, E. et al. Frontal theta activity reflects distinct aspects of mental fatigue. Biol. Psychol. 96, 57–65 (2014).Article 
PubMed 

Google Scholar 
Kabat-Zinn, J. Mindfulness. Mindfulness 6, 1481–1483 (2015).Article 

Google Scholar 
McGarrigle, T. & Walsh, C. A. Mindfulness, self-care, and wellness in social work: Effects of contemplative training. J. Relig. Spiritual. Soc. Work Soc. Thought 30, 212–233 (2011).
Google Scholar 
Grossman, P., Niemann, L., Schmidt, S. & Walach, H. Mindfulness-based stress reduction and health benefits: A meta-analysis. J. Psychosom. Res. 57, 35–43 (2004).Article 
PubMed 

Google Scholar 
Bailey, A. W., Allen, G., Herndon, J. & Demastus, C. Cognitive benefits of walking in natural versus built environments. World Leisure J. 60, 293–305 (2018).Article 

Google Scholar 
Qin, J., Zhou, X., Sun, C., Leng, H. & Lian, Z. Influence of green spaces on environmental satisfaction and physiological status of urban residents. Urban For. Urban Green. 12, 490–497 (2013).Article 

Google Scholar 
Kolb, B. & Whishaw, I. Q. Fundamentals of Human Neuropsychology (Freeman, 1990).
Google Scholar 
Milner, B. Visual recognition and recall after right temporal-lobe excision in man. Neuropsychologia 6, 191–209 (1968).Article 

Google Scholar 
Corbetta, M. & Shulman, G. L. Control of goal-directed and stimulus-driven attention in the brain. Nat. Rev. Neurosci. 3, 201–215. https://doi.org/10.1038/nrn755 (2002).Article 
CAS 
PubMed 

Google Scholar 
Chang, C.-Y. & Chen, P.-K. Human response to window views and indoor plants in the workplace. HortScience 40, 1354–1359 (2005).Article 

Google Scholar 
Herzog, T. R., Black, A. M., Fountaine, K. A. & Knotts, D. J. Reflection and attentional recovery as distinctive benefits of restorative environments. J. Environ. Psychol. 17, 165–170 (1997).Article 

Google Scholar 
Baehr, E., Rosenfeld, J. P. & Baehr, R. Clinical use of an alpha asymmetry neurofeedback protocol in the treatment of mood disorders: Follow-up study one to five years post therapy. J. Neurother. 4, 11–18 (2001).Article 

Google Scholar 
Sia, A. et al. Nature-based activities improve the well-being of older adults. Sci. Rep. 10, 1–8 (2020).Article 

Google Scholar 
Olszewska-Guizzo, A., Sia, A., Fogel, A. & Ho, R. Can exposure to certain urban green spaces trigger frontal alpha asymmetry in the brain?—Preliminary findings from a passive task EEG study. Int. J. Environ. Res. Public Health 17, 394 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Olszewska-Guizzo, A. et al. Therapeutic garden with contemplative features induces desirable changes in mood and B rain activity in depressed adults. Front. Psychiatry https://doi.org/10.3389/fpsyt.2022.757056 (2021).Article 

Google Scholar 
Tan, S. B., Vignesh, L. N. & Donald, L. Public Housing in Singapore: Examining Fundamental Shifts (Lee Kuan Yew School of Public Policy, National University of Singapore, 2014).Tan, P. Y. Nature, Place & People: Forging Connections Through Neighbourhood Landscape Design (World Scientific Publishing Co., 2018).Book 

Google Scholar 
Peirce, J. et al. PsychoPy2: Experiments in behavior made easy. Behav. Res. Methods 51, 195–203. https://doi.org/10.3758/s13428-018-01193-y (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Edwards, A. L. Balanced Latin-square designs in psychological research. Am. J. Psychol. 64, 598–603 (1951).Article 
CAS 
PubMed 

Google Scholar 
Korpela, K. M., Ylén, M., Tyrväinen, L. & Silvennoinen, H. Determinants of restorative experiences in everyday favorite places. Health Place 14, 636–652 (2008).Article 
PubMed 

Google Scholar 
Ojala, A., Korpela, K., Tyrväinen, L., Tiittanen, P. & Lanki, T. Restorative effects of urban green environments and the role of urban-nature orientedness and noise sensitivity: A field experiment. Health Place 55, 59–70 (2019).Article 
PubMed 

Google Scholar 
Tyrväinen, L. et al. The influence of urban green environments on stress relief measures: A field experiment. J. Environ. Psychol. 38, 1–9 (2014).Article 

Google Scholar 
Herzog, T. R. & Barnes, G. J. Tranquility and preference revisited. J. Environ. Psychol. 19, 171–181 (1999).Article 

Google Scholar 
Neale, C. et al. The impact of walking in different urban environments on brain activity in older people. Cities Health 4, 94–106. https://doi.org/10.1080/23748834.2019.1619893 (2020).Article 

Google Scholar 
Kaplan, R. & Kaplan, S. The Experience of Nature: A Psychological Perspective (CUP Archive, 1989).
Google Scholar 
Treib, M. In Contemporary Landscapes of Contemplation (ed Rebecca Krinke) 27–49 (Routledge, 2005).Appleton, J. The Experience of Landscape (Wiley Chichester, 1996).
Google Scholar 
Grahn, P., Ottosson, J. & Uvnäs-Moberg, K. The oxytocinergic system as a mediator of anti-stress and instorative effects induced by nature: The calm and connection theory. Front. Psychol. 2021, 12 (2021).
Google Scholar 
Hartig, T., Mang, M. & Evans, G. W. Restorative effects of natural environment experiences. Environ. Behav. 23, 3–26. https://doi.org/10.1177/0013916591231001 (1991).Article 

Google Scholar 
Stamps Iii, A. E. Use of photographs to simulate environments: A meta-analysis. Percept. Mot. Skills 71, 907–913 (1990).Article 

Google Scholar 
Menardo, E., Brondino, M., Hall, R. & Pasini, M. Restorativeness in natural and urban environments: A meta-analysis. Psychol. Rep. 124, 417–437 (2021).Article 
PubMed 

Google Scholar  More

von Humboldt, A., and A. Bonpland. Essai sur la geographiedes plantes. Chez Levrault, Schoell et Campagnie, Libraries, Paris.(1805).Malhi, Y. et al. Introduction: elevation gradients in the tropics: laboratories for ecosystem ecology and global change research. Glob. Change Biol. 16, 3171–3175 (2010).Article 

Google Scholar 
Nottingham, A. T. et al. Climate warming and soil carbon in tropical forests: insights from an elevation gradient in the Peruvian Andes. BioScience 65, 906–921 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Malhi, Y. et al. The variation of productivity and its allocation along a tropical elevation gradient: a whole carbon budget perspective. N. Phytologist 214, 1019–1032 (2017).Article 
CAS 

Google Scholar 
Nottingham, A. T. et al. Soil microbial nutrient constraints along a tropical forest elevation gradient: a belowground test of a biogeochemical paradigm. Biogeosciences 12, 6071–6083 (2015).Article 

Google Scholar 
Nottingham, A. T. et al. Microbes follow Humboldt: temperature drives plant and soil microbial diversity patterns from the Amazon to the Andes. Ecology 99, 2455–2466 (2018).Article 
PubMed 

Google Scholar 
Jenny, H., Bingham, F. & Padillasaravia, B. Nitrogen and organic matter contents of equatorial soils of Colombia, South-America. Soil Sci. 66, 173–186 (1948).Article 
CAS 

Google Scholar 
Tanner, E., Vitousek, P. & Cuevas, E. Experimental investigation of nutrient limitation of forest growth on wet tropical mountains. Ecology 79, 10–22 (1998).Article 

Google Scholar 
Vitousek, P. M., Matson, P. A. & Turner, D. R. Elevational and age gradients in Hawaiian montane rainforest: foliar and soil nutrients. Oecologia 77, 565–570 (1988).Article 
PubMed 

Google Scholar 
Vitousek, P. M. & Sanford, R. L. Nutrient cycling in moist tropical forest. Annu. Rev. Ecol. Syst. 17, 137–167 (1986).Article 

Google Scholar 
Krishnaswamy, J., John, R. & Joseph, S. Consistent response of vegetation dynamics to recent climate change in tropical mountain regions. Glob. Change Biol. 20, 203–215 (2014).Article 

Google Scholar 
Duque, A. et al. Mature Andean forests as globally important carbon sinks and future carbon refuges. Nat. Commun. 12, 2138 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Fadrique, B. et al. Widespread but heterogeneous responses of Andean forests to climate change. Nature 564, 207–212 (2018).Article 
CAS 
PubMed 

Google Scholar 
Nottingham, A. T. et al. Microbial responses to warming enhance soil carbon loss following translocation across a tropical forest elevation gradient. Ecol. Lett. 22, 1889–1899 (2019).Article 
PubMed 

Google Scholar 
Marrs, R. H., Proctor, J., Heaney, A. & Mountford, M. D. Changes in soil nitrogen-mineralization and nitrification along an altitudinal transect in tropical rain forest in Costa Rica. J. Ecol. 76, 466–482 (1988).Grubb, P. J. Control of forest growth and distribution on wet tropical mountains: with special reference to mineral nutrition. Annu. Rev. Ecol. Syst. 8, 83–107 (1977).Article 
CAS 

Google Scholar 
Wolf, K., Veldkamp, E., Homeier, J. & Martinson, G. O. Nitrogen availability links forest productivity, soil nitrous oxide and nitric oxide fluxes of a tropical montane forest in southern Ecuador. Glob. Biogeochem. Cycles 25, GB4009 (2011).Barthel, M. et al. Low N2O and variable CH4 fluxes from tropical forest soils of the Congo Basin. Nat. Commun. 13, 330 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Brookshire, E. N. J., Hedin, L. O., Newbold, J. D., Sigman, D. M. & Jackson, J. K. Sustained losses of bioavailable nitrogen from montane tropical forests. Nat. Geosci. 5, 123–126 (2012).Article 
CAS 

Google Scholar 
Rütting, T. et al. Leaky nitrogen cycle in pristine African montane rainforest soil. Glob. Biogeochem. Cycles 29, 1754–1762 (2015).Article 

Google Scholar 
Batjes, N. H. Total carbon and nitrogen in the soils of the world. Eur. J. Soil Sci. 47, 151–163 (1996).Article 
CAS 

Google Scholar 
Hengl, T. et al. SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12, e0169748 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Poggio, L. et al. SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. SOIL 7, 217–240 (2021).Article 
CAS 

Google Scholar 
Bauters, M. et al. Parallel functional and stoichiometric trait shifts in South American and African forest communities with elevation. Biogeosciences 14, 5313–5321 (2017).Article 
CAS 

Google Scholar 
Dalling, J. W., Heineman, K., González, G. & Ostertag, R. Geographic, environmental and biotic sources of variation in the nutrient relations of tropical montane forests. J. Tropical Ecol. 32, 368–383 (2016).Article 

Google Scholar 
Porder, S., Vitousek, P., Chadwick, O., Chamberlain, C. & Hilley, G. Uplift, erosion, and phosphorus limitation in terrestrial ecosystems. Ecosystems 10, 158–170 (2007).Article 
CAS 

Google Scholar 
Houlton, B. Z., Morford, S. L. & Dahlgren, R. A. Convergent evidence for widespread rock nitrogen sources in Earth’s surface environment. Science 360, 58–62 (2018).Article 
CAS 
PubMed 

Google Scholar 
Hilton, R. G., Galy, A., West, A. J., Hovius, N. & Roberts, G. G. Geomorphic control on the delta N-15 of mountain forests. Biogeosciences 10, 1693–1705 (2013).Article 
CAS 

Google Scholar 
Vitousek, P. M., Van Cleve, K., Balakrishnan, N. & Mueller-Dombois, D. Soil development and nitrogen turnover in montane rainforest soils on Hawai’i. Biotropica 268–274 (1983).Taylor, P. G. et al. Temperature and rainfall interact to control carbon cycling in tropical forests. Ecol. Lett. 20, 779–788 (2017).Article 
PubMed 

Google Scholar 
Houlton, B. & Bai, E. Imprint of denitrifying bacteria on the global terrestrial biosphere. Proc. Natl Acad. Sci. USA 106, 21713–21716 (2009).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Shi, Z. et al. The age distribution of global soil carbon inferred from radiocarbon measurements. Nat. Geosci. 13, 555–559 (2020).Article 
CAS 

Google Scholar 
Craine, J. M. et al. Ecological interpretations of nitrogen isotope ratios of terrestrial plants and soils. Plant and Soil 396, 1–26 (2015).Högberg, P. Tansley Review No. 95. 15N Natural Abundance in Soil-Plant Systems. N. Phytologist 137, 179–203 (1997).Article 

Google Scholar 
Martinelli, L. et al. Nitrogen stable isotopic composition of leaves and soil: Tropical versus temperate forests. Biogeochemistry 46, 45–65 (1999).Article 
CAS 

Google Scholar 
Amundson, R. et al. Global patterns of the isotopic composition of soil and plant nitrogen. Glob. Biogeochem. Cycles 17, (2003).Craine, J. M. et al. Convergence of soil nitrogen isotopes across global climate gradients. Sci. Rep. 5, 8280 (2015).Mooshammer, M. et al. Adjustment of microbial nitrogen use efficiency to carbon:nitrogen imbalances regulates soil nitrogen cycling. Nat. Commun. 5, 3694 (2014).Camenzind, T., Hättenschwiler, S., Treseder, K. K., Lehmann, A. & Rillig, M. C. Nutrient limitation of soil microbial processes in tropical forests. Ecol. Monogr. 88, 4–21 (2018).Article 

Google Scholar 
Mariotti, A., Pierre, D., Vedy, J. C., Bruckert, S. & Guillemot, J. The abundance of natural nitrogen 15 in the organic matter of soils along an altitudinal gradient (Chablais, Haute Savoie, France). Catena 7, 293–300 (1980).Article 
CAS 

Google Scholar 
Sena‐Souza, J. P., Houlton, B. Z., Martinelli, L. A. & Nardoto, G. B. Reconstructing continental-scale variation in soil δ15N: a machine learning approach in South America. Ecosphere 11, e03223 (2020).Article 

Google Scholar 
Nottingham, A. T., Bååth E., Reischke, S., Salinas, N. & Meir, P. Adaptation of soil microbial growth to temperature: Using a tropical elevation gradient to predict future changes. Glob. change Biol. 25, 827–838 (2019).Liu, Y. et al. A global synthesis of the rate and temperature sensitivity of soil nitrogen mineralization: latitudinal patterns and mechanisms. Glob. Change Biol. 23, 455–464 (2017).Article 

Google Scholar 
Davidson, E. A. & Janssens, I. A. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440, 165–173 (2006).Article 
CAS 
PubMed 

Google Scholar 
Zimmermann, M. & Bird, M. I. Temperature sensitivity of tropical forest soil respiration increase along an altitudinal gradient with ongoing decomposition. Geoderma 187–188, 8–15 (2012).Article 

Google Scholar 
Page, S. E., Rieley, J. O. & Banks, C. J. Global and regional importance of the tropical peatland carbon pool. Glob. Change Biol. 17, 798–818 (2011).Article 

Google Scholar 
Wright, S. J. Plant responses to nutrient addition experiments conducted in tropical forests. Ecol. Monogr. 89, e01382 (2019).Article 

Google Scholar 
Brookshire, E. N. J., Gerber, S., Menge, D. N. L. & Hedin, L. O. Large losses of inorganic nitrogen from tropical rainforests suggest a lack of nitrogen limitation. Ecol. Lett. 15, 9–16 (2012).Article 
CAS 
PubMed 

Google Scholar 
Corrales, A., Henkel, T. W. & Smith, M. E. Ectomycorrhizal associations in the tropics—biogeography, diversity patterns and ecosystem roles. N. Phytologist 220, 1076–1091 (2018).Article 

Google Scholar 
Zeng, Z. et al. Deforestation-induced warming over tropical mountain regions regulated by elevation. Nat. Geosci. 1–7 https://doi.org/10.1038/s41561-020-00666-0 (2020).Nogués-Bravo, D., Araújo, M. B., Errea, M. P. & Martínez-Rica, J. P. Exposure of global mountain systems to climate warming during the 21st Century. Glob. Environ. Change 17, 420–428 (2007).Article 

Google Scholar 
Weintraub, S. R., Cole, R. J., Schmitt, C. G. & All, J. D. Climatic controls on the isotopic composition and availability of soil nitrogen across mountainous tropical forest. Ecosphere 7, e01412 (2016).Article 

Google Scholar 
Brookshire, E. N. J. & Thomas, S. A. Ecosystem consequences of tree monodominance for nitrogen cycling in lowland tropical forest. PLoS ONE 8, e70491 (2013).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Kitayama, K. & Iwamoto, K. Patterns of natural 15N abundance in the leaf-to-soil continuum of tropical rain forests differing in N availability on Mount Kinabalu, Borneo. Plant Soil 229, 203–212 (2001).Article 
CAS 

Google Scholar 
Bauters, M. et al. Contrasting nitrogen fluxes in African tropical forests of the Congo Basin. Ecol. Monogr. 89, e01342 (2019).Article 

Google Scholar 
Proctor, J., Edwards, I. D., Payton, R. W. & Nagy, L. Zonation of forest vegetation and soils of Mount Cameroon, West Africa. Plant Ecol. 192, 251–269 (2007).Article 

Google Scholar 
Grubb, P. J. & Stevens, P. F. The Forests of the Fatima Basin and Mt Kerigomna, Papua New Guinea with a Review of Montane and Subalpine Rainforests in Papuasia (Department of Human Geography, Research School of Pacific Studies…, 2017).Dieleman, W. I. J., Venter, M., Ramachandra, A., Krockenberger, A. K. & Bird, M. I. Soil carbon stocks vary predictably with altitude in tropical forests: Implications for soil carbon storage. Geoderma 204–205, 59–67 (2013).Article 

Google Scholar 
Kapos, V., Rhind, J., Edwards, M., Price, M. F. & Ravilious, C. in Forests in sustainable mountain development: a state of knowledge report for 2000. Task Force on Forests in Sustainable Mountain Development. 4–19 (CABI, 2000). https://doi.org/10.1079/9780851994468.0004.Sexton, J. O. et al. Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error. Int. J. Digital Earth 6, 427–448 (2013).Article 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org (2022).Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48, https://doi.org/10.18637/jss.v067.i01 (2015).Article 

Google Scholar 
Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest Package: tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017).Article 

Google Scholar 
Bartoń K. MuMIn: Multi-Model Inference. R package version 1.43.17 (2020).Grömping, U. Relative Importance for Linear Regression in R: The Package Relaimpo. J. Stat. Softw. 17, 1–27 (2006).Article 

Google Scholar 
Baty, F. et al. A Toolbox for Nonlinear Regression in R: The Package nlstools. J. Stat. Softw. 66, 1–21 (2015).Article 

Google Scholar  More

Singh, Y. D., Jena, B. & Ningthoujam, R. Potential bioactive molecules from natural products to combat against coronavirus. Adv. trad. Med. 1, 1–12. https://doi.org/10.1007/s13596-020-00496-w (2020).Article 
CAS 

Google Scholar 
Badke, M. R. et al. Popular knowledge: The use of medicinal plants as therapeutic form in health care. Rev. Enferm. UFSM. 6, 225–234. https://doi.org/10.1590/S0104-07072012000200014 (2016).Article 

Google Scholar 
Macedo, J. G. F. et al. Analysis of the variability of therapeutic indications of medicinal species in the Northeast of Brazil: Comparative study. Evid. Based Complementary Altern. Med. 2018, 1–29. https://doi.org/10.1155/2018/6769193 (2018).Article 

Google Scholar 
Farias, J. C., Bomfim, B. L. S., Fonseca Filho, I. C., Silva, P. R. R. & Barros, R. F. M. Insecticides and repellents plants used in a rural community in northeast Brazilian. Revista Espacios. 37, 1–6 (2016).
Google Scholar 
Silva, M. G. V., Lima, D. R., Monteiro, J. A. & Magalhães, F. E. A. Anxiolytic-like effect of chrysophanol from Senna Cana Stem in Adult Zebrafish (Danio Rerio). Nat. Prod. Res. 22, 1–5. https://doi.org/10.1080/14786419.2021.1980788 (2021).Article 
CAS 

Google Scholar 
Vincenzi, F., Borea, P. A. & Varani, K. Anxiolytic properties of A1 adenosine receptor PAMs. Oncotarget 8, 7216–7217. https://doi.org/10.18632/oncotarget.13802 (2017).Article 
PubMed 

Google Scholar 
Silva, M. I. G., Gondim, A. P. S., Nunes, I. F. S. & Sousa, F. C. F. Utilização de fitoterápicos nas unidades básicas de atenção à saúde da família no município de Maracanaú (CE). Rev. Bras. Farmacog. 16, 455–462. https://doi.org/10.1590/S0102-695X2006000400003 (2006).Article 

Google Scholar 
Guimarães, L. G. L., Silva, M. L. M., Reis, P. C. J., Costa, M. T. R. & Alves, L. L. General characteristics, phytochemistry and pharmacognosy of Lippia sidoides. Nat. Prod. Commun. 10, 1861–1867. https://doi.org/10.1177/1934578X1501001116 (2015).Article 

Google Scholar 
Veras, H. L. H. et al. Synergistic antibiotic activity of volatile compounds from the essential oil of Lippia sidoides and thymol. Fitoterap. 83, 508–512. https://doi.org/10.1016/j.fitote.2011.12.024 (2012).Article 
CAS 

Google Scholar 
Farias, E. M. F. G. et al. Antifungal activity of Lippia sidoides Cham. (Verbenaceae) against clinical isolates of Candida species. J. Herb. Med. 2, 63–67. https://doi.org/10.1016/j.hermed.2012.06.002 (2012).Article 

Google Scholar 
Cavalcanti, S. C. H. et al. Composition and acaricidal activity of Lippia sidoides essential oil Against two-spotted spider mite (Tetranychus urticae Koch). Bioresour. Technol. 101, 829–832. https://doi.org/10.1016/j.biortech.2009.08.053 (2010).Article 
CAS 
PubMed 

Google Scholar 
Monteiro, M. V. B., Leite, A. K. R. M., Bertini, L. M., Morais, S. M. & Nunes-Pinheiro, D. C. S. Topical anti-inflammatory, gastroprotective and antioxidant effects of the essential oil of Lippia sidoides Cham. Leaves. J. Ethnopharmacol. 111, 378–382. https://doi.org/10.1016/j.jep.2006.11.036 (2007).Article 
CAS 
PubMed 

Google Scholar 
Botelho, M. A. et al. Effect of a novel essential oil mouthrinse without alcohol on gingivitis: A double-blinded randomized controlled tria. J. Appl. Oral. Sci. 15, 175–180 (2007).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Botelho, M. A. et al. Comparative effect of an essential oil mouthrinse on plaque, gingivitis and salivary Streptococcus mutans levels: A double blind randomized study. Phytother. Res. 23, 1214–1219. https://doi.org/10.1002/ptr.2489 (2009).Article 
CAS 
PubMed 

Google Scholar 
Medeiros, M. G. F. et al. In vitro antileishmanial activity and cytotoxicity of essential oil from Lippia sidoides Cham. Parasitol. Inter. 60, 237–241. https://doi.org/10.1016/j.parint.2011.03.004 (2011).Article 
CAS 

Google Scholar 
Gomide, M. S. et al. The effect of the essential oils from five different Lippia species on the viability of tumor cell lines. Rev. Bras. Farmacogn. 23, 895–902. https://doi.org/10.1590/S0102-695X2013000600006 (2013).Article 
CAS 

Google Scholar 
Murade, V. et al. A plausible involvement of GABAA/benzodiazepine receptor in the anxiolytic-like effect of ethyl acetate fraction and quercetin isolated from Ricinus communis Linn. leaves in mice. Phytomed. Plus. 1, 100041. https://doi.org/10.1016/j.phyplu.2021.100041 (2021).Article 

Google Scholar 
Coleta, M., Campos, M. A., Cotrim, M. D., Lima, T. C. M. & Cunha, A. P. Assessment of luteolin (3′,4′,5,7-tetrahydroxyflavone) neuropharmacological activity. Behav. Brain Res. 189, 75–82. https://doi.org/10.1016/j.bbr.2007.12.010 (2008).Article 
CAS 
PubMed 

Google Scholar 
Kosalec, I., Bakmaz, M., Pepeliniak, S. & Vladimir-Knezevic, S. Quantitative analysis of the flavonoids in raw propolis from northern Croatia. A Pharmaceut. 54, 65–72 (2004).CAS 

Google Scholar 
Cunha, F. A. B. et al. Eugenia uniflora leaves essential oil induces toxicity in Drosophila melanogaster: Involvement of oxidative stress mechanisms. Toxicol. Res. 4, 634–644. https://doi.org/10.1039/c4tx00162a (2015).Article 

Google Scholar 
Coulom, H. & Birman, S. Chronic exposure to rotenone models sporadic Parkinson’s disease in Drosophila melanogaster. J. Neurosci. 24, 10993–10998. https://doi.org/10.1523/JNEUROSCI.2993-04.2004 (2004).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Barros, F. J. et al. Activity of essential oils of Piper aduncum anf and Cinnamomum zeylanicum by evaluating osmotic and morphologic fragility of erythrocytes. Eur. J. Integr. Med. 515, 1–8. https://doi.org/10.1016/j.eujim.2016.02.011 (2016).Article 

Google Scholar 
Meyer, B. N. et al. Brine Shrimp: A convenient general bioassay for active plant constituints. Planta Med. 45, 31–34. https://doi.org/10.1055/s-2007-971236 (1982).Article 
CAS 
PubMed 

Google Scholar 
de Magalhães, F. E. A. et al. Adult zebrafish: an alternative behavioral model of formalin-induced nociception. Zebrafish 4, 422–429. https://doi.org/10.1089/zeb.2017.1436 (2017).Article 
CAS 

Google Scholar 
OECD guideline for testing acute toxicity in fishes, Test No. 1992. http://www.oecd.org/chemicalsafety/risk-assessment/1948241.pdf. (Acessado em 25 de octuber, 2021).Arellano-Aguilar, O. et al. Use of the zebrafish embryo toxicity test for use of the zebrafish embryo toxicity test for risk assessment purpose: Case study. J. Fish Sci. 4, 52–62 (2015).
Google Scholar 
Gonçalves, N. G. G. et al. Protein fraction from Artocarpus Altilis pulp exhibits antioxidant properties and reverses anxiety behavior in adult zebrafish via the serotoninergic system. J. Funct. Foods. 66, 103772. https://doi.org/10.1016/j.jff.2019.103772 (2020).Article 
CAS 

Google Scholar 
Gebauer, D. L. et al. Effects of anxiolytics in zebrafish: Similarities and differences between benzodiazepines. Buspirone and Ethanol. Pharmacol. Biochem. Behav. 99, 480–486. https://doi.org/10.1016/j.pbb.2011.04.021 (2011).Article 
CAS 
PubMed 

Google Scholar 
Benneh, C. K. et al. Maerua Angolensis stem bark extract reverses anxiety and related behaviours in zebrafish—Involvement of GABAergic and 5-HT systems. J. Ethnopharmacol. 207, 129–145. https://doi.org/10.1016/j.jep.2017.06.012 (2017).Article 
CAS 
PubMed 

Google Scholar 
Santos, S. A., Vilela, C., Freire, C. S., Neto, C. P. & Silvestre, A. J. Ultra-high performance liquid chromatography coupled to mass spectrometry applied to the identification of valuable phenolic compounds from Eucalyptus wood. J. Chromatogr. B. 938, 65–74. https://doi.org/10.1016/j.jchromb.2013.08.034 (2013).Article 
CAS 

Google Scholar 
Pereira, O. R., Peres, A. M., Silva, A. M. S., Domingues, M. R. M. & Cardoso, S. M. Simultaneous characterization and quantification of phenolic compounds in Thymus x citriodorus using a validated HPLC–UV and ESI–MS combined method. Food Res. Inter. 54, 1773–1780. https://doi.org/10.1016/j.foodres.2013.09.016.( (2013).Article 
CAS 

Google Scholar 
Zhao, Y. et al. Characterization of phenolic constituents in Lithocarpus polystachyus. Royal Soc. Chem. https://doi.org/10.1039/c3ay41288a (2014).Article 

Google Scholar 
Petkovska, A., Gjamovski, V., Stanoeva, J. P. & Stefova, M. Characterization of the polyphenolic profiles of peel, flesh and leaves of malus domestica cultivars using UHPLC-DAD-HESI-MSn. Nat. Prod. Commun. https://doi.org/10.1177/1934578X1701200111 (2017).Article 
PubMed 

Google Scholar 
Mena, P. et al. Rapid and comprehensive evaluation of (poly)phenolic compounds in pomegranate (Punica granatum L.) juice by UHPLC-MSn. Molecules 17, 14821–14840. https://doi.org/10.3390/molecules171214821 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ye, M., Han, J., Chen, H., Zheng, J. & Guo, D. Analysis of phenolic compounds in rhubarbs using liquid chromatography coupled with electrospray ionization mass spectrometry. J. Am. Soc. Mass Spectrom. 18, 82–91. https://doi.org/10.1016/j.jasms.2006.08.009 (2007).Article 
CAS 
PubMed 

Google Scholar 
Kang, J., Price, W., Ashton, J., Tapsell, L. C. & Johnson, S. Identification and characterization of phenolic compounds in hydromethanolic extracts of sorghum wholegrains by LC-ESI-MSn. Food Chem. 211, 215–226. https://doi.org/10.1016/j.foodchem.2016.05.052 (2016).Article 
CAS 
PubMed 

Google Scholar 
Schutz, K., Kammerer, D. R., Carle, R. & Schieber, A. Characterization of phenolic acids and flavonoids in dandelion (Taraxacum officinale WEB. ex WIGG.) root and herb by high-performance liquid chromatography/electrospray ionization mass spectrometry. Rapid Commun. Mass Spectrom. 19, 179–186. https://doi.org/10.1002/rcm.1767.15593267 (2005).Article 
PubMed 

Google Scholar 
Hassan, K. O., Bedgood, D. R. Jr., Prenzler, P. D. & Robards, K. Chemical screening of olive biophenol extracts by hyphenated liquid chromatography. Anal. Chim. Acta 603, 176–189. https://doi.org/10.1016/j.aca.2007.09.044 (2007).Article 
CAS 

Google Scholar 
Brito, A., Ramirez, J. E., Areche, C., Sepúlveda, B. & Simirgiotis, M. J. HPLC-UV-MS profiles of phenolic compounds and antioxidant activity of fruits from three citrus species consumed in Northern Chile. Molecules 19, 17400–17421. https://doi.org/10.3390/moléculas191117400 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
McNab, H., Ferreira, E. S. B., Hulme, A. N. & Quye, A. Negative ion ESI–MS analysis of natural yellow dye flavonoids—An isotopic labelling study. Int. J. Mass Spectrometry. 284, 57–65. https://doi.org/10.1016/j.ijms.2008.05.039 (2009).Article 
CAS 

Google Scholar 
Gouveia, S. & Castilho, P. C. Characterisation of phenolic acid derivatives and flavonoids from different morphological parts of Helichrysum obconicum by a RP-HPLC–DAD-()–ESI-MSn method. Food Chem. 129, 333–344. https://doi.org/10.1016/j.foodchem.2011.04.078 (2011).Article 
CAS 
PubMed 

Google Scholar 
Peter, S. R., Peru, K. M., Fahlman, B., McMartin, D. W. & Headley, J. V. The application of HPLC ESI MS in the investigation of the flavonoids and flavonoid glycosides of a Caribbean Lamiaceae plant with potential for bioaccumulation. J. Environ. Sci. Health B. 50, 819–826. https://doi.org/10.1080/03601234.2015.1058103 (2015).Article 
CAS 
PubMed 

Google Scholar 
Rashid, N. A. A., Lau, B. F. & Kue, C. S. Differential toxicity and teratogenic effects of the hot water and cold water extracts of Lignosus rhinocerus (Cooke) Ryvarden sclerotium on zebrafish (Danio rerio) embryos. J. Ethnopharmacol. 285(114787), 2022. https://doi.org/10.1016/j.jep.2021.114787 (2022).Article 
CAS 

Google Scholar 
Costa, S. M. O. et al. Chemical constituents from Lippia sidoides and cytotoxic activity. J. Nat. Prod. 64, 792–795. https://doi.org/10.1021/np0005917 (2001).Article 
CAS 
PubMed 

Google Scholar 
Fabri, R. L., Nogueira, M. S., Moreira, J. R., Bouzada, M. L. M. & Scio, E. Identification of antioxidant and antimicrobial compounds of Lippia Species by bioautography. J. Med. Food. 14, 840–846. https://doi.org/10.1089/jmf.2010.0141 (2011).Article 
CAS 
PubMed 

Google Scholar 
Funari, C. S. et al. Chemical and antifungal investigations of six Lippia species (Verbenaceae) from Brazil. Food Chem. 135, 2086–2094. https://doi.org/10.1016/j.foodchem.2012.06.077 (2012).Article 
CAS 
PubMed 

Google Scholar 
Garmus, T. T., Paviani, L. C., Queiroga, C. L. & Cabral, F. A. Extraction of phenolic compounds from pepper-rosmarin (Lippia sidoides Cham.) leaves by sequential extraction in fixed bed extractorusing supercritical CO2, ethanol and water as solvents. J. Supercrit. Fluids. 99, 68–75. https://doi.org/10.1016/j.supflu.2015.01.016 (2015).Article 
CAS 

Google Scholar 
Botelho, M. A. et al. Nanotechnology in phytotherapy: Antiinflammatory effect of a nanostructured thymol gel from Lippia sidoides in acute periodontitis in rats. Phytother. Res. 30, 152–159. https://doi.org/10.1002/ptr.5516 (2016).Article 
CAS 
PubMed 

Google Scholar 
Veras, H. N. et al. Atividade anti-inflamatória tópica do óleo essencial de Lippia sidoides cham: Possível mecanismo de ação. Phytother. Res. 27, 179–185. https://doi.org/10.1002/ptr.4695 (2013).Article 
CAS 
PubMed 

Google Scholar 
Fernandes, L. M., Guterres, Z. R., Almeida, I. V. & Vicentini, V. E. P. Genotoxicity and antigenotoxicity assessments of the flavonoid vitexin by the Drosophila melanogaster somatic mutation and recombination test. J. Med. food. 20, 1–9. https://doi.org/10.1089/jmf.2016.0149 (2017).Article 
CAS 

Google Scholar 
Sotibrán, A. N. C., Ordaz-Téllez, M. G. & Rodríguez-Arnaiz, R. Flavonoids and oxidative stress in Drosophila melanogaster. Mutation Res. 726(60–65), 2011. https://doi.org/10.1016/j.mrgentox.2011.08.005 (2011).Article 
CAS 

Google Scholar 
Silva, L. V. F., Mourão, R. H. V., Manimala, J. & Lnenicka, G. A. The essential oil of Lippia alba and its components affect Drosophila behavior and synaptic physiology. J. Experim. Biol. 221, 1–10. https://doi.org/10.1242/jeb.176909 (2018).Article 

Google Scholar 
Poetini, M. R. et al. Hesperidin attenuates iron-induced oxidative damage and dopamine depletion in Drosophila melanogaster model of Parkinson’s disease. Chem. Biol. Interact. 279, 177–186. https://doi.org/10.1016/j.cbi.2017.11.018 (2018).Article 
CAS 
PubMed 

Google Scholar 
Xavier, A. L. et al. Chemical composition, antitumor activity, and toxicity of essential oil from the leaves of Lippia microphylla. Z. Naturforsch. 70, 129–137. https://doi.org/10.1515/znc-2014-4138 (2015).Article 
CAS 

Google Scholar 
Freitas, M. V. et al. Influence of aqueous crude extracts of medicinal plants on the osmotic stability of human erythrocytes. Toxicol. In Vitro. 22, 219–224. https://doi.org/10.1016/j.tiv.2007.07.010 (2008).Article 
CAS 
PubMed 

Google Scholar 
Oyedapo, O. O., Akinpelu, B. A., Akinwunmi, K. F., Adeyinka, M. O. & Sipeolu, F. O. Red blood cell membrane stabilizing potentials of extracts of Lantana camara and its fractions. Plant Physiol. Biochem. 2, 46–51 (2010).
Google Scholar 
Bilto, Y. Y., Suboh, S., Aburjai, T. & Abdalla, S. Structure-activity relationships regarding the antioxidant effects of the flavonoids on human erythrocytes. Nat. Sci. 4, 740–747. https://doi.org/10.4236/ns.2012.4909 (2012).Article 

Google Scholar 
Ajaiyeoba, E. O. et al. In vitro cytotoxicity studies of 20 plants used in Nigerian antimalarial ethnomedicine. Phytomed. 13, 295–298 (2006).Article 
CAS 

Google Scholar 
Vélez, E., Regnault, H. D., Jaramillo, C. J., Veléz, A. P. E. & Isitua, C. C. Fitoquímica de Lippia citriodora K cultivada en Ecuador y su actividad biológica. Rev. Cien. UNEMI. 12, 9–19 (2019).Article 

Google Scholar 
Costa, P. S. et al. Antifungal activity and synergistic effect of essential oil from Lippia alba against trichophyton rubrum and Candida spp. Rev. Virt. Quim. 12, 1–12. https://doi.org/10.21577/1984-6835.20200119 (2020).Article 
CAS 

Google Scholar 
Gupta, P., Khobragade, S. B., Shingatgeri, V. M. & Rajaram, S. M. Assessment of locomotion behavior in adult Zebrafish after acute exposure to different pharmacological reference compounds. Drug Des. Devel. Ther. 5, 127–133. https://doi.org/10.4103/2394-2002.139626 (2014).Article 
CAS 

Google Scholar 
Bezerra, P. et al. Composição química e atividade biológicade óleos essenciais de plantas do Nordeste—gênero Lippia. Cienc. Cult. 33, 1–14 (1981).CAS 

Google Scholar 
Pascual, M. E., Slowing, K., Carretero, E., Sánchez Mata, D. & Villar, A. Lippia: Traditional uses, chemistry and pharmacology: A review. J. Ethnopharmacol. 76, 201–214. https://doi.org/10.1016/s0378-8741(01)00234-3 (2001).Article 
CAS 
PubMed 

Google Scholar 
Mamun-Or-Rashid, A. N. M., Sen, M. K., Jamal, M. A. H. M. & Nasrin, S. A comprehensive ethnopharmacological review on Lippia alba M. Int. J. Biomed. Mater. Res. 1, 14–20. https://doi.org/10.11648/j.ijbmr.20130101.13 (2013).Article 

Google Scholar 
Mácová, S. et al. Comparison of acute toxicity of 2-phenoxyethanol and clove oil to juvenile and embryonic stages of Danio rerio. Neuroendocrinol. Lett. 29, 680–684 (2008).PubMed 

Google Scholar 
Batista, F. L. A. et al. Antinociceptive effect of volatile oils from Ocimum basilicum flowers on Adult Zebrafish. Rev. Bras. Farmacog. 31, 282–289. https://doi.org/10.1007/s43450-021-00154-5 (2021).Article 
CAS 

Google Scholar 
Horzmann, K. A. & Freeman, J. L. Making waves: New developments in toxicology with the Zebrafish. Toxicol. Sci. 163, 5–12. https://doi.org/10.1093/toxsci/kfy044 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ferreira, M. K. A. et al. Anxiolytic-like effect of chalcone N-{(4′-[(E)-3-(4-fluorophenyl)-1-(phenyl) prop-2-en-1-one]} acetamide on adult zebrafish (Danio Rerio): Involvement of the GABAergic system. Behav. Brain Res. 374, 111871. https://doi.org/10.1016/j.bbr.2019.03.040 (2019).Article 
CAS 
PubMed 

Google Scholar 
Siqueira-Lima, P. S. et al. Central nervous system and analgesic profiles of Lippia Genus. Rev. Bras. Farmacogn. 29, 125–135. https://doi.org/10.1016/j.bjp.2018.11.006 (2019).Article 
CAS 

Google Scholar 
Ferreira, M.K.A. da Silva, A.W. dos Santos Moura, A.L. Sales, K.V.B. Marinho, E.M. do Nascimento Martins Cardoso, J. Marinho, M.M. Bandeira, P.N. Magalhães, F.E.A. Marinho, E.S. et al. Chalcones reverse the anxiety and convulsive behavior of adult zebrafish. Epilepsy Behav. https://doi.org/10.1016/j.yebeh.2021.107881 (2021).Silva, A. W., Wlisses, A., Kueirislene, M., Ferreira, A. & Ramos, L. Combretum lanceolatum extract reverses anxiety and seizure behavior in adult zebrafish through GABAergic neurotransmis-Sion: An in vivo and in silico study. J. Biomol. Struct. Dyn. https://doi.org/10.1080/07391102.2021.1935322 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Selmani, A. & Kovaˇcevi´, D., Bohinc, K.,. Nanoparticles: From synthesis to applications and beyond. Adv. Colloid Interface Sci. 303, 102640. https://doi.org/10.1016/j.cis.2022.102640 (2022).Article 
CAS 
PubMed 

Google Scholar  More

Suborder Glossiphoniiformes Tessler & de Carle, 2018Family Glossiphoniidae Vaillant, 1890Comments. Our two-locus phylogeny reveals the presence of two large clades, corresponding to the subfamilies Glossiphoniinae and Haementeriinae (Fig. 1). The subfamily Theromyzinae Sawyer, 1986, delineated by some authors2,10,22, was not supported as a distant phylogenetic clade and their representatives are clustered within the monophyletic Glossiphoniinae. The same pattern was recovered by earlier phylogenetic reconstructions3,30,33,34. These data indicate that Theromyzinae may represent a synonym of the latter subfamily. However, a subfamily-level revision of the Glossiphoniidae is beyond the framework of the present study.Subfamily Glossiphoniinae Vaillant, 1890Genus Alboglossiphonia Lukin, 1976Type species: Alboglossiphonia heteroclita (Linnaeus, 1761) (= Hirudo heteroclita Linnaeus, 1761; by original designation).Arctic occurrences. Our results reveal that members of this genus are not common inhabitants of the Arctic but two species, A. heteroclita (Linnaeus, 1761) and A. sibirica sp. nov., cross the Arctic Circle on the Yamal Peninsula through the Ob and Taz rivers (Table 1). Previously, it was shown that A. heteroclita occurs in the lower Ob Basin, northern edge of Western Siberia23.Comments. This genus contains inconspicuous minute leeches and is characterized by a nearly global distribution1. It definitely requires an integrative taxonomic revision. Available genetic evidence (Fig. 1 and Supplementary Fig. S1) reveals that the North American populations of what was traditionally assigned to A. heteroclita should be considered a separate species, A. pallida (Verrill, 1872) (type locality: West River near New Haven, Connecticut, USA)35,36. Other species, which occurs in Siberia and the Far East, was tentatively assigned to Alboglossiphonia cf. papillosa (Braun, 1805) based on a darker pigmentation of its dorsum37,38 but it represents a separate North Asian species, which is described here.
Alboglossiphonia sibirica Bolotov, Eliseeva, Klass & Kondakov sp. nov = Alboglossiphonia heteroclita Lukin (1957): 27339 (identification error). = Alboglossiphonia heteroclita papillosa Kaygorodova et al. (2014): 337; Kaygorodova (2015): 4140 (identification error). = Alboglossiphonia cf. papillosa Klass et al. (2018): 2638 (identification error).Figures 4a, 5a, 7a, Supplementary Figs. S2a, S3a, S4, Supplementary Table S2.LSID: https://zoobank.org/urn:lsid:zoobank.org:act:19B581C3-E912-487C-B9EC-8E50DDEFD380.Holotype. RMBH Hir_0542_2-H (non-sequenced), RUSSIA: Lake Torfyanka, 43.0761° N, 131.9620° E, Vladivostok, Primorye, August 12, 2021, Y. E. Chapurina leg.Paratypes (N = 13). RUSSIA: 1 specimen RMBH Hir_0542_2 (sequenced: COI sequence acc. No. ON873332), the type locality, the same date, and collector; 1 specimen RMBH Hir_0396 (non-sequenced), an oxbow lake of Taz River, near Tazovsky settlement, 67.5063° N, 78.6751° E, Yamal-Nenets Region, August 22, 2019, E. S. Babushkin leg.; 1 specimen RMBH Hir_0394 (DNA voucher; sequenced: COI sequence acc. No. ON548508), Vitim River, 57.2010° N, 116.4300° E, Lena River basin, Vitimsky Nature Reserve, Irkutsk Region, July 12, 2019, E. S. Babushkin leg.; 4 specimens RMBH Hir_0013 (3 sequenced with DNA vouchers and one placed on 36 permanent slides as a series of slices; COI sequence acc. No. MH286267, MH286268, and MH286269; 18S rRNA sequence acc. No. MH286273), between zooids of a bryozoan colony, small floodplain lake of the Lena River near Yakutsk, 62.3076° N, 129.8999° E, Yakutia Republic, August 20, 2017, I. N. Bolotov leg.; 1 specimen RMBH Hir_0417_2 (DNA voucher; sequenced: COI sequence acc. No. ON548511), Oron Lake, Gnilaya Kurya Bay, 57.1750° N, 116.4031° E, Lena River basin, Vitimsky Nature Reserve, Irkutsk Region, July 1, 2019, E. S. Babushkin leg.; 1 specimen RMBH Hir_0409_1 (sequenced: COI sequence acc. No. ON548509), a roadside ditch in Knevichi settlement, 43.3886° N, 132.1880° E, Primorye, September 10, 2020, O. V. Aksenova et al. leg.; 1 specimen RMBH Hir_0413 (sequenced: COI sequence acc. No. ON548510), a puddle near railway at Artem city, 43.3794° N, 132.2188° E, Primorye, September 10, 2020, O. V. Aksenova et al. leg.; 1 specimen RMBH Hir_0003_3 (DNA voucher; sequenced: COI sequence acc. No. MN393256), Tumnin River, 49.9451° N, 139.9181° E, Khabarovsk Region, July 14, 2014, I. N. Bolotov & I. V. Vikhrev leg.; 1 specimen RMBH Hir_0509_1 (sequenced: COI sequence acc. No. ON548516), a reservoir on the Bolshoy Alim River, near Tolstovka settlement, 50.1981° N, 127.9431° E, Amur Region, July 3, 2021, O. V. Aksenova et al. leg.; 1 specimen RMBH Hir_0510_1 (DNA voucher; sequenced: COI sequence acc. No. ON548517), an oxbow lake of Bureya River, near Novospassk, 49.6756° N, 129.7343° E, Amur Region, July 3, 2021, O. V. Aksenova et al. leg.Etymology. The name of this species reflects its broad distribution in Siberia.Differential diagnosis. Small leech, which could be distinguished from other congeners by a combination of the following characters: dorsum covered by numerous small, shallow, and indistinct papillae, light yellow, with multiple dark spots and short dashes arranged to 18–24 longitudinal rows; these spots and dashes merged into longitudinal lines in the anterior half of the body (the dark markings pattern often lost in ethanol-preserved animals). Externally, the new species is similar to A. heteroclita, A. hyalina (O. F. Müller, 1773), and A. striata (Apáthy, 1888). However, all these species do not have numerous dark spots and short dashes arranged to multiple longitudinal rows. Additionally, A. heteroclita differs from the new species by having a median row of segmentally arranged dark spots and a smooth dorsum without papillae. A. hyalina differs from A. sibirica sp. nov. by the general lack of dark pigmentation. A. striata differs from the new species by having a median row of segmentally arranged dark transverse stripes and a smooth dorsum without papillae.Molecular diagnosis. The new species represents a separate genetic lineage but is more closely related to A. heteroclita (mean pairwise COI p-distance = 5.1%; range 4.9–5.4%). The intraspecific pairwise COI p-distance ranges from 0.0 to 2.1% (mean ± s.e.m. = 1.31 ± 0.10%; N = 14 sequences and 91 pairwise distance values). The GenBank acc. numbers of reference DNA sequences (COI and 18S rRNA) are given in Supplementary Table S2 and Supplementary Datasets S1–S2.Description. Small leech (body length up to 11.9 mm). Measurements of the type series are given in Supplementary Table S2. Body broad, leaf-like, ovate. Dorsum with numerous small, shallow, and indistinct papillae. Posterior sucker small, circular (maximum diameter of 2.25 mm), ventrally directed. Proboscis pore in the center of anterior sucker. Coloration of living animals: body dirty yellow with multiple brown spots and dashes arranged to longitudinal rows; in the anterior half of the body, these spots and dashes merged into longitudinal lines. Coloration of ethanol-preserved animals: body light yellow; dorsum with multiple dark spots and short dashes arranged to 18–24 longitudinal rows; these spots and dashes merged into longitudinal lines in the anterior half of the body but the dark markings pattern often lost due to preservation. Three pairs of eyespots; the eyespots of the distal pair joined into a single spot; the eyespots of the next two pairs are spaced apart and fused together. Venter light yellow or whitish. Total number of annuli: 70. Somites I–IV joined to form a head region, somites V–XXIV triannulate, somites XXV–XXVII uniannulate. Gonopores joined and open in the furrow XIIa1/a2. Reproductive system: 6 pairs of large, bag-like testisacs inter-segmentally from XIII/XIV to XIX/XX; atrium small, spherical, the atrial cornua twisted anteriorly; paired ejaculatory ducts twisted, short; paired ovisacs narrow, very short. Digestive system: proboscis sheath massive, long, thick; salivary glands diffuse; crop with 6 pairs of crop caeca: 1st-5th uniform, bag-like, 6th pair (posterior caeca) with 3 blind processes; intestine with 4 pairs of rather short processes and an ovate extention after the last pair of processes.Distribution. North Asia: Western Siberia, Eastern Siberia, the Russian Far East, and Mongolia39.Habitats and ecology. This species is known to occur in a broad range of freshwater environments such as rivers, oxbow lakes, large to small natural lakes, reservoirs, road ditches, and even puddles (Supplementary Dataset S2). An unusual example of its association with a bryozoan species was described from Eastern Siberia38. Probably, the record of an Alboglossiphonia leech in the mantle cavity of an unidentified lymnaeid snail from the Altai Mountains, Russia41 could also be attributed to this species. The life cycle of the new species is unknown.Genus Glossiphonia Johnson, 1816Type species: Glossiphonia complanata (Linnaeus, 1758) (= Hirudo complanata Linnaeus, 1758; by subsequent designation).Arctic occurrences. Representatives of this genus are the most remarkable component of the Arctic Glossiphoniidae fauna. Altogether seven species were recorded north of the Arctic Circle, two of which are new to science and described here (Table 1).Comments. In general, sequenced representatives of the genus Glossiphonia could phylogenetically be delineated to three species groups (or subgenera): (1) the complanata-group (= subgenus Glossiphonia s. str.); (2) the verrucata-group (= subgenus Boreobdella Johansson, 1929; type species: Clepsine verrucata Müller, 1844); and (3) the concolor-group (= subgenus Paratorix Lukin & Epstein, 1960; type species: Torix baicalensis Stschegolew, 1922) (Table 1, Fig. 1 and Supplementary Fig. S1).
Glossiphonia arctica Bolotov, Eliseeva, Klass & Kondakov sp. novFigures 4B, 5b,c, 7c, Supplementary Figs. S2b, S3b, S5, Supplementary Table S2.LSID: https://zoobank.org/urn:lsid:zoobank.org:act:FADF0993-A946-413A-9680-25BA0F9BE90D.Holotype. RMBH Hir_0457_2_1-H (sequenced: COI sequence acc. No. ON810735; 18S rRNA sequence acc. No. ON819028), RUSSIA: a large lake near Sob’ railway station, 67.0480°N, 65.6316°E, Polar Urals, June 23, 2021, A. V. Kondakov et al. leg.Paratypes (N = 18). 18 specimens RMBH Hir_0457 (two specimens sequenced: COI sequence acc. No. ON810736 and ON810737; 18S rRNA sequence acc. No. ON819029; one specimen placed on 18 permanent slides as a series of slices), the type locality, the same date, and collectors.Etymology. The name of the new species indicates that its type locality is situated in the Arctic Region.Differential diagnosis. Medium-sized leech, which could be distinguished from other congeners by a combination of the following characters: dorsum with four rows of ovate, broad but very shallow and indistinct papillae on annulus a2 (outer paramedian and inner paramarginal series); each papilla bears ovate light yellow or white spot; dorsal black markings pattern absent. Externally, the new species is similar to G. mollissima. However, the latter species differs from G. arctica sp. nov. by having larger papillae and a well-developed black markings pattern dorsally.Molecular diagnosis. The new species represents a separate genetic lineage belonging to the verrucata-group (Fig. 1). The pairwise COI p-distance of the new species from other congeners varies from 7.0 to 12.4%. The intraspecific pairwise COI p-distance ranges from 0.0 to 0.2% (mean ± s.e.m. = 0.10 ± 0.05%; N = 3 sequences and 3 pairwise distance values). The GenBank acc. numbers of reference DNA sequences (COI and 18S rRNA) are given in Supplementary Table S2 and Supplementary Datasets S1–S2.Description. Medium-sized leech (body length up to 13.3 mm). Measurements of the type series are given in Supplementary Table S2. Body broad, leaf-like, ovate. Dorsum with four rows of ovate, broad but very shallow and indistinct papillae on annulus a2 (outer paramedian and inner paramarginal series). Posterior sucker small, circular (maximum diameter of 1.9 mm), ventrally directed. Proboscis pore in the center of anterior sucker. Coloration of living animals: body almost transparent, light brown, with multiple yellowish pigment cells. Coloration of ethanol-preserved animals: dorsum beige to light brown, with darker broad inner paramedian lines and light yellowish areas laterally and anteriorly; ovate light yellow or white spots at each papillae on annulus a2 arranged into four longitudinal rows (outer paramedian and inner paramarginal), sometimes with a few white spots between them. Three pairs of ovate eyespots arranged to two parallel rows; in some specimens eyes on each side are joined to a single large spot. Venter whitish to light brown, sometimes with irregular brownish shading. Total number of annuli: 70. Somites I–III uniannulate, IV biannulate, V–XXIV triannulate, XXV biannulate, XXVII uniannulate. The male and female genital pores are separated by two annuli and are located in the furrows XIa3/XIIa1 and XIIa2/a3, respectively. Reproductive system: 6 pairs of spherical testisacs inter-segmentally from XIII/XIV to XVIII/XIX; atrium spherical, the atrial cornua large, twisted anteriorly; paired ejaculatory ducts very long, extending to XVIII; paired ovisacs massive, long, with multiple lobes, arranged as loops, extending to XVIII (pregnant specimen with eggs). Digestive system: proboscis sheath massive, thick, elongated; esophagus narrow; salivary glands diffuse; crop with 7 pairs of crop caeca: 1st-6th uniform, bag-like, 7th pair (posterior caeca) with 4 blind processes and several smaller lobes; intestine enlarged, with 4 pairs of large, long, bag-like processes, expanding distally, each with several short lobes; a large circular extension after the last pair of processes.Distribution. Polar Urals (not known beyond the type locality).Habitats and ecology. The type series of this species was collected from a natural mountain lake with stony bottom. The leeches were recorded beneath flat stones (Fig. 3b); their feeding behavior and life cycle remain unknown.
Glossiphonia taymyrensis Bolotov, Eliseeva, Klass & Kondakov sp. novFigures 4E, 5d, 7b, Supplementary Figs. S2h, S3c, S6, Supplementary Table S2.LSID: https://zoobank.org/urn:lsid:zoobank.org:act:40269BF4-FE1C-4269-A7CC-41020789DC44.Holotype. RMBH Hir_0258_1-H (sequenced: COI sequence acc. No. ON810695), RUSSIA: small lake near Dudinka on Taymyr Peninsula, 69.4008°N, 86.3384°E, July 16, 2018, O. V. Aksenova et al. leg.Paratypes (N = 8). RUSSIA: 2 specimens RMBH Hir_0263_1 and RMBH Hir_0264_3 (sequenced: COI sequence acc. No. ON810701 and ON810705; 18S rRNA sequence acc. No. ON819017), the type locality, the same date, and collectors; 2 specimens RMBH Hir_0256_1 (one sequenced and one placed on 20 permanent slides as a series of slices; COI sequence acc. No. ON810693), small lake near Dudinka on Taymyr Peninsula, 69.3987° N, 86.3505° E, July 16, 2018, O. V. Aksenova et al. leg.; 1 specimen RMBH Hir_0261_2 (sequenced: COI sequence acc. No. ON810699; 18S rRNA sequence acc. No. ON819016), small lake near Dudinka on Taymyr Peninsula, 69.4014° N, 86.3250° E, July 16, 2018, O. V. Aksenova et al. leg.; 1 specimen RMBH Hir_0265_2 (sequenced: COI sequence acc. No. ON810706; 18S rRNA sequence acc. No. ON819021), Bolgokhtokh River near Dudinka, Taymyr Peninsula, 69.3780° N, 87.2215° E, July 21, 2018, O. V. Aksenova et al. leg.; 1 specimen RMBH Hir_0488 (sequenced: COI sequence acc. No. ON810755), a lake on Putorana Plateau, 68.7607° N, 91.9014° E, July, 2021, E. S. Chertoprud leg.; 1 specimen RMBH Hir_0449 (sequenced: COI sequence acc. No. ON810731), Pyzas River near Ust-Kabyrza settlement, 52.8277° N, 88.3973° E, Tashtagolsky District, Kemerovo Region, July 23, 2020, E. S. Babushkin & M. V. Vinarski leg.Etymology. The new species is named after the Taymyr Peninsula, where the majority of the type specimens were collected.Differential diagnosis. Small leech with broad, leaf-like, ovate body; three pairs of eyespots (distal pair joined; next two pairs separate); dorsal papillae absent; dorsal coloration with two inner paramedian rows of black spots, sometimes joining into unclear dashed lines; two annuli between the male (XIa3/XIIa1) and female (XIIa2/a3) genital pores. The new species largely resembles G. complanata but could be distinguished from it by having a smooth dorsum, without clear papillae. These taxa seem to have non-overlapping, allopatric ranges and, hence, could be separated on the basis of geographic criteria. However, the DNA approach seems to be the most appropriate way to distinguish these two species.Molecular diagnosis. The new species represents a separate genetic lineage belonging to the complanata-group (Fig. 1). The pairwise COI p-distance of the new species from other congeners varies from 6.0 to 12.2%. The intraspecific pairwise COI p-distance ranges from 0.0 to 1.1% (mean ± s.e.m. = 0.52 ± 0.07%; N = 8 sequences and 28 pairwise distance values). The GenBank acc. numbers of reference DNA sequences (COI and 18S rRNA) are given in Supplementary Table S2 and Supplementary Datasets S1–S2.Description. Small leech (body length up to 11.3 mm). Measurements of the type series are given in Supplementary Table S2. Body broad, leaf-like, ovate. Dorsum smooth, without clear papillae. Posterior sucker ovate (maximum diameter of 3.0 mm), ventrally directed. Proboscis pore in the center of anterior sucker. Coloration of living animals: not examined. Coloration of ethanol-preserved animals: (1) typical form having beige to light brown ground color without light spots but with darker brown coloration between inner paramedian lines; (2) melanic forms having dark brown ground color with four rows of large yellow spots (outer paramedian and marginal series) and yellow median stripe anteriorly (f. ‘maculosa’) or with strongly reduced yellow markings pattern. In all forms, there are two inner paramedian rows of black spots, sometimes joining into unclear dashed lines. Three pairs of ovate eyespots; the eyespots of the distal pair joined into a single spot; the eyespots of the next two pairs separate and are spaced apart. In the typical form, venter light yellow, with paired brown median and outer paramedian lines, which may be reduced to series of narrow brown longitudinal stripes. In melanic forms, ventral markings is more developed, with a series of brown longitudinal lines from median to inner paramarginal position and outer paramarginal brown spots. Posterior sucker with dense brown spots in melanic forms and with scarce brown spots in typical form. Total number of annuli: 68. Somites I–IV uniannulate, V–XXIV triannulate, XXV biannulate, XXVI–XXVII uniannulate. The male and female genital pores are separated by two annuli and are located in the furrows XIa3/XIIa1 and XIIa2/a3, respectively. Reproductive system: 6 pairs of spherical testisacs inter-segmentally from XII/XIII to XVIII/XIX; atrium ovate, the atrial cornua directed laterally; paired ejaculatory ducts twisted, short; paired ovisacs short, thick (undeveloped). Digestive system: salivary glands diffuse; proboscis sheath moderately thick; esophagus ovate; crop with 6 pairs of massive, bag-like, uniform crop caeca; intestine with 4 pairs of processes.Distribution. Western and Eastern Siberia.Habitats and ecology. The new species was recorded from natural lakes and rivers (Supplementary Dataset S2); its feeding behavior and life cycle are unknown.Genus Hyperboreomyzon Bolotov, Eliseeva, Klass & Kondakov gen. novLSID: https://zoobank.org/urn:lsid:zoobank.org:act:298FF41E-AF0D-4442-9F82-3022B8094A67.Type species: Hyperboreomyzon polaris gen. & sp. nov.Etymology. This name is compiled using two Greek words: ‘Hyperborea’ (meaning a mythical far northern land) and ‘myzon’ (meaning sucking).Diagnosis. Medium-sized, elongate, sub-fusiform glossiphoniid leeches; body and posterior sucker densely covered by shallow, ‘fish-scale’-like papillae; somite V biannulate; somites XII–XXIII secondarily sexannulate dorsally and ventrally due to the presence of very deep, prominent furrows separating each annulus to two semi-annuli; six rows of prominent dorsal tubercle-like papillae at a2 (inner paramedian, inner paramarginal, and marginal series) from V to XXVI; two pairs of circular eyespots on II and Va1 at inner paramedian position; gonopores at the furrows XIa3/XIIa1 (male) and XIIa2/a3 (female) and separated by two annuli; male atrium spherical; proboscis pore opens in a thick velar fold in the anterior half of oral sucker; one pair of compact, massive, elongated, incurved salivary glands, each gland with a bunch of a few short processes apically; 9 crop caeca pairs. Comparison of the new genus with other genera in the family based on morphological and anatomical features is presented in
Supplementary Table S3. Sexannulate condition was also recorded in the genus Actinobdella Moore, 1901 from North America36, but it differs from Hyperboreomyzon gen. nov. by having one pair of eyespots, diffuse salivary glands, and an apical position of proboscis pore (Supplementary Table S3).Comments. This genus is established for a single species, which is described below.
Hyperboreomyzon polaris Bolotov, Eliseeva, Klass & Kondakov gen. & sp. nov.Figures 4J, 5e, 6a-j, 7c, Supplementary Figs. S21, S8, S9, S10, S11, Supplementary Table S2.LSID: https://zoobank.org/urn:lsid:zoobank.org:act:503A9A26-CEDE-4747-952D-8416AE4EF4EB.Holotype. RMBH Hir_0486-H (sequenced: COI sequence acc. No. ON810753; 18S rRNA sequence acc. No. ON819030), RUSSIA: small alpine lake on Putorana Plateau, 68.9008°N, 94.1599°E, July, 2021, E. S. Chertoprud leg.Paratypes (N = 2). RUSSIA: 1 specimen RMBH Hir_0689 (dissected and placed on 60 permanent slides as a series of slices), small alpine lake on Putorana Plateau, 68.6659° N, 93.1365° E, August 11, 2021, E. S. Chertoprud leg.; 1 specimen RMBH Hir_0216 (sequenced and dissected; COI sequence acc. No. ON810677; 18S rRNA sequence acc. No. ON819005), water puddle on Kolguev Island, 68.9300° N, 49.0303° E, August 12, 2018, O. V. Travina & V. M. Spitsyn leg.Etymology. The name of the new species reflects its occurrences in polar (Arctic) areas of Eurasia.Differential diagnosis. As for the genus.Molecular diagnosis. None of congeneric species is known. Based on uncorrected pairwise COI p-distances between a haplotype of the new taxon and selected species-level haplotypes in each genus (Supplementary Table S1), Hyperboreomyzon seems to be more closely related to members of Hemiclepsis (mean distance ± s.e.m. = 11.62 ± 0.15%, range = 9.75–14.08%, N = 9) and Theromyzon (mean distance ± s.e.m. = 11.37 ± 0.07%, range = 10.47–12.64%, N = 9) without significant differences between distances from these two genera (Mann–Whitney test: p = 0.72). Other Glossiphoniidae genera are more distantly related, with a mean pairwise uncorrected COI p-distance of  > 13.0% (Mann–Whitney test: p  More

Study siteThe Cariaco Basin, located on the continental shelf off Venezuela, is a large (about 160 km long and about 65 km wide) depression, composed of two approximately 1,400-m-deep sub-basins. It is partially isolated from the Caribbean Sea by a series of sills with depths of less than 150 m (ref. 47). This limits renewal of deep water in the basin and, paired with the high oxygen demand resulting from intense surface primary productivity, leads to anoxic waters below a depth of about 275 m at present47,48.The marked seasonality in the Cariaco Basin, combined with anoxic bottom waters that effectively prevent bioturbation, results in the accumulation of annually laminated (varved) sediments. As sediments are varved for the last deglaciation and the Holocene, and because of the sensitivity of the area to climate change, they are considered to be one of the most valuable high-resolution marine climate archives and have been successfully used to study climate variability in the tropics3,11,16,17,18. Varve thickness is about 1 mm or more during the YD–Holocene transition18.Core and age modelCore MD03-2621 was retrieved during IMAGES cruise XI (PICASSO) aboard R/V Marion Dufresne in 2003 (Laj and Shipboard Party 2004). Cariaco cores have been collected under the regulations of the Ocean Drilling Program and the IMAGES coring programme. In this study, data from depths between 480 and 540 cm below the seafloor are presented, encompassing the YD–Holocene transition. A detailed age model for core MD03-2621 was established by Deplazes et al.11 and is based on the cross-correlation of total reflectance to dated colour records from the Cariaco Basin49,50. For the studied interval, the original age model is based on a floating varve chronology anchored to tree ring data by matching 14C data49. The age model for core MD03-2621 was further fine-tuned by correlation of reflectance data to the NGRIP ice core δ18O record on the GICC05 age scale11. The transition from the YD to the Holocene is characterized by a decrease in the sedimentation rate from 1.4 to 0.5 mm year−1.To account for possible depth offsets during storage and subsampling, we matched sediment colour data expressed as greyscale (GS) to the reflectance data from Deplazes et al.11 with the software QAnalySeries51. To enable comparison with our record, ages in Lea et al.3 were corrected for the age difference between the sediment-colour-based midpoint of the YD–Holocene transition in their record (11.56 kyr b2k) and in data from Deplazes et al.11 (11.673 kyr b2k). The start and end of the change in reflectance were determined by the RAMPFIT software52.Sample preparationSamples for MSI of molecular proxies were prepared as described in Alfken et al.53: the original core was subsampled by LL channels, from which X-ray pictures (Hewlett-Packard Faxitron 43855A X-ray cabinet) and high-resolution digital images (smart-CIS 1600 Line Scanner) were obtained. The LL channels were then cut into 5-cm pieces, which were subsequently freeze-dried, embedded in a gelatin:carboxymethyl cellulose (4%:1%) mixture and thin-sectioned on a Microm HM 505 E cryomicrotome. From each piece, one 60-µm-thick and one 100-µm-thick, longitudinal slice (spanning the whole 5 cm piece) were prepared and affixed to indium-tin-oxide-coated glass slides (Bruker Daltonik, Bremen, Germany) for MSI and elemental mapping, respectively. Slices for MSI were further amended with a fullerite matrix54.For all slices, a high-resolution picture was taken on a M4 Tornado micro-X-ray fluorescence spectroscopy system (Bruker Nano Analytics). This picture was used as a reference to set up elemental mapping and MSI analysis, and also for the 2D comparison of elemental and proxy data to sediment colour. Sediment colour is expressed as GS value. To account for differences between single slices, ΔGS was calculated as the difference between a value and the median GS of each individual slice. Very low GS values corresponding to areas devoid of sediment, identified by a black background, were excluded from analysis.Elemental mappingElemental mapping of 100-µm-thick slices was performed on a M4 Tornado micro-X-ray fluorescence spectroscopy system (Bruker Nano Analytics) equipped with a micro-focused Rh source (50 kV, 600 µA) with a polycapillary optic. Measurements were conducted under vacuum, with a resolution of 50 µm, two scans per spot and a scan time of 5 ms per scan. Data were initially processed and visualized with M4 Tornado Software version 1.3. XY matrices of relevant elements and sediment colour were imported into MATLAB (R2016b) for further processing. To assess the correspondence between sediment colour and elemental composition, for each 5-cm piece, signal intensities of Ca, Fe, Ti and Si in single spots were binned according to ΔGS and average intensities were calculated for each bin (Extended Data Fig. 5). The bin size was 5 GS units.Molecular proxy analysis by MSIMSI was carried out on a 7T solariX XR Fourier transform ion cyclotron resonance mass spectrometer coupled to a matrix-assisted laser desorption/ionization source equipped with a Smartbeam II laser (Bruker Daltonik, Bremen, Germany). Analyses were performed in positive ionization mode selecting for a continuous accumulation of selective ions window of m/z 554 ± 12. Spectra were acquired with 25% data reduction to limit data size. Spatial resolution was obtained by rastering the ionizing laser across the sample in a defined rectangular area at a 100-µm spot distance. Considering laminae thickness in the millimetre range18, such raster resolution is suited for seasonally resolved SST reconstruction. Settings for laser power, frequency and number of shots were adjusted for optimal signal intensities before each measurement; typical values were 250 shots with 200 Hz frequency and 60% laser power. External mass calibration was performed in electrospray ionization mode with sodium trifluoroacetate (Sigma-Aldrich). Each spectrum was also calibrated after data acquisition by an internal lock mass calibration using the Na+ adduct of pyropheophorbide a (m/z 557.2523), a chlorophyll a derivative generally present in relatively young marine sediments. Around 20,000 individual spots were thereby obtained for every 5-cm slice, each spot containing information on the abundance of diunsaturated and triunsaturated C37 alkenones needed to calculate the ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) SST proxy.We provide a two-pronged approach to decode SST proxy information: (1) a downcore ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) profile is obtained by pooling alkenone data from coeval horizons, and results in SST reconstructions with annual resolution, and (2) 2D images of alkenone distribution are examined in conjunction with maps of sediment colour and elemental distribution to filter single-spot alkenone data for season of deposition.SST reconstruction with yearly resolutionFor the downcore profile, MSI data were referenced to the X-ray image by the identification of three teaching points per 5-cm piece. Afterwards, the X-ray image was corrected for tilting of laminae in the LL channels. This was done by identification of single laminae in the X-ray image and selection of a minimum of four tie points per lamina. A detailed description can be found in Alfken et al.9. After applying the corresponding age model, downcore profiles were established with 1-year resolution: the intensity of the two alkenone species relevant to the ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) proxy (C37:2 and C37:3) were recorded for each individual laser spot and filtered for a signal-to-noise threshold of 3. Only spots in which both compounds were detected were further considered. Intensity values were then summed over the depth corresponding to 1 year. By pooling proxy data into 1-year horizons, the effect of changing sedimentation rate and, thereby, changing downcore resolution is minimized. If at least ten spots presenting both compounds were available for a single horizon, data quality criteria were satisfied54 and a ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) value was calculated as defined by Prahl and Wakeham22:$${{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}=frac{{text{C}}_{37:2}}{{text{C}}_{37:2}+{text{C}}_{37:3}}$$
(1)
To apply the gas chromatography (GC)-based calibrations for the ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) proxy, MSI-based data were converted to GC equivalents. Therefore, after MSI, sediment slices were extracted for conventional proxy analysis. Sediment was scraped off the slide and extracted following a modified Bligh and Dyer procedure55,56. Extracts were evaporated under a stream of nitrogen, re-dissolved in n-hexane and analysed on a Thermo Finnigan Trace GC-FID equipped with a Restek Rxi-5ms capillary column (30 m × 0.25 mm ID). For each 5-cm piece, a ratio between the ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) values obtained by GC flame ionization detector analysis and MSI of the whole piece was calculated. The average ratio of all pieces for which GC-based values could be obtained was 1.194, with a standard deviation of 0.021.$${{rm{U}}}_{37,{rm{G}}{rm{C}}-{rm{F}}{rm{I}}{rm{D}}}^{{{rm{K}}}^{{prime} }}=1.194times {{rm{U}}}_{37,{rm{M}}{rm{S}}{rm{I}}}^{{{rm{K}}}^{{prime} }}$$
(2)
This ratio was used to calculate GC-equivalent ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) values, which were then translated into SST using the BAYSPLINE calibration57. The average standard error of the BAYSPLINE model is 0.049 ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) units (corresponding to 1.4 °C) for samples with SST below 23.4 °C, but increases at higher values (to up to 4.4 °C)57. This is explained by the fact that sensitivity of the ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) to SST (that is, the slope of the regression) declines at higher values. In the current dataset, the 95% confidence interval is, on average, ±3.6 °C. The analytical precision of MSI-based SST reconstructions for the ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}), using at least ten data points, according to Alfken et al.9, is about 0.3 °C. Sources of uncertainty are summarized in Extended Data Fig. 10a.For frequency analysis, a continuous, annually spaced record was constructed by linearly interpolating 49 missing values. The record was subsequently detrended. Spectral analysis was performed with the REDFIT module58 using a Hanning window (oversample 2, segments 2). Continuous wavelet transforms were applied to investigate changes in cyclicity over time, using the Morlet wavelet with code provided by Torrence and Compo59 for MATLAB. All steps, except for the wavelet analysis, were performed with the PAST software60.For the assessment of the interannual variability, the SST record was band-pass-filtered for periods between 2 and 8 years. The record is based on 1-year binned data; seasonality is thereby nullified and the highest frequency to be evaluated (Nyquist frequency) corresponds to a period of 2 years. Variability of this time series was quantified by calculating the standard deviation of the band-pass-filtered ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) signal in 25-year intervals. To account for the potential impact of analytical precision on the observed signal (Methods, section titled ‘The effect of changing sedimentation rate on reconstructed interannual SST variability during the YD–Holocene transition’), the variability experiment from Alfken et al.9 was revisited. A sediment extract had been sprayed on an ITO slide and analysed by MSI. We then randomly selected n spots and obtained a ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) value for the summed intensities of these spots. Precision was calculated as the standard deviation of five replicate experiments for n = 1, 5, 10, 20, 30, 40, 50 and 60. Decreasing analytical variability with increasing number of observations was fitted to a curve (R2 = 0.838) described by the equation$${rm{Analytical}},{rm{variability}}=0.0741times {rm{number}},{rm{of}},{{rm{spots}}}^{-0.558}$$
(3)
On the basis of this equation, analytical variability for each horizon could be calculated on the basis of the number of values included (Extended Data Fig. 10b). The mean variability for each 25-year window was then subtracted from the observed variability in the band-pass-filtered signal and the resulting proxy values were translated to SST following the equation by Müller et al.61. Statistical significance of the change in corrected SST variability after 11.66 kyr b2k was assessed with a t-test.Assessment of SST seasonalityFor the assessment of SST seasonality, alkenone intensities from individual spots were binned according to ΔGS, with a bin size of 1 unit. Spots were then separated into the categories upwelling season and non-upwelling season by identifying the threshold ΔGS value that maximized the difference between average SST in the bins above and below it. Furthermore, this value had to fulfill three conditions: (1) be higher (lighter) than the bins with the highest relative abundance of Ca, Ti and Fe, which is indicative of the dark sediments associated to non-upwelling season, (2) be lower (darker) than the bin with highest relative abundance for Si indicative of light sediment associated to the upwelling season and (3) the number of spots categorized as upwelling and non-upwelling had to account for at least 25% of total spots. If criteria 1 and 2 prevented criteria 3 from being fulfilled, a limit of 15% was set. After separating data into these two categories, data were processed separately as described above for the unfiltered dataset and a downcore temporal resolution of 5 years was applied. Seasonality was calculated as the difference between both records and thus represents the difference between 5-year average SST in the non-upwelling and upwelling seasons.Shift in seasonality was fitted to two different ramps with the RAMPFIT software52. An unconstrained approach and a constrained approach (in which the start and end points of the ramp were restricted to the intervals 11.725–11.8 kyr b2k and 11.6–11.675 kyr b2k) were applied. Negative values were excluded from this fitting. The resulting groups of data were compared by a Mann–Whitney rank test.SST seasonality in the modern Cariaco Basin was calculated for the years 1980 to 2020 based on the HadISST dataset62 by dividing monthly data from each year into two groups and searching for the largest difference between the average temperatures of both groups. Each group had to include at least three consecutive months. In 36 out of 41 years, the warm season was defined from May to November or from July to November.Decadal-scale to centennial-scale SST changes during the YD–Holocene transition and in the early HoloceneAnnually reconstructed SST (average SST = 24.3 °C) remains relatively stable during the YD–Holocene transition. At around 11.4 kyr b2k, a warming trend is observed. Averaging all data before 11.39 kyr and after 11.37 kyr results in a warming from 23.9 ± 1.6 °C to 25.5 ± 1.4 °C. Trends identified by MSI are consistent with conventional ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) analyses performed in the present study and those previously reported by Herbert and Schuffert23 on Ocean Drilling Program core 165-1002C (Extended Data Fig. 1). These authors observed a slight warming several hundred years after the transition into the Holocene, between about 11.53 and 11.32 kyr b2k.Three prominent SST maxima are observed between about 11.50 and 11.45 kyr b2k. The average SST in these 50 years is 1.3 °C higher than in the 50 years before and after. These maxima are synchronous with the 11.4-ka cold event or PBO characterized by a negative excursion in δ18O and reduced snow accumulation rates in Greenland ice cores63 (Extended Data Fig. 2). The PBO coincides with the oldest of the Bond events, that is, pulses of ice rafting in the Northern Atlantic indicative of climatic deterioration64.A warm tropical response to the PBO would be supported by the lower-resolution foraminiferal SST record of Lea et al.3, which shows two data points of increased SST shortly after the end of the YD–Holocene transition. To enable direct comparison, ages in Lea et al.3 were corrected for the age difference between the sediment-colour-based YD termination midpoint in their record and in data from Deplazes et al.11. After this correction, these maxima correspond to 11.43 and 11.50 kyr b2k (Extended Data Fig. 2). Further, the SST maxima coincide with a short-lived change to lighter-coloured sediments. Hughen et al.19 described a correlation between brief North Atlantic cold events, such as the PBO, and changes in tropical primary productivity mediated by stronger upwelling that result in lighter sediments in the Cariaco Basin. Far-reaching effects of the PBO have previously been described in West Asia, with increased dust plumes being related to a southward shift of the westerlies65.The identification of the mechanisms behind a potential TNA response to the PBO is beyond the scope of this study. However, we wish to point out that high-resolution records are crucial to identify such events and to differentiate between underlying changes coinciding in time and, as in the present case, sharp signals that act on the same multidecadal timescales and can potentially be triggered by the same processes66.The effect of changing sedimentation rate on reconstructed interannual SST variability during the YD–Holocene transitionPooling proxy data into 1-year horizons establishes a constant sampling rate and thereby prevents potential effects of changing sedimentation rates. The onset of the Holocene in the Cariaco Basin sediments is characterized by a sharp decrease in sedimentation rates from 1.4 to 0.5 mm year−1 (refs. 11,19). Consequently, in the yearly pooled data, we observe a reduction in the number of values summed for each horizon (Extended Data Fig. 10b), as fewer laser spots fit into the thinner Holocene annual layers. At the same time, the mean intensity in each of these spots slightly increases, consistent with a relative increase of the contribution of haptophytes to primary production20.We have previously shown that the precision of MSI-based molecular proxy analysis is dependent on both the number of spots pooled per data point and the signal intensity in these spots54. All horizons used in the downcore record are above the established threshold of ten spots and proxy variability was shown to stabilize above this threshold9,54. However, as a decrease in the number of values per horizon might still result in lower analytical precision and contribute to higher signal variability, we corrected variability in the 2–8-year window with the estimated analytical variability (see equation (3)). With this correction, the magnitude of the described variability decreases across the record, but the trend towards higher interannual variability in the Holocene persists (Fig. 2c).Varve formation and alkenone deposition in the sediments of the Cariaco Basin during the YD–Holocene transitionComparison of elemental maps and sediment colour (Extended Data Fig. 5) shows a consistent pattern of lamination across the YD–Holocene transition that results from the seasonal interplay of precipitation, upwelling and dominant phytoplankton community composition. Darker laminae represent the rainy, non-upwelling (summer/fall) season and are enriched in Fe and Ti from terrigenous material and Ca sourced from biogenic CaCO3 produced by foraminifera or coccolithophores. Lighter laminae are characterized by high abundance of Si and correspond to the increased production of biogenic opal by diatoms during the upwelling (winter/spring) season67. This is in agreement with observations by Hughen et al.18, who described the laminae couplets in the Cariaco Basin as representing annual cycles, whereby light laminae are an indicator of high productivity associated with the winter/spring upwelling season and dark laminae are an indicator of summer/fall runoff and accumulation of terrigenous material. Deplazes et al.68 described a divergent origin of lamination for a deeper section of the YD, with light laminae being rich in calcareous and terrigenous elements characteristic for the summer season, whereas dark layers were enriched in Si and Br, indicative of diatoms and organic-walled primary producers characteristic for the more productive winter season. Such an alteration of the characteristic pattern of lamination is not observed in the late YD investigated here.This blueprint of seasonality was used to assess the seasonal behaviour of alkenones. Alkenones were deposited throughout the year, as evidenced by the fact that the number of spots containing detectable amounts of both alkenone species are not restricted to the upwelling or non-upwelling seasons but distributed across a relatively wide range of GS values to both sides of the median (Extended Data Fig. 6). Average alkenone signal intensity is higher in the non-upwelling season, pointing to a preference of alkenone producers for this season and/or to a stronger dilution of the signal in the upwelling season. In regards to the ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) SST proxy distribution in light versus dark layers, our observations are in agreement with the ability to capture the seasonal SST cycle with alkenones in sinking particles in the modern Cariaco Basin69.Effect of changing seasonality on YD and early Holocene SST records from the western TNAChanging seasonality can contribute to explaining contrasting lower-resolution SST records in the western TNA during the YD and the early Holocene. The strong warming during the YD–Holocene transition recorded in the foraminiferal Mg/Ca record of the Cariaco Basin (Lea et al.3; Extended Data Fig. 1) might be reflecting the more robust thermohaline stratification and increasingly warmer non-upwelling seasons, given the preference of Globigerinoides ruber for this season.Globigerinoides ruber (white), as used by Lea et al.3, is considered to be a dominant species in the tropics, with a relatively uniform annual distribution. However, in the modern Cariaco Basin, upwelling leads to a distinct foraminiferal community composition and seasonal turnover70, consistent with the notion of warm-water foraminifera narrowing their occurrence to the warmest season71. The relative abundance of G. ruber increases in the non-upwelling (warm) season but rarely exceeds 15%, whereas the upwelling season is clearly dominated by Globigerina bulloides72,73. Globigerinoides ruber fluxes are consistently lowest when upwelling is most vigorous, as expressed in annual minima in SST (Extended Data Fig. 9b). As upwelling during the YD and early Holocene was more intense than in the present70, the preference of G. ruber for the summer (non-upwelling) season might have been even more pronounced.The development of a stronger seasonality in the early Holocene would thus have led to a narrower temporal occurrence of G. ruber in the non-upwelling season, during which it would also be exposed to higher SST. The average SST difference between seasons obtained in our analysis can be converted into annual SST amplitude by assuming a sinusoidal curve. By doing so, we observe an increase in the seasonal amplitude of 1.5 to 1.9 °C (depending on the ramp fitted), which is similar to the warming described by Lea et al.3.This interpretation is in agreement with Bova et al.46, who observed that most Holocene climate reconstructions are biased towards the boreal summer/fall and reflect the evolution of seasonal rather than annual temperatures. As discussed above, this is probably not true for the ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) index in the Cariaco Basin, as alkenones are deposited throughout the year. The suggested weakening of summer stratification during the YD (as compared with the Holocene) might, however, explain why the lower-resolution ({{rm{U}}}_{37}^{{{rm{K}}}^{{prime} }}) records from the semi-enclosed Cariaco Basin show no or weaker warming23 than other, open-ocean, tropical YD records4, where the interplay of upwelling, freshwater input and stratification are less relevant to the SST signal. More

Hawley, W. A. The biology of Aedes albopictus. J. Am. Mosq. Control Assoc. 1, 1–39 (1988).CAS 

Google Scholar 
Benedict, M. Q., Levine, R. S., Hawley, W. A. & Lounibos, L. P. Spread of the tiger: global risk of invasion by the mosquito Aedes albopictus. Vector-Borne Zoonotic Dis. 7, 76–85 (2007).Article 
PubMed 

Google Scholar 
Paupy, C., Delatte, H., Bagny, L., Corbel, V. & Fontenille, D. Aedes albopictus, an arbovirus vector: From the darkness to the light. Microb. Infect. 11, 1177–1185 (2009).Article 
CAS 

Google Scholar 
Delatte, H. et al. Blood-feeding behavior of Aedes albopictus, a vector of Chikungunya on La Réunion. Vector-Borne Zoonotic Dis. 10, 249–258 (2010).Article 
PubMed 

Google Scholar 
Pereira-dos-Santos, T., Roiz, D., Lourenço-de-Oliveira, R. & Paupy, C. A systematic review: Is Aedes albopictus an efficient bridge vector for zoonotic arboviruses? Pathogens 9, 266 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Gratz, N. Critical review of the vector status of Aedes albopictus. Med. Vet. Entomol. 18, 215–227 (2004).Article 
CAS 
PubMed 

Google Scholar 
Grard, G. et al. Zika virus in Gabon (Central Africa)—2007: A new threat from Aedes albopictus? PLoS Negl. Trop. Dis. 8, e2681 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Lambrechts, L., Scott, T. W. & Gubler, D. J. Consequences of the expanding global distribution of Aedes albopictus for dengue virus transmission. PLoS Negl. Trop. Dis. 4, e646 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Lounibos, L. P. & Kramer, L. D. Invasiveness of Aedes aegypti and Aedes albopictus and vectorial capacity for chikungunya virus. J. Infect. Dis. 214, S453–S458 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
European Centre for Disease Prevention and Control (ECDC). Vector Control with a Focus on Aedes aegypti and Aedes albopictus Mosquitoes: Literature Review and Analysis of Information (ECDC, Stockholm, Sweden, 2017).Tatem, A. J., Hay, S. I. & Rogers, D. J. Global traffic and disease vector dispersal. PNAS 103, 6242–6247 (2006).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Lowe, S., Browne, M., Boudjelas, S. & De Poorter, M. 100 of the World’s Worst Invasive Alien Species: A Selection From the Global Invasive Species Database, Vol. 12 (Invasive Species Specialist Group, 2000).Diagne, C. et al. High and rising economic costs of biological invasions worldwide. Nature 592, 571–576 (2021).Article 
CAS 
PubMed 

Google Scholar 
Hulme, P. E. Trade, transport and trouble: Managing invasive species pathways in an era of globalization. J. Appl. Ecol. 46, 10–18 (2009).Article 

Google Scholar 
Marini, F., Caputo, B., Pombi, M., Tarsitani, G. & Della-Torre, A. Study of Aedes albopictus dispersal in Rome, Italy, using sticky traps in mark–release–recapture experiments. Med. Vet. Entomol. 24, 361–368 (2010).Article 
CAS 
PubMed 

Google Scholar 
Bonizzoni, M., Gasperi, G., Chen, X. & James, A. A. The invasive mosquito species Aedes albopictus: current knowledge and future perspectives. Trends Parasitol. 29, 460–468 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Collantes, F. et al. Review of ten-years presence of Aedes albopictus in Spain 2004–2014: Known distribution and public health concerns. Parasit Vectors 8, 1–11 (2015).Article 

Google Scholar 
Aranda, C., Eritja, R. & Roiz, D. First record and establishment of the mosquito Aedes albopictus in Spain. Med. Vet. Entomol. 20, 150–152 (2006).Article 
CAS 
PubMed 

Google Scholar 
Giménez, N. et al. Introduction of Aedes albopictus in Spain: A new challenge for public health. Gac. Sanit. 21, 25–28 (2007).Article 
PubMed 

Google Scholar 
European Centre for Disease Prevention and Control and European Food Safety Authority. Mosquito maps [internet]. Stockholm: ECDC. https://ecdc.europa.eu/en/disease-vectors/surveillance-and-disease-data/mosquito-maps (2022).Shigesada, N. & Kawasaki, K. Biological Invasions: Theory and Practice (Oxford University Press, 1997).
Google Scholar 
Puth, L. M. & Post, D. M. Studying invasion: Have we missed the boat? Ecol. Lett. 8, 715–721 (2005).Article 

Google Scholar 
Leung, B. et al. An ounce of prevention or a pound of cure: Bioeconomic risk analysis of invasive species. Proc. R Soc. Lond. Ser. B Biol. Sci. 269, 2407–2413 (2002).Article 

Google Scholar 
Lounibos, L. P. Invasions by insect vectors of human disease. Annu. Rev. Entomol. 47, 233–266 (2002).Article 
CAS 
PubMed 

Google Scholar 
Manni, M. et al. Genetic evidence for a worldwide chaotic dispersion pattern of the arbovirus vector, Aedes albopictus. PLoS Negl. Trop. Dis. 11, e0005332 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Roiz, D. et al. Integrated Aedes management for the control of Aedes-borne diseases. PLoS Negl. Trop. Dis. 12, e0006845 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Lühken, R. et al. Microsatellite typing of Aedes albopictus (Diptera: Culicidae) populations from Germany suggests regular introductions. Infect. Genet. Evol. 81, 104237 (2020).Article 
PubMed 

Google Scholar 
Battaglia, V. et al. The worldwide spread of the tiger mosquito as revealed by mitogenome haplogroup diversity. Front. Genet. 7, 208 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Medley, K. A., Jenkins, D. G. & Hoffman, E. A. Human-aided and natural dispersal drive gene flow across the range of an invasive mosquito. Mol. Ecol. 24, 284–295 (2015).Article 
PubMed 

Google Scholar 
Eritja, R., Palmer, J. R., Roiz, D., Sanpera-Calbet, I. & Bartumeus, F. Direct evidence of adult Aedes albopictus dispersal by car. Sci. Rep. 7, 1–15 (2017).Article 
CAS 

Google Scholar 
Sherpa, S. et al. Unravelling the invasion history of the Asian tiger mosquito in Europe. Mol. Ecol. 28, 2360–2377 (2019).Article 
PubMed 

Google Scholar 
Swan, T. et al. A literature review of dispersal pathways of Aedes albopictus across different spatial scales: Implications for vector surveillance. Parasit Vectors 15, 1–13 (2022).Article 

Google Scholar 
Ballard, J. W. O. & Whitlock, M. C. The incomplete natural history of mitochondria. Mol. Ecol. 13, 729–744. https://doi.org/10.1046/j.1365-294X.2003.02063.x (2004).Article 
PubMed 

Google Scholar 
Toews, D. P. L. & Brelsford, A. The biogeography of mitochondrial and nuclear discordance in animals. Mol. Ecol. 21, 3907–3930. https://doi.org/10.1111/j.1365-294X.2012.05664.x (2012).Article 
CAS 
PubMed 

Google Scholar 
Hurst, G. D. & Jiggins, F. M. Problems with mitochondrial DNA as a marker in population, phylogeographic and phylogenetic studies: The effects of inherited symbionts. Proc. R. Soc. B: Biol. Sci. 272, 1525–1534 (2005).Article 
CAS 

Google Scholar 
Cariou, M., Duret, L. & Charlat, S. The global impact of Wolbachia on mitochondrial diversity and evolution. J. Evol. Biol. 30, 2204–2210 (2017).Article 
CAS 
PubMed 

Google Scholar 
Zug, R. & Hammerstein, P. Still a host of hosts for Wolbachia: analysis of recent data suggests that 40% of terrestrial arthropod species are infected. PLoS ONE 7, e38544 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Weinert, L. A., Araujo-Jnr, E. V., Ahmed, M. Z. & Welch, J. J. The incidence of bacterial endosymbionts in terrestrial arthropods. Proc. R. Soc. B: Biol. Sci. 282, 20150249 (2015).Article 

Google Scholar 
Goubert, C., Minard, G., Vieira, C. & Boulesteix, M. Population genetics of the Asian tiger mosquito Aedes albopictus, an invasive vector of human diseases. Heredity 117, 125–134 (2016).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Western, D. Human-modified ecosystems and future evolution. PNAS 98, 5458–5465 (2001).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Pech-May, A. et al. Population genetics and ecological niche of invasive Aedes albopictus in Mexico. Acta Trop. 157, 30–41 (2016).Article 
PubMed 

Google Scholar 
Vargo, E. L. et al. Hierarchical genetic analysis of German cockroach (Blattella germanica) populations from within buildings to across continents. PLoS ONE 9, e102321 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
von Beeren, C., Stoeckle, M. Y., Xia, J., Burke, G. & Kronauer, D. J. Interbreeding among deeply divergent mitochondrial lineages in the American cockroach (Periplaneta americana). Sci. Rep. 5, 1–7 (2015).
Google Scholar 
Tseng, S.-P. et al. Genetic diversity and Wolbachia infection patterns in a globally distributed invasive ant. Front. Genet. 10, 838 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wesson, D. M., Porter, C. H. & Collins, F. H. Sequence and secondary structure comparisons of ITS rDNA in mosquitoes (Diptera: Culicidae). Mol. Phylogen. Evol. 1, 253–269 (1992).Article 
CAS 

Google Scholar 
Mishra, S., Sharma, G., Das, M. K., Pande, V. & Singh, O. P. Intragenomic sequence variations in the second internal transcribed spacer (ITS2) ribosomal DNA of the malaria vector Anopheles stephensi. PLoS ONE 16, e0253173 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Artigas, P. et al. Aedes albopictus diversity and relationships in south-western Europe and Brazil by rDNA/mtDNA and phenotypic analyses: ITS-2, a useful marker for spread studies. Parasit Vectors 14, 1–23 (2021).Article 

Google Scholar 
Armbruster, P. et al. Infection of New-and Old-World Aedes albopictus (Diptera: Culicidae) by the intracellular parasite Wolbachia: implications for host mitochondrial DNA evolution. J. Med. Entomol. 40, 356–360 (2003).Article 
PubMed 

Google Scholar 
Maia, R., Scarpassa, V. M., Maciel-Litaiff, L. & Tadei, W. P. Reduced levels of genetic variation in Aedes albopictus (Diptera: Culicidae) from Manaus, Amazonas State, Brazil, based on analysis of the mitochondrial DNA ND5 gene. Gen. Mol. Res. 2000, 998–1007 (2009).Article 

Google Scholar 
Birungi, J. & Munstermann, L. E. Genetic structure of Aedes albopictus (Diptera: Culicidae) populations based on mitochondrial ND5 sequences: Evidence for an independent invasion into Brazil and United States. Ann. Entomol. Soc. Am. 95, 125–132 (2002).Article 
CAS 

Google Scholar 
Kambhampati, S. & Rai, K. S. Mitochondrial DNA variation within and among populations of the mosquito Aedes albopictus. Genome 34, 288–292 (1991).Article 
CAS 
PubMed 

Google Scholar 
Werren, J. H., Baldo, L. & Clark, M. E. Wolbachia: master manipulators of invertebrate biology. Nat. Rev. Microbiol. 6, 741–751 (2008).Article 
CAS 
PubMed 

Google Scholar 
Wiwatanaratanabutr, I. Geographic distribution of wolbachial infections in mosquitoes from Thailand. J. Invertebr. Pathol. 114, 337–340 (2013).Article 
PubMed 

Google Scholar 
Carvajal, T. M., Hashimoto, K., Harnandika, R. K., Amalin, D. M. & Watanabe, K. Detection of Wolbachia in field-collected Aedes aegypti mosquitoes in metropolitan Manila, Philippines. Parasit. Vectors 12, 1–9 (2019).Article 

Google Scholar 
Atyame, C. M., Delsuc, F., Pasteur, N., Weill, M. & Duron, O. Diversification of Wolbachia endosymbiont in the Culex pipiens mosquito. Mol. Biol. Evol. 28, 2761–2772 (2011).Article 
CAS 
PubMed 

Google Scholar 
Damiani, C. et al. Wolbachia in Aedes koreicus: Rare detections and possible implications. Insects 13, 216 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Jiggins, F. M. Male-killing Wolbachia and mitochondrial DNA: Selective sweeps, hybrid introgression and parasite population dynamics. Genetics 164, 5–12 (2003).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Schuler, H. et al. The hitchhiker’s guide to Europe: The infection dynamics of an ongoing Wolbachia invasion and mitochondrial selective sweep in Rhagoletis cerasi. Mol. Ecol. 25, 1595–1609 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Ross, P. A., Ritchie, S. A., Axford, J. K. & Hoffmann, A. A. Loss of cytoplasmic incompatibility in Wolbachia-infected Aedes aegypti under field conditions. PLoS Negl. Trop. Dis. 13, e0007357 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Avise, J. C. Phylogeography: The history and formation of species (Harvard University Press, 2000).Book 

Google Scholar 
Rokas, A., Atkinson, R. J., Brown, G. S., West, S. A. & Stone, G. N. Understanding patterns of genetic diversity in the oak gallwasp Biorhiza pallida: Demographic history or a Wolbachia selective sweep? Heredity 87, 294–304 (2001).Article 
CAS 
PubMed 

Google Scholar 
Porretta, D., Mastrantonio, V., Bellini, R., Somboon, P. & Urbanelli, S. Glacial history of a modern invader: Phylogeography and species distribution modelling of the Asian tiger mosquito Aedes albopictus. PLoS ONE 7, e44515. https://doi.org/10.1371/journal.pone.0044515 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Motoki, M. T. et al. Population genetics of Aedes albopictus (Diptera: Culicidae) in its native range in Lao People’s Democratic Republic. Parasit. Vectors 12, 1–12 (2019).Article 
CAS 

Google Scholar 
Zhong, D. et al. Genetic analysis of invasive Aedes albopictus populations in Los Angeles County, California and its potential public health impact. PLoS ONE 8, e68586 (2013).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Usmani-Brown, S., Cohnstaedt, L. & Munstermann, L. E. Population genetics of Aedes albopictus (Diptera: Culicidae) invading populations, using mitochondrial nicotinamide adenine dinucleotide dehydrogenase subunit 5 sequences. Ann. Entomol. Soc. Am. 102, 144–150 (2009).Article 
CAS 
PubMed 

Google Scholar 
Mousson, L. et al. Phylogeography of Aedes (Stegomyia) aegypti (L.) and Aedes (Stegomyia) albopictus (Skuse) (Diptera: Culicidae) based on mitochondrial DNA variations. Genet. Res. 86, 1–11 (2005).Article 
CAS 
PubMed 

Google Scholar 
Bazin, E., Glémin, S. & Galtier, N. Population size does not influence mitochondrial genetic diversity in animals. Science 312, 570–572. https://doi.org/10.1126/science.1122033 (2006).Article 
CAS 
PubMed 

Google Scholar 
Dowling, D. K., Friberg, U. & Lindell, J. Evolutionary implications of non-neutral mitochondrial genetic variation. Ecol. Evol. 23, 546–554 (2008).Article 

Google Scholar 
Montero-Pau, J., Gómez, A. & Muñoz, J. Application of an inexpensive and high-throughput genomic DNA extraction method for the molecular ecology of zooplanktonic diapausing eggs. Limnol. Oceanogr. Methods 6, 218–222 (2008).Article 
CAS 

Google Scholar 
Porter, C. H. & Collins, F. H. Species-diagnostic differences in a ribosomal DNA internal transcribed spacer from the sibling species Anopheles freeborni and Anopheles hermsi (Diptera: Culicidae). Am. J. Trop. Med. 45, 271–279 (1991).Article 
CAS 

Google Scholar 
Folmer, O., Black, M., Hoeh, W., Lutz, R. & Vrijenhoek, R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol. Mar. Biol. Biotechnol. 3, 294–299 (1994).CAS 
PubMed 

Google Scholar 
Prosser, S., Martínez-Arce, A. & Elías-Gutiérrez, M. A new set of primers for COI amplification from freshwater microcrustaceans. Mol. Ecol. Resour. 13, 1151–1155 (2013).CAS 
PubMed 

Google Scholar 
Ivanova, N. V., Zemlak, T. S., Hanner, R. H. & Hebert, P. D. Universal primer cocktails for fish DNA barcoding. Mol. Ecol. Notes 7, 544–548 (2007).Article 
CAS 

Google Scholar 
Kumar, S., Stecher, G. & Tamura, K. MEGA7: Molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 33, 1870–1874 (2016).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Zhou, W., Rousset, F. & O’Neill, S. Phylogeny and PCR–based classification of Wolbachia strains using wsp gene sequences. Proc. R Soc. Lond. Ser. B Biol. Sci. 265, 509–515 (1998).Article 
CAS 

Google Scholar 
Braig, H. R., Zhou, W., Dobson, S. L. & O’Neill, S. L. Cloning and characterization of a gene encoding the major surface protein of the bacterial endosymbiont Wolbachia pipientis. J. Bacteriol. 180, 2373–2378 (1998).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hu, Y. et al. Identification and molecular characterization of Wolbachia strains in natural populations of Aedes albopictus in China. Parasit. Vectors 13, 1–14 (2020).
Google Scholar 
Heddi, A., Grenier, A.-M., Khatchadourian, C., Charles, H. & Nardon, P. Four intracellular genomes direct weevil biology: Nuclear, mitochondrial, principal endosymbiont, and Wolbachia. PNAS 96, 6814–6819 (1999).Article 
CAS 
PubMed 
PubMed Central 

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

Google Scholar 
Salzburger, W., Ewing, G. B. & Von Haeseler, A. The performance of phylogenetic algorithms in estimating haplotype genealogies with migration. Mol. Ecol. 20, 1952–1963 (2011).Article 
PubMed 

Google Scholar 
Stamatakis, A. RAxML-VI-HPC: Maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22, 2688–2690 (2006).Article 
CAS 
PubMed 

Google Scholar 
Darriba, D., Taboada, G. L., Doallo, R. & Posada, D. jModelTest 2: More models, new heuristics and parallel computing. Nat. Methods 9, 772. https://doi.org/10.1038/nmeth.2109 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Gower, J. C. Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53, 325–338 (1966).Article 
MathSciNet 
MATH 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. http://www.R-project.org/. (2021).Hijmans, R. J., Williams, E., Vennes, C. & Hijmans, M. R. J. Package ‘geosphere’. Spher. Trigon. 1, 5 (2017).
Google Scholar 
Palmer, J. R. et al. Citizen science provides a reliable and scalable tool to track disease-carrying mosquitoes. Nat. Commun. 8, 1–13 (2017).Article 

Google Scholar 
Mantel, N. & Valand, R. S. A technique of nonparametric multivariate analysis. Biometrics 1970, 547–558 (1970).Article 

Google Scholar 
Goslee, S. C. & Urban, D. L. The ecodist package for dissimilarity-based analysis of ecological data. J. Stat. Softw. 22, 1–19 (2007).Article 

Google Scholar 
Stewart, C. Zero-inflated beta distribution for modeling the proportions in quantitative fatty acid signature analysis. J. Appl. Stat. 40, 985–992 (2013).Article 
MathSciNet 
MATH 

Google Scholar 
Figueroa-Zúñiga, J. I., Arellano-Valle, R. B. & Ferrari, S. L. Mixed beta regression: A Bayesian perspective. Comput. Stat. Data Anal. 61, 137–147 (2013).Article 
MathSciNet 
MATH 

Google Scholar 
Branscum, A. J., Johnson, W. O. & Thurmond, M. C. Bayesian beta regression: Applications to household expenditure data and genetic distance between foot-and-mouth disease viruses. Aust. N. Z. J. Stat. 49, 287–301 (2007).Article 
MathSciNet 
MATH 

Google Scholar 
Ospina, R. & Ferrari, S. L. Inflated beta distributions. Stat. Pap. 51, 111–126 (2010).Article 
MathSciNet 
MATH 

Google Scholar 
Chung, H. & Beretvas, S. N. The impact of ignoring multiple membership data structures in multilevel models. Br. J. Math. Stat. Psychol. 65, 185–200 (2012).Article 
MathSciNet 
PubMed 
MATH 

Google Scholar  More

Author notesMikayla M. ClarkPresent address: University of Tennessee, Knoxville, TN, USAMichael W. SneddonPresent address: Predicine, Inc., Hayward, CA, USARoman SutorminPresent address: Google, Inc., San Francisco, CA, USAAuthors and AffiliationsLawrence Berkeley National Laboratory, Berkeley, CA, USADylan Chivian, Sean P. Jungbluth, Paramvir S. Dehal, Elisha M. Wood-Charlson, Richard S. Canon, Gavin A. Price, William J. Riehl, Michael W. Sneddon, Roman Sutormin & Adam P. ArkinOak Ridge National Laboratory, Oak Ridge, TN, USABenjamin H. Allen, Mikayla M. Clark, Miriam L. Land & Robert W. CottinghamArgonne National Laboratory, Lemont, IL, USATianhao Gu, Qizhi Zhang & Chris S. HenryAuthorsDylan ChivianSean P. JungbluthParamvir S. DehalElisha M. Wood-CharlsonRichard S. CanonBenjamin H. AllenMikayla M. ClarkTianhao GuMiriam L. LandGavin A. PriceWilliam J. RiehlMichael W. SneddonRoman SutorminQizhi ZhangRobert W. CottinghamChris S. HenryAdam P. ArkinCorresponding authorsCorrespondence to
Dylan Chivian or Adam P. Arkin. More

Department of Zoology, University of Cambridge, Cambridge, UKYucheng Wang, Bianca De Sanctis, Ruairidh Macleod, Daniel Money & Eske WillerslevLundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, DenmarkYucheng Wang, Ana Prohaska, Jialu Cao, Antonio Fernandez-Guerra, James Haile, Kurt H. Kjær, Thorfinn Sand Korneliussen, Nicolaj Krog Larsen, Ruairidh Macleod, Hugh McColl, Mikkel Winther Pedersen, Fernando Racimo, Alexandra Rouillard, Anthony H. Ruter, Lasse Vinner, David J. Meltzer & Eske WillerslevALPHA, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research (ITPCAS), Chinese Academy of Sciences (CAS), Beijing, ChinaYucheng WangKey Laboratory of Western China’s Environmental Systems (Ministry of Education), College of Earth and Environmental Science, Lanzhou University, Lanzhou, ChinaHaoran DongGénomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, FranceAdriana Alberti, France Denoeud & Patrick WinckerInstitute for Integrative Biology of the Cell (I2BC), Université Paris-Saclay, CEA, CNRS, Gif-sur-Yvette, FranceAdriana AlbertiThe Arctic University Museum of Norway, UiT—The Arctic University of Norway, Tromsø, NorwayInger Greve Alsos, Eric Coissac, Galina Gusarova, Youri Lammers & Marie Kristine Føreid MerkelDepartment of Geography and Environment, University of Hawaii, Honolulu, HI, USADavid W. BeilmanDepartment of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, DenmarkAnders A. BjørkInstitute of Earth Sciences, St Petersburg State University, St Petersburg, RussiaAnna A. Cherezova & Grigory B. FedorovArctic and Antarctic Research Institute, St Petersburg, RussiaAnna A. Cherezova & Grigory B. FedorovUniversité Grenoble-Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, FranceEric CoissacDepartment of Genetics, University of Cambridge, Cambridge, UKBianca De Sanctis & Richard DurbinCarlsberg Research Laboratory, Copenhagen V, DenmarkChristoph Dockter & Birgitte SkadhaugeSchool of Geography and Environmental Science, University of Southampton, Southampton, UKMary E. EdwardsAlaska Quaternary Center, University of Alaska Fairbanks, Fairbanks, AK, USAMary E. EdwardsSchool of Environment, Earth and Ecosystem Sciences, The Open University, Milton Keynes, UKNeil R. Edwards & Philip B. HoldenCenter for the Environmental Management of Military Lands, Colorado State University, Fort Collins, CO, USAJulie EsdaleDepartment of Earth and Atmospheric Sciences, University of Alberta, Edmonton, Alberta, CanadaDuane G. FroeseFaculty of Biology, St Petersburg State University, St Petersburg, RussiaGalina GusarovaDepartment of Glaciology and Climate, Geological Survey of Denmark and Greenland, Copenhagen K, DenmarkKristian K. KjeldsenDepartment of Earth Science, University of Bergen, Bergen, NorwayJan Mangerud & John Inge SvendsenBjerknes Centre for Climate Research, Bergen, NorwayJan Mangerud & John Inge SvendsenDepartment of Geology, Quaternary Sciences, Lund University, Lund, SwedenPer MöllerCenter for Macroecology, Evolution and Climate, Globe Institute, University of Copenhagen, Copenhagen Ø, DenmarkDavid Nogués-Bravo, Hannah Lois Owens & Carsten RahbekCentre d’Anthropobiologie et de Génomique de Toulouse, Faculté de Médecine Purpane, Université Paul Sabatier, Toulouse, FranceLudovic OrlandoCenter for Global Mountain Biodiversity, Globe Institute, University of Copenhagen, Copenhagen, DenmarkHannah Lois Owens & Carsten RahbekGates of the Arctic National Park and Preserve, US National Park Service, Fairbanks, AK, USAJeffrey T. RasicDepartment of Geosciences, UiT—The Arctic University of Norway, Tromsø, NorwayAlexandra RouillardZoological Institute, Russian academy of sciences, St Petersburg, RussiaAlexei TikhonovResource and Environmental Research Center, Chinese Academy of Fishery Sciences, Beijing, ChinaYingchun XingCollege of Plant Science, Jilin University, Changchun, Jilin, ChinaYubin ZhangDepartment of Anthropology, Southern Methodist University, Dallas, TX, USADavid J. MeltzerWellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UKEske WillerslevMARUM, University of Bremen, Bremen, GermanyEske WillerslevAll authors contributed to the conception of the presented ideas. Y.W. and H.D. analysed the data. Y.W., D.J.M., A.P. and E.W. wrote the paper with inputs from all authors. More