Ecology

Walker, D. A. et al. The circumpolar Arctic vegetation map. J. Veg. Sci. 16, 267–282 (2005).Article 

Google Scholar 
Raynolds, M. K. et al. A raster version of the Circumpolar Arctic Vegetation Map (CAVM). Remote Sens. Environ. 232, 111297 (2019).ADS 
Article 

Google Scholar 
Danell, K. What Is the Arctic? In Which Ways Is the Arctic Different? In Arctic Ecology (ed. Thomas, D. N.) 1–22 (University of Helsinki, 2021).
Google Scholar 
Tarnocai, C. et al. Soil organic carbon pools in the northern circumpolar permafrost region. Global Biogeochem. Cycles 23(2), 1–11. https://doi.org/10.1029/2008GB003327 (2009).CAS 
Article 

Google Scholar 
Hugelius, G. et al. Large stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw. Proc. Natl. Acad. Sci. U.S.A. 117(34), 20438–20446. https://doi.org/10.1073/pnas.1916387117 (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Loisel, J. et al. A database and synthesis of northern peatland soil properties and Holocene carbon and nitrogen accumulation. Holocene 24(9), 1028–1042. https://doi.org/10.1177/0959683614538073 (2014).ADS 
Article 

Google Scholar 
Gallego-Sala, A. V. et al. Latitudinal limits to the predicted increase of the peatland carbon sink with warming. Nat. Clim. Chang. 8(10), 907–913. https://doi.org/10.1038/s41558-018-0271-1 (2018).ADS 
CAS 
Article 

Google Scholar 
Yu, Z., Beilman, D. W. & Jones, M. C. Sensitivity of Northern Peatland carbon dynamics to holocene climate change. Carbon Cycl. Northern Peatl. C https://doi.org/10.1029/2008GM000822 (2009).Article 

Google Scholar 
Svendsen, J. & Mangerud, J. Paleoclimatic inferences from glacial fluctuations on Svalbard during the last 20 000 years. Clim. Dyn. 6(3–4), 213–220. https://doi.org/10.1007/BF00193533 (1992).Article 

Google Scholar 
Farnsworth, W. R. et al. Holocene glacial history of Svalbard: Status, perspectives and challenges. Earth Sci. Rev. 208(April), 103249. https://doi.org/10.1016/j.earscirev.2020.103249 (2020).CAS 
Article 

Google Scholar 
D’Andrea, W. J. et al. Mild Little Ice Age and unprecedented recent warmth in an 1800 year lake sediment record from Svalbard. Geology 40(11), 1007–1010. https://doi.org/10.1130/G33365.1 (2012).ADS 
CAS 
Article 

Google Scholar 
Miller, G. H., Landvik, J. Y., Lehman, S. J. & Southon, J. R. Episodic Neoglacial snowline descent and glacier expansion on Svalbard reconstructed from the 14C ages of ice-entombed plants. Quatern. Sci. Rev. 155, 67–78. https://doi.org/10.1016/j.quascirev.2016.10.023 (2017).ADS 
Article 

Google Scholar 
Røthe, T. O. et al. Arctic Holocene glacier fluctuations reconstructed from lake sediments at Mitrahalvøya, Spitsbergen. Quatern. Sci. Rev. 109, 111–125. https://doi.org/10.1016/j.quascirev.2014.11.017 (2015).Article 

Google Scholar 
van der Bilt, W. G. M. et al. Reconstruction of glacier variability from lake sediments reveals dynamic Holocene climate in Svalbard. Quatern. Sci. Rev. 126, 201–218. https://doi.org/10.1016/j.quascirev.2015.09.003 (2015).ADS 
Article 

Google Scholar 
Allaart, L. et al. Glacial history of the Åsgardfonna Ice Cap, NE Spitsbergen, since the last glaciation. Quatern. Sci. Rev. https://doi.org/10.1016/j.quascirev.2020.106717 (2021).Article 

Google Scholar 
Humlum, O. et al. Late-Holocene glacier growth in Svalbard, documented by subglacial relict vegetation and living soil microbes. Holocene 15(3), 396–407. https://doi.org/10.1191/0959683605hl817rp (2005).ADS 
Article 

Google Scholar 
Yang, Z., Yang, W., Yuan, L., Wang, Y. & Sun, L. Evidence for glacial deposits during the Little Ice Age in Ny-Alesund, western Spitsbergen. J. Earth Syst. Sci. https://doi.org/10.1007/s12040-019-1274-7 (2020).Article 

Google Scholar 
AMAP – ARCTIC MONITORING AND ASSESSMENT PROGRAMME. (2019). Arctic Climate Change Update 2019: An update to key findings of Snow, Water, Ice, and Permafrost in the Arctic (SWIPA) 2017. Assessment Report, 12. https://www.amap.no/documents/doc/amap-climate-change-update-2019/1761.Nordli, Ø. et al. Polar Res. 39, 3614. https://doi.org/10.33265/polar.v39.3614 (2020).Article 

Google Scholar 
Førland, E. J., Benestad, R., Hanssen-Bauer, I., Haugen, J. E. & Skaugen, T. E. Temperature and precipitation development at svalbard 1900–2100. Adv. Meteorol. 2011, 1–14. https://doi.org/10.1155/2011/893790 (2011).Article 

Google Scholar 
Van Der Knaap, W. O. (1988). A pollen diagram from Broggerhalvoya, Spitsbergen: changes in vegetation and environment from ca. 4400 to ca. 800 BP. Arctic & Alpine Research, 20(1), 106–116. Doi: https://doi.org/10.2307/1551703Rozema, J. et al. A vegetation, climate and environment reconstruction based on palynological analyses of high arctic tundra peat cores (5000–6000 years BP) from Svalbard. Plant Ecol. 182(1–2), 155–173. https://doi.org/10.1007/s11258-005-9024-0 (2006).Article 

Google Scholar 
Nakatsubo, T. et al. Carbon accumulation rate of peatland in the High Arctic, Svalbard: Implications for carbon sequestration. Polar Sci. 9(2), 267–275. https://doi.org/10.1016/j.polar.2014.12.002 (2015).ADS 
Article 

Google Scholar 
Magnússon, B., Magnússon, S. & Fridriksson, S. (2009). Developments in plant colonization and succession on Surtsey during 1999–2008. Surtsey Res. pp. 57–76.Zwolicki, A., Zmudczyńska-Skarbek, K. M., Iliszko, L. & Stempniewicz, L. Guano deposition and nutrient enrichment in the vicinity of planktivorous and piscivorous seabird colonies in Spitsbergen. Polar Biol. 36(3), 363–372. https://doi.org/10.1007/s00300-012-1265-5 (2013).Article 

Google Scholar 
Leblans, N. I. W. et al. Effects of seabird nitrogen input on biomass and carbon accumulation after 50 years of primary succession on a young volcanic island Surtsey. Biogeosciences 11(22), 6237–6250. https://doi.org/10.5194/bg-11-6237-2014 (2014).ADS 
Article 

Google Scholar 
Zmudczyńska-Skarbek, K. et al. Transfer of ornithogenic influence through different trophic levels of the Arctic terrestrial ecosystem of Bjørnøya (Bear Island), Svalbard. Soil Biol. Biochem. 115, 475–489. https://doi.org/10.1016/j.soilbio.2017.09.008 (2017).CAS 
Article 

Google Scholar 
Hodkinson, I. D., Coulson, S. J. & Webb, N. R. Community assembly along proglacial chronosequences in the high arctic: vegetation and soil development in north-west Svalbard. J. Ecol. 91(4), 651–663. https://doi.org/10.1046/j.1365-2745.2003.00786.x (2003).Article 

Google Scholar 
Ravolainen, V. et al. High Arctic ecosystem states: Conceptual models of vegetation change to guide long-term monitoring and research. Ambio 49(3), 666–677. https://doi.org/10.1007/s13280-019-01310-x (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
van der Wal, R. & Brooker, R. W. Mosses mediate grazer impacts on grass abundance in arctic ecosystems. Funct. Ecol. 18(1), 77–86. https://doi.org/10.1111/j.1365-2435.2004.00820.x (2004).Article 

Google Scholar 
Vanderpuye, A. W., Elvebakk, A. & Nilsen, L. Plant communities along environmental gradients of high-arctic mires in Sassendalen Svalbard. J. Veg. Sci. 13(6), 875–884. https://doi.org/10.1111/j.1654-1103.2002.tb02117.x (2002).Article 

Google Scholar 
Le Moullec, M., Pedersen, Å. Ø., Stien, A., Rosvold, J. & Hansen, B. B. A century of conservation: the ongoing recovery of svalbard reindeer. J. Wildl. Manag. 83(8), 1676–1686. https://doi.org/10.1002/jwmg.21761 (2019).Article 

Google Scholar 
Garfelt-Paulsen, I. M. et al. Don’t go chasing the ghosts of the past: habitat selection and site fidelity during calving in an Arctic ungulate. Wildl. Biol. https://doi.org/10.2981/wlb.00740 (2021).Article 

Google Scholar 
Moreau, M., Mercier, D., Laffly, D. & Roussel, E. Impacts of recent paraglacial dynamics on plant colonization: a case study on Midtre Lovénbreen foreland, Spitsbergen (79°N). Geomorphology 95(1–2), 48–60. https://doi.org/10.1016/j.geomorph.2006.07.031 (2008).ADS 
Article 

Google Scholar 
Moreau, M., Laffly, D. & Brossard, T. Recent spatial development of Svalbard strandflat vegetation over a period of 31 years. Polar Res. 28(3), 364–375. https://doi.org/10.1111/j.1751-8369.2009.00119.x (2009).Article 

Google Scholar 
Wietrzyk, P., Wȩgrzyn, M. & Lisowska, M. Vegetation diversity and selected abiotic factors influencing the primary succession process on the foreland of Gåsbreen Svalbard. Pol. Polar Res. 37(4), 493–509. https://doi.org/10.1515/popore-2016-0026 (2016).Article 

Google Scholar 
Divine, D. et al. Thousand years of winter surface air temperature variations in Svalbard and northern norway reconstructed from ice-core data. Polar Res. 30(SUPPL.1), 1–12. https://doi.org/10.3402/polar.v30i0.7379 (2011).ADS 
Article 

Google Scholar 
Van Pelt, W. et al. A long-term dataset of climatic mass balance, snow conditions, and runoff in Svalbard (1957–2018). Cryosphere 13(9), 2259–2280. https://doi.org/10.5194/tc-13-2259-2019 (2019).ADS 
Article 

Google Scholar 
Johansen, B. E., Karlsen, S. R. & Tømmervik, H. Vegetation mapping of Svalbard utilising Landsat TM/ETM+ data. Polar Rec. 48(1), 47–63. https://doi.org/10.1017/S0032247411000647 (2012).Article 

Google Scholar 
Norwegian Polar Institute. Available online at: https://npolar.no (2021).Norwegian Meteorological Institute. Available online at: https://seklima.met.no (2019).Kelly, T. J. et al. The vegetation history of an Amazonian domed peatland. Palaeogeogr. Palaeoclimatol. Palaeoecol. 468(November), 129–141. https://doi.org/10.1016/j.palaeo.2016.11.039 (2017).Article 

Google Scholar 
Estop-Aragonés, C. et al. Limited release of previously-frozen C and increased new peat formation after thaw in permafrost peatlands. Soil Biol. Biochem. 118, 115–129. https://doi.org/10.1016/j.soilbio.2017.12.010 (2018).CAS 
Article 

Google Scholar 
Blaauw, M., Christen, J. A. & Aquino-Lopez, M. A. rplum: Bayesian Age-Depth Modelling of Cores Dated by Pb-210. R package version 0.2.2. https://CRAN.R-project.org/package=rplum (2021).R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2020).Heiri, O., Lotter, A. F. & Lemcke, G. Loss on ignition as a method for estimating organic and carbonate content in sediments: Reproducibility and comparability of results. J. Paleolimnol. 25(1), 101–110. https://doi.org/10.1023/A:1008119611481 (2001).ADS 
Article 

Google Scholar 
Booth, R. K., Lamentowicz, M. & Charman, D. J. Preparation and analysis of testate amoebae in peatland palaeoenvironmental studies. Mires and Peat 7(2), 1–7 (2010).
Google Scholar 
Charman, D., Hendon, D. & Woodland, W. A. The Identification of Testate Amoebae (Protozoa: Rhizopoda) in Peats (Quaternary Research Association, 2000).
Google Scholar 
Siemensma, F. J. Microworld, world of Amoeboid Organisms. World-Wide Electronic Publication, Kortenhoef, the Netherlands. Available online at: https://www.arcella.nl (2019).Payne, R. J. & Mitchell, E. A. D. How many is enough? Determining optimal count totals for ecological and palaeoecological studies of testate amoebae. J. Paleolimnol. 42(4), 483–495. https://doi.org/10.1007/s10933-008-9299-y (2009).ADS 
Article 

Google Scholar 
Swindles, G. T. et al. Testing peatland water-table depth transfer functions using high-resolution hydrological monitoring data. Q. Sci. Rev. 120, 107–117. https://doi.org/10.1016/j.quascirev.2015.04.019 (2015).ADS 
Article 

Google Scholar 
Amesbury, M. J. et al. Development of a new pan-European testate amoeba transfer function for reconstructing peatland palaeohydrology. Quatern. Sci. Rev. 152, 132–151. https://doi.org/10.1016/j.quascirev.2016.09.024 (2016).ADS 
Article 

Google Scholar 
Amesbury, M. J. et al. Towards a Holarctic synthesis of peatland testate amoeba ecology: Development of a new continental-scale palaeohydrological transfer function for North America and comparison to European data. Quatern. Sci. Rev. 201, 483–500. https://doi.org/10.1016/j.quascirev.2018.10.034 (2018).ADS 
Article 

Google Scholar 
Zhang, H. et al. Testate amoeba as palaeohydrological indicators in the permafrost peatlands of north-east European Russia and Finnish Lapland. J. Quat. Sci. 32(7), 976–988. https://doi.org/10.1002/jqs.2970 (2017).Article 

Google Scholar 
Sim, T. G. et al. Pathways for Ecological Change in Canadian High Arctic Wetlands Under Rapid Twentieth Century Warming. Geophys. Res. Lett. 46(9), 4726–4737. https://doi.org/10.1029/2019GL082611 (2019).ADS 
Article 

Google Scholar 
Elmendorf, S. C. et al. Global assessment of experimental climate warming on tundra vegetation: Heterogeneity over space and time. Ecol. Lett. 15(2), 164–175. https://doi.org/10.1111/j.1461-0248.2011.01716.x (2012).Article 
PubMed 

Google Scholar 
Lupascu, M. et al. High Arctic wetting reduces permafrost carbon feedbacks to climate warming. Nat. Clim. Chang. 4(1), 51–55. https://doi.org/10.1038/nclimate2058 (2014).ADS 
CAS 
Article 

Google Scholar 
Bjorkman, A. D. et al. Status and trends in Arctic vegetation: Evidence from experimental warming and long-term monitoring. Ambio 49(3), 678–692. https://doi.org/10.1007/s13280-019-01161-6 (2020).MathSciNet 
Article 
PubMed 

Google Scholar 
Egli, M., Mavris, C., Mirabella, A. & Giaccai, D. Soil organic matter formation along a chronosequence in the Morteratsch proglacial area (Upper Engadine, Switzerland). CATENA 82(2), 61–69. https://doi.org/10.1016/j.catena.2010.05.001 (2010).CAS 
Article 

Google Scholar 
Prach, K. & Rachlewicz, G. Succession of vascular plants in front of retreating glaciers in central Spitsbergen. Polish Polar Research 33(4), 319–328. https://doi.org/10.2478/v10183-012-0022-3 (2012).Article 

Google Scholar 
Låg, J. Special Peat Formations in Svalbard. Acta Agric. Scand. 30(2), 205–210. https://doi.org/10.1080/00015128009435267 (1980).Article 

Google Scholar 
Serebryannyy, L. P., Tishkov, A. A., Malyasova, Y. S., Solomina, O. N. & Il’ves, E. O.,. Reconstruction of the development of vegetation in Arctic high latitudes. Polar Geogr. Geol. 9(4), 308–320. https://doi.org/10.1080/10889378509377261 (1985).Article 

Google Scholar 
Surova, T. G., Troitskiy, L. S., Skobeyeva, Y. I. & Punning, Y. M. K. Glacioclimatic conditions in the european arctic in the late holocene. Polar Geogr. Geol. 11(1), 50–57. https://doi.org/10.1080/10889378709377310 (1987).Article 

Google Scholar 
Surova, T. G., Troitskiy, L. S., Skobeyeva, Y. I. & Troitskiy, Y. M. K. Changes in glacioclimatic conditions on svalbard during the subboreal period. Polar Geogr. Geol. 12(3), 221–226. https://doi.org/10.1080/10889378809377366 (1988).Article 

Google Scholar 
Låg, J. Peat Accumulation in Steep Hills at Alkhornet Spitsbergen. Acta Agric. Scand. 40(3), 217–219. https://doi.org/10.1080/00015129009438554 (1990).Article 

Google Scholar 
Oliva, M. et al. Sedimentological characteristics of ice-wedge polygon terrain in adventdalen (Svalbard) environmental and climatic implications for the late Holocene. Solid Earth 5(2), 901–914. https://doi.org/10.5194/se-5-901-2014 (2014).ADS 
Article 

Google Scholar 
Van der Knaap, W. O. Past Vegetation and Reindeer on Edgeoya (Spitsbergen) Between c. 7900 and c. 3800 BP, Studied by Means of Peat Layers and Reindeer Faecal Pellets. J. Biogeogr. 16(4), 379. https://doi.org/10.2307/2845229 (1989).Article 

Google Scholar 
Røthe, T. O., Bakke, J., Støren, E. W. N. & Bradley, R. S. Reconstructing holocene glacier and climate fluctuations from lake sediments in Vårfluesjøen Northern Spitsbergen. Front. Earth Sci. 6(July), 1–20. https://doi.org/10.3389/feart.2018.00091 (2018).Article 

Google Scholar 
Alsos, I. G. et al. Sedimentary ancient DNA from Lake Skartjørna, Svalbard: assessing the resilience of arctic flora to Holocene climate change. Holocene 26(4), 627–642. https://doi.org/10.1177/0959683615612563 (2016).ADS 
Article 

Google Scholar 
Klimowicz, Z., Melke, J. & Uziak, S. Peat soils in the Bellsund region Spitsbergen. Pol. Polar Res. 18(1), 25–39 (1997).
Google Scholar 
Yang, Z. et al. Total photosynthetic biomass record between 9400 and 2200 BP and its link to temperature changes at a High Arctic site near Ny-Ålesund Svalbard. Polar Biol. 42(5), 991–1003. https://doi.org/10.1007/s00300-019-02493-5 (2019).Article 

Google Scholar 
Vickers, H. et al. Changes in greening in the high arctic: insights from a 30-year AVHRR max NDVI dataset for Svalbard. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/11/10/105004 (2016).Article 

Google Scholar 
Van Der Knaap, W. O. Human influence on natural Arctic vegetation in the 17th century and climatic change since AD 1600 in northwest Spitsbergen: a paleobotanical study. Arct. Alp. Res. 17(4), 371–387. https://doi.org/10.2307/1550863 (1985).Article 

Google Scholar 
Martín-Moreno, R., Allende Álvarez, F. & Hagen, J. O. ‘Little Ice Age’ glacier extent and subsequent retreat in Svalbard archipelago. Holocene 27(9), 1379–1390. https://doi.org/10.1177/0959683617693904 (2017).ADS 
Article 

Google Scholar 
Rachlewicz, G., Szczuziński, W. & Ewertowski, M. Post-“Little Ice Age” retreat rates of glaciers around Billefjorden in central Spitsbergen Svalbard. Pol. Polar Res. 28(3), 159–186 (2007).
Google Scholar 
Matthews, J. A. & Whittaker, R. J. Vegetation succession on the storbreen glacier foreland, Jotunheimen, Norway : a review. Arct. Alp. Res. 19(4), 385–395 (1987).Article 

Google Scholar 
Beyens, L. & Chardez, D. Evidence from testate amoebae for changes in some local hydrological conditions between c. 5000 BP and c. 3800 BP on Edgeøya (Svalbard). Polar Res. 5(2), 165–169. https://doi.org/10.1111/j.1751-8369.1987.tb00619.x (1987).Article 

Google Scholar 
Lawrence, D. M., Koven, C. D., Swenson, S. C., Riley, W. J. & Slater, A. G. Permafrost thaw and resulting soil moisture changes regulate projected high-latitude CO2 and CH4 emissions. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/10/9/094011 (2015).Article 

Google Scholar 
Isaksen, K., Benestad, R. E., Harris, C. & Sollid, J. L. Recent extreme near-surface permafrost temperatures on Svalbard in relation to future climate scenarios. Geophys. Res. Lett. 34(17), 1–5. https://doi.org/10.1029/2007GL031002 (2007).Article 

Google Scholar 
Cable, S., Elberling, B. & Kroon, A. Holocene permafrost history and cryostratigraphy in the High-Arctic Adventdalen Valley, central Svalbard. Boreas 47(2), 423–442. https://doi.org/10.1111/bor.12286 (2018).Article 

Google Scholar 
König, M., Kohler, J. & Nuth, C. Glacier Area Outlines–Svalbard, v1.0, http://data.npolar.no/dataset/89f430f8-862f-11e2-8036-005056ad0004 Delivered by CryoClim service (2013).Box, J. E. et al. Key indicators of Arctic climate change: 1917–2017. Environ. Res. Lett. 14(4), 045010. https://doi.org/10.1088/1748-9326/aafc1b (2019).ADS 
CAS 
Article 

Google Scholar 
Zhang, H. et al. Decreased carbon accumulation feedback driven by climate-induced drying of two southern boreal bogs over recent centuries. Glob. Change Biol. 26(4), 2435–2448. https://doi.org/10.1111/gcb.15005 (2020).ADS 
Article 

Google Scholar 
Szymański, W., Wojtuń, B., Stolarczyk, M., Siwek, J. & Waścińska, J. Organic carbon and nutrients (N, P) in surface soil horizons in a non-glaciated catchment SW Spitsbergen. Pol. Polar Res. 37(1), 49–66. https://doi.org/10.1515/popore-2016-0006 (2016).Article 

Google Scholar 
Hugelius, G. et al. Estimated stocks of circumpolar permafrost carbon with quantified uncertainty ranges and identified data gaps. Biogeosciences 11(23), 6573–6593. https://doi.org/10.5194/bg-11-6573-2014 (2014).ADS 
Article 

Google Scholar 
Palmtag, J. et al. Storage, landscape distribution, and burial history of soil organic matter in contrasting areas of continuous permafrost. Arct. Antarct. Alp. Res. 47(1), 71–88. https://doi.org/10.1657/AAAR0014-027 (2015).Article 

Google Scholar 
Siewert, M. B. et al. Comparing carbon storage of Siberian tundra and taiga permafrost ecosystems at very high spatial resolution. J. Geophys. Res. Biogeosci. 120, 1973–1994 (2015).CAS 
Article 

Google Scholar 
Wojcik, R., Palmtag, J., Hugelius, G., Weiss, N. & Kuhry, P. Land cover and landform-based upscaling of soil organic carbon stocks on the Brøgger Peninsula, Svalbard. Arct. Antarct. Alp. Res. 51(1), 40–57. https://doi.org/10.1080/15230430.2019.1570784 (2019).Article 

Google Scholar 
Yoshitake, S. et al. Vegetation development and carbon storage on a glacier foreland in the High Arctic, Ny-Ålesund Svalbard. Polar Sci. 5(3), 391–397. https://doi.org/10.1016/j.polar.2011.03.002 (2011).ADS 
Article 

Google Scholar 
Mack, M. C. et al. Carbon loss from an unprecedented Arctic tundra wildfire. Nature 475(7357), 489–492. https://doi.org/10.1038/nature10283 (2011).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Cooper, E. J., Dullinger, S. & Semenchuk, P. Late snowmelt delays plant development and results in lower reproductive success in the High Arctic. Plant Sci. 180(1), 157–167. https://doi.org/10.1016/j.plantsci.2010.09.005 (2011).CAS 
Article 
PubMed 

Google Scholar  More

Bokulich, N. A. et al. Associations among wine grape microbiome, metabolome, and fermentation behavior suggest microbial contribution to regional wine characteristics. MBio, https://doi.org/10.1128/mBio.00631-16 (2016).Zohary, D. The Domestication of the Grapevine Vitis Vinifera L. in the Near East (Chapter 2) in The Origins and Ancient History of Wine (eds McGovern, P. E., Katz, S. H. & Fleming, S. J.) 21–28. (Routledge, 2003).Whalen, P. ‘Insofar as the ruby wine seduces them’: cultural strategies for selling wine in inter-war Burgundy. Contemp. Eur. Hist. 18, 67–98 (2009).
Google Scholar 
Østerlie, M. & Wicklund, T. In Nutritional and Health Aspects of Food in Nordic Countries (eds Bar, E., Wirtanen, G. & Veslemøy Andersen, V.) Ch. 2 (Elsevier Inc., 2018).Planète Terroirs. The future needs terroirs. https://planeteterroirs.org/ (2010).California Wine-Growing Regions, https://discovercaliforniawines.com/wine-map-winery-directory/Agricultura, M. D. E. & Ambiente. Compendio informativo en relación con las DOPs/IGPs y terminos tradicionales de vino, las indicaciones geograficas de bebidas espirituosas, y las indicaciones geograficas de productos vitivinicolas aromatizados. https://www.mapa.gob.es/es/alimentacion/temas/calidad-diferenciada/relaciondisposicionesdopseigpsdevinosbbeevinosaromatiz_tcm30-432336.pdf (2016).Ballantyne, D., Terblanche, N. S., Lecat, B. & Chapuis, C. Old world and new world wine concepts of terroir and wine: perspectives of three renowned non-French wine makers. J. Wine Res. 30, 122–143 (2019).
Google Scholar 
OIV. Resolution OIV/VITI 333/2010, definition of vitivinicultural “terroir”. https://www.oiv.int/public/medias/379/viti-2010-1-en.pdf (2010).Belda, I., Zarraonaindia, I., Perisin, M., Palacios, A. & Acedo, A. From vineyard soil to wine fermentation: microbiome approximations to explain the ‘terroir’ Concept. Front. Microbiol. 8, 1–12 (2017).
Google Scholar 
Zarraonaindia, I. et al. The soil microbiome influences grapevine-associated microbiota. MBio 6, 1–10 (2015).CAS 

Google Scholar 
Burns, K. N. et al. Vineyard soil bacterial diversity and composition revealed by 16S rRNA genes: differentiation by vineyard management. Soil Biol. Biochem. 103, 337–348 (2016).CAS 

Google Scholar 
Bokulich, N. A., Joseph, C. M. L., Allen, G., Benson, A. K. & Mills, D. A. Next-generation sequencing reveals significant bacterial diversity of botrytized wine. PLoS ONE 7, 3–12 (2012).
Google Scholar 
Portillo, M., del, C., Franquès, J., Araque, I., Reguant, C. & Bordons, A. Bacterial diversity of Grenache and Carignan grape surface from different vineyards at Priorat wine region (Catalonia, Spain). Int. J. Food Microbiol. 219, 56–63 (2016).
Google Scholar 
Mezzasalma, V. et al. Grape microbiome as a reliable and persistent signature of field origin and environmental conditions in Cannonau wine production. PLoS ONE 12, 1–20 (2017).
Google Scholar 
Hermans, S. M. et al. Using soil bacterial communities to predict physico-chemical variables and soil quality. Microbiome 8, 1–13 (2020).
Google Scholar 
OIV. Functional biodiversity in the vineyard. https://www.oiv.int/public/medias/6367/functional-biodiversity-in-the-vineyard-oiv-expertise-docume.pdf (2018).Ortiz-Álvarez, R. et al. Network properties of local fungal communities reveal the anthropogenic disturbance consequences of farming practices in vineyard soils. mSystems 6, e00344-21 (2021).Knight, S., Klaere, S., Fedrizzi, B. & Goddard, M. R. Regional microbial signatures positively correlate with differential wine phenotypes: evidence for a microbial aspect to terroir. Sci. Rep. 5, 1–10 (2015).
Google Scholar 
Belda, I. et al. Unraveling the enzymatic basis of wine ‘flavorome’: a phylo-functional study of wine related yeast species. Front. Microbiol. 7, 1–13 (2016).
Google Scholar 
Gilbert, J. A., van der Lelie, D. & Zarraonaindia, I. Microbial terroir for wine grapes. Proc. Natl Acad. Sci. USA 111, 5–6 (2014).CAS 
PubMed 

Google Scholar 
Belda, I. et al. Microbiomics to Define Wine Terroir (Chapter: 3.32) in Comprehensive Foodomics (Ed. Cifuentes, A.) 438–451 (Elsevier, 2021).Van der Heijden, M. G. A. & Hartmann, M. Networking in the plant microbiome. PLoS Biol. 14, e1002378 (2016).Altieri, M. A. In Invertebrate Biodiversity as Bioindicators of Sustainable Landscapes (1999).Brussaard, L., de Ruiter, P. C. & Brown, G. G. Soil biodiversity for agricultural sustainability. Agric. Ecosyst. Environ. 121, 233–244 (2007).Nielsen, U. N., Wall, D. H. & Six, J. Soil biodiversity and the environment. Annu. Rev. Environ. Resour. 40, 63–90 (2015).Wei, Y. J. et al. High-throughput sequencing of microbial community diversity in soil, grapes, leaves, grape juice and wine of grapevine from China. PLoS ONE 13, 1–17 (2018).
Google Scholar 
Liao, J., Xu, Q., Xu, H. & Huang, D. Natural farming improves soil quality and alters microbial diversity in a cabbage field in Japan. Sustain 11, 1–16 (2019).
Google Scholar 
Yan, J. et al. Plant litter composition selects different soil microbial structures and in turn drives different litter decomposition pattern and soil carbon sequestration capability. Geoderma 319, 194–203 (2018).CAS 

Google Scholar 
Qiao, Q. et al. The variation in the rhizosphere microbiome of cotton with soil type, genotype and developmental stage. Sci. Rep. 7, 1–10 (2017).
Google Scholar 
Pacchioni, R. G. et al. Taxonomic and functional profiles of soil samples from Atlantic forest and Caatinga biomes in northeastern Brazil. Microbiologyopen 3, 299–315 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
Ishaq, S. L. et al. Impact of cropping systems, soil inoculum, and plant species identity on soil bacterial community structure. Microb. Ecol. 73, 417–434 (2017).CAS 
PubMed 

Google Scholar 
Verkley, G. J. M., Da Silva, M., Wicklow, D. T. & Crous, P. W. Paraconiothyrium, a new genus to accommodate the mycoparasite Coniothyrium minitans, anamorphs of Paraphaeosphaeria, and four new species. Stud. Mycol. 50, 323–335 (2004).
Google Scholar 
Thomma, B. P. H. J. Alternaria spp.: from general saprophyte to specific parasite. Mol. Plant Pathol. 4, 225–236 (2003).CAS 
PubMed 

Google Scholar 
Mašínová, T. et al. Drivers of yeast community composition in the litter and soil of a temperate forest. FEMS Microbiol. Ecol. 93, 1–10 (2017).
Google Scholar 
Chen, J., Xu, L., Liu, B. & Liu, X. Taxonomy of Dactylella complex and Vermispora. III. A new genus Brachyphoris and revision of Vermispora. Fungal Divers. 26, 127–142 (2014).Burns, K. N. et al. Vineyard soil bacterial diversity and composition revealed by 16S rRNA genes: differentiation by geographic features. Soil Biol. Biochem. 91, 232–247 (2015).Bokulich, N. A., Thorngate, J. H., Richardson, P. M. & Mills, D. A. Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate. Proc. Natl Acad. Sci. USA 111, 139–148 (2014).
Google Scholar 
Castañeda, L. E. & Barbosa, O. Metagenomic analysis exploring taxonomic and functional diversity of soil microbial communities in Chilean vineyards and surrounding native forests. PeerJ 5, e3098 (2017).PubMed 
PubMed Central 

Google Scholar 
Coller, E. et al. Microbiome of vineyard soils is shaped by geography and management. Microbiome 7, 1–15 (2019).
Google Scholar 
Zhou, J. et al. Wine terroir and the soil bacteria: an amplicon sequencing–based assessment of the Barossa Valley and its sub-regions. Front. Microbiol. 11, 1–15 (2021).
Google Scholar 
Price, C. A. et al. Testing the metabolic theory of ecology. Ecol. Lett. 15, 1465–1474 (2012).PubMed 

Google Scholar 
Jenerette, G. D., Scott, R. L. & Huxman, T. E. Whole ecosystem metabolic pulses following precipitation events. Funct. Ecol. 22, 924–930 (2008).
Google Scholar 
Větrovský, T. et al. A meta-analysis of global fungal distribution reveals climate-driven patterns. Nat. Commun. 10, 1–9 (2019).
Google Scholar 
Arnold, A. E., Maynard, Z., Gilbert, G. S., Coley, P. D. & Kursar, T. A. Are tropical fungal endophytes hyperdiverse? Ecol. Lett. 3, 267–274 (2000).
Google Scholar 
Tedersoo, L. et al. Global diversity and geography of soil fungi. Science 346, 1052–1053 (2014).
Google Scholar 
Janssen, P. H. Identifying the dominant soil bacterial taxa in libraries of 16S rRNA and 16S rRNA genes. Appl. Environ. Microbiol. 72, 1719–1728 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
Bintrim, S. B., Donohue, T. J., Handelsman, J., Roberts, G. P. & Goodman, R. M. Molecular phylogeny of Archaea from soil. Proc. Natl Acad. Sci. USA 94, 277–282 (1997).CAS 
PubMed 
PubMed Central 

Google Scholar 
Simon, H. M., Dodsworth, J. A. & Goodman, R. M. Crenarchaeota colonize terrestrial plant roots. Environ. Microbiol. 2, 495–505 (2000).CAS 
PubMed 

Google Scholar 
Buckley, D. H., Graber, J. R. & Schmidt, T. M. Phylogenetic analysis of nonthermophilic members of the kingdom Crenarchaeota and their diversity and abundance in soils. Appl. Environ. Microbiol. 64, 4333–4339 (1998).CAS 
PubMed 
PubMed Central 

Google Scholar 
Ochsenreiter, T., Selezi, D., Quaiser, A., Bonch-Osmolovskaya, L. & Schleper, C. Diversity and abundance of Crenarchaeota in terrestrial habitats studied by 16S RNA surveys and real time PCR. Environ. Microbiol. 5, 787–797 (2003).CAS 
PubMed 

Google Scholar 
Kemnitz, D., Kolb, S. & Conrad, R. High abundance of Crenarchaeota in a temperate acidic forest soil. FEMS Microbiol. Ecol. 60, 442–448 (2007).CAS 
PubMed 

Google Scholar 
Zhalnina, K. et al. Ca. nitrososphaera and bradyrhizobium are inversely correlated and related to agricultural practices in long-term field experiments. Front. Microbiol. 4, 1–13 (2013).
Google Scholar 
Barata, A., Malfeito-Ferreira, M. & Loureiro, V. The microbial ecology of wine grape berries. Int. J. Food Microbiol. 153, 243–259 (2012).CAS 
PubMed 

Google Scholar 
Yurkov, A. M. Yeasts of the soil—obscure but precious. Yeast 35, 369–378 (2018).CAS 
PubMed 

Google Scholar 
Kachalkin, A. V., Abdullabekova, D. A., Magomedova, E. S., Magomedov, G. G. & Chernov, I. Y. Yeasts of the vineyards in Dagestan and other regions. Microbiology 84, 425–432 (2015).CAS 

Google Scholar 
Čadež, N., Zupan, J. & Raspor, P. The effect of fungicides on yeast communities associated with grape berries. FEMS Yeast Res. 10, 619–630 (2010).PubMed 

Google Scholar 
Comitini, F. & Ciani, M. Influence of fungicide treatments on the occurrence of yeast flora associated with wine grapes. Ann. Microbiol. 58, 489–493 (2008).
Google Scholar 
Kepler, R. M., Maul, J. E. & Rehner, S. A. Managing the plant microbiome for biocontrol fungi: examples from Hypocreales. Curr. Opin. Microbiol. 37, 48–53 (2017).CAS 
PubMed 

Google Scholar 
Berendsen, R. L., Pieterse, C. M. J. & Bakker, P. A. H. M. The rhizosphere microbiome and plant health. Trends Plant Sci. 17, 478–486 (2012).CAS 
PubMed 

Google Scholar 
Liu, D. & Howell, K. Community succession of the grapevine fungal microbiome in the annual growth cycle. Environ. Microbiol. 23, 1842–1857 (2021).CAS 
PubMed 

Google Scholar 
Delgado-Baquerizo, M. et al. Bacteria found in soil. Science 325, 320–325 (2018).
Google Scholar 
Egidi, E. et al. A few Ascomycota taxa dominate soil fungal communities worldwide. Nat. Commun. 10, 2369 (2019).Alonso, A. et al. Looking at the origin: Some insights into the general and fermentative microbiota of vineyard soils. Fermentation 5, 1–15 (2019).
Google Scholar 
OIV. Resolution OIV-VITI 655-2021. OIV recommendations about valuation and importance of microbial biodiversity in a sustainable vitiviniculture context. https://www.oiv.int/public/medias/8097/en-oiv-viti-655-2021.pdf (2021).Vishnivetskaya, T. A. et al. Commercial DNA extraction kits impact observed microbial community composition in permafrost samples. FEMS Microbiol. Ecol. 87, 217–230 (2014).CAS 
PubMed 

Google Scholar 
Gobbi, A. et al. Quantitative and qualitative evaluation of the impact of the G2 enhancer, bead sizes and lysing tubes on the bacterial community composition during DNA extraction from recalcitrant soil core samples based on community sequencing and qPCR. PLoS One 14, e0200979 (2019).Bolyen, E. et al. QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science. PeerJ 37, 852–857 (2018).Callahan, B. J., McMurdie, P. J. & Holmes, S. P. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J. 11, 2639–2643 (2017).PubMed 
PubMed Central 

Google Scholar 
Janssen, S. et al. Phylogenetic placement of exact amplicon sequences improves associations with clinical information. mSystems 3, e00021-18 (2018).Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 1–17 (2018).
Google Scholar 
DeSantis, T. Z. et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Nilsson, R. H. et al. The UNITE database for molecular identification of fungi: Handling dark taxa and parallel taxonomic classifications. Nucleic Acids Res. 47, D259–D264 (2019).CAS 
PubMed 

Google Scholar 
Lozupone, C. & Knight, R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005).Chen, H. VennDiagram: generate high-resolution Venn and Euler plots. R. Packag. Version 1, 1 (2018).
Google Scholar 
Salonen, A., Salojärvi, J., Lahti, L. & de Vos, W. M. The adult intestinal core microbiota is determined by analysis depth and health status. Clin. Microbiol. Infect. 18, 16–20 (2012).CAS 
PubMed 

Google Scholar 
Martín-Fernández, J. A., Hron, K., Templ, M., Filzmoser, P. & Palarea-Albaladejo, J. Bayesian-multiplicative treatment of count zeros in compositional data sets. Stat. Model. 15, 134–158 (2015).
Google Scholar 
Oksanen, J. et al. vegan: community ecology package. R package version 2.4-3. Vienna R Found. Stat. Comput. Sch. (2016).Wright, M. N. & Ziegler, A. Ranger: a fast implementation of random forests for high dimensional data in C++ and R. J. Stat. Softw. 77, 1–17 (2017).Team, R. C. R: a language and environment for statistical computing. (2019).Henschel, A., Anwar, M. Z. & Manohar, V. Comprehensive meta-analysis of ontology annotated 16S rRNA profiles identifies beta diversity clusters of environmental bacterial communities. PLoS Comput. Biol. 11, 1–24 (2015).
Google Scholar 
Lozupone, C. A. et al. Meta-analyses of studies of the human microbiota. Genome Res. 23, 1704–1714 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Lozupone, C. A. & Knight, R. Global patterns in bacterial diversity. Proc. Natl Acad. Sci. USA 104, 11436–11440 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
Pauvert, C. et al. Bioinformatics matters: the accuracy of plant and soil fungal community data is highly dependent on the metabarcoding pipeline. Fungal Ecol. 41, 23–33 (2019).Gobbi, A., Kyrkou, I., Filippi, E., Ellegaard-Jensen, L. & Hansen, L. H. Seasonal epiphytic microbial dynamics on grapevine leaves under biocontrol and copper fungicide treatments. Sci. Rep. 10, 681 (2020).Engelbrektson, A. et al. Experimental factors affecting PCR-based estimates of microbial species richness and evenness. ISME J. 4, 642–647 (2010).CAS 
PubMed 

Google Scholar 
Willis, A. D. Rarefaction, alpha diversity, and statistics. Front. Microbiol. 10, 2407 (2019). More

German, C. R. & Von Damm, K. L. Treatise on Geochemistry (eds Heinrich, D. H. & Karl, K. T.) 181–222 (Pergamon, 2003).Van Dover, C. The Ecology of Deep-Sea Hydrothermal Vents (Princeton University Press, 2000).Spiess, F. N. et al. East Pacific rise: Hot springs and geophysical experiments. Science 207, 1421–1433 (1980).CAS 

Google Scholar 
Haymon, R. M. et al. Hydrothermal vent distribution along the East Pacific Rise crest 9° 09’–54’ N and its relationship to magmatic and tectonic processes on fast-spreading mid-ocean ridges. Earth Planetary Sci. Lett. 104, 513–534 (1991).
Google Scholar 
Edmonds, H. N. et al. Discovery of abundant hydrothermal venting on the ultraslow-spreading Gakkel Ridge in the Arctic Ocean. Nature 421, 252–256 (2003).CAS 

Google Scholar 
German, C. R. et al. Hydrothermal activity and seismicity at Teahitia Seamount: Reactivation of the society islands hotspot? Front. Mar. Sci 7, 73 (2020).
Google Scholar 
de Ronde, C. E. J. et al. Intra-oceanic subduction-related hydrothermal venting, Kermadec volcanic arc, New Zealand. Earth Planetary Sci. Lett. 193, 359–369 (2001).
Google Scholar 
Ishibashi, J. & Urabe, T. Backarc Basins: Tectonics and Magmatism (ed Taylor, B.) 451–495 (Springer, 1995).Fouquet, Y. et al. Hydrothermal activity and metallogenesis in the Lau back-arc basin. Nature 349, 778–781 (1991).CAS 

Google Scholar 
Boschen, R. E., Rowden, A. A., Clark, M. R. & Gardner, J. P. A. Mining of deep-sea seafloor massive sulfides: A review of the deposits, their benthic communities, impacts from mining, regulatory frameworks, and management strategies. Ocean Coastal Manage. 84, 54–67 (2013).
Google Scholar 
Lisitsyn, A. P. et al. Active hydrothermal activity at Franklin Seamount, Western Woodlark Sea (Papua New Guinea). Int. Geol. Rev. 33, 914–929 (1991).
Google Scholar 
Laurila, T. E. et al. Tectonic and magmatic controls on hydrothermal activity in the Woodlark Basin: Hydrothermalism in the Woodlark Basin. Geochem. Geophys. Geosyst. 13, Q09006 (2012).Goodliffe, A. M. et al. Synchronous reorientation of the Woodlark Basin spreading center. Earth Planetary Sci. Lett. 146, 233–242 (1997).CAS 

Google Scholar 
Martínez, F., Taylor, B. & Goodliffe, A. M. Contrasting styles of seafloor spreading in the Woodlark Basin: Indications of rift-induced secondary mantle convection. J. Geophys. Res. 104, 12909–12926 (1999).
Google Scholar 
Taylor, B., Goodliffe, A., Martinez, F. & Hey, R. Continental rifting and initial sea-floor spreading in the Woodlark Basin. Nature 374, 534–537 (1995).CAS 

Google Scholar 
Schellart, W. P., Lister, G. S. & Toy, V. G. A Late Cretaceous and Cenozoic reconstruction of the Southwest Pacific region: Tectonics controlled by subduction and slab rollback processes. Earth-Sci. Rev. 76, 191–233 (2006).
Google Scholar 
Hall, R. Cenozoic geological and plate tectonic evolution of SE Asia and the SW Pacific: Computer-based reconstructions, model and animations. J. Asian Earth Sci. 20, 353–431 (2002).
Google Scholar 
Breusing, C. et al. Allopatric and sympatric drivers of speciation in Alviniconcha hydrothermal vent snails. Mol. Biol. Evol. 37, 3469–3484 (2020).CAS 

Google Scholar 
Ondréas, H., Scalabrin, C., Fouquet, Y. & Godfroy, A. Recent high-resolution mapping of Guaymas hydrothermal fields (Southern Trough). BSGF – Earth Sci. Bull. 189, 6 (2018).
Google Scholar 
Nakamura, K. et al. Water column imaging with multibeam echo-sounding in the mid-Okinawa Trough: Implications for distribution of deep-sea hydrothermal vent sites and the cause of acoustic water column anomaly. Geochem. J. 49, 579–596 (2015).CAS 

Google Scholar 
Xu, G., Jackson, D. R. & Bemis, K. G. The relative effect of particles and turbulence on acoustic scattering from deep sea hydrothermal vent plumes revisited. J. Acoust. Soc. Am. 141, 1446–1458 (2017).
Google Scholar 
Park, S.-H. et al. Petrogenesis of basalts along the eastern Woodlark spreading center, equatorial western Pacific. Lithos 316–317, 122–136 (2018).
Google Scholar 
Chadwick, J. et al. Arc lavas on both sides of a trench: Slab window effects at the Solomon Islands triple junction, SW Pacific. Earth Planetary Sci. Lett. 279, 293–302 (2009).CAS 

Google Scholar 
Fouquet, Y. et al. Geodiversity of Hydrothermal Processes Along the Mid-Atlantic Ridge and Ultramafic-Hosted Mineralization: A New Type of Oceanic Cu-Zn-Co-Au Volcanogenic Massive Sulfide Deposit (eds Rona, P. A., Devey, C. W., Dyment, J. & Murton, B. J.) Vol. 188, 321–367 (American Geophysical Union, 2010).Von Damm, K. et al. Chemistry of submarine hydrothermal solutions at 21N, East Pacific Rise. Geochim. Cosmochim. Acta 49, 2197–2220 (1985).
Google Scholar 
Seyfried, W. E. & Bischoff, J. L. Experimental seawater-basalt interaction at 300 °C, 500 bars, chemical exchange, secondary mineral formation and implications for the transport of heavy metals. Geochim. Cosmochim. Acta 45, 135–147 (1981).CAS 

Google Scholar 
Pester, N. J., Rough, M., Ding, K. & Seyfried, W. E. A new Fe/Mn geothermometer for hydrothermal systems: Implications for high-salinity fluids at 13°N on the East Pacific Rise. Geochim. Cosmochim. Acta https://doi.org/10.1016/j.gca.2011.08.043 (2011).Podowski, E. L., Moore, T. S., Zelnio, K. A., Luther, G. W. & Fisher, C. R. Distribution of diffuse flow megafauna in two sites on the Eastern Lau Spreading Center, Tonga. Deep Sea Res. Part I: Oceanogr. Res. Papers 56, 2041–2056 (2009).CAS 

Google Scholar 
Collins, P., Kennedy, R. & Van Dover, C. A biological survey method applied to seafloor massive sulphides (SMS) with contagiously distributed hydrothermal-vent fauna. Mar. Ecol. Prog. Ser. 452, 89–107 (2012).CAS 

Google Scholar 
Desbruyères, D., Hashimoto, J. & Fabri, M.-C. Composition and biogeography of hydrothermal vent communities in Western Pacific back-arc basins. Geophys. Monogr. Ser. 166, 215–234 (2006).Reid, W. D. K. et al. Spatial differences in East scotia ridge hydrothermal vent food webs: Influences of chemistry, microbiology, and predation on trophodynamics. PLoS One 8, e65553 (2013).CAS 

Google Scholar 
Van Audenhaege, L., Fariñas-Bermejo, A., Schultz, T. & Lee Van Dover, C. An environmental baseline for food webs at deep-sea hydrothermal vents in Manus Basin (Papua New Guinea). Deep Sea Res. Part I: Oceanogr. Res. Papers https://doi.org/10.1016/j.dsr.2019.04.018 (2019).Erickson, K. L., Macko, S. A. & Van Dover, C. L. Evidence for a chemoautotrophically based food web at inactive hydrothermal vents (Manus Basin). Deep-Sea Res. Part II: Top. Stud. Oceanogr. 56, 1577–1585 (2009).CAS 

Google Scholar 
Comeault, A., Stevens, C. J. & Juniper, S. K. Mixed photosynthetic-chemosynthetic diets in vent obligate macroinvertebrates at shallow hydrothermal vents on Volcano 1, South Tonga Arc—evidence from stable isotope and fatty acid analyses. Cahiers de Biologie Marine 51, 351–359 (2010).
Google Scholar 
Bennett, S. A., Dover, C. V., Breier, J. A. & Coleman, M. Effect of depth and vent fluid composition on the carbon sources at two neighboring deep-sea hydrothermal vent fields (Mid-Cayman Rise). Deep-Sea Res. Part I: Oceanogr. Res. Papers 104, 122–133 (2015).CAS 

Google Scholar 
Levin, L. A. et al. Hydrothermal vents and methane seeps: Rethinking the sphere of influence. Front. Marine Sci. 3, 1–23 (2016).
Google Scholar 
Hügler, M. & Sievert, S. M. Beyond the Calvin cycle: Autotrophic carbon fixation in the ocean. Annu. Rev. Mar. Sci. 3, 261–289 (2011).
Google Scholar 
Wang, X., Li, C., Wang, M. & Zheng, P. Stable isotope signatures and nutritional sources of some dominant species from the PACManus hydrothermal area and the Desmos caldera. PLoS One 13, e0208887 (2018).
Google Scholar 
Tunnicliffe, V. & Southward, A. J. Growth and breeding of a primitive stalked barnacle Leucolepas longa (Cirripedia: Scalpellomorpha: Eolepadidae: Neolepadinae) inhabiting a volcanic seamount off Papua New Guinea. J. Mar. Biol. Ass. 84, 121–132 (2004).
Google Scholar 
Auzende, J. M., Pelletier, B. & Lafoy, Y. Twin active spreading ridges in the North Fiji Basin (southwest Pacific). Geology 22, 63–66 (1994).
Google Scholar 
Parson, L. M. & Wright, I. C. The Lau-Havre-Taupo back-arc basin: A southward-propagating, multi-stage evolution from rifting to spreading. Tectonophysics 263, 1–22 (1996).
Google Scholar 
Thaler, A. D. et al. Comparative population structure of two deep-sea hydrothermal-vent-associated decapods (Chorocaris sp. 2 and Munidopsis lauensis) from Southwestern Pacific back-arc basins. PLoS One 9, e101345 (2014).
Google Scholar 
Lee, W.-K., Kim, S.-J., Hou, B. K., Van Dover, C. L. & Ju, S.-J. Population genetic differentiation of the hydrothermal vent crab Austinograea alayseae (Crustacea: Bythograeidae) in the Southwest Pacific Ocean. PLoS One 14, e0215829 (2019).CAS 

Google Scholar 
Plouviez, S. et al. Amplicon sequencing of 42 nuclear loci supports directional gene flow between South Pacific populations of a hydrothermal vent limpet. Ecol. Evol. https://doi.org/10.1002/ece3.5235 (2019).Tran Lu Y, A. et al. Fine-scale genomic patterns of connectivity in the deep sea hydrothermal gastropod Ifremeria nautilei over its species range using outlier scans and demo-genetic inferences. Mol. Ecol. (In Revision).Yearsley, J. M. & Sigwart, J. D. Larval transport modeling of deep-sea invertebrates can aid the search for undiscovered populations. PLoS One 6, e23063 (2011).CAS 

Google Scholar 
Mitarai, S., Watanabe, H., Nakajima, Y., Shchepetkin, A. F. & McWilliams, J. C. Quantifying dispersal from hydrothermal vent fields in the western Pacific Ocean. Proc. Natl Acad. Sci. USA 113, 2976–2981 (2016).CAS 

Google Scholar 
Marsh, L. et al. Microdistribution of faunal assemblages at deep-sea hydrothermal vents in the southern ocean. PLoS One 7, e48348 (2012).CAS 

Google Scholar 
Jollivet, D. et al. The Biospeedo cruise: A new survey of hydrothermal vents along the south East Pacific Rise from 7°24’ S to 21°33’ S. InterRidge News 13, 20–26 (2005).Girard, F. et al. Currents and topography drive assemblage distribution on an active hydrothermal edifice. Prog. Oceanogr. 187, 102397 (2020).
Google Scholar 
Hessler, R. R. & Lonsdale, P. F. Biogeography of Mariana Trough hydrothermal vent communities. Deep Sea Res. Part A. Oceanogr. Res. Papers 38, 185–199 (1991).
Google Scholar 
Fujikura, K. Biology and earth scientific investigation by the submersible ‘Shinkai 6500’ system of deep-sea hydrothermal and lithosphere in the Mariana back-arc basin. JAMSTEC J. Deep Sea Res. 13, 1–20 (1997).
Google Scholar 
Connelly, D. P. et al. Hydrothermal vent fields and chemosynthetic biota on the world’s deepest seafloor spreading centre. Nat. Commun. 3, 620 (2012).
Google Scholar 
Cline, J. D. Spectrophotometric determination of hydrogen sulfide in natural waters. Limnol. Oceanogr. 14, 454–458 (1969).CAS 

Google Scholar 
Craddock, P. R., Rouxel, O. J., Ball, L. A. & Bach, W. Sulfur isotope measurement of sulfate and sulfide by high-resolution MC-ICP-MS. Chem. Geol. 253, 102–113 (2008).CAS 

Google Scholar 
Mateo, M. A., Serrano, O., Serrano, L. & Michener, R. H. Effects of sample preparation on stable isotope ratios of carbon and nitrogen in marine invertebrates: Implications for food web studies using stable isotopes. Oecologia 157, 105–115 (2008).
Google Scholar 
Hedges, J. I. & Stern, J. H. Carbon and nitrogen determinations of carbonate-containing solids1. Limnol. Oceanogr. 29, 657–663 (1984).CAS 

Google Scholar 
Coplen, T. B. Guidelines and recommended terms for expression of stable-isotope-ratio and gas-ratio measurement results: Guidelines and recommended terms for expressing stable isotope results. Rapid Commun. Mass Spectrom. 25, 2538–2560 (2011).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 

Google Scholar 
Methou, P., Michel, L. N., Segonzac, M., Cambon-Bonavita, M.-A. & Pradillon, F. Integrative taxonomy revisits the ontogeny and trophic niches of Rimicaris vent shrimps. R. Soc. Open Sci. 7, 200837 (2020).CAS 

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

Study sites and samplingWe sampled gas and soil in 29 regions throughout the A (rainy tropical), C (temperate), and D (boreal) climate types of the Köppen classification from six continents during the vegetation period between August 2011 and June 2018, following a standard protocol26. According to the protocol, the gas and soil samples were collected from locations in public domain or in previous agreement with the local community and/or property owner. The samples were exported from the origin countries and imported to Estonia, EU in cooperation with customs officers of the respective states, following the legal provisions of soil export and import, specifically exemptions for scientific purposes. To capture the full range of environmental conditions in each region, we established 76 wetland soil sites under different vegetation (mosses, sedges, grasses, herbs, trees, and bare soil) and land-use types (natural—raised bog, fen, and forest; agricultural—arable, hay field and pasture; and a peat extraction area) (Fig. 1a; Supplementary Data 1). We used a four-grade land-use intensity index to quantify the effect of land conversion: 0, no agricultural land use (natural mire, swamp, or bog forest); 1, moderate grazing or mowing (once a year or less); 2, intensive grazing or mowing (more than once a year); and 3, arable land (directly fertilized or unfertilized). The vegetation and land-use intensity types and the land-use intensity index were estimated from observations and contacts with site managers and local researchers.Within the sites, we established 1–4 stations 15–500 m apart to maximize the captured environmental variation. Each of the 196 stations were equipped with 3–5 opaque PVC 65 L truncated conical chambers 1.5–5 m apart and an observation well (perforated, 50 mm diameter PP-HT pipe wrapped in geotextile; 1 m in length). From each of the 645 chambers, N2O fluxes were measured following the static chamber method37 using PVC collars (0.5 m diameter, installed to 0.1 m depth in soil). Stabilization of 3–12 h was allowed before gas sampling to reduce the disturbance effect of inserting the collars on fluxes. The chambers were placed into water-filled rings on top of the collars. Gases were sampled from the chamber headspace into a 50 mL glass vial every 20 min during a 1-h session. The vials had been evacuated in the laboratory 2–6 days before the sampling. At least three sampling sessions per location were run within 3 days. Water-table height was recorded from the observation wells during the gas sampling at least 8 h after placement. Soil temperature was measured at the 10 and 20 cm depth.Soil samples of 150–200 g were collected from the chambers at 0–10 cm depth after the final gas sampling, and transported to laboratories in Tartu, Estonia. The homogenized samples were divided into subsamples for physical–chemical analyses and DNA extraction. The samples for chemical analyses were stored at 4 °C and microbiological samples were stored at –20 °C. DNA extraction was provided at the Tartu University environmental microbiology laboratory (see details below). Using a PP-HT plastic cylinder, intact soil cores (diameter 6.8 cm, height 6 cm) for the N2 analysis with the He–O2 method38 were collected from the topsoil (0−10 cm) inside 252 chambers at 26 sites, starting from 2014. Samples from different climates were run at respective temperatures. During transport, the soil samples were kept below the ambient soil temperature from which they were collected.Gas flux analysesThe gas samples were analyzed for N2O concentration within 2 weeks using two Shimadzu GC-2014 gas chromatographs equipped with ECD, TCD, and a Loftfield-type autosampler. The N2O fluxes were determined on linear regressions obtained from consecutive N2O concentrations taken when the chamber was closed, using p  0.05 we removed one outlier. If the regression remained insignificant but the flux value fell below the gas-chromatography measuring accuracy (regression change of N2O concentration δv  More

In the work reported here, we have examined the interaction of symbiotic partners representative of the three major diversification centers. Although P. vulgaris could establish symbiosis with diverse rhizobial lineages, Rhizobium etli seemed to predominate in nature in the bean nodules collected from the Americas8,9, while the Americas is where the origin and diversification of the host have been experimentally supported19,20. Genotypes other than R. etli that also induce nodule formation in the bean have already been taxonomically defined as species, for instance Rhizobium tropici and Rhizobium ecuadorense, both of which were isolated from areas in northwestern South America, namely Ecuador, Brazil, and Colombia.American-bean rhizobia, from soil samples retrieved by the common bean as well as isolates from nodules found in nature have possessed polymorphism in the nodC gene, disclosing three nodC genotypes namely α, (upgamma), and (updelta)9. The different nodC alleles in American strains exhibit a varying predominance in their regional distributions in correlation with the centers of bean genetic diversification. The nodC types α and (upgamma) were detected both in bean nodules and in soils from Mexico, whereas the nodC type (updelta) was clearly predominant in soil and nodules from the Southern Andes (i. e., in Bolivia and northwest Argentina9). A quantitatively balanced representation of rhizobia with nodC type α and (upgamma) was detected in soils from Ecuador, but the nodC type (upgamma) had been found to be predominantly isolated from nodules formed in nature in that area5,9,10. It should be noted that we have reported finding of equal distribution of allele nodC type α and γ among the nine R etli isolates from bean in Mexico reported by Silva et al.7,9. The occurrence of this polymorphism proved to contribute to examining rhizobial populations inhabiting the Americas and characterizing the interaction with beans in BGD centers from Mexico to the northwest of Argentina. In performing our nodC analysis, we were aware that rhizobia genes for symbiosis are carried on plasmids which might mediate horizontal transfer, however in agreement with Silva et al.7 we assumed that although genetic exchange could be important, it is not so extensive to prevent epidemic clones from arising at significant frequency. Similar findings were found in R. leguminosarum bv trifolii associated with native Trifolium species growing in nature21.Investigations in the last decade have proposed an evolutionary pathway for the host bean that provided us with a framework for examining our results on rhizobia-bean interactions and facilitated an interpretation of the results. The current model proposes the occurrence of a Mesoamerican origin from where dispersion by independent migrations over time led to the Mesoamerican and Andean gene pools and to the Ecuador-Peru wild common-bean populations2,19,20. We found a balanced competition between α and (upgamma) nodC types in beans from Mesoamerica and the southern Andes, whereas the beans from Ecuador and Peru revealed a clear affinity for nodulation with strains of nodC type α rather than with the sympatric strains nodC type (upgamma) that we assayed (R. ecuadorense, CIAT894 and Bra-5). Nevertheless, we have previously reported that native strains and isolates with respectively both nodC types α and (upgamma) were found in soils and bean nodules from Mexico9, whereas lineages harboring nodC type (upgamma) were found to be predominant in beans from the northern and central regions of Ecuador-Peru8,9. The present results, however, indicated a clear affinity of the Ecuadorean-Peruvian—i. e., AHD—beans for strains nodC type α when assessed for competition against nodC type (upgamma) (Fig. 2A). We also found that nodC type (updelta) displayed a clear predominant occupancy of nodules of the AHD beans in contrast to the scarce occupancy of nodules of the Mesoamerican and Andean beans (Fig. 2B). Taken together, these results indicate no affinity of AHD beans for sympatric rhizobial strains containing nodC type (upgamma)—despite the finding that rhizobia of nodC type (upgamma) appear to predominate in isolates of nodules formed in Ecuador9,10.We conclude that although rhizobial type nodC (upgamma) was previously found to predominate in bean nodules from Ecuador, the competitiveness of that rhizobial strain for nodulation compared to other genotypes of bean rhizobia was relatively low. A possible explanation could be that seeds might be assumed to play a key role as carriers during the dissemination of the bean throughout the American regions. Thus, we can hypothesize that at the time of bean dissemination both R. etli nodC types α and (upgamma) (R. ecuadorense and other lineages) moved in conjunction with the host from Mesoamerica to northern Ecuador-Peru, but the strains bearing nodC type (upgamma) achieved an adaptation—probably due to edaphic characteristics, environmental stresses, and other features—in such a way that that strain predominated in soils and succeeded in nodulation.Alternatively, that prevalence might arise from a host selection for a rhizobium that is more effective in nitrogen fixation in a new and different environment. A poor relationship, however, between competitiveness and efficiency was found in the pea22. In line with the concept of adaptation, the bean had been found to be preferentially nodulated by species of R. tropici in acidic soils in regions of Brazil and Africa4,23. Since the environment could also be a major influence on the host and its symbiotic interactions, the Andean area represents a cooler climate for the growth of the bean than the Mesoamerican region24,25. Furthermore, since our assays were performed in laboratory environment parameters, we do not rule out the effect -if any- by the diverse and complex soil microbial community coexisting with bean rhizobia. Within this context, two contrasting soils from Argentina which differ in geolocation and edaphic properties and the perlite substrate were assayed side by side in nodule occupancy of Negro Xamapa after inoculation with a mixture of strains nodC type α and γ (Results not shown). Our results showed that the predominance of nodC type γ in the occupation of the nodules of this variety (about 80% occupation) is not affected by the type of substrate (p = 0.5566). Yet, we assume that the performance in diverse soil and ecosystems should be further evaluated in situ. In agreement, a good coevolution of rhizobia strains with nodC type (upgamma) was detected in nodules of bean varieties from the Mesoamerica and Andean genetic pools inoculated with soil samples from Mexico, Ecuador, and Northwest of Argentina, respectively (see Table 2 in Aguilar et al., 2004) [9].With respect to the interaction in the southern Andes, we propose another interpretation that takes into consideration the bottleneck that occurred before domestication in the Andes, as was indicated by Bitocchi et al.26, which scenario enables the assumption that the adaptation and concomitant diversification involved a coevolution of the symbioses. Therefore, similar profiles of competitiveness for nodulation in Mesoamerican and Andean beans were found between nodC type (upgamma) versus nodC types α and (updelta), but a significant occupancy by the nodC type (updelta) was recorded in the Andean beans.Our work suggests that the genetics of both the host and the bacteria determine the mutual affinity and additionally indicates that symbiotic interaction is another trait of legumes sensitive to the effects of evolution and ecological adaptation to the locale environment such as the characteristics of the soil and the climate.The analysis of the genetic sequences of the bean that encode genes associated with symbiosis, revealed variation of NFR1, NFR5 and NIN over the representative accessions of the Mesoamerican, the Andean, and the AHD gene pools. It is proposed that a receptor complex composed of NFR1 and NFR5 initiates signal transduction in response to Nod-factor synthesized and released by rhizobia27. Although the variation consisted mainly in neutral-amino-acid substitutions, thus suggesting only minimal changes in the functionality, if any at all; we could cite the convincing and relevant evidence reported by Radutoiu et al.27 that the amino-acid residue 118 of the second LysM module of NFR5 is essential for the recognition of rhizobia by species of Lotus japonicus and Lotus filicaulis. Our finding that the Mesoamerican-bean NFR5 has glutamine (Q) in position 151, whereas the Andean and the AHD both have proline (P)—neither of which amino acids is neutral—would merit further investigation to evaluate if such a mutation might play a role in nodulation preference. Although this result must be considered with caution, we found that the conserved polymorphism in the NFR1 and NFR5 proteins has caused the beans representative of the genetic pool Ecuador-Peru—i. e., the AHD—to be grouped in a cluster separate from those of Mesoamerica and the Andes. What we found to be interesting was that the phylogenetic and RMSD profiles of grouping the sequences are consistent with different evolutionary pathways in beans from the AHD and the Andean areas. This observation agrees with the proposal of Randón-Anaya et al.2 that those former beans from northern Peru-Ecuador originated from an ancestral form earlier than that of Mesoamerican- and Andean-bean genotypes. In addition, by applying a suppressive subtractive hybridization approach a set of bean genes were identified in our laboratory to be expressed in early step of infection by the cognate rhizobia28. Taken these results together, we conclude that genomic regions and patterns of expression in the host appear associated with an affinity for nodulation.Within a broader context, we believe that our results on the biogeography of bean-rhizobia interactions in the region where the origin and domestication of the host plants occurred provide novel useful issues to be considered in inoculation programs, for instance those involving selection of strains and cultivars, and invite to validate these findings in follow up field trials. More

Case, T. J., Bolger, D. T. & Richman, A. D. Reptilian extinctions: The last ten thousand years. In Conservation Biology (eds Fiedler, P. L. & Jain, S. K.) 91–125 (Springer, 1992).
Google Scholar 
Shivanna, K. R. The sixth mass extinction crisis and its impact on biodiversity and human welfare. Resonance 25, 93–109 (2020).
Google Scholar 
Ceballos, G., Ehrlich, P. R., Barnosky, A. D., García, A., Pringle, R. M. & Palmer, T. M. Accelerated modern human–induced species losses: Entering the sixth mass extinction. Sci. Adv. 1, (2015)Lawler, J. J. et al. Conservation science: A 20-year report card. Front. Ecol. Environ. 4, 473–480 (2006).
Google Scholar 
Sodhi, N. S., Brook, B. W. & Bradshaw, C. J. A. Tropical Conservation Biology (Wiley-Blackwell, 2007).
Google Scholar 
Scheffers, B. R., Yong, D. L., Harris, J. B. C., Giam, X. & Sodhi, N. S. The world’s rediscovered species: Back from the brink?. PLoS ONE 6, 1–8 (2011).
Google Scholar 
Ineich I. Bocourt’s terrific skink, Phoboscincus bocourti Brocchi, 1876 (Squamata, Scincidae, Lygosominae). In 7. Biodiversity studies in New Caledonia.Mémoires du Muséum National d’Histoire Naturelle (ed. Grancolas, P.) vol. 198, 149–174, Muséum National d’Histoire Naturelle, (2009).Holden, M. & Ineich, I. scinque terrifiant terrifié. Le Courrier de la Nat. 312, 4 (2018).
Google Scholar 
Sadlier, R. A., Deuss, M., Bauer, A. M. & Jourdan, H. Kuniesaurus albiauris, a new genus and species of scincid lizard from the Île des Pins, New Caledonia, with comments on the diversity and affinities of the region’s lizard fauna. Pac. Sci. 73, 123–141 (2019).Bauer, A. M. & Sadlier, R. A. Lizard discoveries and rediscoveries in the New Caledonian region. In Flores, O., Ah-Peng, C., & Wilding, N. Island Biology 2019. Third International Conference on Island Ecology, Evolution and Conservation: Book of Abstracts. Island Biology 2019, Jul 2019, Saint Denis, France. 2020. ffhal-02633975v2 243 (2019).Ineich, I., Sadlier, R. A., Bauer, A. M., Jackman, T. R. & Smith, S. A. Bocourt’s terrific skink, Phoboscincus bocourti (Brocchi, 1876), and the monophyly of the genus Phoboscincus Greer, 1974. In Zoologia Neocaledonica 8. Biodiversity studies in New Caledonia. Mémoires du Muséum National d’Histoire Naturelle (eds Guilbert, E. et al.) 69–78 Muséum National d’Histoire naturelle, (2014).
Google Scholar 
Caut, S., Holden, M., Jowers, M. J., Boistel, R. & Ineich, I. Is Bocourt’s terrific skink really so terrific? Trophic myth and reality. PLoS One 8, e78638 (2013).Sagonas, K. et al. Insularity affects head morphology, bite force and diet in a Mediterranean lizard. Biol. J. Linn. Soc. 112, 469–484 (2014).
Google Scholar 
Tseng, W.-H. et al. Opsin gene expression regulated by testosterone level in a sexually dimorphic lizard. Sci. Rep. 8, 16055 (2018).ADS 
PubMed 
PubMed Central 

Google Scholar 
Avramo, V. et al. Evaluating the island effect on phenotypic evolution in the Italian wall lizard, Podarcis siculus (Reptilia: Lacertidae). Biol. J. Linn. Soc. 132, 655–665 (2021).
Google Scholar 
Siliceo-Cantero, H. H., Benítez-Malvido, J. & Suazo-Ortuño, I. Insularity effects on the morphological space and sexual dimorphism of a tropical tree lizard in western Mexico. J. Zool. 311, 277–285 (2020).
Google Scholar 
Pérez-Mellado, V. & Corti, C. Dietary adaptations and herbivory in lacertid lizards of the genus Podarcis from western Mediterranean islands (Reptilia: Sauria). Bonner Zool. Beiträge 44, 193–220 (1993).
Google Scholar 
Castilla, A. M., Vanhooydonck, B. & Catenazzi, A. Feeding behavior of the Columbretes lizard Podarcis atrata, in relation to the marine species, Ligia italica (Isopoda, Crustaceae). Belgian J. Zool. 138, 146–148 (2008).
Google Scholar 
Castilla, A. M. & Herrel, A. The scorpion Buthus occitanus as a profitable prey for the endemic lizard Podarcis atrata in the volcanic Columbretes islands (Mediterranean, Spain). J. Arid Environ. 73, 378–380 (2009).ADS 

Google Scholar 
Van Damme, R. Evolution of herbivory in lacertid lizards: Effects of insularity and body size. J. Herpetol. 33, 663 (1999).
Google Scholar 
Pafilis, P., Meiri, S., Foufopoulos, J. & Valakos, E. Intraspecific competition and high food availability are associated with insular gigantism in a lizard. Naturwissenschaften 96, 1107–1113 (2009).ADS 
CAS 
PubMed 

Google Scholar 
D’Amore, D. C. et al. Increasing dietary breadth through allometry: Bite forces in sympatric Australian skinks. Herpetol. Notes 11, 179–187 (2018).
Google Scholar 
Taverne, M. et al. Proximate and ultimate drivers of variation in bite force in the insular lizards Podarcis melisellensis and Podarcis sicula. Biol. J. Linn. Soc. 131, 88–108 (2020).
Google Scholar 
Kingsolver, J. G. & Pfennig, D. W. Patterns and power of phenotypic selection in nature. Bioscience 57, 561–572 (2007).
Google Scholar 
Itescu, Y., Foufopoulos, J., Pafilis, P. & Meiri, S. The diverse nature of island isolation and its effect on land bridge insular faunas. Glob. Ecol. Biogeogr. 29, 262–280 (2020).
Google Scholar 
Polis, G. A. & Hurd, S. D. Linking marine and terrestrial food webs: Allochthonous input from the ocean supports high secondary productivity on small islands and coastal land communities. Am. Nat. 147, 396–423 (1996).
Google Scholar 
Donihue, C. M., Brock, K. M., Foufopoulos, J. & Herrel, A. Feed or fight: Testing the impact of food availability and intraspecific aggression on the functional ecology of an island lizard. Funct. Ecol. 30, 566–575 (2016).
Google Scholar 
Runemark, A., Sagonas, K. & Svensson, E. I. Ecological explanations to island gigantism: Dietary niche divergence, predation, and size in an endemic lizard. Ecology 96, 2077–2092 (2015).PubMed 

Google Scholar 
Verwaijen, D., Van Damme, R. & Herrel, A. Relationships between head size, bite force, prey handling efficiency and diet in two sympatric lacertid lizards. Funct. Ecol. 16, 842–850 (2002).
Google Scholar 
Herrel, A., O’Reilly, J. C. & Richmond, A. M. Evolution of bite performance in turtles. J. Evol. Biol. 15, 1083–1094 (2002).
Google Scholar 
Herrel, A., Vanhooydonck, B., Joachim, R. & Irschick, D. J. Frugivory in polychrotid lizards: Effects of body size. Oecologia 140, 160–168 (2004).ADS 
CAS 
PubMed 

Google Scholar 
Herrel, A., Vanhooydonck, B. & Van Damme, R. Omnivory in lacertid lizards: Adaptive evolution or constraint?. J. Evol. Biol. 17, 974–984 (2004).CAS 
PubMed 

Google Scholar 
Herrel, A., Podos, J., Huber, S. K. & Hendry, A. P. Bite performance and morphology in a population of Darwin’s finches: Implications for the evolution of beak shape. Funct. Ecol. 19, 43–48 (2005).
Google Scholar 
Herrel, A., Podos, J., Huber, S. K. & Hendry, A. P. Evolution of bite force in Darwin’s finches: A key role for head width. J. Evol. Biol. 18, 669–675 (2005).CAS 
PubMed 

Google Scholar 
Aguirre, L. F., Herrel, A., Van Damme, R. & MatThysen, E. The implications of food hardness for diet in bats. Funct. Ecol. 17, 201–212 (2003).
Google Scholar 
Herrel, A. & Holanova, V. Cranial morphology and bite force in Chamaeleolis lizards—Adaptations to molluscivory?. Zoology 111, 467–475 (2008).PubMed 

Google Scholar 
Greer, A. E. Distribution of maximum snout-vent length among species of scincid lizards. J. Herpetol. 35, 383 (2001).
Google Scholar 
Burggren, W. W. & McMahon, B. R. Biology of the Land Crabs, Cambridge University Press, (1988).
Google Scholar 
Grubb, P. Ecology of terrestrial decapod crustaceans on Aldabra. Philos. Trans. R. Soc. Lond. B Biol. Sci. 260, 411–416 (1971)Wineski, L. E. & Gans, C. Morphological basis of the feeding mechanics in the shingle-back lizard Trachydosaurus rugosus (Scincidae, Reptilia). J. Morphol. 181, 271–295 (1984).CAS 
PubMed 

Google Scholar 
Herrel, A., Verstappen, M. & De Vree, F. Modulatory complexity of the feeding repertoire in scincid lizards. J. Comp. Physiol. A Sens. Neural Behav. Physiol. 184, 501–518 (1999).Herrel, A., Aerts, P. & De Vree, F. Ecomorphology of the lizard feeding apparatus: A modelling approach. Neth. J. Zool. 48, 1–25 (1998).
Google Scholar 
Hartnoll, R. G. Evolution, systematics, and geographical distribution. In Biology of the Land Crabs (eds Burggren, W. W. & McMahon, B. R.) 6–54, (Cambridge University Press, 1988).
Google Scholar 
Ben-David, M. & Schell, D. M. Mixing models in analyses of diet using multiple stable isotopes: A response. Oecologia 127, 180–184 (2001).ADS 
CAS 
PubMed 

Google Scholar 
Caut, S., Angulo, E. & Courchamp, F. Caution on isotopic model use for analyses of consumer diet. Can. J. Zool. 86, 438–445 (2008).CAS 

Google Scholar 
Warne, R. W., Gilman, C. A. & Wolf, B. O. Tissue-carbon incorporation rates in lizards: Implications for ecological studies using stable isotopes in terrestrial ectotherms. Physiol. Biochem. Zool. 83, 608–617 (2010).PubMed 

Google Scholar 
Steinitz, R., Lemm, J. M., Pasachnik, S. A. & Kurle, C. M. Diet-tissue stable isotope (Δ13C and Δ15N) discrimination factors for multiple tissues from terrestrial reptiles. Rapid Commun. Mass Spectrom. 30, 9–21 (2016).ADS 
CAS 
PubMed 

Google Scholar 
Lattanzio, M. & Miles, D. Stable carbon and nitrogen isotope discrimination and turnover in a small-bodied insectivorous lizard. Isot. Environ. Health Stud. 52, 673–681 (2016).CAS 

Google Scholar 
Durso, A. M., Smith, G. D., Hudson, S. B. & French, S. S. Stoichiometric and stable isotope ratios of wild lizards in an urban landscape vary with reproduction, physiology, space and time. Conserv. Physiol. 8, 1–14 (2020).
Google Scholar 
Warne, R. W. & Wolf, B. O. Nitrogen stable isotope turnover and discrimination in lizards. Rapid Commun. Mass Spectrom. 35, e9030 (2021).Aerts, P., De Vree, F. & Herrel, A. Ecomorphology of the lizard feeding apparatus: A modelling approach. Neth. J. Zool. 48, 1–25 (1997).
Google Scholar 
Herrel, A., Schaerlaeken, V., Meyers, J. J., Metzger, K. A. & Ross, C. F. The evolution of cranial design and performance in squamates: Consequences of skull-bone reduction on feeding behavior. Integr. Comp. Biol. 47, 107–117 (2007).PubMed 

Google Scholar 
Beuttner, A. & Koch, C. Analysis of diet composition and morphological characters of the Peruvian lizard Microlophus stolzmanni (Squamata: Tropiduridae). Phyllomedusa J. Herpetol. 18, 47–62 (2019).
Google Scholar 
Herrel, A., Aerts, P. & Vree, D. Static biting in lizards: Functional morphology of the temporal ligaments. J. Zool. 244, 135–143 (1998).
Google Scholar 
Greer, A. The genetic relationships of the scincid lizard genus Leiolopisma and its relatives. Aust. J. Zool. Suppl. Ser. 22, 1–67 (1974).
Google Scholar 
Shirley, M. H., Carr, A. N., Nestler, J. H., Vliet, K. A. & Brochu, C. A. Systematic revision of the living African slender-snouted crocodiles (Mecistops Gray, 1844). Zootaxa 4504, 151 (2018).PubMed 

Google Scholar 
Yoshioka, S. & Kimura, T. What does the red-eared slider eat on the tidal flats? Comparing the diet of the invasive alien species Trachemys scripta elegans inhabiting the tidal flat and freshwaters. Jpn. J. Benthol. 72, 83–93 (2018).
Google Scholar 
Bernal, S. & Magda, S. Análisis de los contenidos estomacales de las tortugas y cachirres de la Reserva Natural Privada de la Sociedad Civil Bojonawi (Puerto Carreño, Vichada). (Bogotá: Instituto de Investigación de Recursos Biológicos Alexander von Humboldt, 2020).Murphy, J. C. Homalopsid Snakes, Evolution in the Mud (Krieger Publishing Company, 2007).
Google Scholar 
Chen, P. Z. An observation of crab predation by a Gerard’s water snake, Gerarda prevostiana (Reptilia: Squamata: Homalopsidae) in the wild at Sungei Buloh, Singapore. Nat. Singap. 3, 195–197 (2010).
Google Scholar 
Jayne, B. C., Voris, H. K. & Ng, P. K. L. Snake circumvents constraints on prey size. Nature 418, 143–143 (2002).ADS 
CAS 
PubMed 

Google Scholar 
Jayne, B. C., Voris, H. K. & Ng, P. K. L. How big is too big? Using crustacean-eating snakes (Homalopsidae) to test how anatomy and behaviour affect prey size and feeding performance. Biol. J. Linn. Soc. 123, 636–650 (2018).
Google Scholar 
Murphy, J. C. & Voris, H. K. Aquatic snakes with crustacean-eating habits elude herpetologists for two centuries. Litt. Serpentium 22, 107–114 (2002).
Google Scholar 
Voris, H. K. & Murphy, J. C. The prey and predators of Homalopsine snakes. J. Nat. Hist. 36, 1621–1632 (2002).
Google Scholar 
Wai-Neng, L. & Melville, D. S. Notes on the feeding of Enhydris bennetti (Gray) (Reptilia, Squamata, Colubridae) in Hong Kong. Mem. Hong Kong Nat. Hist. Soc. 19, 117 (2020).
Google Scholar 
López-Hurtado, Y., García-Padrón, L. Y., González, A., Díaz, L. M. & Rodríguez-Cabrera, T. M. Notes on the feeding habits of the Caribbean watersnake, Tretanorhinus variabilis (Dipsadidae). Reptil. Amphib. 27, 147–153 (2020).
Google Scholar 
Gripshover, N. D. & Jayne, B. C. Crayfish eating in snakes: Testing how anatomy and behavior affect prey size and feeding performance. Integr. Org. Biol. 3, 1–16 (2021).
Google Scholar 
Naish, D. The Madagascan skink Amphiglossus eats crabs. Sci. Am. Blog Netw. https://blogs.scientificamerican.com/tetrapod-zoology/the-madagascan-skink-amphiglossus-eats-crabs/ (2016).Hediger, H. Beitrag zur herpetologie und zoogeographie Neu Britanniens und einiger umliegender gebiete. Zool. Jahrbücher. Abteilung für Syst. Geogr. und Biol. der Tiere 65, 441–582 (1934).McCoy, M. W. Reptiles of the Solomon Islands, (Pensoft Publishers, 2006).
Google Scholar 
Huang, W. S. Ecology and reproductive patterns of the littoral skink Emoia atrocostata on an East Asian tropical rainforest island. Zool. Stud. 50, 506–512 (2011).
Google Scholar 
Anderson, C. Decapod crustacean species of Aride Island, Seychelles. Phelsuma 2(12), 36–49 (1994).
Google Scholar 
Paulay, G. & Starmer, J. Evolution, insular restriction, and extinction of oceanic land crabs, exemplified by the loss of an endemic Geograpsus in the Hawaiian Islands. PLoS ONE 6, e19916 (2011).Cleuren, J., Aerts, P. & de Vree, F. Bite and joint force analysis in Caiman crocodilus. Belgian J. Zool. 125, 79–94 (1995).
Google Scholar 
Meyers, J. J., Nishikawa, K. C. & Herrel, A. The evolution of bite force in horned lizards: The influence of dietary specialization. J. Anat. 232, 214–226 (2018).PubMed 

Google Scholar 
Van Damme, R., De Vree, F. & Herrel, A. Sexual dimorphism of head size in Podarcis hispanica atrata: Testing the dietary divergence hypothesis by bite force analysis. Neth. J. Zool. 46, 253–262 (1995).
Google Scholar 
Gröning, F. et al. The importance of accurate muscle modelling for biomechanical analyses: A case study with a lizard skull. J. R. Soc. Interface 10, 1–10 (2013).
Google Scholar 
Vanhooydonck, B., Boistel, R., Fernandez, V. & Herrel, A. Push and bite: Trade-offs between burrowing and biting in a burrowing skink (Acontias percivali). Biol. J. Linn. Soc. 102, 91–99 (2011).
Google Scholar 
Handschuh, S. et al. Cranial kinesis in the miniaturised lizard Ablepharus kitaibelii (Squamata: Scincidae). J. Exp. Biol. 222, 1–15 (2019).
Google Scholar 
Le Guilloux, M. et al. Trade-offs between burrowing and biting force in fossorial scincid lizards?. Biol. J. Linn. Soc. 130, 310–319 (2020).
Google Scholar 
Herrel, A, Spithoven, L., Van Damme, R. & De Vree, F. Sexual dimorphism of head size in Gallotia galloti: Testing the niche divergence hypothesis by functional analyses. Funct. Ecol. 13, 289–297 (1999).
Google Scholar 
Herrel, A., De Grauw, E. & Lemos-Espinal, J. A. Head shape and bite performance in xenosaurid lizards. J. Exp. Zool. 290, 101–107 (2001).CAS 
PubMed 

Google Scholar 
Herrel, A., Petrochic, S. & Draud, M. Sexual dimorphism, bite force and diet in the diamondback terrapin. J. Zool. 304, 217–224 (2018).
Google Scholar  More

Stochastic age-specific transmission modelWe formulate a stochastic age-specific transmission model in the general Susceptible(S)-Exposed(E)-Reported(I)-Unreported(U)-Recovered(R) framework. For a particular age group (i) at time (t-1) ((i=1) corresponding to the 0–17 years, (i=2) to 18–44, (i=3) to 45–64 and (i=4) to 65+), we have$$begin{array}{l}{S}_{i}(t)= {S}_{i}(t-1)-{n}_{S{E}_{i}}(t)\ {E}_{i}(t)= {E}_{i}(t-1)+{n}_{S{E}_{i}}(t)-\ {n}_{E{I}_{i}}(t)-{n}_{E{U}_{i}}(t)\ {I}_{i}(t)= {I}_{i}(t-1)+{n}_{E{I}_{i}}(t)-{n}_{I{R}_{i}}(t)\ {U}_{i}(t)= {U}_{i}(t-1)+{n}_{E{U}_{i}}(t)-{n}_{U{R}_{i}}(t)\ {R}_{i}(t)= {R}_{i}(t-1)+{n}_{I{R}_{i}}(t)+{n}_{U{R}_{i}}(t),end{array}$$
(1)
where ({n}_{{XY}_{i}}(t)) represents number of transitions between a class X and class Y for age group (i) at time (t).The number of transitions from the susceptible to exposed class for group (i) at time (t) is modelled by$$begin{aligned}{n}_{S{E}_{i}}(t)&sim Poi({S}_{i}(t-1)times {gamma }_{i}(t)times \ & quad sum_{j=1}beta (t)times {c}_{j,i}(t)times {{I}_{j}(t-1)+{U}_{j}(t-1)}).end{aligned}$$
(2)
Here, (beta (t)) denotes the average infectiousness of an infectious individual and ({c}_{j,i}(t)) is the average number of contacts per day made by age group (j) to (i). Also note that the product (beta (t)times {c}_{j,i}(t)) may represent age-specific transmissibility (of age group (j)) accounting for contacts. We allow and infer two change points of (beta (t)) (one potentially correlates to changes due to the implementation of lockdown and another one to changes due to the lifting of lockdown), i.e.,$$beta left(tright)=left{begin{array}{ll}{beta }_{0},&quad if; tle {T}_{1}\ {beta }_{1}={omega }_{1}times {beta }_{0},&quad if ;{T}_{1}{T}_{2},end{array}right.$$
(3)
where ({T}_{1}) and ({T}_{2}) are the two change points to be inferred (({T}_{2}ge {T}_{1})). ({gamma }_{i}(t)) denotes the susceptibility of group (i) relative to the oldest age group (i.e., ({gamma }_{4}=1)), which is also allowed to change proportionally after lifting the lockdown. Note that ({gamma }_{i}(t)) implicitly incorporates any behavioral effects (e.g., potential reduction of risk of getting infection due to facemask wearing). Transitions between other classes are modelled as:$$begin{aligned}{n}_{E{U}_{i}}(t)sim & Bin({n}_{S{E}_{i}}(t-{D}_{EU}),{p}_{{U}_{i}}(t-{D}_{EU}))\ {n}_{E{I}_{i}}(t)=& {n}_{S{E}_{i}}(t-{D}_{EI})-{n}_{E{U}_{i}}(t)\ {n}_{I{R}_{i}}(t)=& {n}_{E{I}_{i}}(t-{D}_{IR})\ {n}_{U{R}_{i}}(t)=& {n}_{E{U}_{i}}(t-{D}_{UR}),end{aligned}$$
(4)
where ({D}_{EI}), ({D}_{EU}), ({D}_{IR}) and ({D}_{UR}) denote the mean waiting times between the indicated two classes. We assume that ({D}_{EI})= ({D}_{EU})=7 days and ({D}_{IR})= ({D}_{UR})=14 days. ({p}_{{U}_{i}}(t)) represents probability that an infection is unreported at times (t) for age group (i), we assume$${p}_{{U}_{i}}(t)=1-frac{{e}^{{f}_{i}(t)}}{1+{e}^{{f}_{i}(t)}}.$$
(5)
({f}_{i}(.)) is an increasing function with ({f}_{i}(t)={a}_{i}+{b}_{i}times t), where (-infty More

Analysing the relations between FTSE100 and self-reported measures of emotional well-being we confirmed that market ups (higher FTSE100 scores) were associated with higher scores of “happiness” and lower scores in self-reported “negative emotional facets”: irritability, hurt and nervous feelings, anxiety (Fig. 1; Table 1). The identified association also held true for the 5.5-years of the MRI subsample (Supplementary Table S2). We further explored non-imaging variables that are associated with mood changes, i.e. alcohol intake (overall intake frequency and a composite score reflecting weekly intake of all alcoholic beverages) and diastolic blood pressure (automatic readings in mmHg measured at rest), and showed that they were also highly correlated with the FTSE100 (Fig. 1A) in that both measures increased when the stock market decreased in value. Several of these effects (relation between stock market and negative emotions, blood pressure or alcohol-intake) were reproduced in the My Connectome data-set consisting of one single subject whose measurements were taken at 81 timepoints during a period or 1.5 years (Fig. 1B).Figure 1Non-MRI variables and stock market moves. The figure illustrates the identified associations between stock market moves and non-MRI indicators of well-being in the UK Biobank sample (top panel A) and My Connectome data, a single-subject study (bottom panel B); *p  More