Philippa Kaur

IPCC. Climate Change 2021: The Physical Science Basis. (eds Masson-Delmotte, V. et al.) Contribution of working group 1 to the ‘Sixth assessment report of the intergovernmental panel on climate change’ (Cambridge University Press, 2021).Huang, J., Yu, H., Guan, X., Wang, G. & Guo, R. Accelerated dryland expansion under climate change. Nat. Clim. Change 6, 166–171 (2016).Article 

Google Scholar 
Greve, P. et al. Global assessment of trends in wetting and drying over land. Nat. Geosc. 7, 716–721 (2014).CAS 
Article 

Google Scholar 
Lin, L., Gettelman, A., Feng, S. & Fu, Q. Simulated climatology and evolution of aridity in the 21st century. J. Geophys. Res. Atmos. 120, 5795–5815 (2015).Article 

Google Scholar 
Coumou, D. & Rahmstorf, S. A decade of weather extremes. Nat. Clim. Change 2, 491–496 (2012).Article 

Google Scholar 
Williams, A. P. et al. Large contribution from anthropogenic warming to an emerging North American megadrought. Science 368, 314–318 (2020).CAS 
PubMed 
Article 

Google Scholar 
Touma, D., Ashfaq, M., Nayak, M. A., Kao, S.-C. & Diffenbaugh, N. S. A multi-model and multi-index evaluation of drought characteristics in the 21st century. J. Hydrol. 526, 196–207 (2015).Article 

Google Scholar 
Liu, W. et al. Global drought and severe drought-affected populations in 1.5 and 2 °C warmer worlds. Earth Syst. Dyn. 9, 267–283 (2018).Article 

Google Scholar 
Ault, T. R. On the essentials of drought in a changing climate. Science 368, 256–260 (2020).CAS 
PubMed 
Article 

Google Scholar 
Swann, A. L., Hoffman, F. M., Koven, C. D. & Randerson, J. T. Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity. Proc. Natl Acad. Sci. USA 113, 10019–10024 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Milly, P. C. D. & Dunne, K. A. Potential evapotranspiration and continental drying. Nat. Clim. Change 6, 946–949 (2016).Article 

Google Scholar 
Zhou, S. et al. Soil moisture–atmosphere feedbacks mitigate declining water availability in drylands. Nat. Clim. Change 11, 38–44 (2021).Article 

Google Scholar 
Musselman, K. N., Clark, M. P., Liu, C., Ikeda, K. & Rasmussen, R. Slower snowmelt in a warmer world. Nat. Clim. Change 7, 214–219 (2017).Article 

Google Scholar 
Harpold, A. A. et al. Soil moisture response to snowmelt timing in mixed-conifer subalpine forests. Hydrol. Process. 29, 2782–2798 (2015).Article 

Google Scholar 
Lesk, C., Rowhani, P. & Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 529, 84–87 (2016).CAS 
PubMed 
Article 

Google Scholar 
Choat, B. et al. Triggers of tree mortality under drought. Nature 558, 531–539 (2018).CAS 
PubMed 
Article 

Google Scholar 
Reichstein, M. et al. Climate extremes and the carbon cycle. Nature 500, 287–295 (2013).CAS 
PubMed 
Article 

Google Scholar 
Pecl, G. T. et al. Biodiversity redistribution under climate change: impacts on ecosystems and human well-being. Science 355, eaai9214 (2017).Song, J. et al. A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change. Nat. Ecol. Evol. 3, 1309–1320 (2019).PubMed 
Article 

Google Scholar 
Parton, W. et al. Global-scale similarities in nitrogen release patterns during long-term decomposition. Science 315, 361–364 (2007).CAS 
PubMed 
Article 

Google Scholar 
Adair, E. C. et al. Simple three-pool model accurately describes patterns of long-term litter decomposition in diverse climates. Glob. Change Biol. 14, 2636–2660 (2008).Article 

Google Scholar 
Adair, E. C., Parton, W. J., King, J. Y., Brandt, L. A. & Lin, Y. Accounting for photodegradation dramatically improves prediction of carbon losses in dryland systems. Ecosphere 8, e01892 (2017).Article 

Google Scholar 
Chen, M. et al. Simulation of the effects of photodecay on long-term litter decay using DayCent. Ecosphere 7, e01631 (2016).
Google Scholar 
Asao, S., Parton, W. J., Chen, M. & Gao, W. Photodegradation accelerates ecosystem N cycling in a simulated California grassland. Ecosphere 9, e02370 (2018).Article 

Google Scholar 
Berdugo, M. et al. Global ecosystem thresholds driven by aridity. Science 367, 787–790 (2020).CAS 
PubMed 
Article 

Google Scholar 
Feng, S. & Fu, Q. Expansion of global drylands under a warming climate. Atmos. Chem. Phys. 13, 10081–10094 (2013).CAS 
Article 

Google Scholar 
Berg, A. & McColl, K. A. No projected global drylands expansion under greenhouse warming. Nat. Clim. Change 11, 331–337 (2021).Article 

Google Scholar 
Whitford, W. G. & Duval, B. D. Ecology of Desert Systems 2nd edn (Academic Press, 2020).Maestre, F. T. et al. Structure and functioning of dryland ecosystems in a changing world. Annu. Rev. Ecol. Evol. Syst. 47, 215–237 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Schimel, J. P. Life in dry soils: effects of drought on soil microbial communities and processes. Annu. Rev. Ecol. Evol. Syst. 49, 409–432 (2018).Article 

Google Scholar 
Nielsen, U. N. & Ball, B. A. Impacts of altered precipitation regimes on soil communities and biogeochemistry in arid and semi-arid ecosystems. Glob. Change Biol. 21, 1407–1421 (2015).Article 

Google Scholar 
Collins, S. L. et al. A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems. Annu. Rev. Ecol. Evol. Syst. 45, 397–419 (2014).Article 

Google Scholar 
Kim, D.-G., Mu, S., Kang, S. & Lee, D. Factors controlling soil CO2 effluxes and the effects of rewetting on effluxes in adjacent deciduous, coniferous, and mixed forests in Korea. Soil Biol. Biochem. 42, 576–585 (2010).Article 
CAS 

Google Scholar 
Curiel Yuste, J., Janssens, I. A., Carrara, A., Meiresonne, L. & Ceulemans, R. Interactive effects of temperature and precipitation on soil respiration in a temperate maritime pine forest. Tree Physiol. 23, 1263–1270 (2003).CAS 
PubMed 
Article 

Google Scholar 
Savage, K., Davidson, E. A., Richardson, A. D. & Hollinger, D. Y. Three scales of temporal resolution from automated soil respiration measurements. Agric. Meteorol. 149, 2012–2021 (2009).Article 

Google Scholar 
Hao, Y., Wang, Y., Mei, X. & Cui, X. The response of ecosystem CO2 exchange to small precipitation pulses over a temperate steppe. Plant Ecol. 209, 335–347 (2010).Article 

Google Scholar 
Krüger, J. P., Beckedahl, H., Gerold, G. & Jungkunst, H. F. Greenhouse gas emission peaks following natural rewetting of two wetlands in the southern Ukhahlamba-Drakensberg Park, South Africa. S. Afr. Geogr. J. 96, 113–118 (2013).Article 

Google Scholar 
Haverd, V., Ahlström, A., Smith, B. & Canadell, J. G. Carbon cycle responses of semi-arid ecosystems to positive asymmetry in rainfall. Glob. Change Biol. 23, 793–800 (2017).Article 

Google Scholar 
Kim, D. G., Vargas, R., Bond-Lamberty, B. & Turetsky, M. R. Effects of soil rewetting and thawing on soil gas fluxes: a review of current literature and suggestions for future research. Biogeosciences 9, 2459–2483 (2012).CAS 
Article 

Google Scholar 
Barnard, R. L., Blazewicz, S. J. & Firestone, M. K. Rewetting of soil: revisiting the origin of soil CO2 emissions. Soil Biol. Biochem. 147, 107819 (2020).Prieto, I., Armas, C. & Pugnaire, F. I. Water release through plant roots: new insights into its consequences at the plant and ecosystem level. New Phytol. 193, 830–841 (2012).PubMed 
Article 

Google Scholar 
Neumann, R. B. & Cardon, Z. G. The magnitude of hydraulic redistribution by plant roots: a review and synthesis of empirical and modeling studies. New Phytol. 194, 337–352 (2012).PubMed 
Article 

Google Scholar 
Mooney, H. A., Gulmon, S. L., Rundel, P. W. & Ehleringer, J. Further observations on the water relations of Prosopis tamarugo of the northern Atacama desert. Oecologia 44, 177–180 (1980).CAS 
PubMed 
Article 

Google Scholar 
Richards, J. H. & Caldwell, M. M. Hydraulic lift: substantial nocturnal water transport between soil layers by Artemisia tridentata roots. Oecologia 73, 486–489 (1987).CAS 
PubMed 
Article 

Google Scholar 
Caldwell, M. M., Dawson, T. E. & Richards, J. H. Hydraulic lift: consequences of water efflux from the roots of plants. Oecologia 113, 151–161 (1998).PubMed 
Article 

Google Scholar 
Brooks, J. R., Meinzer, F. C., Coulombe, R. & Gregg, J. Hydraulic redistribution of soil water during summer drought in two contrasting Pacific Northwest coniferous forests. Tree Physiol. 22, 1107–1117 (2002).PubMed 
Article 

Google Scholar 
Lee, J. E., Oliveira, R. S., Dawson, T. E. & Fung, I. Root functioning modifies seasonal climate. Proc. Natl Acad. Sci. USA 102, 17576–17581 (2005).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Robinson, J. L., Slater, L. D. & Schäfer, K. V. R. Evidence for spatial variability in hydraulic redistribution within an oak–pine forest from resistivity imaging. J. Hydrol. 430-431, 69–79 (2012).Article 

Google Scholar 
Oliveira, R. S., Dawson, T. E., Burgess, S. S. O. & Nepstad, D. C. Hydraulic redistribution in three Amazonian trees. Oecologia 145, 354–363 (2005).PubMed 
Article 

Google Scholar 
Zapater, M. et al. Evidence of hydraulic lift in a young beech and oak mixed forest using 18O soil water labelling. Trees 25, 885–894 (2011).Article 

Google Scholar 
Sardans, J. & Peñuelas, J. Hydraulic redistribution by plants and nutrient stoichiometry: shifts under global change. Ecohydrology 7, 1–20 (2014).Article 

Google Scholar 
Schenk, H. J. & Jackson, R. B. Rooting depths, lateral root spreads and below‐ground/above‐ground allometries of plants in water‐limited ecosystems. J. Ecol. 90, 480–494 (2002).Article 

Google Scholar 
Choat, B. et al. Global convergence in the vulnerability of forests to drought. Nature 491, 752–755 (2012).CAS 
PubMed 
Article 

Google Scholar 
Wang, L., Kaseke, K. F. & Seely, M. K. Effects of non-rainfall water inputs on ecosystem functions. WIREs Water 4, e1179 (2017).
Google Scholar 
Dawson, T. E. & Goldsmith, G. R. The value of wet leaves. New Phytol. 219, 1156–1169 (2018).PubMed 
Article 

Google Scholar 
Agam, N. & Berliner, P. R. Dew formation and water vapor adsorption in semi-arid environments – a review. J. Arid. Environ. 65, 572–590 (2006).Article 

Google Scholar 
Dirks, I., Navon, Y., Kanas, D., Dumbur, R. & Grünzweig, J. M. Atmospheric water vapor as driver of litter decomposition in Mediterranean shrubland and grassland during rainless seasons. Glob. Change Biol. 16, 2799–2812 (2010).Article 

Google Scholar 
Jacobson, K. et al. Non-rainfall moisture activates fungal decomposition of surface litter in the Namib Sand Sea. PLoS ONE 10, e0126977 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
McHugh, T. A., Morrissey, E. M., Reed, S. C., Hungate, B. A. & Schwartz, E. Water from air: an overlooked source of moisture in arid and semiarid regions. Sci. Rep. 5, 13767 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
Gliksman, D. et al. Biotic degradation at night, abiotic degradation at day: positive feedbacks on litter decomposition in drylands. Glob. Change Biol. 23, 1564–1574 (2017).Article 

Google Scholar 
Goldsmith, G. R., Matzke, N. J. & Dawson, T. E. The incidence and implications of clouds for cloud forest plant water relations. Ecol. Lett. 16, 307–314 (2013).PubMed 
Article 

Google Scholar 
Binks, O. et al. Foliar water uptake in Amazonian trees: evidence and consequences. Glob. Change Biol. 25, 2678–2690 (2019).Article 

Google Scholar 
Benzing, D. H. Vulnerabilities of tropical forests to climate change: the significance of resident epiphytes. Clim. Change 39, 519–540 (1998).Article 

Google Scholar 
Evans, S., Todd-Brown, K. E. O., Jacobson, K. & Jacobson, P. Non-rainfall moisture: a key driver of microbial respiration from standing litter in arid, semiarid, and mesic grasslands. Ecosystems 23, 1154–1169 (2020).CAS 
Article 

Google Scholar 
Newell, S. Y., Fallon, R. D., Rodriguez, R. M. C. & Groene, L. C. Influence of rain, tidal wetting and relative-humidity on release of carbon-dioxide by standing-dead salt-marsh plants. Oecologia 68, 73–79 (1985).CAS 
PubMed 
Article 

Google Scholar 
Kuehn, K. A., Steiner, D. & Gessner, M. O. Diel mineralization patterns of standing-dead plant litter: implications for CO2 flux from wetlands. Ecology 85, 2504–2518 (2004).Article 

Google Scholar 
Doerr, S. H., Shakesby, R. A. & Walsh, R. P. D. Soil water repellency: its causes, characteristics and hydro-geomorphological significance. Earth Sci. Rev. 51, 33–65 (2000).Article 

Google Scholar 
Goebel, M.-O., Bachmann, J., Reichstein, M., Janssens, I. A. & Guggenberger, G. Soil water repellency and its implications for organic matter decomposition – is there a link to extreme climatic events? Glob. Change Biol. 17, 2640–26596 (2011).Article 

Google Scholar 
Mao, J., Nierop, K. G. J., Dekker, S. C., Dekker, L. W. & Chen, B. Understanding the mechanisms of soil water repellency from nanoscale to ecosystem scale: a review. J. Soils Sediments 19, 171–185 (2019).Article 

Google Scholar 
Doerr, S. H., Shakesby, R. A., Dekker, L. W. & Ritsema, C. J. Occurrence, prediction and hydrological effects of water repellency amongst major soil and land-use types in a humid temperate climate. Eur. J. Soil Sci. 57, 741–754 (2006).Article 

Google Scholar 
Lebron, I., Robinson, D. A., Oatham, M. & Wuddivira, M. N. Soil water repellency and pH soil change under tropical pine plantations compared with native tropical forest. J. Hydrol. 414-415, 194–200 (2012).CAS 
Article 

Google Scholar 
Buczko, U., Bens, O. & Hüttl, R. F. Variability of soil water repellency in sandy forest soils with different stand structure under Scots pine (Pinus sylvestris) and beech (Fagus sylvatica). Geoderma 126, 317–336 (2005).Article 

Google Scholar 
Dekker, L. W. & Ritsema, C. J. Variation in water content and wetting patterns in Dutch water repellent peaty clay and clayey peat soils. CATENA 28, 89–105 (1996).CAS 
Article 

Google Scholar 
de Blas, E., Almendros, G. & Sanz, J. Molecular characterization of lipid fractions from extremely water-repellent pine and eucalyptus forest soils. Geoderma 206, 75–84 (2013).Article 
CAS 

Google Scholar 
MacDonald, L. H. & Huffman, E. L. Post-fire soil water repellency. Soil Sci. Soc. Am. J. 68, 1729–1734 (2004).CAS 
Article 

Google Scholar 
Hewelke, E. et al. Intensity and persistence of soil water repellency in pine forest soil in a temperate continental climate under drought conditions. Water 10, 1121 (2018).Article 
CAS 

Google Scholar 
Borken, W. & Matzner, E. Reappraisal of drying and wetting effects on C and N mineralization and fluxes in soils. Glob. Change Biol. 15, 808–824 (2009).Article 

Google Scholar 
Siteur, K. et al. Soil water repellency: a potential driver of vegetation dynamics in coastal dunes. Ecosystems 19, 1210–1224 (2016).CAS 
Article 

Google Scholar 
Austin, A. T. & Vivanco, L. Plant litter decomposition in a semi-arid ecosystem controlled by photodegradation. Nature 442, 555–558 (2006).CAS 
PubMed 
Article 

Google Scholar 
King, J. Y., Brandt, L. A. & Adair, E. C. Shedding light on plant litter decomposition: advances, implications and new directions in understanding the role of photodegradation. Biogeochemistry 111, 57–81 (2012).Article 

Google Scholar 
Moorhead, D. L. & Callaghan, T. Effects of increasing ultraviolet B radiation on decomposition and soil organic matter dynamics: a synthesis and modelling study. Biol. Fertil. Soils 18, 19–26 (1994).CAS 
Article 

Google Scholar 
Sulzberger, B., Austin, A. T., Cory, R. M., Zepp, R. G. & Paul, N. D. Solar UV radiation in a changing world: roles of cryosphere-land-water-atmosphere interfaces in global biogeochemical cycles. Photochem. Photobiol. Sci. 18, 747–774 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Austin, A. T., Mendez, M. S. & Ballaré, C. L. Photodegradation alleviates the lignin bottleneck for carbon turnover in terrestrial ecosystems. Proc. Natl Acad. Sci. USA 113, 4392–4397 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Brandt, L. A., King, J. Y., Hobbie, S. E., Milchunas, D. G. & Sinsabaugh, R. L. The role of photodegradation in surface litter decomposition across a grassland ecosystem precipitation gradient. Ecosystems 13, 765–781 (2010).CAS 
Article 

Google Scholar 
Pieristè, M. et al. Solar UV-A radiation and blue light enhance tree leaf litter decomposition in a temperate forest. Oecologia 191, 191–203 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Wu, C. et al. Photodegradation accelerates coarse woody debris decomposition in subtropical Chinese forests. For. Ecol. Manage. 409, 225–232 (2018).Article 

Google Scholar 
Marinho, O. A., Martinelli, L. A., Duarte-Neto, P. J. R., Mazzi, E. A. & King, J. Y. Photodegradation influences litter decomposition rate in a humid tropical ecosystem, Brazil. Sci. Total Environ. 715, 136601 (2020).CAS 
PubMed 
Article 

Google Scholar 
Wang, Q. W. et al. The contribution of photodegradation to litter decomposition in a temperate forest gap and understorey. New Phytol. 229, 2625–2636 (2021).CAS 
PubMed 
Article 

Google Scholar 
Rutledge, S., Campbell, D. I., Baldocchi, D. & Schipper, L. A. Photodegradation leads to increased carbon dioxide losses from terrestrial organic matter. Glob. Change Biol. 16, 3065–3074 (2010).
Google Scholar 
Williamson, C. E. et al. Solar ultraviolet radiation in a changing climate. Nat. Clim. Change 4, 434–441 (2014).Article 

Google Scholar 
Zepp, R. G., Erickson, D. J. III, Paul, N. D. & Sulzberger, B. Effects of solar UV radiation and climate change on biogeochemical cycling: interactions and feedbacks. Photochem. Photobiol. Sci. 10, 261–271 (2011).CAS 
PubMed 
Article 

Google Scholar 
Austin, A. Has water limited our imagination for aridland biogeochemistry? Trends Ecol. Evol. 26, 229–235 (2011).PubMed 
Article 

Google Scholar 
McCalley, C. K. & Sparks, J. P. Abiotic gas formation drives nitrogen loss from a desert ecosystem. Science 326, 837–840 (2009).CAS 
PubMed 
Article 

Google Scholar 
Lee, H., Rahn, T. & Throop, H. L. An accounting of C-based trace gas release during abiotic plant litter degradation. Glob. Change Biol. 18, 1185–1195 (2012).Article 

Google Scholar 
Wang, B., Lerdau, M. & He, Y. Widespread production of nonmicrobial greenhouse gases in soils. Glob. Change Biol. 23, 4472–4482 (2017).Article 

Google Scholar 
Soper, F. M., McCalley, C. K., Sparks, K. & Sparks, J. P. Soil carbon dioxide emissions from the Mojave desert: isotopic evidence for a carbonate source. Geophys. Res. Lett. 44, 245–251 (2017).CAS 
Article 

Google Scholar 
Day, T. A. & Bliss, M. S. Solar photochemical emission of CO2 from leaf litter: sources and significance to C loss. Ecosystems 23, 1344–1361 (2020).CAS 
Article 

Google Scholar 
Throop, H. L. & Belnap, J. Connectivity dynamics in dryland litter cycles: moving decomposition beyond spatial stasis. Bioscience 69, 602–614 (2019).Article 

Google Scholar 
Throop, H. L. & Archer, S. R. Resolving the dryland decomposition conundrum: some new perspectives on potential drivers. Prog. Bot. 70, 171–194 (2009).CAS 

Google Scholar 
Barnes, P. W. et al. in Progress in Botany Vol. 76 (eds Lüttge, U. & Beyschlag, W.) 273–302 (Springer, 2015).Barnes, P. W., Throop, H. L., Hewins, D. B., Abbene, M. L. & Archer, S. R. Soil coverage reduces photodegradation and promotes the development of soil-microbial films on dryland leaf litter. Ecosystems 15, 311–321 (2012).CAS 
Article 

Google Scholar 
Joly, F. X., Kurupas, K. L. & Throop, H. L. Pulse frequency and soil-litter mixing alter the control of cumulative precipitation over litter decomposition. Ecology 98, 2255–2260 (2017).PubMed 
Article 

Google Scholar 
Weber, B., Büdel, B. & Belnap, J. Biological Soil Crusts: An Organizing Principle in Drylands Vol. 226 (Springer, 2016).Belnap, J. & Lange, O. L. Biological Soil Crusts: Structure, Function, and Management (Springer, 2001).Ferrenberg, S., Tucker, C. L. & Reed, S. C. Biological soil crusts: diminutive communities of potential global importance. Front. Ecol. Environ. 15, 160–167 (2017).Article 

Google Scholar 
Belnap, J. The world at your feet: desert biological soil crusts. Front. Ecol. Environ. 1, 181–189 (2003).Article 

Google Scholar 
Rodríguez-Caballero, E. et al. Dryland photoautotrophic soil surface communities endangered by global change. Nat. Geosci. 11, 185–189 (2018).Article 
CAS 

Google Scholar 
Hawkes, C. V. & Flechtner, V. R. Biological soil crusts in a xeric Florida shrubland: composition, abundance, and spatial heterogeneity of crusts with different disturbance histories. Microb. Ecol. 43, 1–12 (2002).CAS 
PubMed 
Article 

Google Scholar 
Langhans, T. M., Storm, C. & Schwabe, A. Community assembly of biological soil crusts of different successional stages in a temperate sand ecosystem, as assessed by direct determination and enrichment techniques. Microb. Ecol. 58, 394–407 (2009).PubMed 
Article 

Google Scholar 
Veluci, R. M., Neher, D. A. & Weicht, T. R. Nitrogen fixation and leaching of biological soil crust communities in mesic temperate soils. Microb. Ecol. 51, 189–196 (2006).CAS 
PubMed 
Article 

Google Scholar 
Cabała, J. & Rahmonov, O. Cyanophyta and algae as an important component of biological crust from the Pustynia Błędowska Desert (Poland). Pol. Bot. J. 49, 93–100 (2004).
Google Scholar 
Thiet, R. K., Boerner, R. E. J., Nagy, M. & Jardine, R. The effect of biological soil crusts on throughput of rainwater and N into Lake Michigan sand dune soils. Plant Soil 278, 235–251 (2005).CAS 
Article 

Google Scholar 
Jentsch, A. & Beyschlag, W. Vegetation ecology of dry acidic grasslands in the lowland area of Central Europe. Flora 198, 3–25 (2003).Article 

Google Scholar 
Dümig, A. et al. Organic matter from biological soil crusts induces the initial formation of sandy temperate soils. CATENA 122, 196–208 (2014).Article 
CAS 

Google Scholar 
Chamizo, S., Cantón, Y., Rodríguez-Caballero, E. & Domingo, F. Biocrusts positively affect the soil water balance in semiarid ecosystems. Ecohydrology 9, 1208–1221 (2016).Article 

Google Scholar 
Couradeau, E. et al. Bacteria increase arid-land soil surface temperature through the production of sunscreens. Nat. Commun. 7, 10373 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Eldridge, D. J. & Greene, R. S. B. Microbiotic soil crusts: a review of their roles in soil and ecological processes in the rangelands of Australia. Aust. J. Soil Res. 32, 389–415 (1994).Article 

Google Scholar 
Elbert, W. et al. Contribution of cryptogamic covers to the global cycles of carbon and nitrogen. Nat. Geosci. 5, 459–462 (2012).CAS 
Article 

Google Scholar 
Delgado-Baquerizo, M., Maestre, F. T., Rodríguez, J. G. P. & Gallardo, A. Biological soil crusts promote N accumulation in response to dew events in dryland soils. Soil Biol. Biochem. 62, 22–27 (2013).CAS 
Article 

Google Scholar 
Meron, E. From patterns to function in living systems: dryland ecosystems as a case study. Annu. Rev. Condens. Matter Phys. 9, 79–103 (2018).Article 

Google Scholar 
Rietkerk, M. et al. Self-organization of vegetation in arid ecosystems. Am. Nat. 160, 524–530 (2002).PubMed 
Article 

Google Scholar 
Meron, E. Vegetation pattern formation: the mechanisms behind the forms. Phys. Today 72, 30–36 (2019).Article 

Google Scholar 
Gandhi, P., Iams, S., Bonetti, S. & Silber, M. in Dryland Ecohydrology 2nd edn (eds D’Odorico, P. et al.) 469–509 (Springer, 2019).Rietkerk, M., Dekker, S. C., de Ruiter, P. C. & van de Koppel, J. Self-organized patchiness and catastrophic shifts in ecosystems. Science 305, 1926–1929 (2004).CAS 
PubMed 
Article 

Google Scholar 
Lejeune, O., Tlidi, M. & Couteron, P. Localized vegetation patches: a self-organized response to resource scarcity. Phys. Rev. E 66, 010901 (2002).CAS 
Article 

Google Scholar 
Belyea, L. R. & Lancaster, J. Inferring landscape dynamics of bog pools from scaling relationships and spatial patterns. J. Ecol. 90, 223–234 (2002).Article 

Google Scholar 
Eppinga, M. B. et al. Regular surface patterning of peatlands: confronting theory with field data. Ecosystems 11, 520–536 (2008).CAS 
Article 

Google Scholar 
Hiemstra, C. A., Liston, G. E. & Reiners, W. A. Observing, modelling, and validating snow redistribution by wind in a Wyoming upper treeline landscape. Ecol. Modell. 197, 35–51 (2006).Article 

Google Scholar 
Crain, C. M. & Bertness, M. D. Community impacts of a tussock sedge: is ecosystem engineering important in benign habitats? Ecology 86, 2695–2704 (2005).Article 

Google Scholar 
Stanton, D. E., Armesto, J. J. & Hedin, L. O. Ecosystem properties self-organize in response to a directional fog-vegetation interaction. Ecology 95, 1203–1212 (2014).PubMed 
Article 

Google Scholar 
van de Koppel, J., van der Wal, D., Bakker, J. P. & Herman, P. M. Self-organization and vegetation collapse in salt marsh ecosystems. Am. Nat. 165, E1–E12 (2005).PubMed 
Article 

Google Scholar 
Rietkerk, M. & van de Koppel, J. Regular pattern formation in real ecosystems. Trends Ecol. Evol. 23, 169–175 (2008).PubMed 
Article 

Google Scholar 
Aguiar, M. R. & Sala, O. E. Patch structure, dynamics and implications for the functioning of arid ecosystems. Trends Ecol. Evol. 14, 273–277 (1999).CAS 
PubMed 
Article 

Google Scholar 
Bera, B. K., Tzuk, O., Bennett, J. J. & Meron, E. Linking spatial self-organization to community assembly and biodiversity. eLife 10, e73819 (2021).Garcia-Moya, E. & McKell, C. M. Contribution of shrubs to the nitrogen economy of a desert-wash plant community. Ecology 51, 81–88 (1970).Article 

Google Scholar 
Peters, D. P. C. et al. Disentangling complex landscapes: new insights into arid and semiarid system dynamics. Bioscience 56, 491–501 (2006).Article 

Google Scholar 
Okin, G. S. et al. Connectivity in dryland landscapes: shifting concepts of spatial interactions. Front. Ecol. Environ. 13, 20–27 (2015).Article 

Google Scholar 
Ludwig, J. A., Wilcox, B. P., Breshears, D. D., Tongway, D. J. & Imeson, A. C. Vegetation patches and runoff–erosion as interacting ecohydrological processes in semiarid landscapes. Ecology 86, 288–297 (2005).Article 

Google Scholar 
Fahnestock, J. T., Povirk, K. L. & Welker, J. M. Ecological significance of litter redistribution by wind and snow in Arctic landscapes. Ecography 23, 623–631 (2000).Article 

Google Scholar 
Schlesinger, W. H. et al. Biological feedbacks in global desertification. Science 247, 1043–1048 (1990).CAS 
PubMed 
Article 

Google Scholar 
Okin, G. S., Sala, O. E., Vivoni, E. R., Zhang, J. & Bhattachan, A. The interactive role of wind and water in functioning of drylands: what does the future hold? Bioscience 68, 670–677 (2018).Article 

Google Scholar 
Finzi, A. C. et al. Responses and feedbacks of coupled biogeochemical cycles to climate change: examples from terrestrial ecosystems. Front. Ecol. Environ. 9, 61–67 (2011).Article 

Google Scholar 
Yuan, Z. Y. et al. Experimental and observational studies find contrasting responses of soil nutrients to climate change. eLife 6, e23255 (2017).Delgado-Baquerizo, M. et al. Decoupling of soil nutrient cycles as a function of aridity in global drylands. Nature 502, 672–676 (2013).CAS 
PubMed 
Article 

Google Scholar 
Jiao, F., Shi, X. R., Han, F. P. & Yuan, Z. Y. Increasing aridity, temperature and soil pH induce soil C-N-P imbalance in grasslands. Sci. Rep. 6, 19601 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wang, X.-G. et al. Changes in soil C:N:P stoichiometry along an aridity gradient in drylands of northern China. Geoderma 361, 114087 (2020).CAS 
Article 

Google Scholar 
Mulder, C. et al. Connecting the green and brown worlds: allometric and stoichiometric predictability of above- and below-ground networks. Adv. Ecol. Res. 49, 69–175 (2013).Article 

Google Scholar 
Yuan, Z. Y. & Chen, H. Y. H. Decoupling of nitrogen and phosphorus in terrestrial plants associated with global changes. Nat. Clim. Change 5, 465–469 (2015).CAS 
Article 

Google Scholar 
Rotenberg, E. & Yakir, D. Contribution of semi-arid forests to the climate system. Science 327, 451–454 (2010).CAS 
PubMed 
Article 

Google Scholar 
Banerjee, T., De Roo, F. & Mauder, M. Explaining the convector effect in canopy turbulence by means of large-eddy simulation. Hydrol. Earth Syst. Sci. 21, 2987–3000 (2017).Article 

Google Scholar 
Teuling, A. J. et al. Contrasting response of European forest and grassland energy exchange to heatwaves. Nat. Geosci. 3, 722–727 (2010).CAS 
Article 

Google Scholar 
Alkama, R. & Cescatti, A. Biophysical climate impacts of recent changes in global forest cover. Science 351, 600–604 (2016).CAS 
PubMed 
Article 

Google Scholar 
Zellweger, F. et al. Forest microclimate dynamics drive plant responses to warming. Science 368, 772–775 (2020).CAS 
PubMed 
Article 

Google Scholar 
Chen, C. et al. China and India lead in greening of the world through land-use management. Nat. Sustain. 2, 122–129 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Huang, K. et al. Enhanced peak growth of global vegetation and its key mechanisms. Nat. Ecol. Evol. 2, 1897–1905 (2018).De Jong, R., Verbesselt, J., Schaepman, M. E. & De Bruin, S. Trend changes in global greening and browning: contribution of short-term trends to longer-term change. Glob. Change Biol. 18, 642–655 (2012).Article 

Google Scholar 
Pan, N. et al. Increasing global vegetation browning hidden in overall vegetation greening: insights from time-varying trends. Remote Sens. Environ. 214, 59–72 (2018).Article 

Google Scholar 
Mueller, T. et al. Human land-use practices lead to global long-term increases in photosynthetic capacity. Remote Sens. 6, 5717–5731 (2014).Article 

Google Scholar 
Beck, P. S. A. et al. Changes in forest productivity across Alaska consistent with biome shift. Ecol. Lett. 14, 373–379 (2011).PubMed 
Article 

Google Scholar 
Myers-Smith, I. H. et al. Complexity revealed in the greening of the Arctic. Nat. Clim. Change 10, 106–117 (2020).Article 

Google Scholar 
Aguirre-Gutiérrez, J. et al. Drier tropical forests are susceptible to functional changes in response to a long-term drought. Ecol. Lett. 22, 855–865 (2019).PubMed 
Article 

Google Scholar 
Peñuelas, J. et al. Shifting from a fertilization-dominated to a warming-dominated period. Nat. Ecol. Evol. 1, 1438–1445 (2017).PubMed 
Article 

Google Scholar 
Stocker, B. D. et al. Drought impacts on terrestrial primary production underestimated by satellite monitoring. Nat. Geosci. 12, 264–270 (2019).CAS 
Article 

Google Scholar 
Berg, A., Sheffield, J. & Milly, P. C. D. Divergent surface and total soil moisture projections under global warming. Geophys. Res. Lett. 44, 236–244 (2017).Article 

Google Scholar 
Davenport, D. W., Breshears, D. D., Wilcox, B. P. & Allen, C. D. Viewpoint: sustainability of piñon-juniper ecosystems – a unifying perspective of soil erosion thresholds. J. Range Manage. 51, 231 (1998).Article 

Google Scholar 
Briske, D. D., Fuhlendorf, S. D. & Smeins, F. E. A unified framework for assessment and application of ecological thresholds. Rangel. Ecol. Manage. 59, 225–236 (2006).Article 

Google Scholar 
Kayler, Z. E. et al. Experiments to confront the environmental extremes of climate change. Front. Ecol. Environ. 13, 219–225 (2015).Article 

Google Scholar 
Haase, P. et al. The next generation of site-based long-term ecological monitoring: linking essential biodiversity variables and ecosystem integrity. Sci. Total Environ. 613–614, 1376–1384 (2018).PubMed 
Article 
CAS 

Google Scholar 
Halbritter, A. H. et al. The handbook for standardised field and laboratory measurements in terrestrial climate‐change experiments and observational studies (ClimEx). Methods Ecol. Evol. 11, 22–37 (2020).Article 

Google Scholar 
De Boeck, H. J. et al. Global change experiments: challenges and opportunities. Bioscience 65, 922–931 (2015).Article 

Google Scholar 
Kreyling, J. et al. To replicate, or not to replicate – that is the question: how to tackle nonlinear responses in ecological experiments. Ecol. Lett. 21, 1629–1638 (2018).De Boeck, H. J. et al. Understanding ecosystems of the future will require more than realistic climate change experiments – a response to Korell et al. Glob. Change Biol. 26, e6–e7 (2020).Article 

Google Scholar 
Hanson, P. J. & Walker, A. P. Advancing global change biology through experimental manipulations: where have we been and where might we go? Glob. Change Biol. 26, 287–299 (2020).Article 

Google Scholar 
Paschalis, A. et al. Rainfall manipulation experiments as simulated by terrestrial biosphere models: where do we stand? Glob. Change Biol. 26, 3336–3355 (2020).Article 

Google Scholar 
Scheffer, M., Carpenter, S. R., Foley, J. A., Folke, C. & Walker, B. Catastrophic shifts in ecosystems. Nature 413, 591–596 (2001).CAS 
PubMed 
Article 

Google Scholar 
Diaz, S. et al. Assessing nature’s contributions to people. Science 359, 270–272 (2018).CAS 
PubMed 
Article 

Google Scholar 
Thonicke, K. et al. Advancing the understanding of adaptive capacity of social‐ecological systems to absorb climate extremes. Earths Future 8, e2019EF001221 (2020). More

Effects of temperature on total daily locomotor activitiesTo understand the effect of temperature on the daily behavior of Drosophila species distributed in different temperature regions, we examined the daily locomotor activity at different temperatures in the following 11 sequenced Drosophila species: cosmopolitan (D. melanogaster and D. simulans), tropical (D. ananassae, D. erecta, D. yakuba, and D. sechellia), subtropical (D. willistoni and D. mojavensis), and temperate (D. persimilis, D. pseudoobscura, and D. virilis) species. Using the Drosophila Activity Monitor system25, we were able to analyze the amount of daily locomotor activity quantitatively at five experimental temperatures, i.e., 17 °C, 20 °C, 23 °C, 26 °C, and 29 °C. As the viability of the adults of D. persimilis and D. pseudoobscura was low at 29 °C, these two species were analyzed at only four experimental temperatures. First, we compared the amount of daily locomotor activities among these Drosophila species (Supplementary Fig. 1). The ranges of the total daily activity were quite diverse in these species (Kruskal–Wallis test: χ2 = 833.18, p  More

The pre-evaporitic, evaporitic, and post-evaporitic phases are recognized for the late Aptian. These phases are recorded within the K40–K50 sequences (Fig. 2A), and show an average maximum thickness of approximately 650 m in the studied basins. The pre-evaporitic phase is represented by carbonate and siliciclastic deposits formed in fluvial and lacustrine deltaic environments within a large proto-oceanic gulf28 (Fig. 2A). The peak of the evaporitic deposition is recorded in the K50 sequence, with widespread occurrences in the Brazilian equatorial margin. The origin of these deposits is the heat intensification associated with the widening of the Atlantic Ocean. These conditions caused strong evaporation leading to a wide distribution of evaporites (mainly halite and anhydrite gypsum) in the South Atlantic basins. The eastern continental margin of Brazil contains a restricted marine section characterized by evaporites, which are particularly prominent in thickness and occurrence in the Espírito Santo Basin (Itaúnas Member of the Mariricu Formation) and the Sergipe Basin (the Ibura Member of the Muribeca Formation)28. Evaporites form the most prominent evidence of dry climates in the South Atlantic basins11, with evaporation exceeding precipitation. The post-evaporitic phase is characterized by fully marine conditions evidenced by rich assemblages of marine fossils. During this phase, carbonates were deposited, followed by muddy and sandy sediments in shallow-marine and slope environments.Figure 2Paleoclimatic phases scheme and principal component analysis for paleoclimatic phases. (A) Paleoclimatic phases scheme for the late Aptian and the main depositional environments. (B) Principal component plot of bioclimatic groups. (C) Principal component for the pre-evaporitic phase (N = 92), evaporitic phase (N = 78), and post-evaporitic phase (N = 385); see Supplementary Fig. 9 for individual basins.Full size imagePaleovegetationWe identified a rich plant community with 139 spore and pollen genera/morphotypes representing all plant groups: bryophytes (five genera), ferns (58 genera), lycophytes (18 genera), pteridosperms (one genus), gymnosperms (27 genera), and angiosperms (30 genera) (Supplementary Table 2). The inferred systematic affinities at the family level reached 100% in bryophytes, 56.9% in ferns, 100% in lycophytes, 100% in pteridosperms, 92.6% in gymnosperms, and 40.0% in angiosperms, totaling 67.6% of the recorded genera (Supplementary Table 2). Marine elements (e.g., dinoflagellate cysts and microforaminiferal linings) were identified, in particular from the Sergipe and Araripe basins (Fig. 1). Pollen grains from gymnosperms were most abundant, represented mainly by the conifer families Cheirolepidiaceae, Araucariaceae, and Podocarpaceae, although representing different climatic settings. Classopollis (Cheirolepidiaceae) is the most abundant genus in all sections studied, followed by Araucariacites (Araucariaceae). Gymnosperms showed low diversity. Spore-producing plants are the most diverse in the assemblages of all basins (82 genera) and represented by several families of bryophytes, ferns, and lycophytes (e.g., Sphagnaceae, Anemiaceae, Cyatheaceae, Marsileaceae, Selaginellaceae, and Lycopodiaceae). These plant groups depend on water to reproduce and are therefore associated with humid settings.Cicatricosisporites (Anemiaceae) is the third most abundant palynomorph in all the basins, but especially in the northeastern basins (e.g., Sergipe Basin). Angiosperms are among the least abundant; however, they are diverse and include the most abundant and controversial genus Afropollis, herein attributed to angiosperms. In the most recent publication that addressed this question, ref.29 suggest that Afropollis should be treated as an angiosperm genus, although without more precise systematic assignment. The 30 genera/morphotypes of angiosperms are assigned to 8 families, viz., Arecaceae, Chloranthaceae, Euphorbiaceae, Flacourtiaceae, Illiciaceae, Liliaceae, Solanaceae and Trimeniaceae. The second most abundant genus is Stellatopollis also without precise systematic assignment.Spatio-temporal distribution of bioclimatic groupsOn the basis of their botanical affinities, most taxa were classified into five bioclimatic groups [see “Methods” section and Supplementary information], viz., hydrophytes, hygrophytes, tropical lowland flora, upland flora, and xerophytes (Supplementary Table 2) (Fig. 3).Figure 3Relevant palynomorphs of bioclimatic groups: (1) Aequitriradites sp.; (2) Crybelosporites sp.; (3) Perotriletes sp.; (4) Cicatricosisporites sp.; (5) Echinatisporis sp.; (6) Verrucosisporites sp.; (7) Bennettitaepollenites sp.; (8) Stellatopollis sp.; (9) Afropollis sp.; (10) Dejaxpollenites microfoveolatus; (11) Classopollis classoides; (12) Equisetosporites ovatus; (13) Gnetaceaepollenites jansonii; (14) Regalipollenites sp.; (15) Araucariacites sp.; (16) Callialasporites dampieri; (17) Complicatissacus cearensis; (18) Cyathidites sp.. Scale bar 20 µm.Full size imageOverall, the vegetation is dominated by the xerophytic bioclimatic group on account of the very high abundance of Classopollis (Cheirolepidiaceae) (general mean of 60.5%). However, the stratigraphic distribution of the bioclimatic groups in the sections studied (Supplementary Figs. 1–6) indicates wet phases confirmed by the curves of the other bioclimatic groups (hygrophytes, hydrophytes, tropical lowland flora, and upland flora). We used Pearson correlation analysis (Supplementary Fig. 7) to assess the correlation between the bioclimatic groups. The analysis revealed positive correlations between the bioclimatic groups of hygrophytes, hydrophytes, tropical lowland flora, and upland flora, and a negative correlation between these groups and the xerophyte group (Supplementary Fig. 7). The positive correlation between upland flora and hygrophytes confirms previous studies for the Sergipe Basin6,7, suggesting a relation between these groups and the hot and humid climate. The weak negative correlation between tropical lowland flora and upland flora is presumably related to elevation.The upland flora forms the second most abundant bioclimatic group, with an average of 18.9%. The large number of specimens of Araucariacites (Araucariaceae) in this group is notable. The hydrophytes are the least abundant group, with an average of only 1.4%. In this group, the highest values are attributed to the genus Crybelosporites (Marsileaceae).Principal component analyses (PCA) were used to reduce the multidimensional dataset, based on the percent abundance of the bioclimatic groups to a smaller number of dimensions for interpretive analysis. For all sections, two components or axes explain 97.6% of the observed variability (Fig. 2B). Hygrophytes, hydrophytes, tropical lowland flora, and upland flora show positive correlation (positive loading, 0.320, 0.029, 0.006, and 0.468, respectively), whereas xerophytes show a negative relationship (negative loading, − 0.823) on the first axis, which alone explains 83.0% of the variability. In summary, the first axis of the PCA reveals a separation of two major climatic conditions (wet and dry) along the axis (Fig. 2B). The wet conditions include the associations of hygrophytes, hydrophytes, tropical lowland flora, and upland flora, with dry conditions associated with taxa from the xerophyte group. The second axis explains 14.6%, in which hygrophytes, hydrophytes, and tropical lowland flora show a positive correlation relationship (positive loading, 0.719, 0.037, 0.036, respectively), whereas upland flora and xerophytes show a negative relationship (negative loading, − 0.684 and − 0.108, respectively). With respect to the second axis, a polarization between the hygrophytes (positive loading, 0.719) and the upland flora (negative loading, − 0.684) can be interpreted as a lowland–upland trend. The same pattern was recorded for all paleoclimatic phases (Fig. 2C) and sections (Supplementary Fig. 8), that is, the first axis is related to humidity vs. aridity, and the second axis to elevation (lowland vs. upland). This suggests that these two factors, particularly the first one, controlled the vegetation distribution in the late Aptian of the region. As all bioclimatic groups occurred in the three evaporitic phases, these trends in abundance reflect expansion and contraction of the recorded vegetation.Parallel increasing trends of bioclimatic groups mark the pre-evaporitic phase: hygrophytes and upland flora in the Bragança-Viseu, São Luís, Parnaíba, Ceará, Potiguar, and Araripe basins (Supplementary Figs. 1–3 and 5), suggesting that there was a certain amount of moisture in these areas. The xerophytes show the lowest average of this phase (44.1%) (Table 1), whereas hygrophytes show the highest average (27.0%). These humid conditions are confirmed by the highest mean of the Fs/X ratio (Fs/X = 0.4), representing the predominance of spore-producing plants [see Methods section and Supplementary information]. Despite the low abundance of hydrophytes in the sections, a prominent feature is the highest average (2.5%) of this group (Table 1), which is assigned to aquatic environments, confirming relatively wet conditions in this phase. There are no pre-evaporitic samples available from the Sergipe and Espírito Santo basins.Table 1 Average abundance of bioclimatic groups, diversity, Fs/X and marine elements for the paleoclimatic phases.Full size tableThe evaporitic phase is characterized by the highest abundance of the xerophyte bioclimatic group (76.4%) (Table 1), represented mainly by Classopollis (Supplementary Figs. 1–6). A high abundance of xerophytes occurred widely distributed in all basins studied. In this phase, tropical lowland flora is notable, showing an average higher than the overall average (3.3%), particularly in the Bragança-Viseu, São Luís, Parnaíba, and Ceará basins (Supplementary Figs. 1 and 2). This result is related to the moderate to high abundance of the genus Afropollis in these basins. The evaporitic phase is also characterized by the lowest average Fs/X ratio (Fs/X = 0.1) (Table 1), confirming the dominance of xerophytes.The post-evaporitic phase is characterized by the upland flora bioclimatic group (mean = 24.4%) (Table 1). The moderate to high abundance of upland flora in this phase is represented, in particular, by pollen grains of Araucariacites, which represent the high-relief family Araucariaceae. This bioclimatic group is associated with more humid conditions, as confirmed by an Fs/X ratio higher than the overall average (Fs/X = 0.2). The upland flora is significant in all basins, except the Espírito Santo Basin, where xerophytes predominate in both studied phases in this basin.Latitudinal biome distributionsBiome change is a fundamental biological response to climate change. In the study area, the predominance of a specific biome is mainly related to humidity, since all five recorded bioclimatic groups are related to a warm climate (Supplementary Table 2) representing two biomes: tropical xerophytic shrubland and tropical rainforest. In the rainforest biome two phytophysiognomies are recognized: lowland and montane rainforest. The tropical xerophytic shrubland biome predominates in the three paleoclimatic phases, with a wide latitudinal range from the Bragança-Viseu, São Luís, and Parnaíba basins (1° S) to the Espírito Santo Basin (20° S). This wide distribution is compatible with a predominantly arid climate in South America in the late Aptian, as indicated by paleoclimatic maps8,9,15 (Fig. 4A). Most arid and semi-arid ecosystems are mainly controlled by precipitation. Other climate parameters are less important, a condition that simplifies cause-effect interpretations. The PCA (Fig. 2B) demonstrated that the wet–dry trend, which reflects high–low precipitation, was the main determinant in the distribution of the biomes. However, considering all phases, an increasing trend in humidity was observed from the southeast (Espírito Santo Basin) to the northeast (e.g., Potiguar Basin) (Fig. 4B), coinciding with the hot and wet belt attributed to the ITCZ (Fig. 4A)15. The latitudinal distribution of diversity also follows this trend. Diversity increased significantly towards in the basins near the equator. Diversity indices (Shannon – H’) peaked in the Sergipe Basin (H’ = 3.5, CL-47 section) at 11° S. Conversely, the lowest average diversity is recorded in the Espírito Santo Basin (H’ = 1.1) at 20° S. Additionally, there is a clear correlation between high diversity (H’) and humidity (Fs/X ratio) (r = 0.691), regardless of paleoclimatic phase, as evidenced by the synchronicity of the H’ and Fs/X curves (Fig. 5). After data normalization between humidity (Fs/X) and marine elements (dinoflagellate cysts and microforaminifer linings), we performed linear correlation analyses, which showed a weak but positive correlation (r = 0.137). This is due to the fact that pre- evaporitic deposits contain only 19 occurrences of dinoflagellate cysts in 90 samples. Despite this, the curves of Fs/X, marine elements and diversity are synchronous (Fig. 5), suggesting a relation between humidity, diversity, and marine incursions.Figure 4Latitudinal changes in late Aptian biomes from southeast to center-north. (A) Paleoclimatic belts of the late Aptian in South America (climatic belts modified from refer.14). Reconstruction map at 116 Ma modified from ODSN Plate Tectonic Reconstruction Service. The Reconstruction map at 116 Ma was generated by ODSN Plate Tectonic Reconstruction Service (https://www.odsn.de/odsn/services/paleomap/paleomap.html). (B) Late Aptian latitudinal distribution of the tropical xerophytic biome in Brazil. (C) Stratigraphic distribution of biomes for individual basins. (D) Relative Importance of biomes for paleoclimatic phases.Full size imageFigure 5Biome trends in relation to paleoclimatic phases. Change in biomes, diversity, Fs/X ratio and marine elements shown by changepoint analysis plotted against paleoclimatic phases.Full size imageThe pre-evaporitic phase is marked by a certain balance between the biomes (Fig. 4C,D). In the lowlands, the tropical xerophytic shrubland biome predominated in the Bragança- Viseu, São Luís, Parnaíba, and Ceará basins, but in the Potiguar Basin it is co-dominant with the lowland rainforest. The montane rainforest was relatively extensive in this phase, although with several areal changes, and reached its widest extent in the Araripe (7° S) and Potiguar (5° S) basins in response to the deterioration of the tropical xerophytic shrubland biome. These conditions demonstrate that humidity was relatively high at this stage. The pre-evaporitic deposits were characterized by the highest diversity average (H’ = 1.8).The method of indicator species analysis (IndVal) was used to identify the key species of each paleoclimatic phase (Supplementary Table 15). The species identified for the pre-evaporitic phase, Deltoidospora spp. (Cyatheaceae-Dicksoniaceae) related to the montane rainforest, are indicator species for the Bragança-Viseu, São Luís, Parnaíba, and Ceará basins. The Gnetaceaepollenites spp. (Gnetaceae) of the Potiguar Basin and Equisetosporites spp. (Ephedraceae) of the Araripe Basin are related to the tropical xerophytic shrubland biome (Supplementary Table 15). Even for the pre-evaporitic phase, a progressive increase in the tropical xerophytic shrubland biome was observed and interpreted as the start of a climatic deterioration stage (Fig. 4C), which culminated in the evaporitic phase. Shifts in vegetation types may occur when precipitation reaches a threshold value, which means that a regionally synchronous gradual climate change can cause abrupt vegetation shifts. The change from humid to warm and arid conditions (evaporitic phase) is directly related to a decrease in precipitation. This aridization process coincides with the appearance of marine elements (e.g., dinoflagellate cysts). The threshold effect (intense evaporation) is reflected in an abrupt decrease in the abundance of lowland and montane rainforest and a sharp increase to a very high abundance of the tropical xerophytic shrubland biome (Supplementary Figs. 4C and 5). The threshold effect was not detected in the Espírito Santo Basin, where the arid conditions remained stable with minimal shift (expansion and contraction) of the biome. The main representatives of this biome are conifers of the family Cheirolepidiaceae (Classopollis), which were most abundant in lagoons and coastal environments and are often associated with evaporates30,31,32,33,34,35. Even under xeric or water-stressed conditions there was a slight increase in biomes related to a humid climate (lowland and montane rainforest phytophysiognomies) towards the equatorial region, suggesting influence of the ITCZ (Fig. 4A,B).The evaporitic phase was characterized by the lowest diversity average (H’ = 1.2). With modest rainfall, arid regions are generally characterized by fewer species than moister biomes36. However, diversity indices peaked in the Bragança-Viseu, São Luís, and Parnaíba basins (H’ = 2.6, RL-01 section) and along the equatorial margin (2° S) (Supplementary Fig. 1).IndVal emphasizes the xeric conditions in the evaporitic phase by association with the species from the tropical xerophytic shrubland biome: Classopollis spp. (Ceará and Potiguar basins), Classopollis classoides (Sergipe Basin), Classopollis intrareticulatus (Araripe Basin), and Gnetaceaepollenites spp. (Espírito Santo Basin). For the Bragança-Viseu, São Luís, Parnaíba, and Ceará basins, where xeric restrictions are milder, the indicator taxon is Afropollis spp. from the lowland rainforest. This genus shows the weakest negative correlation with xerophytes.After the end of evaporite deposition, all sections indicate climatic stability, which kept the climate hot and arid even in the post-evaporitic phase, although the response was not linear.The shift in the biomes, especially the tropical xerophytic shrubland in the Bragança-Viseu, São Luís, Parnaíba, Ceará, and Araripe basins, occurred in the transition between the evaporitic and post-evaporitic phases, whereas in the Potiguar and Sergipe basins it occurred within the post-evaporitic phase. As indicated in the dendrograms of each section (Supplementary Figs. 1–6), the shift occurred abruptly in all basins, except the Espírito Santo Basin. The tropical rainforest biome (lowland and montane rainforests) replaced the tropical xerophytic shrubland in almost all basins (Fig. 4C). Even the Espírito Santo Basin, far from the influence of the ITCZ, shows a slight increase in lowland rainforest. The changes in the biomes are attributable to threshold effects caused by gradual climate change related to the ITCZ intensification shift and progressive increase in marine influence, indicated by an increase in marine microplankton from an average of 3.9% in the evaporitic phase to 44.1%. The increase in marine influence is reflected in the first major flooding surface observed in the Cretaceous succession27. Thus, a climate amelioration stage was established in the post- evaporitic phase (Fig. 5). In combination with published paleotopographic information25, the bioclimatic groups associated to the humid conditions (hygrophytes, hydrophytes, tropical lowland flora, and upland flora) were combined and visualized to create Fig. 6.Figure 6Reconstruction of the transitional gradient between marine to terrestrial environment (uplands) under ITCZ influence. The illustration is based on paleoflora and environmental information from palynological data from studied sections. Original size illustration: 18 × 24 cm, by Julio Lacerda.Full size imageAccording to refs.7,37, arid conditions are characterized by sea-level lowstands, whereas warm and humid conditions are correlated with sea levels rise, which explains the increase in the tropical rainforest biome (lowland and montane rainforests). The more intense humidity is supported by the results of IndVal for the post-evaporitic phase, with all species related to humid climate: Deltoidospora spp. (Bragança-Viseu, São Luís and Parnaíba basins), Araucariacites limbatus (Ceará Basin), Cicatricosisporites spp. (Potiguar Basin), Cicatricosisporites spp. and Araucariacites australis (Sergipe Basin), Inaperturopollenites spp. (Araripe Basin) and Inaperturopollenites simplex (Espírito Santo Basin).Our results show that the ITCZ combined with the opening of the South Atlantic Ocean during the late Aptian altered vegetation dynamics. As today, the ITCZ influence is stronger in the northeastern and north-central regions of South America. It is notable that the late Aptian climate evolution in the South Atlantic, culminating in higher humidity, was accompanied by an intrinsic relation between plant diversity, humidity, and marine influence. More

Hand, S.C. Metabolic dormancy in aquatic invertebrates. In Advances in Comparative and Environmental Physiology, Vol. 8 (ed. Gilles, R.) 1–50. https://doi.org/10.1007/978-3-642-75900-0_1 (1991).Cáceres, C. E. Dormancy in Invertebrates. Invertebr. Biol. 116(4), 371–383. https://doi.org/10.2307/3226870 (1997).Article 

Google Scholar 
Wilsterman, K., Ballinger, M. A. & Williams, C. M. A unifying, eco-physiological framework for animal dormancy. Funct. Ecol. 35, 11–31. https://doi.org/10.1111/1365-2435.13718 (2021).Article 

Google Scholar 
Bertolani, R., Guidetti, R., Altiero, T., Nelson, D. R. & Rebecchi, L. Dormancy in Freshwater Tardigrades. In Dormancy in Aquatic Organisms. Theory, Human Use and Modeling. Monographiae Biologicae Vol. 92 (eds Alekseev, V. & Pinel-Alloul, B.) (Springer, Cham, 2019). https://doi.org/10.1007/978-3-030-21213-1_3.Chapter 

Google Scholar 
Guidetti, R., Altiero, T. & Rebecchi, L. On dormancy strategies in tardigrades. J. Insect Physiol. 57(5), 567–576. https://doi.org/10.1016/j.jinsphys.2011.03.003 (2011).CAS 
Article 
PubMed 

Google Scholar 
Hahn, D. A. & Denlinger, D. L. Energetics of insect diapause. Annu. Rev. Entomol. 56, 103–121. https://doi.org/10.1146/annurev-ento-112408-085436 (2011).CAS 
Article 
PubMed 

Google Scholar 
Ragland, G. J. & Keep, E. Comparative transcriptomics support evolutionary convergence of diapause responses across Insecta. Physiol. Entomol. 42(3), 246–256. https://doi.org/10.1111/phen.12193 (2017).CAS 
Article 

Google Scholar 
Wang, Y., Ezemaduka, A. N., Tang, Y. & Chang, Z. Understanding the mechanism of the dormant dauer formation of C. elegans: From genetics to biochemistry. IUBMB Life 61(6), 607–12. https://doi.org/10.1002/iub.211 (2009).CAS 
Article 
PubMed 

Google Scholar 
Dias, I. B., Bouma, H. R. & Henning, R. H. Unraveling the big sleep: Molecular aspects of stem cell dormancy and hibernation. Front. Physiol. 12, 624950. https://doi.org/10.3389/fphys.2021.624950 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Storey, K. B. & Storey, J. M. Metabolic regulation and gene expression during aestivation. Prog. Mol. Subcell. Biol. 49, 25–45. https://doi.org/10.1007/978-3-642-02421-4_2 (2010).CAS 
Article 
PubMed 

Google Scholar 
Hand, S. C., Denlinger, D. L., Podrabsky, J. E. & Roy, R. Mechanisms of animal diapause: Recent developments from nematodes, crustaceans, insects, and fish. Am. J. Physiol. Regul. Integr. Comp. Physiol. 310(11), R1193–R1211. https://doi.org/10.1152/ajpregu.00250.2015 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Ikeda, H., Ohtsu, K. & Uye, S. I. Fine structure, histochemistry, and morphogenesis during excystment of the podocysts of the giant jellyfish Nemopilema nomurai (Scyphozoa, Rhizostomeae). Biol. Bull. 221(3), 248–260 (2011).PubMed 
Article 

Google Scholar 
Bushnell, J. H. & Rao, K. S. Dormant or quiescent stages and structures among the Ectoprocta: Physical and chemical factors affecting viability and germination of statoblasts. Trans. Am. Microsc. Soc. 93, 524–543. https://doi.org/10.2307/3225156 (1974).Article 

Google Scholar 
Hyman, L. H. The Invertebrates: Acanthocephala, Aschelminthes and Entoprocta Vol. III (McGraw-Hill, 1951).
Google Scholar 
Mukai, H. & Toshiki, M. Studies on the regeneration of an entoproct, Barentsia discreta. J. Exp. Zool. 205(2), 261–276. https://doi.org/10.1002/jez.1402050210 (1978).Article 

Google Scholar 
Nakauchi, M. Asexual development of ascidians: Its biological significance, diversity, and morphogenesis. Am. Zool. 22(4), 753–763. https://doi.org/10.1093/icb/22.4.753 (1982).Article 

Google Scholar 
Hyams, Y., Paz, G., Rabinowitz, C. & Rinkevich, B. Insights into the unique torpor of Botrylloides leachi, a colonial urochordate. Dev. Biol. 428(1), 101–117. https://doi.org/10.1016/j.ydbio.2017.05.020 (2017).CAS 
Article 
PubMed 

Google Scholar 
Brown, C. J. D. A limnological study of certain fresh-water Polyzoa with special reference to their statoblasts. Trans. Am. Microsc. Soc. 52, 271–313 (1933).CAS 
Article 

Google Scholar 
Mukai, H. Development of freshwater bryozoans (Phylactolaemata). In Developmental Biology of Freshwater Invertebrates (eds Harrison, R. W. & Cowden, R. R.) 535–576 (Alan R. Liss Inc., 1982).
Google Scholar 
Wood, T. S. Phyla ectoprocta and entoprocta (Bryozoans). In Freshwater Invertebrates (eds Thorp, J. H. & Covich, A. P.) 327–345 (Academic Press, 2015). https://doi.org/10.1016/B978-0-12-385026-3.00016-4.Chapter 

Google Scholar 
Simpson, T. L. The Cell Biology of Sponges (Springer, New York, 1984). https://doi.org/10.1007/978-1-4612-5214-6.Book 

Google Scholar 
Alié, A., Hiebert, L. S., Scelzo, M. & Tiozzo, S. The eventful history of nonembryonic development in tunicates. J. Exp. Zool. Part B Mol. Dev. Evol. 33(3), 181–217. https://doi.org/10.1002/jez.b.22940 (2020).Article 

Google Scholar 
Brown, F. D. & Swalla, B. J. Evolution and development of budding by stem cells: Ascidian coloniality as a case study. Dev. Biol. 3692, 151–162 (2012).Article 
CAS 

Google Scholar 
Kawamura, K. & Fujiwara, S. Cellular and molecular characterization of transdifferentiation in the process of morphallaxis of budding tunicates. Semin. Cell Biol. 6, 117–126 (1995).CAS 
PubMed 
Article 

Google Scholar 
Kassmer, S. H., Langenbacher, A. D. & De Tomaso, A. W. Integrin-alpha-6+ candidate stem cells are responsible for whole body regeneration in the invertebrate chordate Botrylloides diegensis. Nat. Commun. 11(1), 4435–4511. https://doi.org/10.1038/s41467-020-18288-w (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Freeman, G. The role of blood cells in the process of asexual reproduction in the tunicate Perophora viridis. J. Exp. Zool. 156, 157–183 (1964).CAS 
PubMed 
Article 

Google Scholar 
Kürn, U., Rendulic, S., Tiozzo, S. & Lauzon, R. J. Asexual propagation and regeneration in colonial ascidians. Biol. Bull. 221(1), 43–61. https://doi.org/10.1086/BBLv221n1p43 (2011).Article 
PubMed 

Google Scholar 
Sköld, H. N., Obst, M., Sköld, M. & Åkesson, B. Stem cells in asexual reproduction of marine invertebrates. In Stem Cells in Marine Organisms (eds Rinkevich, B. & Matranga, V.) 105–137 (Springer, Dordrecht, 2009).Chapter 

Google Scholar 
Tiozzo, S., Brown, F. D. & De Tomaso, A. W. Regeneration and stem cells in ascidians. In Stem Cells (ed. Bosch, T. C. G.) (Springer, Dordrecht, 2008). https://doi.org/10.1007/978-1-4020-8274-0_6.Chapter 

Google Scholar 
Mukai, H., Koyama, H. & Watanabe, H. Studies on the reproduction of three species of Perophora (Ascidiacea). Biol. Bull. 164(2), 251–266 (1983).Article 

Google Scholar 
Huxley, J. Memoirs: studies in dedifferentiation: II. Dedifferentiation and resorption in Perophora. Q. J. Microsc. Sci. s2-65(260), 643–697 (1921).
Google Scholar 
Huxley, J. Studies in dedifferentiation. VI. Reduction phenomena in Clavelina lepadiformis. Pubb. Staz. Zool. Napoli. 7, 1–34 (1926).
Google Scholar 
Turon, X. Periods of nonfeeding in Polysyncraton-lacazei (Ascidiacea, Didemnidae)—A process. Mar. Biol. 112, 647–655 (1992).Article 

Google Scholar 
Delsuc, F. et al. A phylogenomic framework and timescale for comparative studies of tunicates. BMC Biol. 16, 39 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Giard, M. A. & Caullery, M. On the hibernation of Clavelina lepadiformis, Müller. Ann. Mag. Nat. Hist. 18(108), 485–486. https://doi.org/10.1080/00222939608680499 (1896).Article 

Google Scholar 
Orton, J. H. The production of living Clavellina Zooids in winter by experiment. Nature 107, 75. https://doi.org/10.1038/107075a0 (1921).ADS 
Article 

Google Scholar 
Della, Valle P. Studii sui rapporti fra differenziazione e rigenerazione. 4. Bollettino Della Società Dei Naturalisti in Napoli 7, 1–37 (1915).
Google Scholar 
Scelzo, M. et al. Novel budding mode in Polyandrocarpa zorritensis: a model for comparative studies on asexual development and whole body regeneration. EvoDevo https://doi.org/10.1186/s13227-019-0121-x (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Berrill, N. J. Regeneration and budding in tunicates. Biol. Rev. 26, 456–475. https://doi.org/10.1111/j.1469-185X.1951.tb01207.x/full (1951).Article 

Google Scholar 
Kilpatrick, K. A., Podestá, G. P. & Evans, R. Overview of the NOAA/NASA advanced very high resolution radiometer Pathfinder algorithm for sea surface temperature and associated matchup database. J. Geophys. Res. 106(C5), 9179–9197. https://doi.org/10.1029/1999JC000065 (2001).ADS 
Article 

Google Scholar 
Berrill, N. J. & Cohen, A. Regeneration in Clavelina lepadiformis. J. Exp. Biol. 13(3), 352–362. https://doi.org/10.1242/jeb.13.3.352 (1936).Article 

Google Scholar 
Jiménez-Merino, J. et al. Putative stem cells in the hemolymph and in the intestinal submucosa of the solitary ascidian Styela plicata. EvoDevo https://doi.org/10.1186/s13227-019-0144-3 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Du, Q., Luu, P.-L., Stirzaker, C. & Clark, S. J. Methyl-CpG-binding domain proteins: Readers of the epigenome. Epigenomics UK 7, 1051–1073 (2015).CAS 
Article 

Google Scholar 
Rea, S. & Akhtar, A. MSL proteins and the regulation of gene expression. In DNA Methylation: Development, Genetic Disease and Cancer: Current Topics in Microbiology and Immunology Vol. 310 (eds Doerfler, W. & Böhm, P.) (Springer, 2006). https://doi.org/10.1007/3-540-31181-5_7.Chapter 

Google Scholar 
Orton, J. H. Preliminary account of a contribution to an evaluation of the sea. J. Mar. Biol. Assoc. UK 10(2), 312–326. https://doi.org/10.1017/S0025315400007815 (1914).Article 

Google Scholar 
Mukai, H. Histological and histochemical studies of two compound ascidians, Clavelina lepadiformis and Diazona violacea, with special reference to the trophocytes, ovary and pyloric gland. Sci. Rep. Fac. Educ. Gunma Univ. 26, 37–77 (1977).
Google Scholar 
de Caralt, S., López-Legentil, S., Tarjuelo, I., Uriz, M. J. & Turon, X. Contrasting biological traits of Clavelina lepadiformis (Ascidiacea) populations from inside and outside harbours in the western Mediterranean. Mar. Ecol. Prog. Ser. 244, 125–137 (2002).ADS 
Article 

Google Scholar 
Turon, X. A new mode of colony multiplication by modified budding in the ascidian Clavelina gemmae n. sp. (Clavelinidae). Invertebr. Biol. 124(3), 273–283. https://doi.org/10.1111/j.1744-7410.2005.00025.x (2005).Article 

Google Scholar 
Pyo, J. & Shin, S. A new record of invasive alien colonial tunicate Clavelina lepadiformis (Ascidiacea: Aplousobranchia: Clavelinidae) in Korea. Anim. Syst. Evol. Divers. 27, 197–200 (2011).Article 

Google Scholar 
Reinhardt, J. et al. First record of the non-native light bulb tunicate Clavelina lepadiformis (Müller, 1776) in the northwest Atlantic. Aquat. Invasions 5(2), 185–190. https://doi.org/10.3391/ai.2010.5.2.09 (2010).Article 

Google Scholar 
Turon, X., Tarjuelo, I., Duran, S. & Pascual, M. Characterising invasion processes with genetic data: An Atlantic clade of Clavelina lepadiformis (Ascidiacea) introduced into Mediterranean harbours. Hydrobiologia 503(1–3), 29–35. https://doi.org/10.1023/b:hydr.0000008481.10705.c2 (2003).Article 

Google Scholar 
Van Name, W. G. The North and South American ascidians. Bull. Am. Mus. Nat. Hist. 84, 1–476 (1945).
Google Scholar 
Carman, M. et al. Ascidians at the Pacific and Atlantic entrances to the Panama Canal. Aquat. Invasions 6(4), 371–380. https://doi.org/10.3391/ai.2011.6.4.02 (2011).Article 

Google Scholar 
Holman, L. E. et al. Managing human-mediated range shifts: Understanding spatial, temporal and genetic variation in marine non-native species. Philos. Trans. R. Soc. B 377, 20210025 (2022).CAS 
Article 

Google Scholar 
Lambert, C. C. & Lambert, G. Persistence and differential distribution of nonindigenous ascidians in harbors of the Southern California Bight. Marine Ecology Progress Series 259, 145–161. https://doi.org/10.3354/meps259145 (2003).ADS 
Article 

Google Scholar 
Brunetti, R. Polyandrocarpa zorritensis (Van Name, 1931). A colonial ascidian new to the Mediterranean record. Vie et Milieu 28–29, 647–652 (1978).
Google Scholar 
Brunetti, R. & Mastrototaro, F. The non-indigenous stolidobranch ascidian Polyandrocarpa zorritensis in the Mediterranean: Description, larval morphology and pattern of vascular budding. Zootaxa 528, 1–8 (2004).Article 

Google Scholar 
Mastrototaro, F., D’Onghia, G. & Tursi, A. Spatial and seasonal distribution of ascidians in a semi-enclosed basin of the Mediterranean Sea. J. Mar. Biol. Assoc. UK 88, 1053–1061 (2008).Article 

Google Scholar 
Stabili, L., Licciano, M., Longo, C., Lezzi, M. & Giangrande, A. The Mediterranean non- indigenous ascidian Polyandrocarpa zorritensis: Microbiological accumulation capability and environmental implications. Mar. Pollut. Bull. 101, 146–152 (2015).CAS 
PubMed 
Article 

Google Scholar 
Turon, X. & Becerro, M. A. Growth and survival of several ascidian species from the northwestern Mediterranean. Mar. Ecol. Prog. Ser. 82, 235–247 (1992).ADS 
Article 

Google Scholar 
Sumida, P. Y. G. et al. Pressure tolerance of tadpole larvae of the Atlantic ascidian Polyandrocarpa zorritensis: Potential for deep-sea invasion. Braz. J. Oceanogr. 63, 515–520 (2015).Article 

Google Scholar 
Vázquez, E. & Young, C. M. Responses of compound ascidian larvae to haloclines. Mar. Ecol. Prog. Ser. 133, 179–190 (1996).ADS 
Article 

Google Scholar 
Vázquez, E. & Young, C. M. Ontogenetic changes in phototaxis during larval life of the Ascidian Polyandrocarpa zorritensis (Van Name, 1931). J. Exp. Mar. Biol. Ecol. 231, 267–277 (1998).Article 

Google Scholar 
Brien, P. & Brien-Gavage, E. Contribution à l’étude de la Blastogénèse des Tuniciers: III: Bourgeonnement de Clavelina Lepadiformis Müller. Recueil de L’Institut Zoologique Torley-Rousseau 1–56 (1927).Fujimoto, H. & Watanabe, H. The characterization of granular amoebocytes and their possible roles in the asexual reproduction of the polystyelid ascidian, Polyzoa vesiculiphora. J. Morphol. 150(3), 623–637. https://doi.org/10.1002/jmor.1051500303 (1976).Article 
PubMed 

Google Scholar 
Cima, F., Franchi, N. & Ballarin, L. Origin and functions of tunicate hemocytes. In The Evolution of the Immune System (ed. Malagoli, D.) 29–49 (Elsevier, 2016). https://doi.org/10.1016/B978-0-12-801975-7/00002-5.Chapter 

Google Scholar 
Kerb, H. Biologische Beiträge zur Frage der Überwinterung der Ascidien. Arch. Mikrosk. Anat. 72(1), 386–414 (1908).Article 

Google Scholar 
Driesch, H. Studien über das Regulationsvermögen de Organismen. 6. Die Restitutionen der Clavellina lepadiformis. Arch. F. Entw.-Mech. 14, 247–287 (1902).Article 

Google Scholar 
Schultz, E. Über Reductionen. III. Die Reduction und Regeneration des abgeschnitten Kiemenkorbes von Clavellina lepadiformis. Arch. Entw. Mech. Org. 24, 503–523 (1907).
Google Scholar 
Spek, J. Über die Winterknospenentwicklung, Regeneration und Reduktion bei Clavellina lepadiformis und die Bedeutung besonderer “omnipotenter” Zellelemente für diese Vorgänge. Wilhelm Roux’Archiv Entwicklungsmechanik der Org 111(119), 172 (1927).
Google Scholar 
Brien, P. Contribution à l’étude de la régéneration naturelle et expérimentale chez les Clavelinidae. Soc. R. Zool. Belg. Ann LXI, 19–112 (1930).
Google Scholar 
Ries, E. Die Tropfenzellen und ihre Bedeutung für die Tunicabildung bei Clavelina. Wilhelm Roux Arch. Entwickl. Mech. Org. 137(3), 363–371. https://doi.org/10.1007/BF00593066 (1937).Article 
PubMed 

Google Scholar 
Fischer, I. Über das Verhalten des stolonialen Gewebes der Ascidie Clavelina lepadiformis in vitro. Wilhelm Roux Arch. Entwickl. Mech. Org. 137(3), 383–403. https://doi.org/10.1007/BF00593068 (1937).Article 
PubMed 

Google Scholar 
Seelinger, O. Eibildung und Knospung von Clavelina lepadiformis. Sitzungsber. d. Kais. Kgl. Acad. d. Wiss 1–56 (1882).Van Beneden, E. & Julin, C. Recherches sur la morphologie des tuniciers. Arch. Biol. 6, 237–476 (1886).
Google Scholar 
Garstang, W. Memoirs: The morphology of the Tunicata, and its bearings on the phylogeny of the Chordata. J. Cell Sci. 1928(2), 51–187 (1928).Article 

Google Scholar 
Kimura, K. D., Tissenbaum, H. A., Liu, Y. X. & Ruvkun, G. daf-2, an insulin receptor-like gene that regulates longevity and diapause in Caenorhabditis elegans. Science 277, 942–946 (1997).CAS 
PubMed 
Article 

Google Scholar 
Ogawa, A. & Brown, F. Dauer formation and dauer-specific behaviours in Pristionchus pacificus. In Pristionchus pacificus—A nematode model for comparative and evolutionary biology (ed. Sommer, R. J.) (Brill, 2015). https://doi.org/10.1163/9789004260306_011.Chapter 

Google Scholar 
Wisdom, R. AP-1: One switch for many signals. Exp. Cell Res. 253(1), 180–185. https://doi.org/10.1006/excr.1999.4685 (1999).CAS 
Article 
PubMed 

Google Scholar 
Karin, M., Liu, Z. & Zandi, E. AP-1 function and regulation. Curr. Opin. Cell Biol. 9, 240–246 (1997).CAS 
PubMed 
Article 

Google Scholar 
Srivastava, M. Beyond casual resemblances: rigorous frameworks for comparing regeneration across species. Annu. Rev. Cell Dev. Biol. 37, 1–26 (2021).Article 
CAS 

Google Scholar 
Alié, A. et al. Convergent acquisition of nonembryonic development in styelid ascidians. Mol. Biol. Evol. 35, 1728–1743. https://doi.org/10.1093/molbev/msy068 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Wang, W., Razy-Krajka, F., Siu, E., Ketcham, A. & Christiaen, L. NK4 antagonizes Tbx1/10 to promote cardiac versus pharyngeal muscle fate in the ascidian second heart field. PLoS Biol. 11, 1. https://doi.org/10.1371/journal.pbio.1001725 (2013).CAS 
Article 

Google Scholar 
Prünster, M. M., Ricci, L., Brown, F. D. & Tiozzo, S. Modular co-option of cardiopharyngeal genes during non-embryonic myogenesis. EvoDevo https://doi.org/10.1186/s13227-019-0116-7 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Kawamura, K., Shiohara, M., Kanda, M. & Fujiwara, S. Retinoid X receptor-mediated transdifferentiation cascade in budding tunicates. Dev. Biol. 384, 343–355 (2013).CAS 
PubMed 
Article 

Google Scholar 
Rinkevich, Y., Paz, G., Rinkevich, B. & Reshef, R. Systemic bud induction and retinoic acid signaling underlie whole body regeneration in the urochordate Botrylloides leachi. PLoS Biol. 5, e71. https://doi.org/10.1371/journal.pbio.0050071 (2007).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Song, L. & Florea, L. Rcorrector: Efficient and accurate error correction for Illumina RNA-seq reads. GigaScience. 4(1), 48. https://doi.org/10.1186/s13742-015-0089-y (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Krueger, F. Trim Galore!: A wrapper tool around Cutadapt and FastQC to consistently apply quality and adapter trimming to FastQ files. http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ (2015).Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17(1), 10–12. https://doi.org/10.14806/ej.17.1.200 (2011).Article 

Google Scholar 
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9(4), 357–359. https://doi.org/10.1038/nmeth.1923 (2012).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Andrews, S. FastQC: A quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc (2010).Grabherr, M. G. et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 29, 644–652. https://doi.org/10.1038/nbt.1883 (2011).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Laetsch, D. R. & Blaxter, M. L. BlobTools: Interrogation of genome assemblies. F1000Research 6, 1287. https://doi.org/10.12688/f1000research.12232.1 (2017).Article 

Google Scholar 
Li, W. & Godzik, A. Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22(13), 1658–1659. https://doi.org/10.1093/bioinformatics/btl158 (2006).CAS 
Article 
PubMed 

Google Scholar 
Seppey, M., Manni, M. & Zdobnov, E. M. BUSCO: Assessing genome assembly and annotation completeness. In Gene prediction (ed. Kollmar, M.) 227–245 (Humana, New York, 2019). https://doi.org/10.1007/978-1-4939-9173-0_14.Chapter 

Google Scholar 
Buchfink, B., Reuter, K. & Drost, H. G. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat. Methods 18, 366–368. https://doi.org/10.1038/s41592-021-01101-x (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
The UniProt Consortium. UniProt: The universal protein knowledgebase in 2021. Nucleic Acids Res. 49(D1), D480–D489. https://doi.org/10.1093/nar/gkaa1100 (2021).CAS 
Article 

Google Scholar 
Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34(5), 525–527. https://doi.org/10.1038/nbt.3519 (2016).CAS 
Article 
PubMed 

Google Scholar 
Law, C. W., Chen, Y., Shi, W. & Smyth, G. K. voom: Precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 15(2), 1–17. https://doi.org/10.1186/gb-2014-15-2-r29 (2014).CAS 
Article 

Google Scholar 
Chen, H. & Boutros, P. C. VennDiagram: A package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinform. 12(1), 35. https://doi.org/10.1186/1471-2105-12-35 (2011).Article 

Google Scholar 
Kanehisa, M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 28, 1947–1951. https://doi.org/10.1002/pro.3715 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28(1), 27–30. https://doi.org/10.1093/nar/28.1.27 (2000).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Kanehisa, M., Furumichi, M., Sato, Y., Ishiguro-Watanabe, M. & Tanabe, M. KEGG: Integrating viruses and cellular organisms. Nucleic Acids Res 49(D1), D545–D551. https://doi.org/10.1093/nar/gkaa970 (2021).CAS 
Article 
PubMed 

Google Scholar 
Huang, D. W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4(1), 44–57 (2009).CAS 
Article 

Google Scholar 
Huang, D. W., Sherman, B. T. & Lempicki, R. A. Bioinformatics enrichment tools: Paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37(1), 1–13 (2009).Article 
CAS 

Google Scholar  More

Ogle K, Barber JJ, Barron-Gafford GA, Bentley LP, Young JM, Huxman TE, et al. Quantifying ecological memory in plant and ecosystem processes. Ecol Lett. 2015;18:221–35.PubMed 
Article 

Google Scholar 
Schweiger AH, Boulangeat I, Conradi T, Davis M, Svenning JC. The importance of ecological memory for trophic rewilding as an ecosystem restoration approach. Biol Rev. 2019;94:1–15.Article 

Google Scholar 
Webster CR, Dickinson YL, Burton JI, Frelich LE, Jenkins MA, Kern CC, et al. Promoting and maintaining diversity in contemporary hardwood forests: confronting contemporary drivers of change and the loss of ecological memory. Ecol Manag. 2018;421:98–108.Article 

Google Scholar 
Hughes TP, Kerry JT, Connolly SR, Baird AH, Eakin CM, Heron SF, et al. Ecological memory modifies the cumulative impact of recurrent climate extremes. Nat Clim Change. 2019;9:40–43.Article 

Google Scholar 
Stockwell SR, Landry CR, Rifkin SA. The yeast galactose network as a quantitative model for cellular memory. Mol Biosyst. 2015;11:28–37.PubMed 
Article 
CAS 

Google Scholar 
Wolf DM, Fontaine-Bodin L, Bischofs I, Price G, Keasling J, Arkin AP. Memory in microbes: quantifying history-dependent behavior in a bacterium. PLoS ONE. 2008;3:e1700.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Lyon P. The cognitive cell: bacterial behavior reconsidered. Front Microbiol. 2015;6:264.PubMed 
PubMed Central 
Article 

Google Scholar 
Smith MB, Rocha AM, Smillie CS, Olesen SW, Paradis C, Wu L, et al. Natural bacterial communities serve as quantitative geochemical biosensors. mBio. 2015;6:e00326–15.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Cordeiro MC, Garcia GD, Rocha AM, Tschoeke DA, Campeão ME, Appolinario LR, et al. Insights on the freshwater microbiomes metabolic changes associated with the world’s largest mining disaster. Sci Total Environ. 2019;654:1209–17.PubMed 
Article 
CAS 

Google Scholar 
Kuster SP, Rudnick W, Shigayeva A, Green K, Baqi M, Gold WL, et al. Previous antibiotic exposure and antimicrobial resistance in invasive pneumococcal disease: results from prospective surveillance. Clin Infect Dis. 2014;59:944–52.PubMed 
Article 
CAS 

Google Scholar 
Carmody RN, Gerber GK, Luevano JM, Gatti DM, Somes L, Svenson KL, et al. Diet dominates host genotype in shaping the murine gut microbiota. Cell Host Microbe. 2015;17:72–84.PubMed 
Article 
CAS 

Google Scholar 
David LA, Weil A, Ryan ET, Calderwood SB, Harris JB, Chowdhury F, et al. Gut microbial succession follows acute secretory diarrhea in humans. mBio. 2015;6:e00381–15.PubMed 
PubMed Central 

Google Scholar 
Stacy A, Andrade-Oliveira V, McCulloch JA, Hild B, Oh JH, Perez-Chaparro PJ, et al. Infection trains the host for microbiota-enhanced resistance to pathogens. Cell. 2021;184:615–27.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Thaiss CA, Itav S, Rothschild D, Meijer MT, Levy M, Moresi C, et al. Persistent microbiome alterations modulate the rate of post-dieting weight regain. Nature. 2016;540:544–51.PubMed 
Article 
CAS 

Google Scholar 
Coyte KZ, Rakoff-Nahoum S. Understanding competition and cooperation within the mammalian gut microbiome. Curr Biol. 2019;29:R538–R544.Johnson AJ, Vangay P, Al-Ghalith GA, Hillmann BM, Ward TL, Shields-Cutler RR, et al. Daily sampling reveals personalized diet-microbiome associations in humans. Cell Host Microbe. 2019;25:789–802.PubMed 
Article 
CAS 

Google Scholar 
Tarini J, Wolever TMS. The fermentable fibre inulin increases postprandial serum short-chain fatty acids and reduces free-fatty acids and ghrelin in healthy subjects. Appl Physiol Nutr Metab. 2010;35:9–16.PubMed 
Article 
CAS 

Google Scholar 
van Loo J, Coussement P, de Leenheer L, Hoebreg H, Smits G. On the presence of inulin and oligofructose as natural ingredients in the western diet. Crit Rev Food Sci Nutr. 1995;35:525–52.PubMed 
Article 

Google Scholar 
Holmes ZC, Silverman JD, Dressman HK, Wei Z, Dallow EP, Armstrong SC, et al. Short-chain fatty acid production by gut microbiota from children with obesity differs according to prebiotic choice and bacterial community composition. mBio. 2020;11:e00914–20.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Shafquat A, Joice R, Simmons SL, Huttenhower C. Functional and phylogenetic assembly of microbial communities in the human microbiome. Trends Microbiol. 2014;22:261–6.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Silverman JD, Durand HK, Bloom RJ, Mukherjee S, David LA. Dynamic linear models guide design and analysis of microbiota studies within artificial human guts. Microbiome. 2018;6:1–20.Article 

Google Scholar 
Pompei A, Cordisco L, Raimondi S, Amaretti A, Pagnoni UM, Matteuzzi D, et al. In vitro comparison of the prebiotic effects of two inulin-type fructans. Anaerobe. 2008;14:280–86.den Besten G, van Eunen K, Groen AK, Venema K, Reijngoud D-J, Bakker BM. The role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolism. J Lipid Res. 2013;54:2325–40.Article 
CAS 

Google Scholar 
Reichardt N, Vollmer M, Holtrop G, Farquharson FM, Wefers D, Bunzel M, et al. Specific substrate-driven changes in human faecal microbiota composition contrast with functional redundancy in short-chain fatty acid production. ISME J. 2018;12:610–22.PubMed 
Article 
CAS 

Google Scholar 
Sonnenburg ED, Zheng H, Joglekar P, Higginbottom SK, Firbank SJ, Bolam DN, et al. Specificity of polysaccharide use in intestinal bacteroides species determines diet-induced microbiota alterations. Cell. 2010;141:1241–52.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Rakoff-Nahoum S, Foster KR, Comstock LE. The evolution of cooperation within the gut microbiota. Nature. 2016;533:255–9.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Wong JMW, de Souza R, Kendall CWC, Emam A, Jenkins DJA. Colonic health: fermentation and short chain fatty acids. J Clin Gastroenterol. 2006;40:235–43.PubMed 
Article 
CAS 

Google Scholar 
van de Wiele T, Boon N, Possemiers S, Jacobs H, Verstraete W. Inulin-type fructans of longer degree of polymerization exert more pronounced in vitro prebiotic effects. J Appl Microbiol. 2007;102:452–60.PubMed 

Google Scholar 
Aguirre M, Eck A, Koenen ME, Savelkoul PHM, Budding AE, Venema K. Diet drives quick changes in the metabolic activity and composition of human gut microbiota in a validated in vitro gut model. Res Microbiol. 2016;167:114–25.PubMed 
Article 
CAS 

Google Scholar 
Solopova A, van Gestel J, Weissing FJ, Bachmann H, Teusink B, Kok J, et al. Bet-hedging during bacterial diauxic shift. Proc Natl Acad Sci USA 2014;111:7427–32.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Noronha A, Modamio J, Jarosz Y, Guerard E, Sompairac N, Preciat G, et al. The Virtual Metabolic Human database: Integrating human and gut microbiome metabolism with nutrition and disease. Nucleic Acids Res. 2019;47:D614–D624.PubMed 
Article 
CAS 

Google Scholar 
Li H, Liu F, Lu J, Shi J, Guan J, Yan F, et al. Probiotic mixture of Lactobacillus plantarum strains improves lipid metabolism and gut microbiota structure in high fat diet-fed mice. Front Microbiol. 2020;11:512.PubMed 
PubMed Central 
Article 

Google Scholar 
Terrapon N, Lombard V, Drula É, Lapébie P, Al-Masaudi S, Gilbert HJ, et al. PULDB: the expanded database of polysaccharide utilization loci. Nucleic Acids Res. 2018;46:D677–D683.PubMed 
Article 
CAS 

Google Scholar 
Bolam DN, van den Berg B. TonB-dependent transport by the gut microbiota: novel aspects of an old problem. Curr Opin Struct Biol. 2018;51:35–43.PubMed 
Article 
CAS 

Google Scholar 
Duncan SH, Holtrop G, Lobley GE, Calder AG, Stewart CS, Flint HJ. Contribution of acetate to butyrate formation by human faecal bacteria. Br J Nutr. 2004;91:915–23.PubMed 
Article 
CAS 

Google Scholar 
Holmes ZC, Villa MM, Durand HK, Jiang S, Dallow EP, Petrone BL, et al. Microbiota responses to different prebiotics are conserved within individuals and associated with habitual fiber intake. bioRxiv. 2021. https://doi.org/10.1101/2021.06.26.450023.Holscher HD, Gregory Caporaso J, Hooda S, Brulc JM, Fahey GC, Swanson KS. Fiber supplementation influences phylogenetic structure and functional capacity of the human intestinal microbiome: follow-up of a randomized controlled trial. Am J Clin Nutr. 2015;101:55–64.Liu H, Liao C, Wu L, Tang J, Chen J, Lei C, et al. Ecological dynamics of the gut microbiome in response to dietary fiber. ISME J. 2022;16:2040–55.David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE, Wolfe BE, et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature. 2014;505:559–63.PubMed 
Article 
CAS 

Google Scholar 
Kaczmarek JL, Musaad SMA, Holscher HD. Time of day and eating behaviors are associated with the composition and function of the human gastrointestinal microbiota. Am J Clin Nutr. 2017;106:1220–31.Basan M, Honda T, Christodoulou D, Hörl M, Chang YF, Leoncini E, et al. A universal trade-off between growth and lag in fluctuating environments. Nature. 2020;584:470–4.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Matenchuk BA, Mandhane PJ, Kozyrskyj AL. Sleep, circadian rhythm, and gut microbiota. Sleep Med Rev. 2020;53:101340.PubMed 
Article 

Google Scholar 
Costello EK, Stagaman K, Dethlefsen L, Bohannan BJM, Relman DA. The application of ecological theory toward an understanding of the human microbiome. Science. 2012;336:1255–62.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444:1027–31.PubMed 
Article 

Google Scholar 
Vich Vila A, Collij V, Sanna S, Sinha T, Imhann F, Bourgonje AR, et al. Impact of commonly used drugs on the composition and metabolic function of the gut microbiota. Nat Commun. 2020;11:1–11.Article 
CAS 

Google Scholar 
Wilson ID, Nicholson JK. Gut microbiome interactions with drug metabolism, efficacy, and toxicity. Transl Res. 2017;179:204–22.PubMed 
Article 
CAS 

Google Scholar 
Salonen A, Lahti L, Salojärvi J, Holtrop G, Korpela K, Duncan SH, et al. Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men. ISME J. 2014;8:2218–30.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Wissel EF, Smith LK. Inter-individual variation shapes the human microbiome. Behav Brain Sci. 2019;42:E79.Wurster JI, Peterson RL, Brown CE, Penumutchu S, Guzior DV, Neugebauer K, et al. Streptozotocin-induced hyperglycemia alters the cecal metabolome and exacerbates antibiotic-induced dysbiosis. Cell Rep. 2021;37:110113.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Kerimi A, Kraut NU, da Encarnacao JA, Williamson G. The gut microbiome drives inter- and intra-individual differences in metabolism of bioactive small molecules. Sci Rep. 2020;10:1–12.Article 
CAS 

Google Scholar 
di Bartolomeo F, van den Ende W. Fructose and fructans: opposite effects on health? Plant Foods Hum Nutr. 2015;70:227–37.Pereira FC, Berry D. Microbial nutrient niches in the gut. Environ Microbiol. 2017;19:1366–78.PubMed 
PubMed Central 
Article 

Google Scholar 
Rettedal EA, Gumpert H, Sommer MOA. Cultivation-based multiplex phenotyping of human gut microbiota allows targeted recovery of previously uncultured bacteria. Nat Commun. 2014;5:1–9.Article 
CAS 

Google Scholar 
Oliphant K, Parreira VR, Cochrane K, Allen-Vercoe E. Drivers of human gut microbial community assembly: coadaptation, determinism and stochasticity. ISME J. 2019;13:3080–92.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Possemiers S, Verthé K, Uyttendaele S, Verstraete W. PCR-DGGE-based quantification of stability of the microbial community in a simulator of the human intestinal microbial ecosystem. FEMS Microbiol Ecol. 2004;49:495–507.PubMed 
Article 
CAS 

Google Scholar 
Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA. 2011;108(supplement_1):4516–22.Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012;6:1621–24.Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Markowitz VM, Chen IMA, Palaniappan K, Chu K, Szeto E, Grechkin Y, et al. IMG: the integrated microbial genomes database and comparative analysis system. Nucleic Acids Res. 2012;40:D115–D122.Bioinformatics B, Tatusov RL, Fedorova ND, Jackson JD, Jacobs AR, Kiryutin B, et al. The COG database: an updated version includes eukaryotes. BMC Bioinformatics. 2003;4:41.Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 1999;27:29–34.Webb EC. Enzyme nomenclature 1992: Recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology on the nomenclature and classification of Enzymes. Cambridge, MA, USA: Academic Press; 1992.Enriquez-Hesles E, Smith DL, Maqani N, Wierman MB, Sutcliffe MD, Fine RD, et al. A cell-nonautonomous mechanism of yeast chronological aging regulated by caloric restriction and one-carbon metabolism. J Biol Chem. 2021;296:100125.Kind T, Wohlgemuth G, Lee DY, Lu Y, Palazoglu M, Shahbaz S, et al. FiehnLib: Mass spectral and retention index libraries for metabolomics based on quadrupole and time-of-flight gas chromatography/mass spectrometry. Anal Chem. 2009;81:10038–48.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Fernandes AD, Macklaim JM, Linn TG, Reid G, Gloor GB. ANOVA-like differential expression (ALDEx) analysis for mixed population RNA-Seq. PLoS ONE. 2013;8:e67019.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Sakamoto M, Ohkuma M. Identification and classification of the genus Bacteroides by multilocus sequence analysis. Microbiology. 2011;157:3388–97.PubMed 
Article 

Google Scholar 
Silverman JD, Roche K, Holmes ZC, David LA, Mukherjee S. Bayesian multinomial logistic normal models through marginally latent matrix-T processes. J Mach Learn Res. 2022;23:1–42.
Google Scholar  More

Pimentel D, McNair S, Janecka J, Wightman J, Simmonds C, O’Connell C, et al. Economic and environmental threats of alien plant, animal, and microbe invasions. Agric Ecosyst Environ. 2001;84:1–20.Article 

Google Scholar 
Diagne C, Leroy B, Vaissière AC, Gozlan RE, Roiz D, Jarić I, et al. High and rising economic costs of biological invasions worldwide. Nature. 2021;592:571–6.Article 
CAS 

Google Scholar 
Catford JA, Jansson R, Nilsson C. Reducing redundancy in invasion ecology by integrating hypotheses into a single theoretical framework. Divers Distrib. 2009;15:22–40.Article 

Google Scholar 
Pearson DE, Ortega YK, Eren Ö, Hierro JL. Community assembly theory as a framework for biological invasions. Trends Ecol Evol. 2018;33:313–25.PubMed 
Article 

Google Scholar 
Inderjit, van der Putten WH. Impacts of soil microbial communities on exotic plant invasions. Trends Ecol Evol. 2010;25:512–9.PubMed 
Article 
CAS 

Google Scholar 
Keane RM, Crawley MJ. Exotic plant invasions and the enemy release hypothesis. Trends Ecol Evol. 2002;17:164–70.Article 

Google Scholar 
Stinson KA, Campbell SA, Powell JR, Wolfe BE, Callaway RM, Thelen GC, et al. Invasive plant suppresses the growth of native tree seedlings by disrupting belowground mutualisms. PLoS Biol. 2006;4:e140.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Hierro JL, Callaway RM. Allelopathy and exotic plant invasion. Plant Soil. 2003;256:29–39.Article 
CAS 

Google Scholar 
Reinhart KO, Callaway RM. Soil biota and invasive plants. N Phytol. 2006;170:445–57.Article 

Google Scholar 
Waller LP, Allen WJ, Barratt BIP, Condron LM, França FM, Hunt JE, et al. Biotic interactions drive ecosystem responses to exotic plant invaders. Science. 2020;368:967–72.PubMed 
Article 
CAS 

Google Scholar 
McLeod ML, Cleveland CC, Lekberg Y, Maron JL, Philippot L, Bru D, et al. Exotic invasive plants increase productivity, abundance of ammonia-oxidizing bacteria and nitrogen availability in intermountain grasslands. J Ecol. 2016;104:994–1002.Article 
CAS 

Google Scholar 
Saul WC, Jeschke JM. Eco-evolutionary experience in novel species interactions. Ecol Lett. 2015;18:236–45.PubMed 
Article 

Google Scholar 
Desprez-Loustau M, Robin C, Buee M, Courtecuisse R, Garbaye J, Suffert F, et al. The fungal dimension of biological invasions. Trends Ecol Evol. 2007;22:472–80.PubMed 
Article 

Google Scholar 
Hierro JL, Maron JL, Callaway RM. A biogeographical approach to plant invasions: the importance of studying exotics in their introduced and native range. J Ecol. 2005;93:5–15.Article 

Google Scholar 
Callaway RM, Thelen GC, Rodriguez A, Holben WE. Soil biota and exotic plant invasion. Nature. 2004;427:731–3.PubMed 
Article 
CAS 

Google Scholar 
Maron JL, Klironomos J, Waller L, Callaway RM. Invasive plants escape from suppressive soil biota at regional scales. J Ecol. 2014;102:19–27.Article 

Google Scholar 
Brundrett MC. Mycorrhizal associations and other means of nutrition of vascular plants: understanding the global diversity of host plants by resolving conflicting information and developing reliable means of diagnosis. Plant Soil. 2009;320:37–77.Article 
CAS 

Google Scholar 
Smith SE, Read DJ. Mycorrhizal symbiosis. London: Academic Press; 2008.O’Neill EG, O’Neill RV, Norby RJ. Hierarchy theory as a guide to mycorrhizal research on large-scale problems. Environ Pollut. 1991;73:271–84.PubMed 
Article 

Google Scholar 
Johnson NC, Wilson GWTT, Wilson JA, Miller RM, Bowker MA. Mycorrhizal phenotypes and the Law of the Minimum. N Phytol. 2015;205:1473–84.Article 
CAS 

Google Scholar 
Lekberg Y, Arnillas CA, Borer ET, Bullington LS, Fierer N, Kennedy PG, et al. Nitrogen and phosphorus fertilization consistently favor pathogenic over mutualistic fungi in grassland soils. Nat Commun. 2021;12:3484.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Richardson DM, Allsopp N, D’Antonio CM, Milton S, Rejmanek M. Plant invasions – the role of mutualisms. Biol Rev. 2000;75:65–93.PubMed 
Article 
CAS 

Google Scholar 
Marler MJ, Zabinski CA, Callaway RM. Mycorrhizae indirectly enhance competitive effects of an invasive forb on a native bunchgrass. Ecology. 1999;80:1180–6.Article 

Google Scholar 
Soti PG, Jayachandran K, Purcell M, Volin JC, Kitajima K. Mycorrhizal symbiosis and Lygodium microphyllum invasion in South Florida—a biogeographic comparison. Symbiosis. 2014;62:81–90.Article 

Google Scholar 
Fumanal B, Plenchette C, Chauvel B, Bretagnolle F. Which role can arbuscular mycorrhizal fungi play in the facilitation of Ambrosia artemisiifolia L. invasion in France? Mycorrhiza. 2006;17:25–35.PubMed 
Article 
CAS 

Google Scholar 
Hart MM, Reader RJ. Taxonomic basis for variation in the colonization strategy of arbuscular mycorrhizal fungi. N Phytol. 2002;153:335–44.Article 

Google Scholar 
Maherali H, Klironomos JN. Influence of phylogeny on fungal community assembly and ecosystem functioning. Science. 2007;316:1746–8.PubMed 
Article 
CAS 

Google Scholar 
Kivlin SN, Hawkes CV, Treseder KK. Global diversity and distribution of arbuscular mycorrhizal fungi. Soil Biol Biochem. 2011;43:2294–303.Article 
CAS 

Google Scholar 
Davison J, Moora M, Öpik M, Adholeya A, Ainsaar L, Bâ A, et al. Global assessment of arbuscular mycorrhizal fungus diversity reveals very low endemism. Science. 2015;349:970–3.PubMed 
Article 
CAS 

Google Scholar 
Mitchell CE, Agrawal AA, Bever JD, Gilbert GS, Hufbauer RA, Klironomos JN, et al. Biotic interactions and plant invasions. Ecol Lett. 2006;9:726–40.PubMed 
Article 

Google Scholar 
Ehrenfeld JG. Effects of exotic plant invasions on soil nutrient cycling processes. Ecosystems. 2003;6:503–23.Article 
CAS 

Google Scholar 
Rout ME, Chrzanowski TH. The invasive Sorghum halepense harbors endophytic N2-fixing bacteria and alters soil biogeochemistry. Plant Soil. 2009;315:163–72.Article 
CAS 

Google Scholar 
Sardans J, Bartrons M, Margalef O, Gargallo-Garriga A, Janssens IA, Ciais P, et al. Plant invasion is associated with higher plant-soil nutrient concentrations in nutrient-poor environments. Glob Change Biol. 2017;23:1282–91.Article 

Google Scholar 
Bossdorf O, Auge H, Lafuma L, Rogers WE, Siemann E, Prati D. Phenotypic and genetic differentiation between native and introduced plant populations. Oecologia. 2005;144:1–11.PubMed 
Article 

Google Scholar 
Lankau RA. Resistance and recovery of soil microbial communities in the face of Alliaria petiolata invasions. N Phytol. 2011;189:536–48.Article 

Google Scholar 
Blossey B, Nötzold R. Evolution of increased competitive ability in invasive nonindigenous plants: a hypothesis. J Ecol. 1995;83:887–9.Article 

Google Scholar 
van Kleunen M, Bossdorf O, Dawson W. The ecology and evolution of alien plants. Annu Rev Ecol Evol Syst. 2018;49:25–47.Article 

Google Scholar 
Rosche C, Hensen I, Schaar A, Zehra U, Jasieniuk M, Callaway RM, et al. Climate outweighs native vs. nonnative range‐effects for genetics and common garden performance of a cosmopolitan weed. Ecol Monogr. 2019;89:e01386.Article 

Google Scholar 
Weaver SE. The biology of Canadian weeds. 115. Conyza canadensis. Can J Plant Sci. 2001;81:867–75.Article 

Google Scholar 
Gange AC, Ayres RL. On the relation between arbuscular mycorrhizal colonization and plant ’ benefit. Oikos. 1999;87:615–21.Article 

Google Scholar 
Řezáčová V, Konvalinková T, Řezáč M. Decreased mycorrhizal colonization of Conyza canadensis (L.) Cronquist in invaded range does not affect fungal abundance in native plants. Biologia. 2020;75:693–9.Article 

Google Scholar 
Zhang Q, Sun Q, Koide RT, Peng Z, Zhou J, Gu X, et al. Arbuscular mycorrhizal fungal mediation of plant-plant onteractions in a marshland plant community. Sci World J. 2014;2014:1–10.
Google Scholar 
Zhang HY, Goncalves P, Copeland E, Qi SS, Dai ZC, Li GL, et al. Invasion by the weed Conyza canadensis alters soil nutrient supply and shifts microbiota structure. Soil Biol Biochem. 2020;143:107739.Article 
CAS 

Google Scholar 
Shah MA, Callaway RM, Shah T, Houseman GR, Pal RW, Xiao S, et al. Conyza canadensis suppresses plant diversity in its nonnative ranges but not at home: a transcontinental comparison. N Phytol. 2014;202:1286–96.Article 

Google Scholar 
Colautti RI, Lau JA. Contemporary evolution during invasion: evidence for differentiation, natural selection, and local adaptation. Mol Ecol. 2015;24:1999–2017.PubMed 
Article 

Google Scholar 
Rosche C, Hensen I, Lachmuth S. Local pre-adaptation to disturbance and inbreeding-environment interactions affect colonisation abilities of diploid and tetraploid Centaurea stoebe. Plant Biol. 2018;20:75–84.PubMed 
Article 
CAS 

Google Scholar 
Hart SC, Start JM, Davidson EA, Firestone MK. Nitrogen mineralization, immobilization, and nitrification. In: Weaver RW, Angle J., Bottomley P., editors. Methods of soil analysis, part 2 microbiological and biochemical properties. Madison, WI: Soil Science Society of America; 1994. p. 985–1018.Brundrett M, Bougher N, Dell B, Grove T, Malajczuk N. Working with mycorrhizas in forestry and agriculture. ACIAR Monogr. 1996;32:1–374.
Google Scholar 
McGonigle TP, Miller MH, Evans DG, Fairchild GL, Swan JA. A new method which gives an objective measure of colonization of roots by vesicular—arbuscular mycorrhizal fungi. N Phytol. 1990;115:495–501.Article 
CAS 

Google Scholar 
Fick SE, Hijmans RJ. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol. 2017;4315:4302–15.Article 

Google Scholar 
Hijmans RJ. raster: Geographic data analysis and modeling. R package version 3.3-13. 2020. https://cran.r-project.org/package=raster.R Core Team. R: A language and environment for statistical computing [https://www.r-project.org/]. Vienna, Austria: R Foundation for Statistical Computing; 2019.Oksanen J, Guillaume BF, Friendly M, Kindt R, Legendre P, McGlinn D, et al. vegan: community ecology package. R package. 2019. https://cran.r-project.org/package=vegan.Dumbrell AJ, Ashton PD, Aziz N, Feng G, Nelson M, Dytham C, et al. Distinct seasonal assemblages of arbuscular mycorrhizal fungi revealed by massively parallel pyrosequencing. N Phytol. 2011;190:794–804.Article 
CAS 

Google Scholar 
Lee J, Lee S, Young JPW. Improved PCR primers for the detection and identification of arbuscular mycorrhizal fungi. FEMS Microbiol Ecol. 2008;65:339–49.PubMed 
Article 
CAS 

Google Scholar 
Bullington LS, Lekberg Y, Larkin BG. Insufficient sampling constrains our characterization of plant microbiomes. Sci Rep. 2021;11:3645.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852–7.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.PubMed 
PubMed Central 
CAS 

Google Scholar 
Öpik M, Vanatoa A, Vanatoa E, Moora M, Davison J, Kalwij JM, et al. The online database MaarjAM reveals global and ecosystemic distribution patterns in arbuscular mycorrhizal fungi (Glomeromycota). N Phytol. 2010;188:223–41.Article 
CAS 

Google Scholar 
Chen J. GUniFrac: generalized UniFrac distances. R package version 1.1. 2018. https://cran.r-project.org/package=GUniFrac.Webb CO. Exploring the phylogenetic structure of ecological communities: an example for rain forest trees. Am Nat. 2000;156:145–55.PubMed 
Article 

Google Scholar 
Kembel SW, Cowan PD, Helmus MR, Cornwell WK, Morlon H, Ackerly DD, et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics. 2010;26:1463–4.PubMed 
Article 
CAS 

Google Scholar 
Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30:772–80.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Price MN, Dehal PS, Arkin AP. FastTree 2 – approximately maximum-likelihood trees for large alignments. PLoS ONE. 2010;5:e9490.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Yu G, Smith DK, Zhu H, Guan Y, Lam TT. GGTREE: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol Evol. 2017;8:28–36.Article 

Google Scholar 
Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. J Stat Softw. 2014;67.Borcard D, Gillet F, Legendre P. Numerical ecology with R. New York: Springer; 2011.Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc. 1995;57:289–300.
Google Scholar 
Anderson MJ, Walsh DCI. PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: What null hypothesis are you testing? Ecol Monogr. 2013;83:557–74.Article 

Google Scholar 
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Felker-Quinn E, Schweitzer JA, Bailey JK. Meta-analysis reveals evolution in invasive plant species but little support for Evolution of Increased Competitive Ability (EICA). Ecol Evol. 2013;3:739–51.PubMed 
PubMed Central 
Article 

Google Scholar 
Pal RW, Maron JL, Nagy DU, Waller LP, Tosto A, Liao H, et al. What happens in Europe stays in Europe: apparent evolution by an invader does not help at home. Ecology 2020;101:e03072.PubMed 
Article 

Google Scholar 
Matesanz S, Sultan SE. High-performance genotypes in an introduced plant: insights to future invasiveness. Ecology. 2013;94:2464–74.PubMed 
Article 

Google Scholar 
Hart M, Reader R. Host plant benefit from association with arbuscular mycorrhizal fungi: variation due to differences in size of mycelium. Biol Fertil Soils. 2002;36:357–66.Article 

Google Scholar 
Yang H, Zhang Q, Koide RT, Hoeksema JD, Tang J, Bian X, et al. Taxonomic resolution is a determinant of biodiversity effects in arbuscular mycorrhizal fungal communities. J Ecol. 2017;105:219–28.Article 
CAS 

Google Scholar 
Moora M, Berger S, Davison J, Öpik M, Bommarco R, Bruelheide H, et al. Alien plants associate with widespread generalist arbuscular mycorrhizal fungal taxa: evidence from a continental-scale study using massively parallel 454 sequencing. J Biogeogr. 2011;38:1305–17.Article 

Google Scholar 
Policelli N, Bruns TD, Vilgalys R, Nuñez MA. Suilloid fungi as global drivers of pine invasions. N Phytol. 2019;222:714–25.Article 

Google Scholar 
Jia Y, Heijden MGA, Wagg C, Feng G, Walder F. Symbiotic soil fungi enhance resistance and resilience of an experimental grassland to drought and nitrogen deposition. J Ecol. 2021;109:3171–81.Article 
CAS 

Google Scholar 
Van Der Heijden MGAA, Klironomos JN, Ursic M, Moutoglis P, Streitwolf-Engel R, Boller T, et al. Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature. 1998;396:69–72.Article 
CAS 

Google Scholar 
Zhang Q, Yang R, Tang J, Yang H, Hu S, Chen X. Positive feedback between mycorrhizal fungi and plants influences plant invasion success and resistance to invasion. PLoS ONE. 2010;5:e12380.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Shah MA, Reshi ZA, Khasa DP. Arbuscular mycorrhizas: drivers or passengers of alien plant invasion. Bot Rev. 2009;75:397–417.Article 

Google Scholar 
Valverde-Barrantes OJ, Horning AL, Smemo KA, Blackwood CB. Phylogenetically structured traits in root systems influence arbuscular mycorrhizal colonization in woody angiosperms. Plant Soil. 2016;404:1–12.Article 
CAS 

Google Scholar 
Wilson GWT, Hartnett DC. Interspecific variation in plant responses to mycorrhizal colonization in tallgrass prairie. Am J Bot. 1998;85:1732–8.PubMed 
Article 
CAS 

Google Scholar 
Seifert EK, Bever JD, Maron JL. Evidence for the evolution of reduced mycorrhizal dependence during plant invasion. Ecology 2009;90:1055–62.PubMed 
Article 

Google Scholar 
Deveautour C, Donn S, Power SA, Bennett AE, Powell JR. Experimentally altered rainfall regimes and host root traits affect grassland arbuscular mycorrhizal fungal communities. Mol Ecol. 2018;27:2152–63.PubMed 
Article 

Google Scholar 
Osborne OG, De-Kayne R, Bidartondo MI, Hutton I, Baker WJ, Turnbull CGN, et al. Arbuscular mycorrhizal fungi promote coexistence and niche divergence of sympatric palm species on a remote oceanic island. N Phytol. 2018;217:1254–66.Article 
CAS 

Google Scholar 
Tian B, Pei Y, Huang W, Ding J, Siemann E. Increasing flavonoid concentrations in root exudates enhance associations between arbuscular mycorrhizal fungi and an invasive plant. ISME J. 2021;15:1919–30.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Pimprikar P, Gutjahr C. Transcriptional regulation of arbuscular mycorrhiza development. Plant Cell Physiol. 2018;59:673–90.PubMed 
Article 
CAS 

Google Scholar 
Wendlandt CE, Helliwell E, Roberts M, Nguyen KT, Friesen ML, Wettberg E, et al. Decreased coevolutionary potential and increased symbiont fecundity during the biological invasion of a legume‐rhizobium mutualism. Evolution. 2021;75:731–47.PubMed 
Article 

Google Scholar 
Callaway RM, Bedmar EJ, Reinhart KO, Silvan CG, Klironomos J. Effects of soil biota from different ranges on Robinia invasion: acquiring mutualists and escaping pathogens. Ecology. 2011;92:1027–35.PubMed 
Article 

Google Scholar 
Shelby N, Duncan RP, Putten WH, McGinn KJ, Weser C, Hulme PE. Plant mutualisms with rhizosphere microbiota in introduced versus native ranges. J Ecol. 2016;104:1259–70.Article 
CAS 

Google Scholar 
Yang Q, Carrillo J, Jin H, Shang L, Hovick SM, Nijjer S, et al. Plant–soil biota interactions of an invasive species in its native and introduced ranges: Implications for invasion success. Soil Biol Biochem. 2013;65:78–85.Article 
CAS 

Google Scholar 
Bronstein JL. The exploitation of mutualisms. Ecol Lett. 2001;4:277–87.Article 

Google Scholar 
Kiers ET, Duhamel M, Beesetty Y, Mensah JA, Franken O, Verbruggen E, et al. Reciprocal rewards stabilize cooperation in the mycorrhizal symbiosis. Science. 2011;333:880–2.PubMed 
Article 
CAS 

Google Scholar 
Koziol L, Bever JD. Mycorrhizal feedbacks generate positive frequency dependence accelerating grassland succession. J Ecol. 2019;107:622–32.Article 

Google Scholar 
Yang H, Yuan Y, Zhang Q, Tang J, Liu Y, Chen X. Changes in soil organic carbon, total nitrogen, and abundance of arbuscular mycorrhizal fungi along a large-scale aridity gradient. Catena. 2011;87:70–7.Article 
CAS 

Google Scholar 
Zhang J, Wang F, Che R, Wang P, Liu H, Ji B, et al. Precipitation shapes communities of arbuscular mycorrhizal fungi in Tibetan alpine steppe. Sci Rep. 2016;6:23488.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Read DJ. Mycorrhizas in ecosystems. Experientia. 1991;47:376–91.Article 

Google Scholar 
Delavaux CS, Smith-Ramesh LM, Kuebbing SE. Beyond nutrients: a meta-analysis of the diverse effects of arbuscular mycorrhizal fungi on plants and soils. Ecology. 2017;98:2111–9.PubMed 
Article 

Google Scholar  More

Charlesworth, D., Barton, N. H. & Charlesworth, B. The sources of adaptive variation. Proc. R. Soc. B Biol. Sci. 284(1855), 20162864 (1855).Article 
CAS 

Google Scholar 
Whitlock, M. C. Fixation of new alleles and the extinction of small populations: Drift load, beneficial alleles, and sexual selection. Evolution 54(6), 1855–1861 (2000).CAS 
PubMed 
Article 

Google Scholar 
Hamilton, W. D. & Zuk, M. Heritable true fitness and bright birds: a role for parasites?. Science 218(4570), 384 (1982).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Hadany, L. & Beker, T. Sexual selection and the evolution of obligatory sex. BMC Evol. Biol. 7(1), 245 (2007).PubMed 
PubMed Central 
Article 

Google Scholar 
Clutton-Brock, T. Reproductive competition and sexual selection. Philos. Trans. R. Soc. B Biol. Sci. 372(1729), 20160310 (2017).Article 

Google Scholar 
Taddei, F. et al. Role of mutator alleles in adaptive evolution. Nature 387(6634), 700–702 (1997).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Agrawal, A. F. & Wang, A. D. Increased transmission of mutations by low-condition females: Evidence for condition-dependent DNA repair. PLoS Biol. 6(2), e30 (2008).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Petrie, M. & Roberts, G. Sexual selection and the evolution of evolvability. Heredity 98(4), 198–205 (2007).CAS 
PubMed 
Article 

Google Scholar 
Dugand, R. J., Kennington, W. J. & Tomkins, J. L. Evolutionary divergence in competitive mating success through female mating bias for good genes. Sci. Adv. 4(5), eaaq0369 (2018).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Siller, S. Sexual selection and the maintenance of sex. Nature 411(6838), 689–692 (2001).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Agrawal, A. F. Sexual selection and the maintenance of sexual reproduction. Nature 411(6838), 692–695 (2001).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Lehtonen, J., Jennions, M. D. & Kokko, H. The many costs of sex. Trends Ecol. Evol. 27(3), 172–178 (2012).PubMed 
Article 

Google Scholar 
Maynard Smith, J. What use is sex?. J. Theor. Biol. 30(2), 319–335 (1971).ADS 
MathSciNet 
Article 

Google Scholar 
Trivers, R. L. Parental investment and sexual selection. In Sexual Selection and the Descent of Man 1871–1971 (ed. Campbell, B.) 136–179 (Aldone, 1972).
Google Scholar 
Petrie, M. & Lipsitch, M. Avian polygyny is most likely in populations with high variability in heritable male fitness. Proc. R. Soc. Lond. Ser. B Biol. Sci. 256(1347), 275–280 (1994).ADS 
Article 

Google Scholar 
Lumley, A. J. et al. Sexual selection protects against extinction. Nature 522(7557), 470–473 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Andersson, M. Sexual Selection (Princeton University Press, 1994).Book 

Google Scholar 
Petrie, M. Improved growth and survival of offspring of peacocks with more elaborate trains. Nature 371(6498), 598–599 (1994).ADS 
CAS 
Article 

Google Scholar 
Møller, A. P. & Alatalo, R. V. Good-genes effects in sexual selection. Proc. R. Soc. Lond. Ser. B Biol. Sci. 266(1414), 85–91 (1999).Article 

Google Scholar 
David, P. et al. Condition-dependent signalling of genetic variation in stalk-eyed flies. Nature 406(6792), 186–188 (2000).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Hale, M. L. et al. Is the peacock’s train an honest signal of genetic quality at the major histocompatibility complex?. J. Evol. Biol. 22(6), 1284–1294 (2009).CAS 
PubMed 
Article 

Google Scholar 
Prokop, Z. M. et al. Meta-analysis suggests choosy females get sexy sons more than “good genes”. Evolution 66(9), 2665–2673 (2012).PubMed 
Article 

Google Scholar 
Kokko, H. et al. The sexual selection continuum. Proc. R. Soc. Lond. Ser. B Biol. Sci. 269(1498), 1331–1340 (2002).Article 

Google Scholar 
Drake, J. W. et al. Rates of Spontaneous Mutation. Genetics 148(4), 1667 (1998).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Keightley, P. D. Rates and fitness consequences of new mutations in humans. Genetics 190(2), 295–304 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
Haag-Liautard, C. et al. Direct estimation of per nucleotide and genomic deleterious mutation rates in Drosophila. Nature 445(7123), 82–85 (2007).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Metzgar, D. & Wills, C. Evidence for the adaptive evolution of mutation rates. Cell 101(6), 581–584 (2000).CAS 
PubMed 
Article 

Google Scholar 
Janetos, A. C. Strategies of female mate choice: A theoretical analysis. Behav. Ecol. Sociobiol. 7(2), 107–112 (1980).Article 

Google Scholar 
Johnstone, R. A. & Earn, D. J. D. Imperfect female choice and male mating skew on leks of different sizes. Behav. Ecol. Sociobiol. 45(3), 277–281 (1999).Article 

Google Scholar 
Petrie, M., Halliday, T. & Sanders, C. Peahens prefer peacocks with elaborate trains. Anim. Behav. 41(2), 323–331 (1991).Article 

Google Scholar 
Cally, J. G., Stuart-Fox, D. & Holman, L. Meta-analytic evidence that sexual selection improves population fitness. Nat. Commun. 10(1), 2017 (2019).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Kotiaho, J. S. et al. On the resolution of the lek paradox. Trends Ecol. Evol. 23(1), 1–3 (2008).PubMed 
Article 

Google Scholar 
Parker, G. A., Baker, R. R. & Smith, V. G. F. The origin and evolution of gamete dimorphism and the male-female phenomenon. J. Theor. Biol. 36(3), 529–553 (1972).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Parker, G. A. The sexual cascade and the rise of pre-ejaculatory (Darwinian) sexual selection, sex roles, and sexual conflict. Cold Spring Harb. Perspect. Biol. 6(10), a017509–a017509 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
Rowe, L. & Houle, D. The lek paradox and the capture of genetic variance by condition dependent traits. Proc. R. Soc. Lond. Ser. B Biol. Sci. 263(1375), 1415–1421 (1996).ADS 
Article 

Google Scholar 
Petrie, M. Evolution by sexual selection. Front. Ecol. Evol. 9, 950 (2021).Article 

Google Scholar 
Petrie, M. & Kempenaers, B. Extra-pair paternity in birds: Explaining variation between species and populations. Trends Ecol. Evol. 13(2), 52–58 (1998).CAS 
PubMed 
Article 

Google Scholar 
Møller, A. P. & Cuervo, J. J. Minisatellite mutation rates increase with extra-pair paternity among birds. BMC Evol. Biol. 9(1), 100 (2009).PubMed 
PubMed Central 
Article 

Google Scholar 
Anmarkrud, J. A. et al. Factors affecting germline mutations in a hypervariable microsatellite: A comparative analysis of six species of swallows (Aves: Hirundinidae). Mutat. Res. Fundam. Mol. Mech. Mutagen. 708(1), 37–43 (2011).CAS 
Article 

Google Scholar 
Ellegren, H. Characteristics, causes and evolutionary consequences of male-biased mutation. Proc. R. Soc. B Biol. Sci. 274(1606), 1–10 (2007).CAS 
Article 

Google Scholar 
Baur, J. & Berger, D. Experimental evidence for effects of sexual selection on condition-dependent mutation rates. Nat. Ecol. Evol. 4, 737–744 (2020).PubMed 
Article 

Google Scholar 
Vrijenhoek, R. C. & Parker, E. D. Geographical parthenogenesis: General purpose genotypes and frozen niche variation. In Lost Sex (eds Schön, I. et al.) (Springer, Dordrecht, 2009).
Google Scholar 
Reudink, M. W. et al. Evolution of song and color in island birds. Wilson J. Ornithol. 133(1), 1–10 (2021).Article 

Google Scholar 
Iglesias-Carrasco, M. et al. Sexual selection, body mass and molecular evolution interact to predict diversification in birds. Proc. R. Soc. B Biol. Sci. 2019(286), 20190172 (1899).
Google Scholar 
Earl, D. J. & Deem, M. W. Evolvability is a selectable trait. Proc. Natl. Acad. Sci. U. S. A. 101(32), 11531 (2004).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar  More

Bardgett, R. D. et al. Combatting global grassland degradation. Nat. Rev. Earth Environ. 2(10), 720–735. https://doi.org/10.1038/s43017-021-00207-2 (2021).ADS 
Article 

Google Scholar 
O’Mara, F. P. The role of grasslands in food security and climate change. Ann. Bot. 110, 1263–1270. https://doi.org/10.1093/aob/mcs209 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
Eze, S., Palmer, S. M. & Chapman, P. J. Soil organic carbon stock in grasslands: Effects of inorganic fertilizers, liming and grazing in different climate settings. J. Environ. Manage. 223, 74–84. https://doi.org/10.1016/j.jenvman.2018.06.013 (2018).CAS 
Article 
PubMed 

Google Scholar 
Makoudi, B. et al. Phosphorus deficiency increases nodule phytase activity of faba bean rhizobia symbiosis. Acta Physiol. Plant 40, 63. https://doi.org/10.1007/s11738-018-2619-6 (2018).CAS 
Article 

Google Scholar 
Stecca, J. D. L. et al. Inoculation of soybean seeds coated with osmoprotector in differentssoil pH’s. Acta Sci. Agron. 41, 9. https://doi.org/10.4025/actasciagron.v41i1.39482 (2019).Article 

Google Scholar 
Afonso, S., Arrobas, M. & Rodrigues, M. Â. Soil and plant analyses to diagnose hop fields irregular growth. J. Soil Sci. Plant Nutr. 20, 1999–2013. https://doi.org/10.1007/s42729-020-00270-6 (2020).CAS 
Article 

Google Scholar 
Crews, T. E. & Peoples, M. B. Legume versus fertilizer sources of nitrogen: ecological tradeoffs and human needs. Agric. Ecosyst. Environ 102(3), 279–297. https://doi.org/10.1016/j.agee.2003.09.018 (2004).Article 

Google Scholar 
Ossler, J. N., Zielinski, C. A. & Heath, K. D. Tripartite mutualism: Facilitation or trade-offs between rhizobial and mycorrhizal symbionts of legume hosts. Am. J. Bot. 102, 1332–1341. https://doi.org/10.3732/ajb.1500007 (2015).CAS 
Article 
PubMed 

Google Scholar 
Backer, R. et al. Plant growth-promoting rhizobacteria: context, mechanisms of action, and roadmap to commercialization of biostimulants for sustainable agriculture. Front. Plant Sci. 9, 1473. https://doi.org/10.3389/fpls.2018.01473 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Keet, J. H., Ellis, A. G., Hui, C. & Le Roux, J. J. Strong spatial and temporal turnover of soil bacterial communities in South Africa’s hyper diverse fynbos biome. Soil Biol. Biochem. 136, 107541. https://doi.org/10.1016/j.soilbio.2019.107541 (2019).CAS 
Article 

Google Scholar 
Fierer, N. & Jackson, R. B. The diversity and biogeography of soil bacterial communities. Proc. Natl. Acad. Sci. USA 103(3), 626–631. https://doi.org/10.1073/pnas.0507535103 (2006).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Kracmarova, M. et al. Response of soil microbes and soil enzymatic activity to 20 years of fertilization. Agronomy 10, 1542. https://doi.org/10.3390/agronomy10101542 (2020).CAS 
Article 

Google Scholar 
Wang, C., Liu, D. H. & Bai, E. Decreasing soil microbial diversity is associated with decreasing microbial biomass under nitrogen addition. Soil Biol. Biochem. 120, 126–133. https://doi.org/10.1016/j.soilbio.2018.02.003 (2018).CAS 
Article 

Google Scholar 
Lucas, R. W. et al. A meta-analysis of the effects of nitrogen additions on base cations: Implications for plants, soils, and streams. For. Ecol. Manage. 262, 95–104. https://doi.org/10.1016/j.foreco.2011.03.018 (2011).Article 

Google Scholar 
Wang, Y. et al. Soil pH is a major driver of soil diazotrophic community assembly in Qinghai-Tibet alpine meadows. Soil Biol. Biochem. 115, 547–555. https://doi.org/10.1016/j.soilbio.2017.09.024 (2017).CAS 
Article 

Google Scholar 
Wan, S. et al. Effects of lime application and understory removal on soil microbial communities in subtropical eucalyptus L’Hér. plantations. Forests 10, 338 (2019).Article 

Google Scholar 
Yin, C., Schlatter, D. C., Kroese, D. R., Paulitz, T. C. & Hagerty, C. H. Impacts of lime application on soil bacterial microbiome in dryland wheat soil in the Pacific Northwest. Appl. Soil Ecol. 168, 104113 (2021).Article 

Google Scholar 
Schroeder, K. L., Schlatter, D. C. & Paulitz, T. C. Location-dependent impacts of liming and crop rotation on bacterial communities in acid soils of the Pacific Northwest. Appl. Soil. Ecol. 130, 59–68 (2018).Article 

Google Scholar 
Sudhakaran, M. & Ravanachandar, A. Role of soil enzymes in agroecosystem. Biotica Res. Today 2(6), 443–444 (2020).
Google Scholar 
Lacava, P. T., Machado, P. C. & de Andrade, P. H. M. Phosphate solubilization by endophytes from the tropical plants. Endophytes 3, 207–226 (2021).
Google Scholar 
Nannipieri, P., Giagnoni, L., Landi, L. & Renella, G. Role of Phosphatase Enzymes in Soil. Phosphorus in Action 215–243 (Springer, 2011).Book 

Google Scholar 
Zhang, L. et al. Soil labile organic carbon fractions and soil enzyme activities after 10 years of continuous fertilization and wheat residue incorporation. Sci. Rep. 10(1), 11318. https://doi.org/10.1038/s41598-020-68163-3 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Turner, B. L. Variation in pH optima of hydrolytic enzyme activities in tropical rain forest soils. Appl. Environ. Microbiol. 76, 6485–6493 (2010).ADS 
CAS 
Article 

Google Scholar 
Acosta-Martínez, V., Pérez-Guzmán, L. & Johnson, J. M. Simultaneous determination of β-glucosidase, β-glucosaminidase, acid phosphomonoesterase, and arylsulfatase activities in a soil sample for a biogeochemical cycling index. Appl. Soil Ecol. 142, 72–80. https://doi.org/10.12691/aees-8-6-26 (2019).CAS 
Article 

Google Scholar 
Parham, J. A. & Deng, S. P. Detection, quantification and characterization of β-glucosaminidase activity in soil. Soil Biol. Biochem. 32(8–9), 1183–1190. https://doi.org/10.1016/S0038-0717(00)00034-1 (2000).CAS 
Article 

Google Scholar 
Olajuyigbe, F. M. & Fatokun, C. O. Biochemical characterization of an extremely stable pH-versatile laccase from Sporothrix carnis CPF-05. Int. J. Biol. Macromol. 94, 535–543. https://doi.org/10.1016/j.ijbiomac.2016.10.037 (2017).CAS 
Article 
PubMed 

Google Scholar 
Bhuyan, M. B. et al. Explicating physiological and biochemical responses of wheat cultivars under acidity stress: insight into the antioxidant defense and glyoxalase systems. Physiol. Mol. Biol. Plants 25, 865–879. https://doi.org/10.1007/s12298-019-00678-0 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Delgado-Baquerizo, M., Grinyer, J., Reich, P. B. & Singh, B. K. Relative importance of soil properties and microbial community for soil functionality: Insights from a microbial swap experiment. Funct. Ecol. 30, 1862–1873 (2016).Article 

Google Scholar 
Zhao, L. et al. Mercury methylation in rice paddies and its possible controlling factors in the Hg mining area, Guizhou province, Southwest China. Environ. Pollut. 215, 1–9. https://doi.org/10.1016/j.envpol.2016.05.001 (2016).CAS 
Article 
PubMed 

Google Scholar 
Ward, D., Kirkman, K., Hagenah, N. & Tsvuura, Z. Soil respiration declines with increasing nitrogen fertilization and is not related to productivity in long-term grassland experiments. Soil Biol. Biochem. 115, 415–422. https://doi.org/10.1016/j.soilbio.2017.08.035 (2017).CAS 
Article 

Google Scholar 
Ward, M. et al. Impact of 2019–2020 mega-fires on Australian fauna habitat. Nat. Ecol. Evol. 4(10), 1321–1326. https://doi.org/10.1038/s41559-020-1251-1 (2020).Article 
PubMed 

Google Scholar 
Fynn, R. W. & O’Connor, T. G. Determinants of community organization of a South African mesic grassland. J. Veg. Sci. 16(1), 93–102 (2005).Article 

Google Scholar 
Morris, C. & Fynn, R. The Ukulinga long-term grassland trials: Reaping the fruits of meticulous, patient research. Bull. Grassl. Soc. S. Afr. 11(1), 7–22 (2001).
Google Scholar 
Le Roux, N. P. & Mentis, M. Veld compositional response to fertilization in the tall grassveld of Natal. S. Afr. J. Plant Soil 3(1), 1–10. https://doi.org/10.1080/02571862.1986.10634177 (1986).Article 

Google Scholar 
Tsvuura, Z. & Kirkman, K. P. Yield and species composition of a mesic grassland savannah in South Africa are influenced by long-term nutrient addition. Austral Ecol. 38, 959–970 (2013).Article 

Google Scholar 
Goldman, E. & Green, L. H. Practical Handbook of Microbiology 2nd edn, 864 (CRC Press Taylor and Francis Group, 2008).Book 

Google Scholar 
Akinbowale, O. L., Peng, H. & Barton, M. D. Diversity of tetracycline resistance genes in bacteria from aquaculture sources in Australia. J. Appl. Microbiol. 103(5), 2016–2025 (2007).CAS 
Article 

Google Scholar 
Jackson, C. R., Tyler, H. L. & Millar, J. J. Determination of microbial extracellular enzyme activity in waters, soils, and sediments using high throughput microplate assays. Preparation of substrate and buffer solutions for colorimetric analyses of enzyme. J. Vis. Exp. 80, 1–9. https://doi.org/10.3791/50399 (2013).CAS 
Article 

Google Scholar 
Goyal, M. & Kaur, R. Interactive effect of nitrogen nutrition, nitrate reduction and seasonal variation on oxalate synthesis in leaves of Napier-bajar hybrid (Pennisetum purpureum P. glaucum). Crop Pasture Sci 70, 669–675 (2019).CAS 
Article 

Google Scholar 
Pavlovic, J., Kostic, L., Bosnic, P., Kirkby, E. A. & Nikolic, M. Interactions of silicon with essential and beneficial elements in plants. Front. Plant Sci. 12, 1224. https://doi.org/10.3389/fpls.2021.697592 (2021).Article 

Google Scholar 
Li, Y., Tremblay, J., Bainard, L. D., Cade-Menun, B. & Hamel, C. Long-term effects of nitrogen and phosphorus fertilization on soil microbial community structure and function under continuous wheat production. Environ. Microbiol. 22, 1066–1088 (2020).CAS 
Article 

Google Scholar 
Guo, Z., Han, J., Li, J., Xu, Y. & Wang, X. Effects of long-term fertilization on soil organic carbon mineralization and microbial community structure. PLoS ONE 14, e0211163 (2019).CAS 
Article 

Google Scholar 
Shang, L., Wan, L. I., Zhou, X., Li, S. & Li, X. Effects of organic fertilizer on soil nutrient status, enzyme activity, and bacterial community diversity in Leymus chinensis steppe in Inner Mongolia, China. PLoS ONE https://doi.org/10.1371/journal.pone.0240559 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Gautam, A. et al. Responses of soil microbial community structure and enzymatic activities to long-term application of mineral fertilizer and beef manure. Environ. Sustain. Indic. 8, 10007S. https://doi.org/10.1016/j.indic.2020.100073 (2020).Article 

Google Scholar 
Wang, J., Lu, X., Zhang, J., Wei, G. & Xiong, Y. Regulating soil bacterial diversity, community structure and enzyme activity using residues from golden apple snails. Sci. Rep. 10(1), 1–11 (2020).CAS 
Article 

Google Scholar 
Xu, D., Carswell, A., Zhu, Q., Zhang, F. & de Vries, W. Modelling long-term impacts of fertilization and liming on soil acidification at Rothamsted experimental station. Sci. Total Environ. 713, 136249 (2020).ADS 
CAS 
Article 

Google Scholar 
von Tucher, S., Hörndl, D. & Schmidhalter, U. Interaction of soil pH and phosphorus efficacy: Long-term effects of P fertilizer and lime applications on wheat, barley, and sugar beet. Ambio 47, 41–49 (2018).Article 

Google Scholar 
Leff, J. W. et al. Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe. Proc. Natl. Acad. Sci. USA 112, 10967–10972 (2015).ADS 
CAS 
Article 

Google Scholar 
Pan, J. et al. Dynamics of soil nutrients, microbial community structure, enzymatic activity, and their relationships along a chronosequence of Pinus massoniana plantations. Forests 12, 376 (2021).Article 

Google Scholar 
Andrés, J. A., Rovera, M., Guiñazú, L. B., Pastor, N. A. & Rosas, S. B. Role of in crop improvement. In Bacteria in Agrobiology: Plant Growth Responses 107–122 (Springer, 2011).Chapter 

Google Scholar 
Jeong, H., Choi, S. K., Ryu, C. M. & Park, S. H. Chronicle of a soil bacterium: Paenibacillus polymyxa E681 as a tiny guardian of plant and human health. Front. Microbiol. 10, 467 (2019).Article 

Google Scholar 
Garbeva, P. V., van Veen, J. A. & van Elsas, J. D. Microbial diversity in soil: Selection of microbial populations by plant and soil type and implications for disease suppressiveness. Annu. Rev. Phytopathol. 42, 243–270. https://doi.org/10.1146/annurev.phyto.42.012604.135455 (2004).CAS 
Article 
PubMed 

Google Scholar 
Sinsabaugh, R. L. & Moorhead, D. L. Resource allocation to extracellular enzyme production: A model for nitrogen and phosphorus control of litter decomposition. Soil Biol. Biochem. 26(10), 1305–1311. https://doi.org/10.1016/0038-0717(94)90211-9 (1994).Article 

Google Scholar 
Xiao, W., Chen, X., Jing, X. & Zhu, B. A meta-analysis of soil extracellular enzyme activities in response to global change. Soil Biol. Biochem. 123, 21–32. https://doi.org/10.1016/j.soilbio.2018.05.001 (2018).CAS 
Article 

Google Scholar 
Billah, M. et al. Phosphorus & phosphate solubilizing bacteria: Keys for sustainable agriculture. Geomicrobiol. J. 36(10), 904–916. https://doi.org/10.1080/01490451.2019.1654043 (2019).CAS 
Article 

Google Scholar 
Turner, B. L., McKelvie, I. D. & Haygarth, P. M. Characterisation of water-extractable soil organic phosphorus by phosphatase hydrolysis. Soil Biol Biochem. 34, 27–35. https://doi.org/10.1016/S0038-0717(01)00144-4 (2002).CAS 
Article 

Google Scholar 
van Aarle, I. M. & Plassard, C. Spatial distribution of phosphatase activity associated with ectomycorrhizal plants related to soil type. Soil Biol. Biochem. 42(2), 324–330. https://doi.org/10.1016/j.soilbio.2009.11.011 (2020).CAS 
Article 

Google Scholar  More