Philippa Kaur

The interaction between the two factors (substrates and CRF rates) was statistically significant by the F-test (p  More

Thuiller, W., Lavorel, S., Araujo, M. B., Sykes, M. T. & Prentice, I. C. Climate change threats to plant diversity in Europe. Proc. Natl. Acad. Sci. USA 102, 8245–8250. https://doi.org/10.1073/pnas.0409902102 (2005).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Fagundez, J. Heathlands confronting global change: Drivers of biodiversity loss from past to future scenarios. Ann. Bot. 111, 151–172. https://doi.org/10.1093/aob/mcs257 (2013).Article 
PubMed 

Google Scholar 
Nicotra, A. B. et al. Plant phenotypic plasticity in a changing climate. Trends Plant Sci. 15, 684–692. https://doi.org/10.1016/j.tplants.2010.09.008 (2010).CAS 
Article 
PubMed 

Google Scholar 
Dubin, M. J. et al. DNA methylation in Arabidopsis has a genetic basis and shows evidence of local adaptation. Elife 4, 25. https://doi.org/10.7554/eLife.05255 (2015).Article 

Google Scholar 
Herrera, C. M., Medrano, M. & Bazaga, P. Comparative spatial genetics and epigenetics of plant populations: Heuristic value and a proof of concept. Mol. Ecol. 25, 1653–1664. https://doi.org/10.1111/mec.13576 (2016).CAS 
Article 
PubMed 

Google Scholar 
Richards, C. L. et al. Ecological plant epigenetics: Evidence from model and non-model species, and the way forward. Ecol. Lett. 20, 1576–1590. https://doi.org/10.1111/ele.12858 (2017).Article 
PubMed 

Google Scholar 
Münzbergová, Z., Latzel, V., Šurinová, M. & Hadincová, V. DNA methylation as a possible mechanism affecting ability of natural populations to adapt to changing climate. Oikos 128, 124–134. https://doi.org/10.1111/oik.05591 (2019).CAS 
Article 

Google Scholar 
Thiebaut, F., Hemerly, A. S. & Ferreira, P. C. G. A role for epigenetic regulation in the adaptation and stress responses of non-model plants. Front. Plant Sci. 10, 25. https://doi.org/10.3389/fpls.2019.00246 (2019).Article 

Google Scholar 
Verhoeven, K. J. F., Vonholdt, B. M. & Sork, V. L. Epigenetics in ecology and evolution: What we know and what we need to know. Mol. Ecol. 25, 1631–1638. https://doi.org/10.1111/mec.13617 (2016).Article 
PubMed 

Google Scholar 
Lisch, D. How important are transposons for plant evolution?. Nat. Rev. Genet. 14, 49–61. https://doi.org/10.1038/nrg3374 (2013).CAS 
Article 
PubMed 

Google Scholar 
Paszkowski, J. Controlled activation of retrotransposition for plant breeding. Curr. Opin. Biotechnol. 32, 200–206. https://doi.org/10.1016/j.copbio.2015.01.003 (2015).CAS 
Article 
PubMed 

Google Scholar 
Becker, C. et al. Spontaneous epigenetic variation in the Arabidopsis thaliana methylome. Nature 480, 245-U127. https://doi.org/10.1038/nature10555 (2011).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Schmitz, R. J. et al. Transgenerational epigenetic instability is a source of novel methylation variants. Science 334, 369–373. https://doi.org/10.1126/science.1212959 (2011).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Bossdorf, O., Richards, C. L. & Pigliucci, M. Epigenetics for ecologists. Ecol. Lett. 11, 106–115. https://doi.org/10.1111/j.1461-0248.2007.01130.x (2008).Article 
PubMed 

Google Scholar 
Walsh, M. R. et al. Local adaptation in transgenerational responses to predators. Proc. R. Soc. B Biol. Sci. https://doi.org/10.1098/rspb.2015.2271 (2016).Article 

Google Scholar 
Foust, C. M. et al. Genetic and epigenetic differences associated with environmental gradients in replicate populations of two salt marsh perennials. Mol. Ecol. 25, 1639–1652. https://doi.org/10.1111/mec.13522 (2016).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Gugger, P. F., Fitz-Gibbon, S., Pellegrini, M. & Sork, V. L. Species-wide patterns of DNA methylation variation in Quercus lobata and their association with climate gradients. Mol. Ecol. 25, 1665–1680. https://doi.org/10.1111/mec.13563 (2016).CAS 
Article 
PubMed 

Google Scholar 
Herrera, C. M. & Bazaga, P. Untangling individual variation in natural populations: Ecological, genetic and epigenetic correlates of long-term inequality in herbivory. Mol. Ecol. 20, 1675–1688. https://doi.org/10.1111/j.1365-294X.2011.05026.x (2011).CAS 
Article 
PubMed 

Google Scholar 
Medrano, M., Herrera, C. M. & Bazaga, P. Epigenetic variation predicts regional and local intraspecific functional diversity in a perennial herb. Mol. Ecol. 23, 4926–4938. https://doi.org/10.1111/mec.12911 (2014).CAS 
Article 
PubMed 

Google Scholar 
Herrera, C. M., Medrano, M. & Bazaga, P. Comparative epigenetic and genetic spatial structure of the perennial herb Helleborus foetidus: Isolation by environment, isolation by distance, and functional trait divergence. Am. J. Bot. 104, 1195–1204. https://doi.org/10.3732/ajb.1700162 (2017).Article 
PubMed 

Google Scholar 
Sheldon, E. L., Schrey, A., Andrew, S. C., Ragsdale, A. & Griffith, S. C. Epigenetic and genetic variation among three separate introductions of the house sparrow (Passer domesticus) into Australia. R. Soc. Open Sci. https://doi.org/10.1098/rsos.172185 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Gaspar, B., Bossdorf, O. & Durka, W. Structure, stability and ecological significance of natural epigenetic variation: A large-scale survey in Plantago lanceolata. New Phytol. 221, 1585–1596. https://doi.org/10.1111/nph.15487 (2019).Article 
PubMed 

Google Scholar 
Medrano, M., Alonso, C., Bazaga, P., Lopez, E. & Herrera, C. M. Comparative genetic and epigenetic diversity in pairs of sympatric, closely related plants with contrasting distribution ranges in south-eastern Iberian mount. Aob Plants https://doi.org/10.1093/aobpla/plaa013 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Wang, M. Z., Li, H. L., Li, J. M. & Yu, F. H. Correlations between genetic, epigenetic and phenotypic variation of an introduced clonal herb. Heredity 124, 146–155. https://doi.org/10.1038/s41437-019-0261-8 (2020).Article 
PubMed 

Google Scholar 
Miryeganeh, M. & Saze, H. Epigenetic inheritance and plant evolution. Popul. Ecol. 62, 17–27. https://doi.org/10.1002/1438-390x.12018 (2020).Article 

Google Scholar 
Becklin, K. M. et al. Examining plant physiological responses to climate change through an evolutionary lens. Plant Physiol. 172, 635–649. https://doi.org/10.1104/pp.16.00793 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Szymanska, R., Slesak, I., Orzechowska, A. & Kruk, J. Physiological and biochemical responses to high light and temperature stress in plants. Environ. Exp. Bot. 139, 165–177. https://doi.org/10.1016/j.envexpbot.2017.05.002 (2017).CAS 
Article 

Google Scholar 
Agrawal, A. A., Erwin, A. C. & Cook, S. C. Natural selection on and predicted responses of ecophysiological traits of swamp milkweed (Asclepias incarnata). J. Ecol. 96, 536–542. https://doi.org/10.1111/j.1365-2745.2008.01365.x (2008).Article 

Google Scholar 
Azhar, A., Sathornkich, J., Rattanawong, R. & Kasemsap, P. Responses of chlorophyll fluorescence, stomatal conductance, and net photosynthesis rates of four rubber (Hevea brasiliensis) genotypes to drought. Adv. Rubber 844, 11–14. https://doi.org/10.4028/www.scientific.net/AMR.844.11 (2014).CAS 
Article 

Google Scholar 
Bussotti, F., Pancrazi, M., Matteucci, G. & Gerosa, G. Leaf morphology and chemistry in Fagus sylvatica (beech) trees as affected by site factors and ozone: Results from CONECOFOR permanent monitoring plots in Italy. Tree Physiol. 25, 211–219. https://doi.org/10.1093/treephys/25.2.211 (2005).CAS 
Article 
PubMed 

Google Scholar 
Carlson, J. E., Adams, C. A. & Holsinger, K. E. Intraspecific variation in stomatal traits, leaf traits and physiology reflects adaptation along aridity gradients in a South African shrub. Ann. Bot. 117, 195–207. https://doi.org/10.1093/aob/mcv146 (2016).Article 
PubMed 

Google Scholar 
De Frenne, P. et al. Temperature effects on forest herbs assessed by warming and transplant experiments along a latitudinal gradient. Glob. Change Biol. 17, 3240–3253. https://doi.org/10.1111/j.1365-2486.2011.02449.x (2011).ADS 
Article 

Google Scholar 
Reinhardt, K., Castanha, C., Germino, M. J. & Kueppers, L. M. Ecophysiological variation in two provenances of Pinus flexilis seedlings across an elevation gradient from forest to alpine. Tree Physiol. 31, 615–625. https://doi.org/10.1093/treephys/tpr055 (2011).Article 
PubMed 

Google Scholar 
Yamori, W., Hikosaka, K. & Way, D. A. Temperature response of photosynthesis in C-3, C-4, and CAM plants: Temperature acclimation and temperature adaptation. Photosynth. Res. 119, 101–117. https://doi.org/10.1007/s11120-013-9874-6 (2014).CAS 
Article 
PubMed 

Google Scholar 
Stojanova, B. et al. Adaptive differentiation of Festuca rubra along a climate gradient revealed by molecular markers and quantitative traits. PLoS One https://doi.org/10.1371/journal.pone.0194670 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Han, S. K. & Wagner, D. Role of chromatin in water stress responses in plants. J. Exp. Bot. 65, 2785–2799. https://doi.org/10.1093/jxb/ert403 (2014).CAS 
Article 
PubMed 

Google Scholar 
Han, S. K. & Torii, K. U. Lineage-specific stem cells, signals and asymmetries during stomatal development. Development 143, 1259–1270. https://doi.org/10.1242/dev.127712 (2016).CAS 
Article 
PubMed 

Google Scholar 
Torii, K. U. Stomatal differentiation: The beginning and the end. Curr. Opin. Plant Biol. 28, 16–22. https://doi.org/10.1016/j.pbi.2015.08.005 (2015).CAS 
Article 
PubMed 

Google Scholar 
Tricker, P. J., Gibbings, J. G., Lopez, C. M. R., Hadley, P. & Wilkinson, M. J. Low relative humidity triggers RNA-directed de novo DNA methylation and suppression of genes controlling stomatal development. J. Exp. Bot. 63, 3799–3813. https://doi.org/10.1093/jxb/ers076 (2012).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Vrablova, M., Hronkova, M., Vrabl, D., Kubasek, J. & Santrucek, J. Light intensity-regulated stomatal development in three generations of Lepidium sativum. Environ. Exp. Bot. 156, 316–324. https://doi.org/10.1016/j.envexpbot.2018.09.012 (2018).CAS 
Article 

Google Scholar 
Tricker, P. J., Lopez, C. M. R., Gibbings, G., Hadley, P. & Wilkinson, M. J. Transgenerational, dynamic methylation of stomata genes in response to low relative humidity. Int. J. Mol. Sci. 14, 6674–6689. https://doi.org/10.3390/ijms14046674 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Puy, J. et al. Improved demethylation in ecological epigenetic experiments: Testing a simple and harmless foliar demethylation application. Methods Ecol. Evol. 9, 744–753. https://doi.org/10.1111/2041-210x.12903 (2018).Article 

Google Scholar 
Kosová, V., Hájek, T., Hadincová, V. & Münzbergová, Z. The importance of ecophysiological traits in response of Festuca rubra to changing climate. Physiol. Plant. 174, e13608. https://doi.org/10.1111/ppl.13608 (2022).CAS 
Article 
PubMed 

Google Scholar 
Maricle, B. R. & Adler, P. B. Effects of precipitation on photosynthesis and water potential in Andropogon gerardii and Schizachyrium scoparium in a southern mixed grass prairie. Environ. Exp. Bot. 72, 223–231. https://doi.org/10.1016/j.envexpbot.2011.03.011 (2011).Article 

Google Scholar 
Münzbergová, Z. et al. Plant origin, but not phylogeny, drive species ecophysiological response to projected climate. Front. Plant Sci. 11, 400. https://doi.org/10.3389/fpls.2020.00400 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Beerling, D. J. & Chaloner, W. G. The impact of atmospheric CO2 and temperature change on stomatal density—observations from Quercus robur lammas leaves. Ann. Bot. 71, 231–235. https://doi.org/10.1006/anbo.1993.1029 (1993).CAS 
Article 

Google Scholar 
Tang, Y. L. et al. Heat stress induces an aggregation of the light-harvesting complex of photosystem II in spinach plants. Plant Physiol. 143, 629–638. https://doi.org/10.1104/pp.106.090712 (2007).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Jahns, P. & Holzwarth, A. R. The role of the xanthophyll cycle and of lutein in photoprotection of photosystem II. BBA-Bioenerget. 1817, 182–193. https://doi.org/10.1016/j.bbabio.2011.04.012 (2012).CAS 
Article 

Google Scholar 
Baker, N. R. & Rosenqvist, E. Applications of chlorophyll fluorescence can improve crop production strategies: An examination of future possibilities. J. Exp. Bot. 55, 1607–1621. https://doi.org/10.1093/jxb/erh196 (2004).CAS 
Article 
PubMed 

Google Scholar 
Baker, H. G. In The Genetics of Colonizing Species (eds Baker, H. G. & Stebbins, G. L.) 147–168 (Academic Press, 1965).
Google Scholar 
Bartlett, M. K. et al. Global analysis of plasticity in turgor loss point, a key drought tolerance trait. Ecol. Lett. 17, 1580–1590. https://doi.org/10.1111/ele.12374 (2014).Article 
PubMed 

Google Scholar 
Raven, J. A. Selection pressures on stomatal evolution. New Phytol. 153, 371–386. https://doi.org/10.1046/j.0028-646X.2001.00334.x (2002).CAS 
Article 
PubMed 

Google Scholar 
Zhang, F. F. et al. Effects of CO2 enrichment on growth and development of Impatiens hawkeri. Sci. World J. https://doi.org/10.1100/2012/601263 (2012).ADS 
Article 

Google Scholar 
Gonzalez, A. P. R. et al. Stress-induced memory alters growth of clonal off spring of white clover (Trifolium repens). Am. J. Bot. 103, 1567–1574. https://doi.org/10.3732/ajb.1500526 (2016).CAS 
Article 
PubMed 

Google Scholar 
Jones, P. A., Taylor, S. M. & Wilson, V. L. Inhibition of DNA methylation by 5-azacytidine. Recent Results Cancer Res. 84, 202–211 (1983).CAS 
PubMed 

Google Scholar 
Meineri, E., Skarpaas, O., Spindelbock, J., Bargmann, T. & Vandvik, V. Direct and size-dependent effects of climate on flowering performance in alpine and lowland herbaceous species. J. Veg. Sci. 25, 275–286. https://doi.org/10.1111/jvs.12062 (2014).Article 

Google Scholar 
Šurinová, M., Hadincová, V., Vandvik, V. & Münzbergová, Z. Temperature and precipitation, but not geographic distance, explain genetic relatedness among populations in the perennial grass Festuca rubra. J. Plant Ecol. 12, 730–741. https://doi.org/10.1093/jpe/rtz010 (2019).Article 

Google Scholar 
Münzbergová, Z., Hadincová, V., Skálová, H. & Vandvik, V. Genetic differentiation and plasticity interact along temperature and precipitation gradients to determine plant performance under climate change. J. Ecol. 105, 1358–1373. https://doi.org/10.1111/1365-2745.12762 (2017).Article 

Google Scholar 
Klanderud, K., Vandvik, V. & Goldberg, D. The importance of biotic vs abiotic drivers of local plant community composition along regional bioclimatic gradients. PLoS One 10, e0130205. https://doi.org/10.1371/journal.pone.0130205 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Meineri, E., Skarpaas, O. & Vandvik, V. Modeling alpine plant distributions at the landscape scale: Do biotic interactions matter?. Ecol. Model. 231, 1–10. https://doi.org/10.1016/j.ecolmodel.2012.01.021 (2012).Article 

Google Scholar 
Meineri, E., Spindelbock, J. & Vandvik, V. Seedling emergence responds to both seed source and recruitment site climates: A climate change experiment combining transplant and gradient approaches. Plant Ecol. 214, 607–619. https://doi.org/10.1007/s11258-013-0193-y (2013).Article 

Google Scholar 
Vandvik, V., Klanderud, K., Meineri, E., Maren, I. E. & Topper, J. Seed banks are biodiversity reservoirs: Species-area relationships above versus below ground. Oikos 125, 218–228. https://doi.org/10.1111/oik.02022 (2016).Article 

Google Scholar 
Stojanova, B. et al. Evolutionary potential of a widespread clonal grass under changing climate. J. Evol. Biol. 32, 1057–1068. https://doi.org/10.1111/jeb.13507 (2019).Article 
PubMed 

Google Scholar 
Osorio-Montalvo, P., Saenz-Carbonell, L. & De-la-Pena, C. 5-azacytidine: A promoter of epigenetic changes in the quest to improve plant somatic embryogenesis. Int. J. Mol. Sci. 19, 20. https://doi.org/10.3390/ijms19103182 (2018).CAS 
Article 

Google Scholar 
Hurlbert, S. H. Pseudoreplication and the design of ecological field experiments. Ecol. Monogr. 54, 187–211. https://doi.org/10.2307/1942661 (1984).Article 

Google Scholar 
Münzbergová, Z. & Hadincová, V. Transgenerational plasticity as an important mechanism affecting response of clonal species to changing climate. Ecol. Evol. 7, 5236–5247. https://doi.org/10.1002/ece3.3105 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Oksanen, L. Logic of experiments in ecology: Is pseudoreplication a pseudoissue?. Oikos 94, 27–38. https://doi.org/10.1034/j.1600-0706.2001.11311.x (2001).Article 

Google Scholar 
Johnson, S. N., Gherlenda, A. N., Frew, A. & Ryalls, J. M. W. The importance of testing multiple environmental factors in legume-insect research: Replication, reviewers, and rebuttal. Front. Plant Sci. 7, 489. https://doi.org/10.3389/fpls.2016.00489 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Hurlbert, S. H. On misinterpretations of pseudoreplication and related matters: A reply to Oksanen. Oikos 104, 591–597. https://doi.org/10.1111/j.0030-1299.2004.12752.x (2004).Article 

Google Scholar 
Scheepens, J. F. & Stocklin, J. Flowering phenology and reproductive fitness along a mountain slope: Maladaptive responses to transplantation to a warmer climate in Campanula thyrsoides. Oecologia 171, 679–691. https://doi.org/10.1007/s00442-012-2582-7 (2013).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Gugger, S., Kesselring, H., Stoecklin, J. & Hamann, E. Lower plasticity exhibited by high- versus mid-elevation species in their phenological responses to manipulated temperature and drought. Ann. Bot. 116, 953–962. https://doi.org/10.1093/aob/mcv155 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Bezemer, T. M., Thompson, L. J. & Jones, T. H. Poa annua shows inter-generational differences in response to elevated CO2. Glob. Change Biol. 4, 687–691. https://doi.org/10.1046/j.1365-2486.1998.00184.x (1998).ADS 
Article 

Google Scholar 
Cavieres, L. A. & Arroyo, M. T. K. Seed germination response to cold stratification period and thermal regime in Phacelia secunda (Hydrophyllaceae)—altitudinal variation in the mediterranean Andes of central Chile. Plant Ecol. 149, 1–8. https://doi.org/10.1023/a:1009802806674 (2000).Article 

Google Scholar 
Souther, S., Lechowicz, M. J. & McGraw, J. B. Experimental test for adaptive differentiation of ginseng populations reveals complex response to temperature. Ann. Bot. 110, 829–837. https://doi.org/10.1093/aob/mcs155 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
Matias, L. & Jump, A. S. Impacts of predicted climate change on recruitment at the geographical limits of Scots pine. J. Exp. Bot. 65, 299–310. https://doi.org/10.1093/jxb/ert376 (2014).CAS 
Article 
PubMed 

Google Scholar 
Zhang, H. X. et al. Germination shifts of C-3 and C-4 species under simulated global warming scenario. PLoS One 9, e105139. https://doi.org/10.1371/journal.pone.0105139 (2014).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Maxwell, K. & Johnson, G. N. Chlorophyll fluorescence—a practical guide. J. Exp. Bot. 51, 659–668 (2000).Ashraf, M. & Harris, P. J. C. Photosynthesis under stressful environments: An overview. Photosynthetica 51, 163–190. https://doi.org/10.1007/s11099-013-0021-6 (2013).CAS 
Article 

Google Scholar 
Majekova, M., Martinkova, J. & Hajek, T. Grassland plants show no relationship between leaf drought tolerance and soil moisture affinity, but rapidly adjust to changes in soil moisture. Funct. Ecol. 33, 774–785. https://doi.org/10.1111/1365-2435.13312 (2019).Article 

Google Scholar 
Volis, S., Ormanbekova, D., Yermekbayev, K., Song, M. S. & Shulgina, I. Multi-approaches analysis reveals local adaptation in the emmer wheat (Triticum dicoccoides) at macro—but not micro-geographical scale. PLoS One 10, 19. https://doi.org/10.1371/journal.pone.0121153 (2015).CAS 
Article 

Google Scholar 
Younginger, B. S., Sirova, D., Cruzan, M. B. & Ballhorn, D. J. Is biomass a reliable estimate of plant fitness?. Appl. Plant Sci. https://doi.org/10.3732/apps.1600094 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
R Development Core Team. Version 4.0.3 A language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2011).
Google Scholar 
Bossdorf, O., Arcuri, D., Richards, C. L. & Pigliucci, M. Experimental alteration of DNA methylation affects the phenotypic plasticity of ecologically relevant traits in Arabidopsis thaliana. Evol. Ecol. 24, 541–553. https://doi.org/10.1007/s10682-010-9372-7 (2010).Article 

Google Scholar 
Oksanen, J., Blanchet, F. G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P. R., O’Hara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H., Szoecs, E. & Wagner, H. (2020). vegan: Community Ecology Package. R package version 2.5-7.Lande, R. & Arnold, S. J. The measurement of selection on correlated characters. Evolution 37, 1210–1226. https://doi.org/10.2307/2408842 (1983).Article 
PubMed 

Google Scholar 
Rolhauser, A. G., Nordenstahl, M., Aguiar, M. R. & Pucheta, E. Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability. J. Ecol. 107, 1457–1468. https://doi.org/10.1111/1365-2745.13094 (2019).Article 

Google Scholar 
Yan, W. M., Zhong, Y. Q. W. & Shangguan, Z. P. Contrasting responses of leaf stomatal characteristics to climate change: A considerable challenge to predict carbon and water cycles. Glob. Change Biol. 23, 3781–3793. https://doi.org/10.1111/gcb.13654 (2017).ADS 
Article 

Google Scholar 
González, A. P. R., Dumalasová, V., Rosenthal, J., Skuhrovec, J. & Latzel, V. The role of transgenerational effects in adaptation of clonal offspring of white clover (Trifolium repens) to drought and herbivory. Evol. Ecol. 31, 345–361. https://doi.org/10.1007/s10682-016-9844-5 (2017).Article 

Google Scholar 
Shi, W. et al. Transient stability of epigenetic population differentiation in a clonal invader. Front. Plant Sci. https://doi.org/10.3389/fpls.2018.01851 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Quan, J., Münzbergová, Z. & Latzel, V. Time dynamics of stress legacy in clonal transgenerational effects: A case study on Trifolium repens. Ecol. Evol. https://doi.org/10.1002/ece3.8959 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Harris, C. J. et al. A DNA methylation reader complex that enhances gene transcription. Science 362, 1182. https://doi.org/10.1126/science.aar7854 (2018).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Zhang, K. R., Cheng, X. L., Shu, X., Liu, Y. & Zhang, Q. F. Linking soil bacterial and fungal communities to vegetation succession following agricultural abandonment. Plant Soil 431, 19–36. https://doi.org/10.1007/s11104-018-3743-1 (2018).ADS 
CAS 
Article 

Google Scholar 
Xiao, X. L. et al. A group of SUVH methyl-DNA binding proteins regulate expression of the DNA demethylase ROS1 in Arabidopsis. J. Integr. Plant Biol. 61, 110–119. https://doi.org/10.1111/jipb.12768 (2019).CAS 
Article 
PubMed 

Google Scholar 
Gallego-Bartolome, J. DNA methylation in plants: Mechanisms and tools for targeted manipulation. New Phytol. 227, 38–44. https://doi.org/10.1111/nph.16529 (2020).CAS 
Article 
PubMed 

Google Scholar 
Wang, Z. W., Bossdorf, O., Prati, D., Fischer, M. & van Kleunen, M. Transgenerational effects of land use on offspring performance and growth in Trifolium repens. Oecologia 180, 409–420. https://doi.org/10.1007/s00442-015-3480-6 (2016).ADS 
Article 
PubMed 

Google Scholar 
Muir, C. D., Pease, J. B. & Moyle, L. C. Quantitative genetic analysis indicates natural selection on leaf phenotypes across wild tomato species (Solanum sect. Lycopersicon; Solanaceae). Genetics 198, 1629. https://doi.org/10.1534/genetics.114.169276 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Ramirez-Valiente, J. A. et al. Natural selection and neutral evolutionary processes contribute to genetic divergence in leaf traits across a precipitation gradient in the tropical oak Quercus oleoides. Mol. Ecol. 27, 2176–2192. https://doi.org/10.1111/mec.14566 (2018).Article 
PubMed 

Google Scholar 
Jueterbock, A. et al. The seagrass methylome is associated with variation in photosynthetic performance among clonal shoots. Front. Plant Sci. 11, 19. https://doi.org/10.3389/fpls.2020.571646 (2020).Article 

Google Scholar 
Ganguly, D. R., Crisp, P. A., Eichten, S. R. & Pogson, B. J. The Arabidopsis DNA methylome is stable under transgenerational drought stress. Plant Physiol. 175, 1893–1912. https://doi.org/10.1104/pp.17.00744 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Ganguly, D. R., Crisp, P. A., Eichten, S. R. & Pogson, B. J. Maintenance of pre-existing DNA methylation states through recurring excess-light stress. Plant Cell Environ. 41, 1657–1672. https://doi.org/10.1111/pce.13324 (2018).CAS 
Article 
PubMed 

Google Scholar 
Nixon, P. J., Michoux, F., Yu, J. F., Boehm, M. & Komenda, J. Recent advances in understanding the assembly and repair of photosystem II. Ann. Bot. 106, 1–16. https://doi.org/10.1093/aob/mcq059 (2010).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Perez, T. M. & Feeley, K. J. Photosynthetic heat tolerances and extreme leaf temperatures. Funct. Ecol. 34, 2236–2245. https://doi.org/10.1111/1365-2435.13658 (2020).Article 

Google Scholar 
Kitayama, K., Pattison, R., Cordell, S., Webb, D. & MuellerDombois, D. Ecological and genetic implications of foliar polymorphism in Metrosideros polymorpha Gaud (Myrtaceae) in a habitat matrix on Mauna Loa, Hawaii. Ann. Bot. 80, 491–497. https://doi.org/10.1006/anbo.1996.0473 (1997).Article 

Google Scholar 
Konopkova, A. et al. Nucleotide polymorphisms associated with climate and physiological traits in silver fir (Abies alba Mill.) provenances. Flora 250, 37–43. https://doi.org/10.1016/j.flora.2018.11.012 (2019).Article 

Google Scholar 
Baer, A., Wheeler, J. K. & Pittermann, J. Limited hydraulic adjustments drive the acclimation response of Pteridium aquilinum to variable light. Ann. Bot. 125, 691–700. https://doi.org/10.1093/aob/mcaa006 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Hao, X. F., Jin, Z. P., Wang, Z. Q., Qin, W. S. & Pei, Y. X. Hydrogen sulfide mediates DNA methylation to enhance osmotic stress tolerance in Setaria italic L.. Plant Soil 453, 355–370. https://doi.org/10.1007/s11104-020-04590-5 (2020).CAS 
Article 

Google Scholar 
Colaneri, A. C. & Jones, A. M. Genome-wide quantitative identification of DNA differentially methylated sites in Arabidopsis seedlings growing at different water potential. PLoS One 8, 10. https://doi.org/10.1371/journal.pone.0059878 (2013).CAS 
Article 

Google Scholar 
Becker, C. & Weigel, D. Epigenetic variation: Origin and transgenerational inheritance. Curr. Opin. Plant Biol. 15, 562–567. https://doi.org/10.1016/j.pbi.2012.08.004 (2012).CAS 
Article 
PubMed 

Google Scholar 
Spens, A. E. & Douhovnikoff, V. Epigenetic variation within Phragmites australis among lineages, genotypes, and ramets. Biol. Invas. 18, 2457–2462. https://doi.org/10.1007/s10530-016-1223-1 (2016).Article 

Google Scholar 
Herrera, C. M., Pozo, M. I. & Bazaga, P. Jack of all nectars, master of most: DNA methylation and the epigenetic basis of niche width in a flower-living yeast. Mol. Ecol. 21, 2602–2616. https://doi.org/10.1111/j.1365-294X.2011.05402.x (2012).CAS 
Article 
PubMed 

Google Scholar 
Herrera, C. M. & Bazaga, P. Epigenetic correlates of plant phenotypic plasticity: DNA methylation differs between prickly and nonprickly leaves in heterophyllous Ilex aquifolium (Aquifoliaceae) trees. Bot. J. Linn. Soc. 171, 441–452. https://doi.org/10.1111/boj.12007 (2013).Article 

Google Scholar 
Keller, T. E., Lasky, J. R. & Yi, S. V. The multivariate association between genomewide DNA methylation and climate across the range of Arabidopsis thaliana. Mol. Ecol. 25, 1823–1837. https://doi.org/10.1111/mec.13573 (2016).CAS 
Article 
PubMed 

Google Scholar 
Madliger, C. L., Love, O. P., Hultine, K. R. & Cooke, S. J. The conservation physiology toolbox: Status and opportunities. Conserv. Physiol. 6, 16. https://doi.org/10.1093/conphys/coy029 (2018).CAS 
Article 

Google Scholar 
Münzbergová, Z. & Haisel, D. Effects of polyploidization on the contents of photosynthetic pigments are largely population-specific. Photosynth. Res. 140, 289–299. https://doi.org/10.1007/s11120-018-0604-y (2019).CAS 
Article 
PubMed 

Google Scholar 
Balachandran, S. et al. Concepts of plant biotic stress. Some insights into the stress physiology of virus-infected plants, from the perspective of photosynthesis. Physiol. Plant. 100, 203–213. https://doi.org/10.1034/j.1399-3054.1997.1000201.x (1997).CAS 
Article 

Google Scholar 
Pavlíková, Z., Holá, D., Vlasáková, B., Procházka, T. & Münzbergová, Z. Physiological and fitness differences between cytotypes vary with stress in a grassland perennial herb. PLoS One https://doi.org/10.1371/journal.pone.0188795 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Zhang, B. B., Zhang, H., Jing, Q. & Wang, J. X. Light pollution on the growth, physiology and chlorophyll fluorescence response of landscape plant perennial ryegrass (Lolium perenne L.). Ecol. Indic. 115, 9. https://doi.org/10.1016/j.ecolind.2020.106448 (2020).CAS 
Article 

Google Scholar 
Cameron, D. D., Geniez, J. M., Seel, W. E. & Irving, L. J. Suppression of host photosynthesis by the parasitic plant Rhinanthus minor. Ann. Bot. 101, 573–578. https://doi.org/10.1093/aob/mcm324 (2008).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Molina-Montenegro, M. A., Salgado-Luarte, C., Oses, R. & Torres-Diaz, C. Is physiological performance a good predictor for fitness? Insights from an invasive plant species. PLoS One 8, 9. https://doi.org/10.1371/journal.pone.0076432 (2013).CAS 
Article 

Google Scholar 
dos Santos, V. & Ferreira, M. J. Are photosynthetic leaf traits related to the first-year growth of tropical tree seedlings? A light-induced plasticity test in a secondary forest enrichment planting. For. Ecol. Manage. 460, 9. https://doi.org/10.1016/j.foreco.2020.117900 (2020).Article 

Google Scholar 
Shi, Q. W. et al. Phosphorus-fertilisation has differential effects on leaf growth and photosynthetic capacity of Arachis hypogaea L.. Plant Soil 447, 99–116. https://doi.org/10.1007/s11104-019-04041-w (2020).CAS 
Article 

Google Scholar 
Madriaza, K., Saldana, A., Salgado-Luarte, C., Escobedo, V. M. & Gianoli, E. Chlorophyll fluorescence may predict tolerance to herbivory. Int. J. Plant Sci. 180, 81–85. https://doi.org/10.1086/700583 (2019).Article 

Google Scholar 
Franks, P. J., Drake, P. L. & Beerling, D. J. Plasticity in maximum stomatal conductance constrained by negative correlation between stomatal size and density: An analysis using Eucalyptus globulus. Plant Cell Environ. 32, 1737–1748. https://doi.org/10.1111/j.1365-3040.2009.002031.x (2009).Article 
PubMed 

Google Scholar 
Belluau, M. & Shipley, B. Linking hard and soft traits: Physiology, morphology and anatomy interact to determine habitat affinities to soil water availability in herbaceous dicots. PLoS One 13, 25. https://doi.org/10.1371/journal.pone.0193130 (2018).CAS 
Article 

Google Scholar 
Jerbi, A. et al. High biomass yield increases in a primary effluent wastewater phytofiltration are associated to altered leaf morphology and stomatal size in Salix miyabeana. Sci. Total Environ. 738, 12. https://doi.org/10.1016/j.scitotenv.2020.139728 (2020).CAS 
Article 

Google Scholar 
Sakoda, K. et al. Higher stomatal density improves photosynthetic induction and biomass production in Arabidopsis under fluctuating light. Front. Plant Sci. 11, 11. https://doi.org/10.3389/fpls.2020.589603 (2020).Article 

Google Scholar 
Liu, J. Y. et al. Effect of summer warming on growth, photosynthesis and water status in female and male Populus cathayana: Implications for sex-specific drought and heat tolerances. Tree Physiol. 40, 1178–1191. https://doi.org/10.1093/treephys/tpaa069 (2020).CAS 
Article 
PubMed 

Google Scholar 
Griffin, P. T., Niederhuth, C. E. & Schmitz, R. J. A comparative analysis of 5-azacytidine- and zebularine-induced DNA demethylation. G3 Genes Genomes Genet. 6, 2773–2780. https://doi.org/10.1534/g3.116.030262 (2016).CAS 
Article 

Google Scholar 
Zhang, Y. X. et al. Application of 5-azacytidine induces DNA hypomethylation and accelerates dormancy release in buds of tree peony. Plant Physiol. Biochem. 147, 91–100. https://doi.org/10.1016/j.plaphy.2019.12.010 (2020).CAS 
Article 
PubMed 

Google Scholar 
Sammarco, I., Muenzbergova, Z. & Latzel, V. DNA methylation can mediate local adaptation and response to climate change in the clonal plant Fragaria vesca: Evidence from a European-scale reciprocal transplant experiment. Front. Plant Sci. https://doi.org/10.3389/fpls.2022.827166 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Atighi, M. R., Verstraeten, B., De Meyer, T. & Kyndt, T. Genome-wide DNA hypomethylation shapes nematode pattern-triggered immunity in plants. New Phytol. 227, 545–558. https://doi.org/10.1111/nph.16532 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Nowicka, A. et al. Comparative analysis of epigenetic inhibitors reveals different degrees of interference with transcriptional gene silencing and induction of DNA damage. Plant J. 102, 68–84. https://doi.org/10.1111/tpj.14612 (2020).CAS 
Article 
PubMed 

Google Scholar 
Christman, J. K. 5-Azacytidine and 5-aza-2 ’-deoxycytidine as inhibitors of DNA methylation: Mechanistic studies and their implications for cancer therapy. Oncogene 21, 5483–5495. https://doi.org/10.1038/sj.onc.1205699 (2002).CAS 
Article 
PubMed 

Google Scholar 
Issa, J. P. J. & Kantarjian, H. M. Targeting DNA methylation. Clin. Cancer Res. 15, 3938–3946. https://doi.org/10.1158/1078-0432.ccr-08-2783 (2009).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Amoah, S. et al. A hypomethylated population of Brassica rapa for forward and reverse epi-genetics. BMC Plant Biol. https://doi.org/10.1186/1471-2229-12-193 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
McGuigan, K., Hoffmann, A. A. & Sgro, C. M. How is epigenetics predicted to contribute to climate change adaptation? What evidence do we need?. Philos. Trans. R. Soc. B Biol. Sci. 376, 10. https://doi.org/10.1098/rstb.2020.0119 (2021).Article 

Google Scholar 
Sano, H., Kamada, I., Youssefian, S., Katsumi, M. & Wabiko, H. A single treatment of rice seedlings with 5-azacytidine induces heritable dwarfism and undermethylation of genomic DNA. Mol. Gen. Genet. 220, 441–447. https://doi.org/10.1007/bf00391751 (1990).CAS 
Article 

Google Scholar 
Kondo, H., Ozaki, H., Itoh, K., Kato, A. & Takeno, K. Flowering induced by 5-azacytidine, a DNA demethylating reagent in a short-day plant, Perilla frutescens var. crispa. Physiol. Plant. 127, 130–137. https://doi.org/10.1111/j.1399-3054.2005.00635.x (2006).CAS 
Article 

Google Scholar 
Kumpatla, S. P. & Hall, T. C. Longevity of 5-azacytidine-mediated gene expression and re-establishment of silencing in transgenic rice. Plant Mol. Biol. 38, 1113–1122. https://doi.org/10.1023/a:1006071018039 (1998).CAS 
Article 
PubMed 

Google Scholar 
Lira-Medeiros, C. F. et al. Epigenetic variation in mangrove plants occurring in contrasting natural environment. PLoS One https://doi.org/10.1371/journal.pone.0010326 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Raj, S. et al. Clone history shapes Populus drought responses. Proc. Natl. Acad. Sci. USA 108, 12521–12526. https://doi.org/10.1073/pnas.1103341108 (2011).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Richards, C. L., Schrey, A. W. & Pigliucci, M. Invasion of diverse habitats by few Japanese knotweed genotypes is correlated with epigenetic differentiation. Ecol. Lett. 15, 1016–1025. https://doi.org/10.1111/j.1461-0248.2012.01824.x (2012).Article 
PubMed 

Google Scholar 
Platt, A., Gugger, P. F., Pellegrini, M. & Sork, V. L. Genome-wide signature of local adaptation linked to variable CpG methylation in oak populations. Mol. Ecol. 24, 3823–3830. https://doi.org/10.1111/mec.13230 (2015).CAS 
Article 
PubMed 

Google Scholar 
Pfeifer, G. P. Mutagenesis at methylated CpG sequences. DNA Methyl. Basic Mech. 301, 259–281 (2006).CAS 
Article 

Google Scholar 
Walsh, C. P. & Xu, G. L. Cytosine methylation and DNA repair. DNA Methyl. Basic Mech. 301, 283–315 (2006).CAS 
Article 

Google Scholar  More

Angélil, O. et al. An independent assessment of anthropogenic attribution statements for recent extreme temperature and rainfall events. J. Clim. 30(1), 5–16 (2017).ADS 

Google Scholar 
Rosenzweig, C. et al. Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments. Philos. Trans. R. Soc. A. 376, 20160455 (2018).ADS 

Google Scholar 
Mitchell, D. et al. Half a degree additional warming, prognosis and projected impacts (HAPPI): Background and experimental design. Geosci. Model Dev. 10, 571–583 (2017).ADS 
CAS 

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

Google Scholar 
IPCC: Summary for Policymakers. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change 4–6 (Cambridge University Press, 2013).Diffenbaugh, N. S. et al. Quantifying the influence of global warming on unprecedented extreme climate events. PNAS 114(19), 4881–4886 (2016).ADS 

Google Scholar 
Tai, A. P. K., Martin, M. V. & Heald, C. L. Threat to future global food security from climate change and ozone air pollution. Nat. Clim. Change 4, 817–821 (2014).ADS 
CAS 

Google Scholar 
Román-Palacios, C. & Wiens, J. J. Recent responses to climate change reveal the drivers of species extinction and survival. PNAS 117(8), 4211–4217 (2020).ADS 
PubMed 
PubMed Central 

Google Scholar 
Dong, W. H., Liu, Z., Liao, H., Tang, Q. H. & Li, X. E. New climate and socio-economic scenarios for assessing global human health challenges due to heat risk. Clim. Change 130(4), 505–518 (2015).ADS 

Google Scholar 
Brown, S. C., Wigley, T. M. L., Otto-Bliesner, B. L., Rahbek, C. & Fordham, D. A. Persistent Quaternary climate refugia are hospices for biodiversity in the Anthropocene. Nat. Clim. Change 10, 244–248 (2020).ADS 

Google Scholar 
Fischer, H., Amelung, D. & Said, N. The accuracy of German citizens’ confidence in their climate change knowledge. Nat. Clim. Change 9, 776–780 (2020).ADS 

Google Scholar 
Hasegawa, T. et al. Risk of increased food insecurity under stringent global climate change mitigation policy. Nat. Clim. Change 8, 699–703 (2018).ADS 

Google Scholar 
Lobell, D. B., Schlenker, W. & Costa-Roberts, J. Climate trends and global crop production since 1980. Science 333, 616–620 (2011).ADS 
CAS 
PubMed 

Google Scholar 
UNFCCC. The Paris Agreement. 2015, https://unfccc.int/process-and-meetings/the-paris-agreement/the-paris-agreement.Roche, K. R., Müller-Itten, M., Dralle, D. N., Bolster, D. & Müller, M. F. Climate change and the opportunity cost of conflict. PNAS 117(4), 1935–1940 (2020).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Challinor, A. J. et al. A meta-analysis of crop yield under climate change and adaptation. Nat. Clim. Change 4, 287–291 (2014).ADS 

Google Scholar 
Lobell, D. B. et al. Prioritizing climate change adaptation needs for food security in 2030. Science 319, 607–610 (2017).
Google Scholar 
Lv, S. et al. Yield gap simulations using ten maize cultivars commonly planted in Northeast China during the past five decades. Agric. For. Meteorol. 205, 1–10 (2015).ADS 

Google Scholar 
Chao, W., Kehui, C. & Shah, F. Heat stress decreases rice grain weight: Evidence and physiological mechanisms of heat effects prior to flowering. Int. J. Mol. Sci. 23(18), 10922 (2022).
Google Scholar 
Chao, W. et al. Estimating the yield stability of heat-tolerant rice genotypes under various heat conditions across reproductive stages: A 5-year case study. Sci. Rep. 11, 13604 (2021).ADS 

Google Scholar 
IPCC. Food security and food production systems. In Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel of Climate Change 485–533 (Cambridge University Press, 2014).Tigchelaar, M., Battisti, D. S., Naylor, R. L. & Ray, D. K. Future warming increases probability of globally synchronized maize production shocks. PNAS 115(26), 6644–6649 (2018).ADS 
PubMed 
PubMed Central 

Google Scholar 
Zhao, C. et al. Temperature increase reduces global yields of major crops in four independent estimates. PNAS 114, 9326–9331 (2017).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Diffenbaugh, N. S., Hertel, T. W., Scherer, M. & Verma, M. Response of corn markets to climate volatility under alternative energy futures. Nat. Clim. Change 2, 514–518 (2012).ADS 

Google Scholar 
Jensen, H. G. & Anderson, K. Grain price spikes and beggar-thy-neighbor policy responses: A global economywide analysis. World Bank Econ. Rev. 31, 158–175 (2017).
Google Scholar 
Fraser, E. D. G., Simelton, E., Termansen, M., Gosling, S. N. & South, A. “Vulnerability hotspots”: Integrating socio-economic and hydrological models to identify where cereal production may decline in the future due to climate change induced drought. Agric. For. Meteorol. 170, 195–205 (2013).ADS 

Google Scholar 
Puma, M. J., Bose, S., Chon, S. Y. & Cook, B. I. Assessing the evolving fragility of the global food system. Environ. Res. Lett. 10, 024007 (2015).ADS 

Google Scholar 
Wheeler, T. & Braun, J. V. Climate change impacts on global food security. Science 341(6145), 508–513 (2013).ADS 
CAS 
PubMed 

Google Scholar 
Lunt, T., Jones, A. W., Mulhern, W. S., Lezaks, D. P. M. & Jahn, M. M. Vulnerabilities to agricultural production shocks: An extreme, plausible scenario for assessment of risk for the insurance sector. Clim. Risk Manag. 13, 1–9 (2016).
Google Scholar 
Jägermeyr, J. & Frieler, K. Spatial variations in crop growing seasons pivotal to reproduce global fluctuations in maize and wheat yields. Sci. Adv. 4(11), eaat4517 (2018).ADS 
PubMed 
PubMed Central 

Google Scholar 
Elliott, J. et al. Characterizing agricultural impacts of recent large-scale US droughts and changing technology and management. Agric. Syst. 159, 275–281 (2017).
Google Scholar 
Tack, J., Barkley, A. & Nalley, L. L. Effect of warming temperatures on US wheat yields. Proc. Natl. Acad. Sci. 112, 6931–6936 (2015).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Tao, F., Zhang, Z., Liu, J. & Yokozawa, M. Modelling the impacts of weather and climate variability on crop productivity over a large area: A new super-ensemblebased probabilistic projection. Agric. For. Meteorol. 149, 1266–1278 (2009).ADS 

Google Scholar 
Parent, B. et al. Maize yields over Europe may increase in spite of climate change, with an appropriate use of the genetic variability of flowering time. PNAS 115(42), 10642–10647 (2018).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Yang, C. Y., Fraga, H., Ieperen, W. V. & Santos, J. A. Assessment of irrigated maize yield response to climate change scenarios in Portugal. Agric. Water Manag. 184, 178–190 (2017).
Google Scholar 
Miller, S. A. & Moore, F. C. Climate and health damages from global concrete production. Nat. Clim. Change https://doi.org/10.1038/s41558-020-0733-0 (2020).Article 

Google Scholar 
Kassie, B. T. et al. Exploring climate change impacts and adaptation options for maize production in the Central Rift Valley of Ethiopia using different climate change scenarios and crop models. Clim. Change 129, 145–158 (2015).ADS 

Google Scholar 
Tao, F. & Zhang, Z. Climate change, high-temperature stress, rice productivity, and water use in Eastern China: A new superensemble-based probabilistic projection. J. Appl. Meteorol. Climatol. 52, 531–551 (2013).ADS 

Google Scholar 
Glotter, M. & Elliott, J. Simulating US agriculture in a modern Dust Bowl drought. Nat. Plants 3, 16193 (2016).PubMed 

Google Scholar 
Challinor, A. J., Koehler, A. K., Ramirez-Villegas, J., Whitfield, S. & Das, B. Current warming will reduce yields unless maize breeding and seed systems adapt immediately. Nat. Clim. Change 6, 954–958 (2016).ADS 

Google Scholar 
Cammarano, D. et al. Using historical climate observations to understand future climate change crop yield impacts in the Southeastern US. Clim. Change 134, 311–326 (2016).ADS 

Google Scholar 
Etten, J. V. et al. Crop variety management for climate adaptation supported by citizen science. PNAS 116(10), 4194–4199 (2019).ADS 
PubMed 
PubMed Central 

Google Scholar 
Urban, D. W., Sheffield, J. & Lobell, D. B. The impacts of future climate and carbon dioxide changes on the average and variability of US maize yields under two emission scenarios. Environ. Res. Lett. 10, 045003 (2015).ADS 

Google Scholar 
IPCC. Summary for policymakers. In Global Warming of 1.5°C. An IPCC Special Report on the Impacts of Global Warming of 1.5°C Above Pre-industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty 32 (World Meteorological Organization, 2018).Ruane, A. C., Goldberg, R. & Chryssanthacopoulos, J. Climate forcing datasets for agricultural modeling: Merged products for gap-filling and historical climate series estimation. Agr. For. Meteorol. 200, 233–248 (2015).
Google Scholar 
Hempel, S., Frieler, K., Warszawski, L., Schewe, J. & Piontek, F. A trendpreserving bias correction-the ISI-MIP approach. Earth Syst. Dyn. 4, 219–236 (2013).ADS 

Google Scholar 
Monfreda, C., Ramankutty, N. & Foley, J. A. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Glob. Biogeochem. Cycles 22, 1022 (2008).ADS 

Google Scholar 
You, L.Z., et al. Spatial Production Allocation Model (SPAM) 2000 Version 3.2. http://mapspam.info (2015).Hoogenboom, G., et al. Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.6 (DSSAT Foundation, 2015). http://dssat.net (2015).Sacks, W. J., Deryng, D., Foley, J. A. & Ramankutty, N. Crop planting dates: An analysis of global patterns. Glob. Ecol. Biogeogr. 19, 607–620 (2010).
Google Scholar 
Batjes, H.N. A Homogenized Soil Data File for Global Environmental Research: A Subset of FAO. ISRIC and NRCS Profiles (Version 1.0). Working Paper and Preprint 95/10b (International Soil Reference and Information Centre, 1995).Xiong, W. et al. Can climate-smart agriculture reverse the recent slowing of rice yield growth in China?. Agric. Ecosyst. Environ. 196, 125–136 (2014).
Google Scholar 
Hertel, T. W. Global Trade Analysis: Modeling and Applications 5–30 (Cambridge University Press, 1997).
Google Scholar 
Corong, E. L., Hertel, T. W., McDougall, R., Tsigas, M. E. & Mensbrugghe, D. V. The standard GTAP model, version 7. J. Glob. Econ. Anal. 2(1), 1–119 (2017).
Google Scholar 
Ciscar, J. C. et al. Physical and economic consequences of climate change in Europe. PNAS 108, 2678–2683 (2011).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hsiang, S. et al. Estimating economic damage from climate change in the United States. Science 356(6345), 1362–1369 (2017).ADS 
CAS 
PubMed 

Google Scholar 
Taheripour, F., Hertel, T. W. & Liu, J. The role of irrigation in determining the global land use impacts of biofuels. Energy Sustain. Soc. 3(1), 4 (2013).
Google Scholar 
Ali, T., Huang, J. K. & Yang, J. Impact assessment of global and national biofuels developments on agriculture in Pakistan. Appl. Energy 104, 466–474 (2013).
Google Scholar 
Yang, J., Huang, J. K., Qiu, H. G., Rozelle, S. & Sombilla, M. A. Biofuels and the greater Mekong Subregion: Assessing the impact on prices, production and trade. Appl. Energy 86, S37–S46 (2009).
Google Scholar 
Horridge, M. SplitCom, programs to disaggregate a GTAP sector (Centre of Policy Studies, Vitorial University). https://www.copsmodels.com/splitcom.htm (2005).Taylor, K. E., Stouffer, B. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).ADS 

Google Scholar 
Zhou, B. T., Wen, H. Q. Z., Xu, Y., Song, L. C. & Zhang, X. B. Projected changes in temperature and precipitation extremes in China by the CMIP5 multimodel ensembles. J. Clim. 27, 6591–6611 (2014).ADS 

Google Scholar 
Knutti, R., Rogelj, J., Sedláček, J. & Ficher, E. M. A scientific critique of the two-degree climate change target. Nat. Geosci. 9(1), 1–6 (2015).
Google Scholar 
Rogelj, J. et al. Energy system transformations for limiting end-of-century warming to below 1.5°C. Nat. Clim. Change 5(6), 519–527 (2015).ADS 

Google Scholar 
Friedlingstein, P. et al. Persistent growth of CO2 emissions and implications for reaching climate targets. Nat. Geosci. 7(10), 709–715 (2014).ADS 
CAS 

Google Scholar 
Azar, C., Johansson, D. J. A. & Mattsson, N. Meeting global temperature targets the role of bioenergy with carbon capture and storage. Environ. Res. Lett. 8(3), 1345–1346 (2013).
Google Scholar 
Liu, B. et al. Testing the responses of four wheat crop models to heat stress at anthesis and grain filling. Glob. Change Biol. 22, 1890–1903 (2016).ADS 

Google Scholar 
Elad, Y. & Pertot, I. Climate change impacts on plant pathogens and plant diseases. J. Crop Improv. 28, 99–139 (2014).CAS 

Google Scholar 
Challinora, A. J. et al. Improving the use of crop models for risk assessment and climate change adaptation. Agric. Syst. 159, 296–306 (2018).
Google Scholar 
Bassu, S. et al. How do various maize crop models vary in their responses to climate change factors?. Glob. Change Biol. 20, 2301–2320 (2014).ADS 

Google Scholar 
Wang, N. et al. Increased uncertainty in simulated maize phenology with more frequent supra-optimal temperature under climate warming. Eur. J. Agron. 71, 19–33 (2015).
Google Scholar 
Rosenzweig, C. et al. Assessing agricultural risks of climate change in the twenty-first century in a global gridded crop model intercomparison. PNAS 111, 3268–3273 (2014).ADS 
CAS 
PubMed 

Google Scholar  More

Barnes, D. K. A., Galgani, F., Thompson, R. C. & Barlaz, M. Accumulation and fragmentation of plastic debris in global environments. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364, 1526 (2009).Article 

Google Scholar 
Cole, M., Lindeque, P., Halsband, C. & Galloway, T. S. Microplastics as contaminants in the marine environment: A review. Mar. Pollut. Bull. 62, 2588–2597 (2011).CAS 
PubMed 
Article 

Google Scholar 
Waller, C. L. et al. Microplastics in the Antarctic marine system: An emerging area of research. Sci. Total Environ. 598, 220–227 (2017).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Fang, C. et al. Microplastic contamination in benthic organisms from the Arctic and sub-Arctic regions. Chemosphere 209, 298–306 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Suaria, G. et al. Floating macro- and microplastics around the Southern Ocean: Results from the Antarctic Circumnavigation Expedition. Environ. Int. 136, 105494 (2020).PubMed 
Article 

Google Scholar 
Stark, J.S., Raymond, T., Deppeler, S.L. & Morrison, A.K. Antarctic Seas in World Seas: An Environmental Evaluation (ed. Sheppard, C.) 44 (Academic Press 2019).Mishra, A. K., Singh, J. & Mishra, P. P. Microplastics in Polar Regions: An early warning to the world’s pristine ecosystem. Sci. Total Environ. 784, 147149 (2021).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Bargagli, R. Environmental contamination in Antarctic ecosystems. Sci. Total Environ. 400, 212–226 (2008).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Gregory, M. R., Kirk, R. M. & Mabin, M. C. G. Pelagic tar, oil, plastics and other litter in surface waters of the New Zealand sector of the Southern Ocean, and on Ross Dependancy shores. N. Z. Antarct. Rec. 6, 12–26 (1984).
Google Scholar 
Van Franeker, J. A. & Bell, P. J. Plastic Ingestion by Petrels Breeding in Antarctica. Mar. Poll. Bull. 19(12), 672–674 (1988).Article 

Google Scholar 
Harper, P. C. & Fowler, J. A. Plastics pellets in New Zeland storm-killed prions (Pachyptila spp) 1958–1977. Notornis 34, 65–70 (1987).
Google Scholar 
Kelly, A. et al. Microplastic contamination in east Antarctic sea ice. Mar. Poll. Bull. 154, 111130 (2020).CAS 
Article 

Google Scholar 
Gigault, J. et al. Current opinion: What is a nanoplastic?. Environ. Pollut. 235, 1030–1034 (2018).CAS 
PubMed 
Article 

Google Scholar 
Dawson, A. et al. Turning microplastics into nanoplastics through digestive fragmentation by Antarctic krill. Nat. Commun. 9, 1001 (2018).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bergami, E. et al. Plastics everywhere: First evidence of polystyrene fragments inside the common Antarctic collembolan Cryptopygus antarcticus. Biol. Lett. 16, 20200093 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Sfriso, A. A. et al. Microplastic accumulation in benthic invertebrates in Terra Nova Bay (Ross Sea, Antarctica). Environ. Int. 137, 105587 (2020).CAS 
PubMed 
Article 

Google Scholar 
Jones-Williams, K. et al. Close encounters—microplastic availability to pelagic amphipods in sub-Antarctic and Antarctic surface waters. Environ. Int. 140, 105792 (2020).CAS 
PubMed 
Article 

Google Scholar 
Bessa, F. et al. Microplastics in gentoo penguins from the Antarctic region. Sci Rep 9, 14191 (2019).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Le Guen, C. et al. Microplastic study reveals the presence of natural and synthetic fibres in the diet of King Penguins (Aptenodytes patagonicus) foraging from South Georgia. Environ. Int. 134, 105303 (2020).PubMed 
Article 

Google Scholar 
Fragão, J. et al. Microplastics and other anthropogenic particles in Antarctica: Using penguins as biological samplers. Sci. Total Environ. 20, 788 (2021).
Google Scholar 
International Maritime Organization (IMO), Resolution A. 1087 (28): Guidelines for the Designation of Special Areas under MARPOL, in Assembly, 28th Session, Agenda Item 12, (2013).Waller, C. L. & Hughes, K. A. Plastics in the Southern Ocean. Antarct. 30, 269 (2018).Article 

Google Scholar 
Aves, A. R. First evidence of microplastics in Antarctic snow et al. First evidence of microplastics in Antarctic snow. Cryosphere 16, 2127–2145 (2022).ADS 
Article 

Google Scholar 
Vacchi, M., La Mesa, M. & Castelli, A. Diet of two coastal nototheniid fish from Terra Nova Bay, Ross Sea. Antarct. 6, 61–65 (1994).Article 

Google Scholar 
Froese, R., & Pauly D. (eds) FishBase. World Wide Web electronic publication—FishBase (September, 2022).La Mesa, M., Dalù, E. M. & Vacchi, M. Trophic ecology of the emerald notothen Trematomus bernacchii (Pisces, Nototheniidae) from Terra Nova Bay, Ross Sea, Antarctica. Polar Biol. 27, 721–728 (2004).Article 

Google Scholar 
Lamesa, M., Eastman, J. T. & Vacchi, M. The role of notothenioid fish in the food web of the Ross Sea shelf waters: A review. Polar Biol. 27, 321–338. https://doi.org/10.1007/s00300-004-0599-z (2004).Article 

Google Scholar 
Soggia, F., Ianni, C., Magi, E. & Frache, R. Antarctic environmental Specimen Bank in Environmental Contamination in Antarctica, a Challenge to Analytical Chemistry (ed. Caroli, S., Cescon, P., Walton, B.T.) 305–325 (Elsevier, 2001).Anger, P. M. et al. Raman microspectroscopy as a tool for microplastic particle analysis. TrAC Trends Analyt. Chem. 109, 214–226 (2018).CAS 
Article 

Google Scholar 
Savoca, S. et al. Microplastics occurrence in the Tyrrhenian waters and in the gastrointestinal tract of two congener species of seabreams. Environ. Toxicol. Pharmacol. 67, 35–41 (2019).CAS 
PubMed 
Article 

Google Scholar 
Capillo, G. et al. Quali-quantitative analysis of plastics and synthetic microfibers found in demersal species from Southern Tyrrhenian Sea (Central Mediterranean). Mar. Poll. Bull. 150, 110596 (2020).CAS 
Article 

Google Scholar 
Bottari, T. et al. Plastics occurrence in the gastrointestinal tract of Zeus faber and Lepidopus caudatus from the Tyrrhenian Sea. Mar. Poll. Bull. 146, 408–416 (2019).CAS 
Article 

Google Scholar 
Filgueiras, A. V., Preciado, I., Cartón, A. & Gago, J. Microplastic ingestion by pelagic and benthic fish and diet composition: A case study in the NW Iberian shelf. Mar. Poll. Bull. 160, 111623 (2020).CAS 
Article 

Google Scholar 
Mancuso, M. et al. Investigating the effects of microplastic ingestion in Scyliorhinus canicula from the South of Sicily. Sci. Total Environ. 850, 157875 (2022).ADS 
Article 

Google Scholar 
Savoca, S. et al. Ingestion of plastic and non-plastic microfibers by farmed gilthead sea bream (Sparus aurata) and common carp (Cyprinus carpio) at different life stages. Sci. Total Environ. 782, 146851 (2021).ADS 
CAS 
Article 

Google Scholar 
Rodrìguez-Romeu, O. et al. Are anthropogenic fibres a real problem for red mullets (Mullus barbatus) from the NW Mediterranean?. Sci. Total Environ. 733, 139336 (2020).ADS 
PubMed 
Article 

Google Scholar 
Bansode, M. A., Eastman, J. T. & Aronson, R. B. Feeding biomechanics of five demersal Antarctic fishes. Polar Biol. 37, 1835–1848. https://doi.org/10.1007/s00300-014-1565-z (2014).Article 

Google Scholar 
Munari, C. et al. Microplastics in the sediments of Terra Nova Bay (Ross Sea, Antarctica). Mar. Poll. Bull. 122, 161–165 (2017).CAS 
Article 

Google Scholar 
Cincinelli, A. et al. Microplastic in the surface waters of the Ross Sea (Antarctica): Occurrence, distribution and characterization by FTIR. Chemosphere 175, 391–400 (2017).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Eriksson, C. & Burton, H. Origins and biological accumulation of small plastic particles in fur seals from Macquarie Island. Ambio 32, 380–384 (2003).PubMed 
Article 

Google Scholar 
Carr, S. A. Sources and dispersive modes of micro-fibers in the environment. Integr. Environ. Assess. Manag 13(3), 466–469 (2017).CAS 
PubMed 
Article 

Google Scholar 
Gavigan, J. et al. Synthetic microfiber emissions to land rival those to waterbodies and are growing. PLoS ONE 15(9), e0237839 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Manshoven, E. et al. Microplastic pollution from textile consumption in Europe. Eionet Report – ETC/CE 2022/1 (2022).Remy, F. et al. When microplastic is not plastic: The ingestion of artificial cellulose fibers by macrofauna living in seagrass macrophytodetritus. Environ. Sci. Technol. 49, 11158–11166 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Savoca, S. et al. Detection of anthropogenic cellulose microfibers in Boops boops from the northern coasts of Sicily (Central Mediterranean). Sci. Total Environ. 691, 455–465 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Raina, M.A., Gloy, Y.S. & Gries, T. Weaving technologies for manufacturing denim in Denim. Woodhead Publishing Series in Textiles (ed. Paul, R.) 159–187 (2015).Lots, F. A. E. et al. A Large-Scale Investigation of Microplastic Contamination: Abundance and Characteristics of Microplastics in European Beach Sediment. Mar. Pollut. Bull. 123, 219–226 (2017).CAS 
PubMed 
Article 

Google Scholar 
Athey, S. N. et al. The Widespread Environmental Footprint of Indigo Denim Microfibers from Blue Jeans. Environ. Sci. Technol. Lett. 7, 840–847 (2020).CAS 
Article 

Google Scholar 
Lellis, B. et al. Effects of textile dyes on health and the environment and bioremediation potential of living organisms. Biotech. Res. Inn. 3, 275–290 (2019).Article 

Google Scholar 
Sandhya, S. Biodegradation of azodyes under anaerobic condition: Role of azoreductase Biodegradation of azo dyes. The handbook of environmental chemistry (ed. Erkurt ,H.A.) 9, 39–57 (Springer, 2010).Oehlmann, J.R. et al. A critical analysis of the biological impacts of plasticizers on wildlife. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364 (1526), 2047e2062 (2009).Aquino, J. M. et al. Electrochemical degradation of a real textile wastewater using β-PbO2 and DSA® anodes. Chem. Eng. J. 251, 138–145 (2014).CAS 
Article 

Google Scholar 
Newman, M. C. Fundamentals of Ecotoxicology: The Science of Pollution (CRC Press, 2015).
Google Scholar 
Khatri, J., Nidheesh, P. V., Singh, T. A. & Kumar, M. S. Advanced oxidation processes based on zero-valent aluminium for treating textile wastewater. Chem. Eng. J. 348, 67–73 (2018).CAS 
Article 

Google Scholar 
Athey, S. N. & Erdle, L. M. Are we underestimating anthropogenic microfiber pollution? A critical review of occurrence, methods, and reporting. Environ. Tox. Chem. 41, 822–837 (2022).CAS 
Article 

Google Scholar 
Stone, C., Windsor, F. M., Munday, M. & Durance, I. Natural or synthetic – how global trends in textile usage threaten freshwater environments. Sci. Total Environ. 718, 134689 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Wright, S. L. & Kelly, F. J. Plastic and human health: A micro issue?. Environ. Sci. Technol. 51, 6634–6647 (2017).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Ziajahromi, S., Neale, P. A. & Leusch, F. D. Wastewater treatment plant effluent as a source of microplastics: Review of the fate, chemical interactions and potential risks to aquatic organisms. Water Sci. Technol. 74(10), 2253–2269 (2016).CAS 
PubMed 
Article 

Google Scholar 
Aronson, R. B., Thatje, S., McClintock, J. B. & Hughes, K. A. Anthropogenic impacts on marine ecosystems in Antarctica. Ann. N. Y. Acad. Sci. 1223, 82–1072011 (2011).ADS 
PubMed 
Article 

Google Scholar 
Hynes, N. R. J. et al. Modern enabling techniques and adsorbents based dye removal with sustainability concerns in textile industrial sector – A comprehensive review. J. Clean. Prod. 272, 122636 (2020).CAS 
Article 

Google Scholar 
Savoca, S. et al. Plastics occurrence in juveniles of Engraulis encrasicolus and Sardina pilchardus in the Southern Tyrrhenian Sea. Sci Total Environ. 718, 137457 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Galgani, F., Hanke, G., Werner, S. D. V. L. & De Vrees, L. Marine litter within the European marine strategy framework directive. Ices J. Mar. Sci. 70, 1055–1064 (2013).Article 

Google Scholar 
Bottari, T. et al. Microplastics in the bogue, Boops boops: A snapshot of the past from the southern Tyrrhenian Sea. J. Hazardous Mat. 424(15), 127669 (2022).CAS 
Article 

Google Scholar 
Pedà, C. et al. Coupling gastro-intestinal tract analysis with an airborne contamination control method to estimate litter ingestion in demersal elasmobranchs. Front. Environ. Sci. 8, 119 (2020).Article 

Google Scholar  More

Sale, P. F. & Steneck, R. S. Critical Science Gaps Impede Use of No-take Fishery Reserves (University of Maine/University of New Hampshire Sea Grant College Program, 2005).Book 

Google Scholar 
Hilborn, R. & Walters, C. J. Quantitative Fisheries Stock Assessment: Choice, Dynamics and Uncertainty (Springer, 2013).
Google Scholar 
Hamilton, S. L., Regetz, J. & Warner, R. R. Postsettlement survival linked to larval life in a marine fish. Proc. Natl. Acad. Sci. 105, 1561–1566 (2008).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Raventos, N. & Macpherson, E. Effect of pelagic larval growth and size-at-hatching on post-settlement survivorship in two temperate labrid fish of the genus Symphodus. Mar. Ecol. Prog. Ser. 285, 205–211 (2005).ADS 
Article 

Google Scholar 
Johnson, D. W., Christie, M. R., Stallings, C. D., Pusack, T. J. & Hixon, M. A. Using post-settlement demography to estimate larval survivorship: A coral reef fish example. Oecologia 179, 729–739 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Garrido, S. et al. Born small, die young: Intrinsic, size-selective mortality in marine larval fish. Sci. Rep. 5, 17065 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Shima, J. S. et al. Reproductive phenology across the lunar cycle: Parental decisions, offspring responses, and consequences for reef fish. Ecology 101, e03086 (2020).PubMed 
Article 

Google Scholar 
Pini, J., Planes, S., Rochel, E., Lecchini, D. & Fauvelot, C. Genetic diversity loss associated to high mortality and environmental stress during the recruitment stage of a coral reef fish. Coral Reefs 30, 399–404 (2011).ADS 
Article 

Google Scholar 
Bourret, V., Dionne, M. & Bernatchez, L. Detecting genotypic changes associated with selective mortality at sea in Atlantic salmon: Polygenic multilocus analysis surpasses genome scan. Mol. Ecol. 23, 4444–4457 (2014).CAS 
PubMed 
Article 

Google Scholar 
Planes, S. & Lenfant, P. Temporal change in the genetic structure between and within cohorts of a marine fish, Diplodus sargus, induced by a large variance in individual reproductive success. Mol. Ecol. 11, 1515–1524 (2002).CAS 
PubMed 
Article 

Google Scholar 
Planes, S. & Romans, P. Evidence of genetic selection for growth in new recruits of a marine fish. Mol. Ecol. 13, 2049–2060 (2004).CAS 
PubMed 
Article 

Google Scholar 
Davidson, W. S. Adaptation genomics: Next generation sequencing reveals a shared haplotype for rapid early development in geographically and genetically distant populations of rainbow trout. Mol. Ecol. 21, 219–222 (2012).CAS 
PubMed 
Article 

Google Scholar 
Carreras, C. et al. East is east and west is west: Population genomics and hierarchical analyses reveal genetic structure and adaptation footprints in the keystone species Paracentrotus lividus (Echinoidea). Divers. Distrib. 26, 382–398 (2020).Article 

Google Scholar 
Carreras, C. et al. Population genomics of an endemic Mediterranean fish: Differentiation by fine scale dispersal and adaptation. Sci. Rep. 7, 43417 (2017).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Babbucci, M. et al. An integrated genomic approach for the study of mandibular prognathism in the European seabass (Dicentrarchus labrax). Sci. Rep. 6, 38673 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Barbanti, A. et al. Helping decision making for reliable and cost-effective 2b-RAD sequencing and genotyping analyses in non-model species. Mol. Ecol. Resour. 20, 795–806 (2020).CAS 
Article 

Google Scholar 
Torrado, H., Carreras, C., Raventos, N., Macpherson, E. & Pascual, M. Individual-based population genomics reveal different drivers of adaptation in sympatric fish. Sci. Rep. 10, 12683 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Xuereb, A. et al. Asymmetric oceanographic processes mediate connectivity and population genetic structure, as revealed by RADseq, in a highly dispersive marine invertebrate (Parastichopus californicus). Mol. Ecol. 27, 2347–2364 (2018).PubMed 
Article 

Google Scholar 
Benestan, L. et al. Seascape genomics provides evidence for thermal adaptation and current-mediated population structure in American lobster (Homarus americanus). Mol. Ecol. 25, 5073–5092 (2016).PubMed 
Article 

Google Scholar 
Lu, F. et al. Switchgrass genomic diversity, ploidy, and evolution: Novel insights from a network-based SNP discovery protocol. PLoS Genet. 9, e1003215 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wang, S., Meyer, E., McKay, J. K. & Matz, M. V. 2b-RAD: A simple and flexible method for genome-wide genotyping. Nat. Methods 9, 808–810 (2012).CAS 
PubMed 
Article 

Google Scholar 
Raventos, N. & Macpherson, E. Planktonic larval duration and settlement marks on the otoliths of Mediterranean littoral fishes. Mar. Biol. 138, 1115–1120 (2001).Article 

Google Scholar 
Torrado, H. et al. Impact of individual early life traits in larval dispersal: A multispecies approach using backtracking models. Prog. Oceanogr. 192, 102518 (2021).Article 

Google Scholar 
Schunter, C. et al. A novel integrative approach elucidates fine-scale dispersal patchiness in marine populations. Sci. Rep. 9, 10796 (2019).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hixon, M. A. & Carr, M. H. Synergistic predation, density dependence, and population regulation in marine fish. Science 277, 946–949 (1997).CAS 
Article 

Google Scholar 
Macpherson, E. et al. Mortality of juvenile fishes of the genus Diplodus in protected and unprotected areas in the western Mediterranean Sea. Mar. Ecol. Prog. Ser. 160, 135–147 (1997).ADS 
Article 

Google Scholar 
Macpherson, E. Ontogenetic shifts in habitat use and aggregation in juvenile sparid fishes. J. Exp. Mar. Biol. Ecol. 220, 127–150 (1998).Article 

Google Scholar 
Eckert, G. J. Estimates of adult and juvenile mortality for labrid fishes at One Tree Reef, Great Barrier Reef. Mar. Biol. 95, 167–171 (1987).Article 

Google Scholar 
Pascual, M., Rives, B., Schunter, C. & Macpherson, E. Impact of life history traits on gene flow: A multispecies systematic review across oceanographic barriers in the Mediterranean Sea. PLoS ONE 12, e0176419 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Schunter, C. et al. Matching genetics with oceanography: Directional gene flow in a Mediterranean fish species. Mol. Ecol. 20, 5167–5181 (2011).CAS 
PubMed 
Article 

Google Scholar 
Ciotti, B. J. & Planes, S. Within-generation consequences of postsettlement mortality for trait composition in wild populations: An experimental test. Ecol. Evol. 9, 2550–2561 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Yoklavich, M. M. & Bailey, K. M. Hatching period, growth and survival of young walleye pollock Theragra chalcogramma as determined from otolith analysis. Mar. Ecol. Prog. Ser. 64, 13–23 (1990).ADS 
Article 

Google Scholar 
Cargnelli, L. M. & Gross, M. R. The temporal dimension in fish recruitment: Birth date, body size, and size-dependent survival in a sunfish (bluegill: Lepomis macrochirus). Can. J. Fish. Aquat. Sci. 53, 360–367 (1996).Article 

Google Scholar 
Moginie, B. F. & Shima, J. S. Hatch date and growth rate drives reproductive success in nest-guarding males of a temperate reef fish. Mar. Ecol. Prog. Ser. 592, 197–206 (2018).ADS 
Article 

Google Scholar 
Sponaugle, S., Boulay, J. N. & Rankin, T. L. Growth- and size-selective mortality in pelagic­larvae of a common reef fish. Aquat. Biol. 13, 263–273 (2011).Article 

Google Scholar 
Biro, P. A., Abrahams, M. V., Post, J. R. & Parkinson, E. A. Behavioural trade-offs between growth and mortality explain evolution of submaximal growth rates. J. Anim. Ecol. 75, 1165–1171 (2006).PubMed 
Article 

Google Scholar 
Litvak, M. K. & Leggett, W. C. Age and size-selective predation on larval fishes: the bigger-is-better hypothesis revisited. Mar. Ecol. Prog. Ser. 81, 13–24 (1992).ADS 
Article 

Google Scholar 
D’Alessandro, E. K., Sponaugle, S. & Cowen, R. K. Selective mortality during the larval and juvenile stages of snappers (Lutjanidae) and great barracuda Sphyraena barracuda. Mar. Ecol. Prog. Ser. 474, 227–242 (2013).ADS 
Article 

Google Scholar 
Meekan, M. G. et al. Bigger is better: Size-selective mortality throughout the life history of a fast-growing clupeid, Spratelloides gracilis. Mar. Ecol. Progress Ser. 317, 237–244 (2006).ADS 
Article 

Google Scholar 
Takasuka, A., Aoki, I. & Mitani, I. Evidence of growth-selective predation on larval Japanese anchovy Engraulis japonicus in Sagami Bay. Mar. Ecol. Prog. Ser. 252, 223–238 (2003).ADS 
Article 

Google Scholar 
Sanford, E. & Kelly, M. W. Local adaptation in marine invertebrates. Ann. Rev. Mar. Sci. 3, 509–535 (2011).PubMed 
Article 

Google Scholar 
Raventos, N., Torrado, H., Arthur, R., Alcoverro, T. & Macpherson, E. Temperature reduces fish dispersal as larvae grow faster to their settlement size. J. Anim. Ecol. 90, 1419–1432 (2021).PubMed 
Article 

Google Scholar 
Logsdon, N. J., Deshpande, A., Harris, B. D., Rajashankar, K. R. & Walter, M. R. Structural basis for receptor sharing and activation by interleukin-20 receptor-2 (IL-20R2) binding cytokines. Proc. Natl. Acad. Sci. 109, 12704–12709 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Eldon, B., Riquet, F., Yearsley, J., Jollivet, D. & Broquet, T. Current hypotheses to explain genetic chaos under the sea. Curr. Zool. 62, 551–566 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Macpherson, E., Gordoa, A. & Garcia-Rubies, A. Biomass size spectra in littoral fishes in protected and unprotected areas in the NW Mediterranean. Estuarine Coast. Shelf Sci. 55, 777–788 (2002).ADS 
Article 

Google Scholar 
Garcia-Rubies, A. & Zabala I Limousin, M. Effects of total fishing prohibition on the rocky fish assemblages of Medes Islands marine reserve (NW Mediterranean). Sci. Mar. 54(4), 317–328 (1990).
Google Scholar 
Vigliola, L. et al. Spatial and temporal patterns of settlement among sparid fishes of the genus Diplodus in the northwestern Mediterranean. Mar. Ecol. Prog. Ser. 168, 45–56 (1998).ADS 
Article 

Google Scholar 
Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14, 927–930 (2003).Article 

Google Scholar 
Catchen, J., Hohenlohe, P. A., Bassham, S., Amores, A. & Cresko, W. A. Stacks: An analysis tool set for population genomics. Mol. Ecol. 22, 3124–3140 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Goudet, J. hierfstat, a package for r to compute and test hierarchical F-statistics. Mol. Ecol. Notes 5, 184–186 (2005).Article 

Google Scholar 
Jombart, T. adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405 (2008).CAS 
PubMed 
Article 

Google Scholar 
Wickham, H. ggplot2. (2009). https://doi.org/10.1007/978-0-387-98141-3.Forester, B. R., Lasky, J. R., Wagner, H. H. & Urban, D. L. Comparing methods for detecting multilocus adaptation with multivariate genotype-environment associations. Mol. Ecol. 27, 2215–2233 (2018).CAS 
PubMed 
Article 

Google Scholar 
Natsidis, P., Tsakogiannis, A., Pavlidis, P., Tsigenopoulos, C. S. & Manousaki, T. Phylogenomics investigation of sparids (Teleostei: Spariformes) using high-quality proteomes highlights the importance of taxon sampling. Commun. Biol. 2, 400 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Huerta-Cepas, J. et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol. Biol. Evol. 34, 2115–2122 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Al-Shahrour, F. et al. FatiGO: A functional profiling tool for genomic data: Integration of functional annotation, regulatory motifs and interaction data with microarray experiments. Nucleic Acids Res. 35, W91–W96 (2007).PubMed 
PubMed Central 
Article 

Google Scholar 
Supek, F., Bošnjak, M., Škunca, N. & Šmuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE 6, e21800 (2011).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wang, M., Zhao, Y. & Zhang, B. Efficient test and visualization of multi-set intersections. Sci. Rep. 5, 16923 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar  More

Sievers, M. et al. Trends Ecol. Evol. 34, 807–817 (2019).Article 

Google Scholar 
Barbier, E. B. et al. Ecol. Monogr. 81, 169–193 (2011).Article 

Google Scholar 
zu Ermgassen, P. S. E. et al. Estuar. Coast. Shelf Sci. 248, 107159 (2021).Article 

Google Scholar 
Spalding, M. & Parrett, C. L. Mar. Policy 110, 103540 (2019).Article 

Google Scholar 
Dahdouh-Guebas, F. et al. Estuar. Coast. Shelf Sci. 248, 106942 (2021).Article 

Google Scholar 
Dahdouh-Guebas, F. et al. Front. Mar. Sci. 7, 603651 (2020).Article 

Google Scholar 
Friess, D. A. & McKee, K. L. in Dynamic Sedimentary Environments of Mangrove Coasts (eds Sidik, F. & Friess, D.A.) Ch. 7 (Elsevier, 2021).Lee, S. Y. et al. Glob. Ecol. Biogeogr. 23, 726–743 (2014).Article 

Google Scholar 
Goldberg, L., Lagomasino, D., Thomas, N. & Fatoyinbo, T. Glob. Change Biol. 26, 5844–5855 (2020).Article 

Google Scholar 
Cannicci, S. et al. Proc. Natl Acad. Sci. USA 118, e2016913118 (2021).CAS 
Article 

Google Scholar 
Bouillon, S., Koedam, N., Raman, A. & Dehairs, F. Oecologia 130, 441–448 (2002).CAS 
Article 

Google Scholar 
Adame, M. F. et al. Glob. Chang. Biol. 27, 2856–2866 (2021).CAS 
Article 

Google Scholar 
Pittman, S. et al. Mar. Ecol. Prog. Ser. 663, 1–29 (2021).Article 

Google Scholar 
Nagelkerken, I., Sheaves, M. T., Baker, R. & Connolly, R. M. Fish Fish. 16, 362–371 (2015).Article 

Google Scholar 
Huxham, M., Whitlock, D., Githaiga, M. & Dencer-Brown, A. Curr. For. Rep. 4, 101–110 (2018).
Google Scholar 
Bryan-Brown, D. N. et al. Sci. Rep. 10, 7117 (2020).CAS 
Article 

Google Scholar 
Curnick, D. J. et al. Science 363, 239–239 (2019).Article 

Google Scholar 
Dahdouh-Guebas, F. & Cannicci, S. Front. Mar. Sci. 8, 799543 (2021).Article 

Google Scholar 
Bruelheide, H. et al. Nat. Ecol. Evol. 2, 1906–1917 (2018).Article 

Google Scholar 
Harvey, B. P., Marshall, K. E., Harley, C. D. G. & Russell, B. D. Trends Ecol. Evol. 37, 20–29 (2021).Article 

Google Scholar 
Rahman, M. M. et al. Nat. Commun. 12, 3875 (2021).CAS 
Article 

Google Scholar 
Yando, E. S. et al. Biol. Conserv. 263, 109355 (2021).Article 

Google Scholar 
Krauss, K. W. & Osland, M. J. Ann. Bot. 125, 213–234 (2020).PubMed 

Google Scholar 
Asbridge, E. F. et al. Estuar. Coast. Shelf Sci. 228, 106353 (2019).Article 

Google Scholar 
Sippo, J. Z., Lovelock, C. E., Santos, I. R., Sanders, C. J. & Maher, D. T. Estuar. Coast. Shelf Sci. 215, 241–249 (2018).Article 

Google Scholar 
Erftemeijer, P. L. A. & Hamerlynck, O. J. Coast. Res. 42, 228–235 (2005).
Google Scholar 
Abhik, S. et al. Sci. Rep. 11, 20411 (2021).CAS 
Article 

Google Scholar 
Osland, M. J., Day, R. H. & Michot, T. C. Divers. Distrib. 26, 1366–1382 (2020).Article 

Google Scholar 
Dahdouh-Guebas, F. et al. Curr. Biol. 15, 579–586 (2005).CAS 
Article 

Google Scholar 
Turschwell, M. P. et al. Biol. Conserv. 247, 108637 (2020).Article 

Google Scholar 
Saintilan, N. et al. Science 368, 1118–1121 (2020).CAS 
Article 

Google Scholar 
Xie, D. et al. Environ. Res. Lett. 15, 114033 (2020).Article 

Google Scholar 
Ewel, K. C., Twilley, R. R. & Ong, J. E. Glob. Ecol. Biogeogr. Lett. 7, 83–94 (1998).Article 

Google Scholar 
Dahdouh-Guebas, F. in Vers une Nouvelle Synthèse Ecologique: de L’écologie Scientifique au Développement Durable. (ed. Meerts, P.) 182–193 (Centre Paul Duvigneaud de Documentation Ecologique, 2013).Gallup, L., Sonnenfeld, D. A. & Dahdouh-Guebas, F. Ocean Coast. Manage. 185, 105001 (2020).Article 

Google Scholar 
Rist, S. & Dahdouh-Guebas, F. Environ. Dev. Sustain. 8, 467–493 (2006).Article 

Google Scholar 
Foell, J., Harrison, E. & Stirrat, R. L. Participatory Approaches to Natural Resource Management: The Case of Coastal Zone Management in the Puttalam District, Sri Lanka. Project R6977 (School of African and Asian Studies, University of Sussex, 2000).Beymer-Farris, B. A. & Bassett, T. J. Glob. Environ. Change 22, 332–341 (2012).Article 

Google Scholar 
Lovelock, C. E. & Brown, B. M. Nat. Ecol. Evol. 3, 1135 (2019).Article 

Google Scholar 
Dahdouh-Guebas, F. et al. J. Ethnobiol. Ethnomed. 2, 24 (2006).CAS 
Article 

Google Scholar  More

Vega, F. E., Rosenquist, E. & Collins, W. Global project needed to tackle coffee crisis. Nature 425, 343 (2003).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Craparo, A. C. W., Van Asten, P. J. A., Läderach, P., Jassogne, L. T. P. & Grab, S. W. Coffea arabica yields decline in Tanzania due to climate change: global implications. Agric. For. Meteorol. 207, 1–10 (2015).ADS 
Article 

Google Scholar 
Davis, A. P. et al. High extinction risk for wild coffee species and implications for coffee sector sustainability. Sci. Adv. 5, eaav3473 (2019).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Davis, A. P., Gole, T. W., Baena, S. & Moat, J. The impact of climate change on indigenous arabica coffee (Coffea arabica): predicting future trends and identifying priorities. PLoS ONE 7, e47981 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Davis, A. P., Mieulet, D., Moat, J., Sarmu, D. & Haggar, J. Arabica-like flavour in a heat-tolerant wild coffee species. Nat. Plants 7, 413–418 (2021).CAS 
PubMed 
Article 

Google Scholar 
Moat, J., Gole, T. W. & Davis, A. P. Least concern to endangered: applying climate change projections profoundly influences the extinction risk assessment for wild Arabica coffee. Global Change Biol. 25, 390–403 (2019).ADS 
Article 

Google Scholar 
Moat, J. et al. Resilience potential of the Ethiopian coffee sector under climate change. Nat. Plants 3, 17081 (2017).PubMed 
Article 

Google Scholar 
Kath, J. et al. Not so robust: Robusta coffee production is highly sensitive to temperature. Global Change Biol. 26, 3677–3688 (2020).ADS 
Article 

Google Scholar 
Liu, L. et al. Soil moisture dominates dryness stress on ecosystem production globally. Nat. Commun. 11, 1–9 (2020).ADS 
CAS 

Google Scholar 
Grossiord, C. et al. Plant responses to rising vapor pressure deficit. New Phytol. 226, 1550–1566 (2020).PubMed 
Article 

Google Scholar 
IPCC Climate Change 2022: Impacts, Adaptation, and Vulnerability (eds. Pörtner, H.-O. et al.) (Cambridge Univ. Press, 2022).Burke, M. et al. Higher temperatures increase suicide rates in the United States and Mexico. Nat. Clim. Change 8, 723–729 (2018).ADS 
Article 

Google Scholar 
Burke, M., Hsiang, S. M. & Miguel, E. Global non-linear effect of temperature on economic production. Nature 527, 235–239 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Duffy, K. A. et al. How close are we to the temperature tipping point of the terrestrial biosphere? Sci. Adv. 7, eaay1052 (2021).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Scheffer, M. et al. Early-warning signals for critical transitions. Nature 461, 53–59 (2009).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Schneider, S. H. Abrupt non-linear climate change, irreversibility and surprise. Global Environ. Change 14, 245–258 (2004).Article 

Google Scholar 
Lenton, T. M. Early warning of climate tipping points. Nat. Clim. Change 1, 201–209 (2011).ADS 
Article 

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

Google Scholar 
Lobell, D. B., Bänziger, M., Magorokosho, C. & Vivek, B. Nonlinear heat effects on African maize as evidenced by historical yield trials. Nat. Clim. Change 1, 42–45 (2011).ADS 
Article 

Google Scholar 
Lobell, D. B., Deines, J. M. & Tommaso, S. D. Changes in the drought sensitivity of US maize yields. Nat. Food 1, 729–735 (2020).Article 

Google Scholar 
Lobell, D. B. et al. Greater sensitivity to drought accompanies maize yield increase in the US Midwest. Science 344, 516–519 (2014).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Rigden, A., Mueller, N., Holbrook, N., Pillai, N. & Huybers, P. Combined influence of soil moisture and atmospheric evaporative demand is important for accurately predicting US maize yields. Nat. Food 1, 127–133 (2020).Article 

Google Scholar 
Schlenker, W. & Roberts, M. J. Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proc. Natl Acad. Sci. USA 106, 15594–15598 (2009).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
McDowell, N. G. et al. Mechanisms of woody-plant mortality under rising drought, CO2 and vapour pressure deficit. Nat. Rev. Earth Environ. 3, 294–308 (2022).ADS 
CAS 
Article 

Google Scholar 
Sinclair, T. R. et al. Limited-transpiration response to high vapor pressure deficit in crop species. Plant Sci. 260, 109–118 (2017).CAS 
PubMed 
Article 

Google Scholar 
López, J., Way, D. A. & Sadok, W. Systemic effects of rising atmospheric vapor pressure deficit on plant physiology and productivity. Global Change Biol. 27, 1704–1720 (2021).ADS 
Article 

Google Scholar 
McDowell, N. G. & Allen, C. D. Darcy’s law predicts widespread forest mortality under climate warming. Nat. Clim. Change 5, 669–672 (2015).ADS 
Article 

Google Scholar 
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 170191 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
You, L., Wood, S., Wood-Sichra, U. & Wu, W. Generating global crop distribution maps: from census to grid. Agric. Syst. 127, 53–60 (2014).Article 

Google Scholar 
Fong, Y., Huang, Y., Gilbert, P. B. & Permar, S. R. chngpt: threshold regression model estimation and inference. BMC Bioinformatics 18, 1–7 (2017).Article 

Google Scholar 
Qin, Y. et al. Agricultural risks from changing snowmelt. Nat. Clim. Change 10, 459–465 (2020).ADS 
Article 

Google Scholar 
Forster, P. M., Maycock, A. C., McKenna, C. M. & Smith, C. J. Latest climate models confirm need for urgent mitigation. Nat. Clim. Change 10, 7–10 (2020).ADS 
Article 

Google Scholar 
Forster, P. M. et al. Projections of when temperature change will exceed 2 °C above pre-industrial levels. Nat. Clim. Change 10, 407–412 (2011).
Google Scholar 
Joshi, M., Hawkins, E., Sutton, R., Lowe, J. & Frame, D. Projections of when temperature change will exceed 2 °C above pre-industrial levels. Nat. Clim. Change 1, 407–412 (2011).ADS 
Article 

Google Scholar 
IPCC, 2021: Summary for Policymakers. In Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, in press).Lobell, D. B. et al. The critical role of extreme heat for maize production in the United States. Nat. Clim. Change 3, 497–501 (2013).ADS 

Google Scholar 
Sinclair, T. R., Hammer, G. L. & Van Oosterom, E. J. Potential yield and water-use efficiency benefits in sorghum from limited maximum transpiration rate. Funct. Plant Biol. 32, 945–952 (2005).PubMed 
Article 

Google Scholar 
Martins, M. Q. et al. Protective response mechanisms to heat stress in interaction with high [CO2] conditions in Coffea spp. Front. Plant Sci. 7, 947 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Rodrigues, W. P. et al. Long‐term elevated air [CO2] strengthens photosynthetic functioning and mitigates the impact of supra‐optimal temperatures in tropical Coffea arabica and C. canephora species. Global Change Biol. 22, 415–431 (2016).ADS 
Article 

Google Scholar 
Ghini, R. et al. Coffee growth, pest and yield responses to free-air CO2 enrichment. Clim. Change 132, 307–320 (2015).ADS 
Article 

Google Scholar 
Rakocevic, M. et al. The vegetative growth assists to reproductive responses of Arabic coffee trees in a long-term FACE experiment. Plant Growth Regul. 91, 305–316 (2020).CAS 
Article 

Google Scholar 
Hammer, G. L. et al. Designing crops for adaptation to the drought and high‐temperature risks anticipated in future climates. Crop Sci. 60, 605–621 (2020).Article 

Google Scholar 
Gennari, P., Rosero-Moncayo, J. & Tubiello, F. N. The FAO contribution to monitoring SDGs for food and agriculture. Nat. Plants 5, 1196–1197 (2019).PubMed 
Article 

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

Google Scholar 
Ortiz-Bobea, A., Ault, T. R., Carrillo, C. M., Chambers, R. G. & Lobell, D. B. Anthropogenic climate change has slowed global agricultural productivity growth. Nat. Clim. Change 11, 306–312 (2021).ADS 
Article 

Google Scholar 
Davis, A. P. et al. Hot coffee: the identity, climate profiles, agronomy, and beverage characteristics of Coffea racemosa and C. zanguebariae. Front. Sustain. Food Syst. 5, 740137 (2021).Article 

Google Scholar 
Sarmiento-Soler, A. et al. Disentangling effects of altitude and shade cover on coffee fruit dynamics and vegetative growth in smallholder coffee systems. Agric. Ecosyst. Environ. 326, 107786 (2022).CAS 
Article 

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

Google Scholar 
Barton, K. MuMIn: multi-model inference. R-Forge http://r-forge.r-project.org/projects/mumin/ (2009).R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing https://www.r-project.org/ (2021).Harrison, X. A. et al. A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ 6, e4794 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Najafi, E., Devineni, N., Khanbilvardi, R. M. & Kogan, F. Understanding the changes in global crop yields through changes in climate and technology. Earths Future 6, 410–427 (2018).ADS 
CAS 
Article 

Google Scholar 
Ovalle-Rivera, O. et al. Assessing the accuracy and robustness of a process-based model for coffee agroforestry systems in Central America. Agrofor. Syst. 94, 2033–2051 (2020).Article 

Google Scholar 
Varma, S. & Simon, R. Bias in error estimation when using cross-validation for model selection. BMC Bioinformatics 7, 1–8 (2006).Article 

Google Scholar 
Yuan, W. et al. Increased atmospheric vapor pressure deficit reduces global vegetation growth. Sci. Adv. 5, eaax1396 (2019).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Son, H. & Fong, Y. Fast grid search and bootstrap-based inference for continuous two-phase polynomial regression models. Environmetrics 32, e2664 (2021).MathSciNet 
Article 

Google Scholar 
Wintgens, J. N. et al. Coffee: Growing, Processing, Sustainable Production. A Guidebook for Growers, Processors, Traders, and Researchers (Wiley, 2004). More

Birkeland, C. Coral Reefs in the Anthropocene (Springer, 2015).Book 

Google Scholar 
Kleypas, J. A., Mcmanus, J. W. & Meñez, L. A. B. Environmental limits to coral reef development: Where do we draw the line?. Am. Zool. 39(1), 146–159. https://doi.org/10.1093/icb/39.1.146 (1999).Article 

Google Scholar 
Perry, C. T. & Larcombe, P. Marginal and non-reef-building coral environments. Coral Reefs 22, 427–432. https://doi.org/10.1007/s00338-003-0330-5 (2003).Article 

Google Scholar 
Wilkinson, C. R. Global and local threats to coral reef functioning and existence: review and predictions. Mar. Freshw. Res. 50, 867–878. https://doi.org/10.1071/mf99121 (1999).Article 

Google Scholar 
Mies, M. et al. South atlantic coral reefs are major global warming refugia and less susceptible to bleaching. Front. Mar. Sci. 7, 514. https://doi.org/10.3389/fmars.2020.00514 (2020).Article 

Google Scholar 
Leão, Z. M. A. N. et al. Brazilian coral reefsin a period of global change: A synthesis. Braz. J. Oceanogr. 64, 97–116. https://doi.org/10.1590/S1679-875920160916064sp2 (2016).Article 

Google Scholar 
Coker, D. J., Wilson, S. K. & Pratchett, M. S. Importance of live coral habitat for reef fishes. Rev. Fish Biol. Fish. 24, 89–126. https://doi.org/10.1007/s11160-013-9319-5 (2014).Article 

Google Scholar 
Alvarez-Filip, L., Gill, J. A. & Dulvy, N. K. Complex reef architecture supports more small-bodied fishes and longer food chains on Caribbean reefs. Ecosphere 2, 118. https://doi.org/10.1890/ES11-00185.1 (2011).Article 

Google Scholar 
Wilson, S. K., Graham, N. A. J., Pratchett, M. S., Jones, G. P. & Polunin, N. V. C. Multiple disturbances and the global degradation of coral reefs: Are reef fishes at risk or resilient?. Glob. Change Biol. 12, 2220–2234. https://doi.org/10.1111/j.1365-2486.2006.01252.x (2006).ADS 
Article 

Google Scholar 
Sully, S., Burkepile, D. E., Donovan, M. K., Hodgson, G. & van Woesik, R. A global analysis of coral bleaching over the past two decades. Nat. Commun. 10, 1264. https://doi.org/10.1038/s41467-019-09238-2 (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Bellwood, D. R., Hughes, T. P., Folke, C. & Nystrom, M. Confronting the coral reef crisis. Nature 429, 827–833. https://doi.org/10.1038/nature02691 (2004).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Hughes, T. P. et al. climate change, human impacts, and the resilience of coral reefs. Science 301, 929–933. https://doi.org/10.1126/science.1085046 (2003).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Holbrook, N. J. et al. Keeping pace with marine heatwaves. Nat. Rev. Earth Environ. 1, 482–493. https://doi.org/10.1038/s43017-020-0068-4 (2020).ADS 
Article 

Google Scholar 
Bleuel, J., Pennino, M. G. & Longo, G. O. Coral distribution and bleaching vulnerability areas in Southwestern Atlantic under ocean warming. Sci. Rep. 11, 12833. https://doi.org/10.1038/s41598-021-92202-2 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Fontoura, L. et al. The macroecology of reef fish agonistic behaviour. Ecography 43, 1278–1290. https://doi.org/10.1111/ecog.05079 (2020).Article 

Google Scholar 
Inagaki, K. Y., Pennino, M. G., Floeter, S. R., Hay, M. E. & Longo, G. O. Trophic interactions will expand geographically but be less intense as oceans warm. Glob. Change Biol. 26, 6805–6812. https://doi.org/10.1111/gcb.15346 (2020).ADS 
Article 

Google Scholar 
Longo, G. O., Hay, M. E., Ferreira, C. E. L. & Floeter, S. R. Trophic interactions across 61 degrees of latitude in the Western Atlantic. Glob. Ecol. Biogeogr. 28, 107–117. https://doi.org/10.1111/geb.12806 (2019).Article 

Google Scholar 
Pratchett, M. S. et al. Effects of climate-induced coral bleaching on coral-reef fishes: Ecological and economic consequences. Oceanogr. Mar. Biol. Annu. Rev. 46, 251–296. https://doi.org/10.1201/9781420065756.ch6 (2008).Article 

Google Scholar 
Graham, N. A. J. et al. Lag effects in the impacts of mass coral bleaching on coral reef fish, fisheries, and ecosystems. Conserv. Biol. 21, 1291–1300. https://doi.org/10.1111/j.1523-1739.2007.00754.x (2007).Article 
PubMed 

Google Scholar 
Strona, G. et al. Global tropical reef fish richness could decline by around half if corals are lost. Proc. R. Soc. B 288, 20210274. https://doi.org/10.1098/rspb.2021.0274 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
McClenachan, L. Extinction risk in reef fishes 199–207 (Cambridge University Press, 2015).
Google Scholar 
Power, M. E. et al. Challenges in the quest for keystones. Bioscience 46, 609–620. https://doi.org/10.2307/1312990 (1996).Article 

Google Scholar 
Pereira, P. H. C. et al. The influence of multiple factors upon reef fish abundance and species richness in a tropical coral complex. Ichthyol. Res. 61, 375–384. https://doi.org/10.1007/s10228-014-0409-8 (2014).Article 

Google Scholar 
Coni, E. O. C. et al. An evaluation of the use of branching fire-corals (Millepora spp.) as refuge by reef fish in the Abrolhos Bank, eastern Brazil. Environ. Biol. Fish. 96, 45–55. https://doi.org/10.1007/s10641-012-0021-6 (2013).Article 

Google Scholar 
Graham, N. A. J. et al. Extinction vulnerability of coral reef fishes. Ecol. Lett. 14, 341–348. https://doi.org/10.1111/j.1461-0248.2011.01592.x (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Cornwell, W. K., Schwilk, D. W. & Ackerly, D. D. A trait-based test for habitat filtering: convex hull volume. Ecology 87, 1465–1471. https://doi.org/10.1890/0012-9658(2006)87[1465:ATTFHF]2.0.CO;2 (2006).Article 
PubMed 

Google Scholar 
Mouillot, D., Graham, N. A. J., Villéger, S., Mason, N. W. H. & Bellwood, D. R. A functional approach reveals community responses to disturbances. Trends Ecol. Evol. 28(3), 167–177. https://doi.org/10.1016/j.tree.2012.10.004 (2013).Article 
PubMed 

Google Scholar 
Pimiento, C. et al. Functional diversity of marine megafauna in the Anthropocene. Sci. Adv. 6, 7650. https://doi.org/10.1126/sciadv.aay7650 (2020).ADS 
Article 

Google Scholar 
Loiola, M. et al. Structure of marginal coral reef assemblages under different turbidity regime. Mar. Environ. Res. 147, 138–148. https://doi.org/10.1016/j.marenvres.2019.03.013 (2019).CAS 
Article 
PubMed 

Google Scholar 
Aued, A. W. et al. Large-scale patterns of benthic marine communities in the Brazilian Province. PLoS ONE 13, e0198452. https://doi.org/10.1371/journal.pone.0198452 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Leão, Z. M. A. N., Kikuchi, R. K. P. & Testa, V. Corals and Coral Reefs of Brazil 9–52 (Elsevier Publisher, 2003).
Google Scholar 
Pinheiro, H. T. et al. South-western Atlantic reef fishes: Zoogeographical patterns and ecological drivers reveal a secondary biodiversity centre in the Atlantic Ocean. Divers. Distrib. 24, 951–965. https://doi.org/10.1111/ddi.12729 (2018).Article 

Google Scholar 
Floeter, S. R. et al. Atlantic reef fish biogeography and evolution. J. Biogeogr. 35, 22–47. https://doi.org/10.1111/j.1365-2699.2007.01790.x (2008).Article 

Google Scholar 
Cord, I. et al. Brazilian marine biogeography: A multi-taxa approach for outlining sectorization. Mar. Biol. 169(5), 61. https://doi.org/10.1007/s00227-022-04045-8 (2022).Article 

Google Scholar 
Leal, I. C. S., Araújo, M. E. D., Cunha, S. R. D. & Pereira, P. H. C. The influence of fire-coral colony size and agonistic behaviour of territorial damselfish on associated coral reef fish communities. Mar. Environ. Res. 108, 45–54. https://doi.org/10.1016/j.marenvres.2015.04.009 (2015).CAS 
Article 
PubMed 

Google Scholar 
Kéry, M. & Royle, J. A. Applied hierarchical modeling in ecology: Analysis of distribution abundance and species richness in R and BUGS. In Prelude and Static Models Vol. 1 (eds Kéry, M. & Royle, J. A.) (Academic Press, 2016).MATH 

Google Scholar 
Hadj-Hammou, J., Mouillot, D. & Graham, N. A. J. Response and effect traits of coral reef fish. Front. Mar. Sci. https://doi.org/10.3389/fmars.2021.640619 (2021).Article 

Google Scholar 
McLean, M. et al. Trait similarity in reef fish faunas across the world’s oceans. PNAS 118(12), e2012318118. https://doi.org/10.1073/pnas.2012318118 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Brandl, S. J. et al. Coral reef ecosystem functioning: eight core processes and the role of biodiversity. Front. Ecol. Environ. 17, 445–454. https://doi.org/10.1002/fee.2088 (2019).Article 

Google Scholar 
Eggertsen, L. et al. Seaweed beds support more juvenile reef fish than seagrass beds in a south-western Atlantic tropical seascape. Estuar. Coast. Shelf S. 196, 97–108. https://doi.org/10.1016/j.ecss.2017.06.041 (2017).ADS 
Article 

Google Scholar 
Mouillot, D. et al. Functional over-redundancy and high functional vulnerability in global fish faunas on tropical reefs. PNAS 111, 13757–13762. https://doi.org/10.1073/pnas.1317625111 (2014).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Briggs, J. C. Marine Zoogeography (McGraw-Hill, 1974).
Google Scholar 
Garcia, G. S., Dias, M. S. & Longo, G. O. Trade-off between number and length of remote videos for rapid assessments of reef fish assemblages. J. Fish Biol. 99(3), 896–904. https://doi.org/10.1111/jfb.14776 (2021).Article 
PubMed 

Google Scholar 
Quimbayo, J. P. et al. Life-history traits, geographical range, and conservation aspects ofreef fishes from the Atlantic and Eastern Pacific. Ecology 102, e03298. https://doi.org/10.1002/ecy.3298 (2021).Article 
PubMed 

Google Scholar 
Katsanevakis, S. et al. Monitoring marine populations and communities: methods dealing with imperfect detectability. Aquat. Biol. 16, 31–52. https://doi.org/10.3354/ab00426 (2012).Article 

Google Scholar 
Villéger, S., Mason, N. W. H. & Mouillot, D. New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology 89, 2290–2301. https://doi.org/10.1890/07-1206.1 (2008).Article 
PubMed 

Google Scholar 
Maire, E., Grenouillet, G., Brosse, S. & Villéger, S. How many dimensions are needed to accurately assess functional diversity? A pragmatic approach for assessing the quality of functional spaces. Glob. Ecol. Biogeogr. 24, 728–740. https://doi.org/10.1111/geb.12299 (2015).Article 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021)Kellner, K. jagsUI: A Wrapper Around ‘rjags’ to Streamline ‘JAGS’ Analyses. R package version 1.5.2. https://CRAN.R-project.org/package=jagsUI (2021)Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).Book 

Google Scholar 
Ferreira, C. E. L., Gonçalves, J. E. A. & Coutinho, R. Community structure of fishes and habitat complexity on a tropical rocky shore. Environ. Biol. Fish. 61, 353–369 (2001).Article 

Google Scholar 
Fulton, C. J. et al. Macroalgal meadow habitats support fish and fisheries in diverse tropical seascapes. Fish Fish. 21, 700–717. https://doi.org/10.1111/faf.12455 (2020).Article 

Google Scholar 
Ferreira, L. C. L. et al. Different responses of massive and branching corals to a major heatwave at the largest and richest reef complex in South Atlantic. Mar. Biol. 168, 54. https://doi.org/10.1007/s00227-021-03863-6 (2021).CAS 
Article 

Google Scholar 
Lonzetti, B. C., Vieira, E. A. & Longo, G. O. Ocean warming can help zoanthids outcompete branching hydrocorals. Coral Reefs 41, 175–189. https://doi.org/10.1007/s00338-021-02212-9 (2022).Article 

Google Scholar 
Grillo, A. C., Candido, C. F., Giglio, V. J. & Longo, G. O. Unusual high coral cover in a Southwestern Atlantic subtropical reef. Mar. Biodivers. 51, 77. https://doi.org/10.1007/s12526-021-01221-9 (2021).Article 

Google Scholar 
Matheus, Z. et al. Benthic reef assemblages of the Fernando de Noronha Archipelago, tropical South-west Atlantic: Effects of depth, wave exposure and cross-shelf positioning. PLoS ONE 14(1), e0210664. https://doi.org/10.1371/journal.pone.0210664 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Meirelles, P. M. et al. Baseline assessment of mesophotic reefs of the vitória-trindade seamount chain based on water quality, microbial diversity, benthic cover and fish biomass data. PLoS ONE 10(6), e0130084. https://doi.org/10.1371/journal.pone.0130084 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Ferreira, C. E. L., Floeter, S. R., Gasparini, J. L., Ferreira, B. P. & Joyeux, J. C. Trophic structure patterns of Brazilian reef fishes: A latitudinal comparison. J. Biogeogr. 31, 1093–1106. https://doi.org/10.1111/j.1365-2699.2004.01044.x (2004).Article 

Google Scholar 
Fontoura, L. et al. Climate-driven shift in coral morphological structure predicts decline of juvenile reef fishes. Glob. Change Biol. 26, 557–567. https://doi.org/10.1111/gcb.14911 (2020).ADS 
Article 

Google Scholar 
MacNeil, M. A. et al. Accounting for detectability in reef-fish biodiversity estimates. Mar. Ecol.-Prog. Ser. 367, 249–260. https://doi.org/10.3354/meps07580 (2008).ADS 
Article 

Google Scholar 
Capitani, L., de Araujo, J. N., Vieira, E. A., Angelini, R. & Longo, G. O. Ocean warming will reduce standing biomass in a Tropical Western Atlantic reef ecosystem. Ecosystems 25, 843–857. https://doi.org/10.1007/s10021-021-00691-z (2022).Article 

Google Scholar 
Fogliarini, C. O., Longo, G. O., Francini-Filho, R. B., McClenachan, L. & Bender, M. G. Sailing into the past: Nautical charts reveal changes over 160 years in the largest reef complex in the South Atlantic Ocean. PECON 20(3), 231–239. https://doi.org/10.1007/10.1016/j.pecon.2022.05.003 (2022).Article 

Google Scholar 
Gasparini, J. L., Floeter, S. R., Ferreira, C. E. L. & Sazima, I. Marine ornamental trade in Brazil. Biodivers. Conserv. 14, 2883–2899. https://doi.org/10.1007/s10531-004-0222-1 (2005).Article 

Google Scholar 
Francini-Filho, R. B. et al. Brazil 163–198 (Springer, 2019).
Google Scholar 
Bellwood, D. R., Goatley, C. H. R. & Bellwood, O. The evolution of fishes and corals on reefs: Form, function and interdependence. Biol. Rev. 92, 878–901. https://doi.org/10.1111/brv.12259 (2017).Article 
PubMed 

Google Scholar 
Nunes, L. T. et al. Ecology of Prognathodes obliquus, a butterflyfish endemic to mesophotic ecosystems of St. Peter and St. Paul’s Archipelago. Coral Reefs 38, 955–960. https://doi.org/10.1007/s00338-019-01822-8 (2019).ADS 
Article 

Google Scholar 
Liedke, A. et al. Abundance, diet, foraging and nutritional condition of the banded butterflyfish (Chaetodon striatus) along the western Atlantic. Mar. Biol. 163, 6. https://doi.org/10.1007/s00227-015-2788-4 (2016).CAS 
Article 

Google Scholar  More