More stories

  • in

    Hibernation slows epigenetic ageing in yellow-bellied marmots

    Flatt, T. A new definition of aging? Front. Genet. 3, 148 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    Berdasco, M. & Esteller, M. Hot topics in epigenetic mechanisms of aging: 2011. Aging Cell 11, 181–186 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jylhävä, J., Pedersen, N. L. & Hägg, S. Biological age predictors. EBioMedicine 21, 29–36 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Wagner, K. H., Cameron-Smith, D., Wessner, B. & Franzke, B. Biomarkers of aging: from function to molecular biology. Nutrients 8, 338 (2016).
    Google Scholar 
    Field, A. E. et al. DNA methylation clocks in aging: categories, causes, and consequences. Mol. Cell 71, 882–895 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Horvath, S. et al. Decreased epigenetic age of PBMCs from Italian semi-supercentenarians and their offspring. Aging 7, 1159–1170 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nussey, D. H., Froy, H., Lemaitre, J. F., Gaillard, J. M. & Austad, S. N. Senescence in natural populations of animals: widespread evidence and its implications for bio-gerontology. Ageing Res. Rev. 12, 214–225 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Johnson, T. E. Recent results: biomarkers of aging. Exp. Gerontol. 41, 1243–1246 (2006).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Horvath, S. DNA methylation age of human tissues and cell types. Genome Biol. 14, R115 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Hannum, G. et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol. Cell 49, 359–367 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Unnikrishnan, A. et al. The role of DNA methylation in epigenetics of aging. Pharmacol. Ther. 195, 172–185 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bocklandt, S. et al. Epigenetic predictor of age. PLoS ONE 6, e14821 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Horvath, S. & Raj, K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat. Rev. Genet. 19, 371–384 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Polanowski, A. M., Robbins, J., Chandler, D. & Jarman, S. N. Epigenetic estimation of age in humpback whales. Mol. Ecol. Resour. 14, 976–987 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Petkovich, D. A. et al. Using DNA methylation profiling to evaluate biological age and longevity interventions. Cell Metab. 25, 954–960 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stubbs, T. M. et al. Multi-tissue DNA methylation age predictor in mouse. Genome Biol. 18, 68 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Wang, T. et al. Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment. Genome Biol. 18, 57 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Ito, G., Yoshimura, K. & Momoi, Y. Analysis of DNA methylation of potential age-related methylation sites in canine peripheral blood leukocytes. J. Vet. Med. Sci. 79, 745–750 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Thompson, M. J., von Holdt, B., Horvath, S. & Pellegrini, M. An epigenetic aging clock for dogs and wolves. Aging 9, 1055–1068 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lowe, R. et al. Ageing-associated DNA methylation dynamics are a molecular readout of lifespan variation among mammalian species. Genome Biol. 19, 22 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Zannas, A. S. et al. Lifetime stress accelerates epigenetic aging in an urban, African American cohort: relevance of glucocorticoid signaling. Genome Biol. 16, 266 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Zaghlool, S. B. et al. Association of DNA methylation with age, gender, and smoking in an Arab population. Clin. Epigenetics 7, 6 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Gao, X., Zhang, Y., Breitling, L. P. & Brenner, H. Relationship of tobacco smoking and smoking-related DNA methylation with epigenetic age acceleration. Oncotarget 7, 46878–46889 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Marioni, R. E. et al. The epigenetic clock and telomere length are independently associated with chronological age and mortality. Int. J. Epidemiol. 45, 424–432 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Marioni, R. E. et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol. 16, 25 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Perna, L. et al. Epigenetic age acceleration predicts cancer, cardiovascular, and all-cause mortality in a German case cohort. Clin. Epigenetics 8, 64 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Chen, B. H. et al. DNA methylation‐based measures of biological age: meta‐analysis predicting time to death. Aging 8, 1844–1859 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Christiansen, L. et al. DNA methylation age is associated with mortality in a longitudinal Danish twin study. Aging Cell 15, 149–154 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Horvath, S. & Levine, A. J. HIV-1 infection accelerates age according to the epigenetic clock. J. Infect. Dis. 212, 1563–1573 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Horvath, S. et al. Accelerated epigenetic aging in Down syndrome. Aging Cell 14, 491–495 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parrott, B. B. & Bertucci, E. M. Epigenetic aging clocks in ecology and evolution. Trends Ecol. Evol. 34, 767–770 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Wagner, W. Epigenetic aging clocks in mice and men. Genome Biol. 18, 107 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Wang, T. et al. Quantitative translation of dog-to-human aging by conserved remodeling of the DNA methylome. Cell Syst. 11, 176–185 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Wilkinson, G. S. & Adams, D. M. Recurrent evolution of extreme longevity in bats. Biol. Lett. 15, 20180860 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Austad, S. N. Comparative biology of aging. J. Gerontol. A 64, 199–201 (2009).
    Google Scholar 
    Wu, C. W. & Storey, K. B. Life in the cold: links between mammalian hibernation and longevity. Biomol. Concepts 7, 41–52 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Turbill, C., Bieber, C. & Ruf, T. Hibernation is associated with increased survival and the evolution of slow life histories among mammals. Proc. R. Soc. Lond. B 278, 3355–3363 (2011).
    Google Scholar 
    Chen, Y. et al. Mechanisms for increased levels of phosphorylation of elongation factor-2 during hibernation in ground squirrels. Biochemistry 40, 11565–11570 (2001).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Knight, J. E. et al. mRNA stability and polysome loss in hibernating Arctic ground squirrels (Spermophilus parryii). Mol. Cell. Biol. 20, 6374–6379 (2000).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Yan, J., Barnes, B. M., Kohl, F. & Marr, T. G. Modulation of gene expression in hibernating arctic ground squirrels. Physiol. Genomics 32, 170–181 (2008).CAS 

    Google Scholar 
    Van Breukelen, F. & Martin, S. L. Molecular adaptations in mammalian hibernators: unique adaptations or generalized responses? J. Appl. Physiol. 92, 2640–2647 (2002).
    Google Scholar 
    Morin, P. & Storey, K. B. Evidence for a reduced transcriptional state during hibernation in ground squirrels. Cryobiology 53, 310–318 (2006).CAS 

    Google Scholar 
    van Breukelen, F. & Martin, S. L. Reversible depression of transcription during hibernation. J. Comp. Physiol. B 172, 355–361 (2002).
    Google Scholar 
    Azzu, V. & Valencak, T. G. Energy metabolism and ageing in the mouse: a mini-review. Gerontology 63, 327–336 (2017).
    Google Scholar 
    Schrack, J. A., Knuth, N. D., Simonsick, E. M. & Ferrucci, L. ‘IDEAL’ aging is associated with lower resting metabolic rate: the Baltimore Longitudinal Study of Aging. J. Am. Geriatr. Soc. 62, 667–672 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Al-attar, R. & Storey, K. B. Suspended in time: molecular responses to hibernation also promote longevity. Exp. Gerontol. 134, 110889 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Carey, H. V., Andrews, M. T. & Martin, S. L. Mammalian hibernation: cellular and molecular responses to depressed metabolism and low temperature. Physiol. Rev. 83, 1153–1181 (2003).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Turbill, C., Ruf, T., Smith, S. & Bieber, C. Seasonal variation in telomere length of a hibernating rodent. Biol. Lett. 9, 20121095 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Turbill, C., Smith, S., Deimel, C. & Ruf, T. Daily torpor is associated with telomere length change over winter in Djungarian hamsters. Biol. Lett. 8, 304–307 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    Armitage, K. B., Blumstein, D. T. & Woods, B. C. Energetics of hibernating yellow-bellied marmots (Marmota flaviventris). Comp. Biochem. Physiol. A 134, 101–114 (2003).
    Google Scholar 
    Armitage, K. B. in Molecules to Migration: the Pressures of Life (eds Morris, S. & Vosloo, A.) 591–602 (Medimond Publishing, 2008).Haghani, A. et al. DNA methylation networks underlying mammalian traits. Preprint at bioRxiv https://doi.org/10.1101/2021.03.16.435708 (2021).Lu, A. T. et al. Universal DNA methylation age across mammalian tissues. Preprint at bioRxiv https://doi.org/10.1101/2021.01.18.426733 (2021).Yang, S. et al. Rare mutations in AHDC1 in patients with obstructive sleep apnea. Biomed. Res. Int. https://doi.org/10.1155/2019/5907361 (2019).De Paoli-Iseppi, R. et al. Measuring animal age with DNA methylation: from humans to wild animals. Front. Genet. 8, 106 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Arneson, A. et al. A mammalian methylation array for profiling methylation levels at conserved sequences. Nat. Commun. 13, 783 (2022).CAS 

    Google Scholar 
    Armitage, K. B. Reproductive strategies of yellow-bellied marmots: energy conservation and differences between the sexes. J. Mammal. 79, 385–393 (1998).
    Google Scholar 
    Armitage, K. B. in Adaptive Strategies and Diversity in Marmots (eds Ramousse, R. et al.) 133–142 (International Marmot Network, 2003).Snir, S., Farrell, C. & Pellegrini, M. Human epigenetic ageing is logarithmic with time across the entire lifespan. Epigenetics 14, 912–926 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Snir, S., VonHoldt, B. M. & Pellegrini, M. A statistical framework to identify deviation from time linearity in epigenetic aging. PLoS Comput. Biol. 12, e1005183 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Farrell, C., Snir, S. & Pellegrini, M. The epigenetic pacemaker: modeling epigenetic states under an evolutionary framework. Bioinformatics 36, 4662–4663 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Marioni, R. E. et al. Tracking the epigenetic clock across the human life course: a meta-analysis of longitudinal cohort data. J. Gerontol. A 74, 57–61 (2019).
    Google Scholar 
    El Khoury, L. Y. et al. Systematic underestimation of the epigenetic clock and age acceleration in older subjects. Genome Biol. 20, 283 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Kilgore, D. L. & Armitage, K. B. Energetics of yellow-bellied marmot populations. Ecology 59, 78–88 (1978).
    Google Scholar 
    Armitage, K. B. Social and population dynamics of yellow-bellied marmots: results from long-term research. Annu. Rev. Ecol. Syst. 22, 379–407 (1991).
    Google Scholar 
    Webb, D. R. Environmental harshness, heat stress, and Marmota flaviventris. Oecologia 44, 390–395 (1980).
    Google Scholar 
    Armitage, K. B. Evolution of sociality in marmots. J. Mammal. 80, 1–10 (1999).
    Google Scholar 
    Allainé, D. Sociality, mating system and reproductive skew in marmots: evidence and hypotheses. Behav. Processes 51, 21–34 (2000).
    Google Scholar 
    Arnold, W. The evolution of marmot sociality. II. Costs and benefits of joint hibernation. Behav. Ecol. Sociobiol. 27, 239–246 (1990).
    Google Scholar 
    Villanueva-Cañas, J. L., Faherty, S. L., Yoder, A. D. & Albà, M. M. Comparative genomics of mammalian hibernators using gene networks. Integr. Comp. Biol. 54, 452–462 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Lyman, C. P., O’Brien, R. C., Greene, G. C. & Papafrangos, E. D. Hibernation and longevity in the Turkish hamster Mesocricetus brandti. Science 212, 668–670 (1981).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kirby, R., Johnson, H. E., Alldredge, M. W. & Pauli, J. N. The cascading effects of human food on hibernation and cellular aging in free-ranging black bears. Sci. Rep. 9, 2197 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Giroud, S. et al. Late-born intermittently fasted juvenile garden dormice use torpor to grow and fatten prior to hibernation: consequences for ageing processes. Proc. R. Soc. Lond. B 281, 20141131 (2014).
    Google Scholar 
    Hoelzl, F. et al. Telomeres are elongated in older individuals in a hibernating rodent, the edible dormouse (Glis glis). Sci. Rep. 6, 36856 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Haussmann, M. F. & Mauck, R. A. Telomeres and longevity: testing an evolutionary hypothesis. Mol. Biol. Evol. 25, 220–228 (2008).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    van Lieshout, S. H. J. et al. Individual variation in early-life telomere length and survival in a wild mammal. Mol. Ecol. 28, 4152–4165 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Lowe, D., Horvath, S. & Raj, K. Epigenetic clock analyses of cellular senescence and ageing. Oncotarget 7, 8524–8531 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Kabacik, S., Horvath, S., Cohen, H. & Raj, K. Epigenetic ageing is distinct from senescence-mediated ageing and is not prevented by telomerase expression. Aging 10, 2800–2815 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Keil, G., Cummings, E. & Magalhães, J. P. Being cool: how body temperature influences ageing and longevity. Biogerontology 16, 383–397 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Means, L. W., Higgins, J. L. & Fernandez, T. J. Mid-life onset of dietary restriction extends life and prolongs cognitive functioning. Physiol. Behav. 54, 503–508 (1993).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Speakman, J. R. & Mitchell, S. E. Caloric restriction. Mol. Aspects Med. 32, 159–221 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Walford, R. L. & Spindler, S. R. The response to calorie restriction in mammals shows features also common to hibernation: a cross-adaptation hypothesis. J. Gerontol. A 52, B179–B183 (1997).CAS 

    Google Scholar 
    Conti, B. et al. Transgenic mice with a reduced core body temperature have an increased life span. Science 314, 825–828 (2006).CAS 

    Google Scholar 
    Conti, B. Considerations on temperature, longevity and aging. Cell. Mol. Life Sci. 65, 1626–1630 (2008).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gribble, K. E., Moran, B. M., Jones, S., Corey, E. L. & Mark Welch, D. B. Congeneric variability in lifespan extension and onset of senescence suggest active regulation of aging in response to low temperature. Exp. Gerontol. 114, 99–106 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Johns, D. W. & Armitage, K. B. Behavioral ecology of alpine yellow-bellied marmots. Behav. Ecol. Sociobiol. 5, 133–157 (1979).
    Google Scholar 
    Armitage, K. B. Social behaviour of a colony of the yellow-bellied marmot (Marmota flaviventris). Anim. Behav. 10, 319–331 (1962).
    Google Scholar 
    Armitage, K. B. Vernal behaviour of the yellow-bellied marmot (Marmota flaviventris). Anim. Behav. 13, 59–68 (1965).
    Google Scholar 
    Armitage, K. B., Melcher, J. C. & Ward, J. M. Oxygen consumption and body temperature in yellow-bellied marmot populations from montane-mesic and lowland-xeric environments. J. Comp. Physiol. B 160, 491–502 (1990).
    Google Scholar 
    Sheriff, M. J., Williams, C. T., Kenagy, G. J., Buck, C. L. & Barnes, B. M. Thermoregulatory changes anticipate hibernation onset by 45 days: data from free-living arctic ground squirrels. J. Comp. Physiol. B 182, 841–847 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    Schwartz, C., Hampton, M. & Andrews, M. T. Hypothalamic gene expression underlying pre-hibernation satiety. Genes Brain Behav. 14, 310–318 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Geiser, F. Metabolic rate and body temperature reduction during hibernation and daily torpor. Annu. Rev. Physiol. 66, 239–274 (2004).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Maegawa, S. et al. Widespread and tissue specific age-related DNA methylation changes in mice. Genome Res. 20, 332–340 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hampton, M., Melvin, R. G. & Andrews, M. T. Transcriptomic analysis of brown adipose tissue across the physiological extremes of natural hibernation. PLoS ONE 8, e85157 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Lindner, M. et al. Temporal changes in DNA methylation and RNA expression in a small song bird: within- and between-tissue comparisons. BMC Genomics 22, 36 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schwartz, C., Hampton, M. & Andrews, M. T. Seasonal and regional differences in gene expression in the brain of a hibernating mammal. PLoS ONE 8, e58427 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dopico, X. C. et al. Widespread seasonal gene expression reveals annual differences in human immunity and physiology. Nat. Commun. 6, 7000 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jansen, H. T. et al. Hibernation induces widespread transcriptional remodeling in metabolic tissues of the grizzly bear. Commun. Biol. 2, 336 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Viitaniemi, H. M. et al. Seasonal variation in genome-wide DNA methylation patterns and the onset of seasonal timing of reproduction in great tits. Genome Biol. Evol. 11, 970–983 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Johnston, R. A., Paxton, K. L., Moore, F. R., Wayne, R. K. & Smith, T. B. Seasonal gene expression in a migratory songbird. Mol. Ecol. 25, 5680–5691 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Boyer, B. B. & Barnes, B. M. Molecular and metabolic aspects of mammalian hibernation. Bioscience 49, 713–724 (1999).
    Google Scholar 
    Siutz, C., Ammann, V. & Millesi, E. Shallow torpor expression in free-ranging common hamsters with and without food supplements. Front. Ecol. Evol. 6, 190 (2018).
    Google Scholar 
    Langer, F., Havenstein, N. & Fietz, J. Flexibility is the key: metabolic and thermoregulatory behaviour in a small endotherm. J. Comp. Physiol. B 188, 553–563 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Bieber, C., Turbill, C. & Ruf, T. Effects of aging on timing of hibernation and reproduction. Sci. Rep. 8, 13881 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Storey, K. B. & Storey, J. M. Aestivation: signaling and hypometabolism. J. Exp. Biol. 215, 1425–1433 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Krivoruchko, A. & Storey, K. B. Forever young: mechanisms of natural anoxia tolerance and potential links to longevity. Oxid. Med. Cell. Longev. 3, 186–198 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    Storey, K. B. & Storey, J. M. Metabolic rate depression in animals: transcriptional and translational controls. Biol. Rev. 79, 207–233 (2004).PubMed 
    PubMed Central 

    Google Scholar 
    Puspitasari, A. et al. Hibernation as a tool for radiation protection in space exploration. Life 11, 54 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Blumstein, D. T. Yellow-bellied marmots: insights from an emergent view of sociality. Philos. Trans. R. Soc. Lond. B 368, 20120349 (2013).
    Google Scholar 
    Armitage, K. B. & Downhower, J. F. Demography of yellow-bellied marmot populations. Ecology 55, 1233–1245 (1974).
    Google Scholar 
    Zhou, W., Triche, T. J., Laird, P. W. & Shen, H. SeSAMe: reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions. Nucleic Acids Res. 46, e123 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Labarre, B. A. et al. MethylToSNP: identifying SNPs in Illumina DNA methylation array data. Epigenetics Chromatin 12, 79 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Snir, S., Wolf, Y. I. & Koonin, E. V. Universal pacemaker of genome evolution. PLoS Comput. Biol. 8, e1002785 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zou, H. & Hastie, T. Regularization and variable selection via the elastic net. J. R. Stat. Soc. B 67, 301–320 (2005).
    Google Scholar 
    Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1–22 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    Snir, S. & Pellegrini, M. An epigenetic pacemaker is detected via a fast conditional expectation maximization algorithm. Epigenomics 10, 695–706 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wood, S. & Scheipl, F. gamm4: Generalized additive mixed models using mgcv and lme4, R package version 0.2-3 (2014); http://cran.r-project.org/package=gamm4R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).RStudio Team. RStudio: Integrated Development Environment for R (RStudio Inc., 2019).Van Rossum, G. & Drake, F. L. Python 3 Reference Manual (CreateSpace, 2009).Kluyver, T. et al. in Positioning and Power in Academic Publishing: Players, Agents and Agendas (eds Loizides, F. & Scmidt, B.) 87–90 (IOS Press, 2016); https://doi.org/10.3233/978-1-61499-649-1-87Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).Kassambara, A. ggpubr: ‘ggplot2’ based publication ready plots https://cran.r-project.org/package=ggpubr (2020).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).
    Google Scholar 
    Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017).
    Google Scholar 
    Mclean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pinho, G. M. et al. Hibernation slows epigenetic ageing in yellow-bellied marmots data sets. OSF https://doi.org/10.17605/OSF.IO/E42ZV (2021). More

  • in

    The biology of beauty sleep

    Wang, L. C. H. & Lee, T.-F. in Life in the Cold (eds Heldmaier, G. & Klingenspor, M.) 149–158 (Springer, 2000).van Breukelen, F. & Martin, S. L. J. Appl. Physiol. 92, 2640–2647 (2002).Article 

    Google Scholar 
    Turbill, C., Bieber, C. & Ruf, T. Proc. R. Soc. Lond. B 278, 3355–3363 (2011).
    Google Scholar 
    Pinho, G. M. et al. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-022-01679-1 (2022).Article 

    Google Scholar 
    Oli, M. K. & Armitage, K. B. Oecologia 136, 543–550 (2003).Article 

    Google Scholar 
    Horvath, S. Genome Biol. 14, 3156 (2013).Article 

    Google Scholar 
    Anderson, J. A. et al. eLife 10, e66128 (2021).CAS 
    Article 

    Google Scholar 
    Larison, B. et al. Commun. Biol. 4, 1412 (2021).Article 

    Google Scholar 
    Dausmann, K. H., Glos, J., Ganzhorn, J. U. & Heldmaier, G. Nature 429, 825–826 (2004).CAS 
    Article 

    Google Scholar 
    Wilkinson, G. S. & Adams, D. M. et al. Biol. Lett. 15, 20180860 (2019).Article 

    Google Scholar 
    Jansen, H. T. et al. Commun. Biol. 2, 336 (2019).Article 

    Google Scholar 
    Medawar, P. B. An Unsolved Problem Of Biology (H. K. Lewis & Co., 1952). More

  • in

    Rewilding Argentina: lessons for the 2030 biodiversity targets

    Download PDF

    When Mariuá, a 1.5-year-old female jaguar, set foot in our breeding centre in Argentina in December 2018, we did not know that she would make history. Two years later, she walked out with two cubs: the first jaguars to roam the 1.4 million hectares of the Iberá wetlands of northeastern Argentina for at least 70 years. Mariuá and her cubs have started to reverse a process that some had thought irreversible.Within decades, one million species out of a total of some eight million could go extinct globally1. Hunting, habitat loss and ecosystem degradation are propelling this unprecedented biodiversity crisis. Current extinction rates are 100 to 1,000 times higher than in the past several million years.Argentina is no exception. Over the past 150 years, 5 bird and 4 mammal species have gone extinct. Today, about 17% of the country’s 3,000 vertebrate species are imperilled2, and 13 out of the 18 extant species of large mammal, from anteaters to tapirs, are experiencing catastrophic declines, in terms of both number and geographical range (see http://cma.sarem.org.ar).In 1998, we started a rewilding programme in Argentina to try to reverse this appalling loss. Our non-profit foundation, Fundación Rewilding Argentina, was spun out from the US non-profit organization Tompkins Conservation. We create protected areas where we can reintroduce native species, re-establish their interactions, restore ecosystem functionality and build valuable ecotourism based on wildlife viewing.Both rewilding and ecotourism can be controversial. We think that our work is an instructive example of how active restoration of crucial species, when done responsibly, can benefit both ecosystems and local people. It should be in the toolkit for meeting the 2030 biodiversity targets that will be discussed at the Convention on Biological Diversity’s Conference of the Parties in Kunming, China, next month.Three stepsThe popularity of rewilding projects is growing. These include: wolves brought back to Yellowstone National Park in Wyoming, beavers to England, bison and musk ox to northern Russia, leopards to Mozambique and Tasmanian devils to mainland Australia. The International Union for Conservation of Nature reports that, since 2008, at least 418 reintroduction projects have been started3. Most of these projects occur in protected areas and involve one or a few species. Our work in Argentina is broader.As a first step, we acquire private lands with philanthropic funds, reintroduce many species and form government-protected areas that are donated to federal and provincial governments. So far, we have purchased and donated about 400,000 hectares, with an estimated market value of US$91 million. This has created and enlarged six national parks, one national reserve and two provincial parks. Another 100,000 hectares are being donated. Together, these lands comprise a little over 10% of the total terrestrial area currently managed by the National Parks Administration of Argentina.The second step is to restore ecosystems, mainly by reintroducing species at an unprecedented scale. We spend more than $3 million each year on rewilding activities in three regions: the Iberá wetlands in the northeast, the dry Chaco forests in the north and the Patagonian steppe and coast in the south. Most often, we work with species deemed to have large impacts at the ecosystem level, such as large predators and herbivores.

    Jaguars now roam Argentina’s Iberá wetlands for the first time in more than 70 years.Credit: Matías Rebak

    Thus far, we have successfully reintroduced pampas deer, giant anteaters and collared peccaries (a pig-like, hoofed animal). We have also started founding populations of jaguars, coypus (large aquatic rodents), Wolffsohn’s viscachas (rodents that resemble a large chinchilla), red-and-green macaws and bare-faced curassows (birds related to chickens and pheasants). We are currently working on the reintroduction of 14 species.As they become abundant, reintroduced species re-weave the fabric of ecological relationships. For example, jaguars (Panthera onca) and macaws (Ara chloropterus) are reviving a crucial interaction: predation. Jaguars have begun to prey on eight species, including native rodents and feral hogs, which could limit those populations and thus benefit vegetation growth. The macaws are consuming 49 plant species, which could enhance seed dispersal, although this remains to be tested.
    Include the true value of nature when rebuilding economies after coronavirus
    Third, we invest heavily in infrastructure, capacity building and publicity to create an economy based on ecotourism. The species we work with are often highly charismatic, which benefits local communities, creating an economic incentive to conserve native wildlife and habitats. We organize workshops and courses so that locals can train as nature guides, cooks, craftspeople and more. In Iberá, where our work is most advanced, tourist visits increased by 87% between 2015 and 2021, according to official data from the Iberá wetland management agency. There were more than 50,000 visitors last year, despite the COVID-19 pandemic.All of these steps are important: simply setting aside protected areas is not enough. Globally, most modern ecosystems are ecologically damaged4, even in long-standing protected areas5. In Argentina, for example, functional populations of jaguars are missing from 19 of 22 national parks where historical distribution data suggest this key apex predator should occur.Jaguars and capybarasOur flagship project is the rewilding of the Iberá wetland. There, we are working on the restoration of nine species, including jaguars, which were eradicated from this area more than 70 years ago. We have now established a founding population of eight individuals: one adult male and three adult females, two of which (including Mariuá) were each released with two cubs aged four months. Our goal is to release a total of 20 individuals by 2027.Of all the species we work with, giant otters (Pteronura brasiliensis) and macaws have been the most difficult. Both species are extinct in the wild in Argentina. Bureaucratic hurdles have made sourcing wild individuals from neighbouring countries impossible.We obtained two pairs of giant otters from European zoos, and are holding them in pens in the core of Iberá. After several attempts, one pair bred successfully and the female gave birth to three cubs, producing the first litter born in the country for more than 30 years. We plan to release this family to the wild next year.

    This female giant river otter, together with a male and their three cubs, will be released to the wild in Argentina next year to create a founding population.Credit: Matías Rebak

    We source macaws, which have been extinct in the wild in Argentina for 100 years, from zoos, wildlife shelters and breeding centres. Because of their captive origin, we must give them the opportunity to practise flying in an aviary. We provide them with native foods, so that they learn what to eat, and we use a remote-controlled stuffed fox to teach them to avoid predators. This training isn’t always successful. Out of the 87 macaws that we have worked with, 48 were healthy and skilled enough to release. Two founding populations now thrive in the wild; one of them began reproducing in 2020.Efforts elsewhere have demonstrated the powerful effects of restoring species. In the northeast Pacific Ocean, reintroduced sea otters (Enhydra lutris) have voraciously eaten sea urchins, which in turn has allowed the return of lush kelp forests6. In Yellowstone Park, some researchers argue that reintroduced wolves have discouraged herbivores from foraging along stream edges, which might have increased tree growth and stabilized stream banks7. In Mozambique’s Gorongosa Park, the return of wildebeest and other large herbivores has curtailed Mimosa pigra, an undesirable invasive shrub8.
    Biodiversity needs every tool in the box: use OECMs
    Our rewilding work in Argentina could also have profound impacts. Close monitoring of the female jaguars and their cubs in the Iberá wetland has shown that they are largely feeding on the most abundant native prey: capybaras (Hydrochoerus hydrochaeris). Reducing the number of capybaras is expected to allow more vegetation to thrive, providing habitat for arthropods and small vertebrates, and possibly increasing carbon sequestration9. It could also help to reduce the transmission of sarcoptic mange, a density-dependent disease plaguing the capybara population. Jaguars also prey on foxes, which might benefit threatened bird species. We are working with several academic institutions to test how the return of the jaguar is reshaping the ecosystem.Challenges and caveatsAs our rewilding work gained momentum, critics ramped up from different fronts. At first, some were fearful of our policy of acquiring private lands with funds provided largely by foreign philanthropists. Those concerns faded when we began donating the land to federal and provincial governments.Then, ranchers argued that we were taking agricultural land out of production and reintroducing or boosting populations of animals that would conflict with their livestock. For example, in Patagonia, we established several protected areas where pumas (Puma concolor) and guanacos (Lama guanicoe, a relative of the llama) thrive. For almost a century, ranchers have trapped, shot and poisoned these animals, blaming them for killing sheep and competing for forage, respectively. We are conducting research to quantify the impact of pumas and guanacos on livestock, and offering alternative job opportunities based on wildlife viewing.

    Red-and-green macaws went extinct in Argentina in the late 1800s. Rewilding efforts that began in 2016 have now established two founding populations in the Iberá wetlands.Credit: Matías Rebak

    Federal and state managers, and often academics, argue that some founding populations of reintroduced species are too small and genetically related to create a viable, long-term population. This is true in some cases. But careful releases of unrelated animals can sidestep this issue. Worries about the spread of diseases when translocating individuals is also often invoked as a reason to halt rewilding activities. We implement thorough health checks and rigorous quarantines to decrease the risk of introducing unwanted diseases in the regions where we work.Concerns are sometimes raised about whether reintroduced species will recreate historical conditions, or instead create something new. Rewilding, however, seeks to regenerate and maintain ecological processes and biodiversity, rather than reaching some specific, historical equilibrium10. We think it is preferable to assume the uncertainties in trying to restore ecosystems, rather than accepting their degraded state.
    Protect the last of the wild
    Another worry is the possible impacts that tourism can have on climate, biodiversity and society — for instance, on water use, aviation emissions, road building and so on. Our strategy is to limit visitor numbers and avoid crowding by constructing multiple access gates on existing dirt roads.There are many policies that hinder rather than help rewilding. In Argentina, the laws that regulate transportation of wildlife species are built on the assumption that such activities always represent a threat to conservation. Wild animals can typically be imported to the country only through an airport in Buenos Aires. Because of this, an animal that could be driven in a truck from Brazil in a few hours must instead fly more than 1,500 kilometres and then be driven all the way back to its release area. Receiving wild animals at another international port, or moving them around within the country, requires special permits that often take months to obtain. Regulations could be altered to ease rewilding efforts while still policing the illegal wildlife trade.Next stepsNature-based tourism has been growing globally at rates of more than 4% per year, particularly in low- and middle-income countries11. Charismatic fauna, including large predators, are becoming increasingly important. In the Brazilian Pantanal, the world’s largest wetland, wildlife viewing — mostly of jaguars — generated an annual revenue of $6.8 million in 2015. This is three times the revenue obtained from traditional cattle ranching in that region12.With about 97% of the planet’s land surface ravaged by humans4, nature is facing its last stand. Urgent measures are needed not only to halt but also to reverse ecosystem and biodiversity loss. The active reintroduction of key species is one powerful way to heal some degraded ecosystems.This daunting task should not fall solely to non-profit organizations that have limited funds and staff, like us. The United Nations launched its Decade on Ecosystem Restoration in June 2021, calling for massive restoration efforts worldwide to heal nature and the climate. To achieve meaningful results at a global scale, rewilding needs the support of many stakeholders and effective international cooperation. Crucially, it requires the active involvement of governments to facilitate, fund and lead restoration efforts.

    Nature 603, 225-227 (2022)
    doi: https://doi.org/10.1038/d41586-022-00631-4

    ReferencesIPBES. Summary for Policymakers of the Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (eds Diaz, S. et al.) (IPBES, 2019).
    Google Scholar 
    Bauni, V. et al. Zookeys 1085, 101–127 (2022).Article 

    Google Scholar 
    Soorae, P. S. (ed.) Global Conservation Translocation Perspectives: 2021. Case Studies from Around the Globe (IUCN SSC Conservation Translocation Specialist Group, Environment Agency — Abu Dhabi & Calgary Zoo, 2021).
    Google Scholar 
    Plumptre, A. J. et al. Front. For. Glob. Chang. https://doi.org/10.3389/ffgc.2021.626635 (2021).Article 

    Google Scholar 
    Jones, K. R. et al. Science 360, 788–791 (2018).PubMed 
    Article 

    Google Scholar 
    Estes, J. A. & Duggins, D. O. Ecol. Monogr. 65, 75–100 (1995).Article 

    Google Scholar 
    Allen, B. L. et al. Food Webs 12, 64–75 (2017).Article 

    Google Scholar 
    Guyton, J. A. et al. Nature Ecol. Evol. 4, 712–724 (2020).PubMed 
    Article 

    Google Scholar 
    Schmitz, O. J. et al. Science 362, eaar3213 (2018).PubMed 
    Article 

    Google Scholar 
    Svenning, J. C., Munk, M. & Schweiger, A. in Rewilding (eds Pettorelli, N., Durant, S. M. & Du Toit, J. T.) 73–98 (Cambridge Univ. Press, 2019).
    Google Scholar 
    Balmford, A. et al. PLoS Biol. 7, e1000144 (2009).PubMed 
    Article 

    Google Scholar 
    Tortato, F. R., Izzo, T. J., Hoogesteijn, R. & Peres, C. A. Glob. Ecol. Conserv. 11, 106–114 (2017).Article 

    Google Scholar 
    Download references

    Competing Interests
    The authors declare no competing interests.

    Related Articles

    Biodiversity needs every tool in the box: use OECMs

    Collection: Global biodiversity policy post-2020

    Protect the last of the wild

    Include the true value of nature when rebuilding economies after coronavirus

    Georgina Mace (1953–2020)

    Subjects

    Ecology

    Conservation biology

    Biodiversity

    Latest on:

    Ecology

    How itchy vicuñas remade a vast wilderness
    Research Highlight 04 MAR 22

    How colonialism fed the flames of Australia’s catastrophic wildfires
    Research Highlight 24 FEB 22

    Apply Singapore Index on Cities’ Biodiversity at scale
    Correspondence 22 FEB 22

    Biodiversity

    Apply Singapore Index on Cities’ Biodiversity at scale
    Correspondence 22 FEB 22

    Do not downplay biodiversity loss
    Matters Arising 26 JAN 22

    Shifting baselines and biodiversity success stories
    Matters Arising 26 JAN 22

    Jobs

    Senior Scientific Officer – Functional Genomics (Dr Rachael Natrajan)

    Institute of Cancer Research (ICR)
    London, United Kingdom

    Senior Laboratory Research Scientist

    Francis Crick Institute
    London, United Kingdom

    Postdoctoral Training Fellow – Proteomics

    Francis Crick Institute
    London, United Kingdom

    Laboratory Operations Lead / Hub Lead as Science Support Manager

    Francis Crick Institute
    London, United Kingdom More

  • in

    Spatial occurrence and sources of PAHs in sediments drive the ecological and health risk of Taihu Lake in China

    Froehner, S., Rizzi, J., Vieira, L. M. & Sanez, J. PAHs in water, sediment and biota in an area with port activities. Arch. Environ. Contam. Toxicol. 75, 236–246. https://doi.org/10.1007/s00244-018-0538-6 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Anyanwu, I. N., Sikoki, F. D. & Semple, K. T. Risk assessment of PAHs and N-PAH analogues in sediment cores from the Niger Delta. Mar. Pollut. Bull. 161, 111684. https://doi.org/10.1016/j.marpolbul.2020.111684 (2020).CAS 
    Article 
    PubMed 

    Google Scholar 
    Han, B., Cui, D. Y., Liu, A., Li, Q. & Zheng, L. Distribution, sources, and risk assessment of polycyclic aromatic hydrocarbons (PAHs) in surface sediments from Daya Bay, South China. Environ. Sci. Pollut. Res. 28, 25858–25865. https://doi.org/10.1007/s11356-020-11956-w (2021).CAS 
    Article 

    Google Scholar 
    Li, J. W. et al. Polycyclic aromatic hydrocarbons in water, sediment, soil, and plants of the Aojiang River waterway in Wenzhou, China. J. Hazardous Mater. 173, 75–81. https://doi.org/10.1016/j.jhazmat.2009.08.050 (2010).CAS 
    Article 

    Google Scholar 
    Honda, M. & Suzuki, N. Toxicities of polycyclic aromatic hydrocarbons for aquatic animals. Int. J. Environ. Res. Public Health 17, 1363. https://doi.org/10.3390/ijerph17041363 (2020).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    Lu, G. N., Tao, X. Q., Dang, Z., Yi, X. Y. & Yang, C. Estimation of n-octanol/water partition coefficients of polycyclic aromatic hydrocarbons by quantum chemical descriptors. Cent. Eur. J. Chem. 6, 310–318. https://doi.org/10.2478/s11532-008-0010-y (2008).CAS 
    Article 

    Google Scholar 
    Yuan, H. Z., Zhang, E. L., Lin, Q., Wang, R. & Liu, E. F. Sources appointment and ecological risk assessment of polycyclic aromatic hydrocarbons (PAHs) in sediments of Erhai Lake, a low-latitude and high-altitude lake in southwest China. Environ. Sci. Pollut. Res. 23, 4430–4441. https://doi.org/10.1007/s11356-015-5626-9 (2016).CAS 
    Article 

    Google Scholar 
    Souza, M. R. R. et al. Concentration, distribution and source apportionment of polycyclic aromatic hydrocarbons (PAH) in Poxim River sediments, Brazil. Mar. Pollut. Bull. 127, 478–483. https://doi.org/10.1016/j.marpolbul.2017.12.045 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Davis, E. et al. Source apportionment of polycyclic aromatic hydrocarbons (PAHs) in small craft harbor (SCH) surficial sediments in Nova Scotia, Canada. Sci. Total Environ. 691, 528–537. https://doi.org/10.1016/j.scitotenv.2019.07.114 (2019).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    Dreyer, A., Radke, M., Turunen, J. & Blodau, C. Long-term change of polycyclic aromatic hydrocarbon deposition to peatlands of eastern Canada. Environ. Sci. Technol. 39, 3918–3924. https://doi.org/10.1021/es0481880 (2005).CAS 
    Article 
    PubMed 
    ADS 

    Google Scholar 
    Ma, W. L. et al. Polycyclic aromatic hydrocarbons in water, sediment and soil of the Songhua River Basin, China. Environ. Monitoring Assessment 185, 8399–8409. https://doi.org/10.1007/s10661-013-3182-7 (2013).CAS 
    Article 

    Google Scholar 
    Yang, Y. Y. et al. Distributions, compositions, and ecological risk assessment of polycyclic aromatic hydrocarbons and phthalic acid esters in surface sediment of Songhua river, China. Mar. Pollut. Bull. 152, 10923. https://doi.org/10.1016/j.marpolbul.2020.110923 (2020).CAS 
    Article 

    Google Scholar 
    Rahmanpoor, S., Ghafourian, H., Hashtroudi, S. M. & Bastami, K. D. Distribution and sources of polycyclic aromatic hydrocarbons in surface sediments of the Hormuz strait, Persian Gulf. Mar. Pollut. Bull. 78, 224–229. https://doi.org/10.1016/j.marpolbul.2013.10.032 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    Aghadadashi, V., Mehdinia, A., Bakhtiari, A. R., Mohammadi, J. & Moradi, M. Source, spatial distribution, and toxicity potential of Polycyclic Aromatic Hydrocarbons in sediments from Iran’s environmentally hot zones, the Persian Gulf. Ecotoxicol. Environ. Saf. 173, 514–525. https://doi.org/10.1016/j.ecoenv.2019.02.029 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    Zhang, L., Zhu, B., Gao, J. H. & Kang, H. Q. Impact of Taihu Lake on city ozone in the Yangtze River Delta. Adv. Atmos. Sci. 34, 226–234. https://doi.org/10.1007/s00376-016-6099-6 (2017).CAS 
    Article 

    Google Scholar 
    Huang, S. B., Qiao, M., Wang, H. & Wang, Z. J. Organchlorinated pesticides in surface sediments of meiliang bay in Taihu Lake, China. J. Environ. Sci. Health Part a-Toxic/Hazardous Substances Environ. Eng. 41, 223–234. https://doi.org/10.1080/10934520500354664 (2006).CAS 
    Article 

    Google Scholar 
    Su, H. L. et al. Distribution characteristics and risk assessments of PAHs in fish from Lake Taihu, China. Hum. Ecol. Risk Assessment 21, 1753–1765. https://doi.org/10.1080/10807039.2014.975003 (2015).CAS 
    Article 

    Google Scholar 
    Wang, W. W., Qu, X. L., Lin, D. H. & Yang, K. Octanol-water partition coefficient (logKow) dependent movement and time lagging of polycyclic aromatic hydrocarbons (PAHs) from emission sources to lake sediments: A case study of Taihu Lake, China. Environ. Pollut. 288, 117709. https://doi.org/10.1016/j.envpol.2021.117709 (2021).CAS 
    Article 
    PubMed 

    Google Scholar 
    Peng, X. Z., Zhang, G., Zheng, L. P., Mai, B. X. & Zeng, S. W. The vertical variations of hydrocarbon pollutants and organochlorine pesticide residues in a sediment core in Lake Taihu, East China. Geochem.-Exploration Environ. Anal. 5, 99–104. https://doi.org/10.1144/1467-7873/03-038 (2005).CAS 
    Article 

    Google Scholar 
    Zhang, Y., Lu, Y. & Zhao, W. Y. Spatial distribution of polycyclic aromatic hydrocarbons from Lake Taihu, China. Bull. Environ. Contam. Toxicol. 87, 80–85. https://doi.org/10.1007/s00128-011-0292-1 (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    Dong, Y. B. et al. Polycyclic aromatic hydrocarbons in sediments from typical Algae, Macrophyte Lake Bay and adjoining river of Taihu Lake, China: Distribution, sources, and risk assessment. Water 13, 470. https://doi.org/10.3390/w13040470 (2021).CAS 
    Article 

    Google Scholar 
    Chen, P. & Liang, J. Polycyclic aromatic hydrocarbons in green space soils in Shanghai: Source, distribution, and risk assessment. J. Soils Sediments 21, 967–977. https://doi.org/10.1007/s11368-020-02838-2 (2021).CAS 
    Article 

    Google Scholar 
    Xia, Z. et al. New approaches to reduce sample processing times for the determination of polycyclic aromatic compounds in environmental samples. Chemosphere 274, 129738. https://doi.org/10.1016/j.chemosphere.2021.129738 (2021).CAS 
    Article 
    PubMed 
    ADS 

    Google Scholar 
    Sun, T., Wang, Y. H., Tian, J. M. & Kong, X. G. Characteristics of PAHs in soils under different land-use types and their associated health risks in the northern Taihu Basin, China. J. Soils Sediments 22, 134–145. https://doi.org/10.1007/s11368-021-03050-6 (2022).CAS 
    Article 

    Google Scholar 
    Abdollahi, S. et al. Contamination levels and spatial distributions of heavy metals and PAHs in surface sediment of Imam Khomeini Port, Persian Gulf, Iran. Mar. Pollut. Bull. 72, 336–345. https://doi.org/10.1016/j.marpolbul.2013.01.025 (2013).CAS 
    Article 

    Google Scholar 
    Santos, E. et al. Polycyclic aromatic hydrocarbons (PAH) in superficial water from a tropical estuarine system: Distribution, seasonal variations, sources and ecological risk assessment. Mar. Pollut. Bull. 127, 352–358. https://doi.org/10.1016/j.marpolbul.2017.12.014 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Long, E. R., Field, L. J. & Macdonald, D. D. Predicting toxicity in marine sediments with numerical sediment quality guidelines. Environ. Toxicol. Chem. 17, 714–727. https://doi.org/10.1002/etc.5620170428 (1998).CAS 
    Article 

    Google Scholar 
    Han, B., Liu, A., He, S., Li, Q. & Zheng, L. Composition, content, source, and risk assessment of PAHs in intertidal sediment in Shilaoren Bay, Qingdao, China. Mar. Pollut. Bull. 159, 111499. https://doi.org/10.1016/j.marpolbul.2020.111499 (2020).CAS 
    Article 
    PubMed 

    Google Scholar 
    Abba, E. J., Unnikrishnan, S., Kumar, R., Yeole, B. & Chowdhury, Z. Fine aerosol and PAH carcinogenicity estimation in outdoor environment of Mumbai City, India. Int. J. Environ. Health Res. 22, 134–149. https://doi.org/10.1080/09603123.2011.613112 (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    Ji, H., Zhang, D. & Shinohara, R. Size distribution and estimated carcinogenic potential of particulate polycyclic aromatic hydrocarbons collected at a downtown site in Kumamoto, Japan, in Spring. J. Health Sci. 53, 700–707. https://doi.org/10.1248/jhs.53.700 (2007).CAS 
    Article 

    Google Scholar 
    Lei, P., Zhang, H. & Shan, B. Q. Vertical records of sedimentary PAHs and their freely dissolved fractions in porewater profiles from the northern bays of Taihu Lake, Eastern China. RSC Adv. 6, 98835–98844. https://doi.org/10.1039/c6ra11180g (2016).CAS 
    Article 
    ADS 

    Google Scholar 
    Li, A. L. et al. Sedimentary archive of Polycyclic Aromatic Hydrocarbons and perylene sources in the northern part of Taihu Lake, China. Environ. Pollut. 246, 198–206. https://doi.org/10.1016/j.envpol.2018.11.112 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    Zhang, Y. et al. Potential source contributions and risk assessment of PAHs in sediments from Taihu Lake, China: Comparison of three receptor models. Water Res. 46, 3065–3073. https://doi.org/10.1016/j.watres.2012.03.006 (2012).CAS 
    Article 
    PubMed 
    ADS 

    Google Scholar 
    Qiao, M., Wang, C. X., Huang, S. B., Wang, D. H. & Wang, Z. J. Composition, sources, and potential toxicological significance of PAHs in the surface sediments of the Meiliang Bay, Taihu Lake, China. Environ. Int. 32, 28–33. https://doi.org/10.1016/j.envint.2005.04.005 (2016).CAS 
    Article 

    Google Scholar 
    Sun, L., Zang, S. Y. & Sun, H. J. Sources and history of PAHs in lake sediments from oil-producing and industrial areas, northeast China. Int. J. Environ. Sci. Technol. 11, 2051–2060. https://doi.org/10.1007/s13762-013-0396-8 (2014).CAS 
    Article 

    Google Scholar 
    Guo, J. Y. et al. Screening level of PAHs in sediment core from Lake Hongfeng, Southwest China. Arch. Environ. Contam. Toxicol. 60, 590–596. https://doi.org/10.1007/s00244-010-9568-4 (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    Zhang, Z. D. et al. A study on PAHs in the surface soil of the region around Qinghai Lake in the Tibet plateau: Evaluation of distribution characteristics, sources and ecological risks. Environ. Res. Commun. 3, 041005. https://doi.org/10.1088/2515-7620/abf3d9 (2021).Article 

    Google Scholar 
    Li, C. C. et al. Spatial distribution, potential risk assessment, and source apportionment of polycyclic aromatic hydrocarbons (PAHs) in sediments of Lake Chaohu, China. Environ. Sci. Pollut. Res. 21, 12028–12039. https://doi.org/10.1007/s11356-014-3137-8 (2014).CAS 
    Article 

    Google Scholar 
    Romo-Gomez, C., Monks, S., Pulido-Flores, G. & Gordillo-Martinez, A. J. Determination of polycyclic aromatic hydrocarbons (PAHs) in superficial water and sediment of Lake Tecocomulco, Mexico. Interciencia 35, 905–911 (2010).
    Google Scholar 
    Yuan, Z. J. et al. Polycyclic aromatic hydrocarbons (PAHs) in urban stream sediments of Suzhou Industrial Park, an emerging eco-industrial park in China: Occurrence, sources and potential risk. Ecotoxicol. Environ. Saf. 214, 112095. https://doi.org/10.1016/10.1016/j.ecoenv.2021.112095 (2021).CAS 
    Article 
    PubMed 

    Google Scholar 
    Shen, B. B., Wu, J. L. & Zhao, Z. H. Residues of organochlorine pesticides and polycyclic aromatic hydrocarbons in surface waters, soils and sediments of the Kaidu River catchment, northwest China. Int. J. Environ. Pollut. 63, 104–116. https://doi.org/10.1504/IJEP.2018.10014155 (2018).CAS 
    Article 

    Google Scholar 
    Yan, W., Chi, J. S., Wang, Z. Y., Huang, W. X. & Zhang, G. Spatial and temporal distribution of polycyclic aromatic hydrocarbons (PAHs) in sediments from Daya Bay, South China. Environ. Pollut. 157, 1823–1830. https://doi.org/10.1016/j.envpol.2009.01.023 (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Arias, A. H. et al. Presence, distribution, and origins of polycyclic aromatic hydrocarbons (PAHs) in sediments from Bahia Blanca estuary, Argentina. Environ. Monitor. Assess. 160, 301–314. https://doi.org/10.1007/s10661-008-0696-5 (2010).CAS 
    Article 

    Google Scholar 
    Yunker, M. B. et al. PAHs in the Fraser River basin: A critical appraisal of PAH ratios as indicators of PAH source and composition. Org. Geochem. 33, 489–515. https://doi.org/10.1016/S0146-6380(02)00002-5 (2002).CAS 
    Article 

    Google Scholar 
    Tobiszewski, M. & Namiesnik, J. PAH diagnostic ratios for the identification of pollution emission sources. Environ. Pollut. 162, 110–119. https://doi.org/10.1016/j.envpol.2011.10.025 (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    Chen, M. H., Li, C. H., Ye, C. & Xu, S. H. Distribution, sources and risk assessment of polycyclic aromatic hydrocarbon in sediments from Zhushan Bay littoral zone, Lake Taihu. J. Environ. Eng. Technol. 4, 199–205 (2014) (in Chinese).
    Google Scholar 
    Zhao, Q., Yu, Q. & Chen, L. M. Particulate matter and particle-bound polycyclic aromatic hydrocarbons in the Dapu road tunnel in Shanghai. Int. J. Environ. Pollut. 41, 21–37. https://doi.org/10.1504/IJEP.2010.032243 (2010).CAS 
    Article 

    Google Scholar 
    Tian, Y. Z. et al. Source contributions and spatiotemporal characteristics of PAHs in sediments: Using three-way source apportionment approach. Environ. Toxicol. Chem. 33, 1747–1753. https://doi.org/10.1002/etc.2628 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    Zhang, F. et al. Polycyclic aromatic hydrocarbons (PAHs) and Pb isotopic ratios in a sediment core from Shilianghe Reservoir, eastern China: Implying pollution sources. Appl. Geochem. 66, 140–148. https://doi.org/10.1016/j.apgeochem.2015.12.010 (2016).CAS 
    Article 
    ADS 

    Google Scholar 
    Harrison, R. M., Smith, D. J. T. & Luhana, L. Source apportionment of atmospheric polycyclic aromatic hydrocarbons collected from an urban location in Birmingham, UK. Environ. Sci. Technol. 30, 825–832. https://doi.org/10.1021/es950252d (1996).CAS 
    Article 
    ADS 

    Google Scholar 
    Simcik, M. F., Eisenreich, S. J. & Lioy, P. J. Source apportionment and source/sink relationships of PAHs in the coastal atmosphere of Chicago and Lake Michigan. Atmos. Environ. 33, 5071–5079. https://doi.org/10.1016/S1352-2310(99)00233-2 (1999).CAS 
    Article 
    ADS 

    Google Scholar 
    Yang, J., Xu, W. L. & Cheng, H. Y. Seasonal variations and sources of airborne polycyclic aromatic hydrocarbons (PAHs) in Chengdu, China. Atmosphere 9, 63. https://doi.org/10.3390/atmos9020063 (2018).CAS 
    Article 
    ADS 

    Google Scholar 
    Cetin, B. Investigation of PAHs, PCBs and PCNs in soils around a Heavily Industrialized Area in Kocaeli, Turkey: Concentrations, distributions, sources and toxicological effects. Sci. Total Environ. 560, 160–169. https://doi.org/10.1016/j.scitotenv.2016.04.037 (2016).CAS 
    Article 
    PubMed 
    ADS 

    Google Scholar 
    Ali-Taleshi, M. S., Squizzato, S., Riyahi Bakhtiari, A., Moeinaddini, M. & Masiol, M. Using a hybrid approach to apportion potential source locations contributing to excess cancer risk of PM25-bound PAHs during heating and non-heating periods in a megacity in the Middle East. Environ. Res. 201, 111617. https://doi.org/10.1016/j.envres.2021.111617 (2021).CAS 
    Article 
    PubMed 

    Google Scholar 
    Xu, J. et al. Historical trends of concentrations, source contributions and toxicities for PAHs in dated sediment cores from five lakes in western China. Sci. Total Environ. 470, 519–526. https://doi.org/10.1016/j.scitotenv.2013.10.022 (2014).CAS 
    Article 
    PubMed 
    ADS 

    Google Scholar 
    Wei, H., Liu, G. B., Yong, T. & Qin, Z. Emission of polycyclic aromatic hydrocarbons from different types of motor vehicles’ exhaust. Environ. Earth Sci. 74, 5557–5564. https://doi.org/10.1007/s12665-015-4570-9 (2015).CAS 
    Article 

    Google Scholar  More

  • in

    Tropical extreme droughts drive long-term increase in atmospheric CO2 growth rate variability

    Cox, P. M. et al. Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability. Nature 494, 341–344 (2013).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Bousquet, P. et al. Regional changes of CO2 fluxes of land and oceans since 1980. Science 290, 1253–1262 (2000).
    Google Scholar 
    Lee, K., Wanninkhof, R., Takahashi, T., Doney, S. C. & Feely, R. A. Low interannual variability in recent oceanic uptake of atmospheric carbon dioxide. Nature 396, 155 (1998).ADS 
    CAS 

    Google Scholar 
    Le Quéré, C. et al. Trends in the sources and sinks of carbon dioxide. Nat. Geosci. 2, 831 (2009).ADS 

    Google Scholar 
    Yue, C., Ciais, P., Houghton, R. A. & Nassikas, A. A. Contribution of land use to the interannual variability of the land carbon cycle. Nat. Commun. 11, 3170 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wang, W. et al. Variations in atmospheric CO2 growth rates coupled with tropical temperature. Proc. Natl Acad. Sci. 110, 13061–13066 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Keeling, C. D., Whorf, T. P., Wahlen, M. & van der Plichtt, J. Interannual extremes in the rate of rise of atmospheric carbon dioxide since 1980. Nature 375, 666–670 (1995).ADS 
    CAS 

    Google Scholar 
    Wang, X. et al. A two-fold increase of carbon cycle sensitivity to tropical temperature variations. Nature 506, 212–215 (2014).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Humphrey, V. et al. Sensitivity of atmospheric CO2 growth rate to observed changes in terrestrial water storage. Nature 560, 628–631 (2018).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Rödenbeck, C., Zaehle, S., Keeling, R. & Heimann, M. History of El Niño impacts on the global carbon cycle 1957–2017: A quantification from atmospheric CO2 data. Philos. Trans. R. Soc. B Biol. Sci. 373, 20170303 (2018).Peylin, P. et al. Global atmospheric carbon budget: Results from an ensemble of atmospheric CO2 inversions. Biogeosciences 10, 6699–6720 (2013).ADS 
    CAS 

    Google Scholar 
    Fan, L. et al. Satellite-observed pantropical carbon dynamics. Nat. Plants. 5, 944–951 (2019).Poulter, B. et al. Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature 509, 600–603 (2014).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Ahlström, A. et al. The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink. Science 348, 895 LP–895899 (2015).ADS 

    Google Scholar 
    Piao, S. et al. Interannual variation of terrestrial carbon cycle: Issues and perspectives. Glob. Chang. Biol. 26, 300–318 (2020).ADS 
    PubMed 

    Google Scholar 
    Wang, J., Zeng, N. & Wang, M. Interannual variability of the atmospheric CO2 growth rate: Roles of precipitation and temperature. Biogeosciences 13, 2339–2352 (2016).ADS 
    CAS 

    Google Scholar 
    Clark, D. A., Piper, S. C., Keeling, C. D. & Clark, D. B. Tropical rain forest tree growth and atmospheric carbon dynamics linked to interannual temperature variation during 1984-2000. Proc. Natl Acad. Sci. 100, 5852–5857 (2003).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Doughty, C. E. & Goulden, M. L. Are tropical forests near a high temperature threshold? J. Geophys. Res. Biogeosciences 114, 1–12 (2009).
    Google Scholar 
    Ballantyne, A. et al. Accelerating net terrestrial carbon uptake during the warming hiatus due to reduced respiration. Nat. Clim. Chang. 7, 148–152 (2017).ADS 
    CAS 

    Google Scholar 
    Anderegg, W. R. L. et al. Tropical nighttime warming as a dominant driver of variability in the terrestrial carbon sink. Proc. Natl Acad. Sci. 112, 201521479 (2015).
    Google Scholar 
    Jung, M. et al. Compensatory water effects link yearly global land CO2 sink changes to temperature. Nature 541, 516–520 (2017).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Humphrey, V. et al. Soil moisture – atmosphere feedback dominates land carbon uptake variability. Nature 592, 65–69 (2021).Green, J. K. et al. Large influence of soil moisture on long-term terrestrial carbon uptake. Nature 565, 476–479 (2019).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Liu, Y., Kumar, M., Katul, G. G., Feng, X. & Konings, A. G. Plant hydraulics accentuates the effect of atmospheric moisture stress on transpiration. Nat. Clim. Chang. 10, 691–695 (2020).ADS 
    CAS 

    Google Scholar 
    Phillips, O. L. et al. Drought–mortality relationships for tropical forests Oliver. N. Phytol. 187, 631–646 (2010).
    Google Scholar 
    Bigler, C., Gavin, D. G., Gunning, C. & Veblen, T. T. Drought induces lagged tree mortality in a subalpine forest in the Rocky Mountains. Oikos 116, 1983–1994 (2007).
    Google Scholar 
    Anderegg, W. R. L. et al. Pervasive drought legacies in forest ecosystems and their implications for carbon cycle models. Science 349, 528–532 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Aragão, L. E. O. C. et al. Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia. Philos. Trans. R. Soc. B Biol. Sci. 363, 1779–1785 (2008).
    Google Scholar 
    Schwalm, C. R. et al. Global patterns of drought recovery. Nature 548, 202–205 (2017).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Huang, M., Wang, X., Keenan, T. F. & Piao, S. Drought timing influences the legacy of tree growth recovery. Glob. Chang. Biol. 24, 3546–3559 (2018).ADS 
    PubMed 

    Google Scholar 
    Chambers, J. Q., Higuchi, N., Schimel, J. P., Ferreira, L. V. & Melack, J. M. Decomposition and carbon cycling of dead trees in tropical forests of the central Amazon. Oecologia 122, 380–388 (2000).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Berenguer, E. et al. Tracking the impacts of El Niño drought and fire in human-modified Amazonian forests. Proc. Natl Acad. Sci. 118, e2019377118 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ma, X. et al. Drought rapidly diminishes the large net CO2 uptake in 2011 over semi-arid Australia. Sci. Rep. 6, 1–9 (2016).CAS 

    Google Scholar 
    Sitch, S. et al. Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs). Glob. Chang. Biol. 14, 2015–2039 (2008).ADS 

    Google Scholar 
    Sitch, S. et al. Recent trends and drivers of regional sources and sinks of carbon dioxide. Biogeosciences 12, 653–679 (2015).ADS 

    Google Scholar 
    Van Der Werf, G. R. et al. Global fire emissions estimates during 1997-2016. Earth Syst. Sci. Data 9, 697–720 (2017).ADS 

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

    Google Scholar 
    IPCC. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. (Cambridge University Press, 2013). https://doi.org/10.1017/CBO9781107415324.Reichstein, M. et al. Climate extremes and the carbon cycle. Nature 500, 287 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Frank, D. et al. Effects of climate extremes on the terrestrial carbon cycle: Concepts, processes and potential future impacts. Glob. Change Biol. 21, 2861–2880 (2015).ADS 

    Google Scholar 
    Zscheischler, J. et al. A few extreme events dominate global interannual variability in gross primary production. Environ. Res. Lett. 9, 035001 (2014).Von Buttlar, J. et al. Impacts of droughts and extreme-temperature events on gross primary production and ecosystem respiration: A systematic assessment across ecosystems and climate zones. Biogeosciences 15, 1293–1318 (2018).ADS 

    Google Scholar 
    Anderegg, W. R. L., Berry, J. A. & Field, C. B. Linking definitions, mechanisms, and modeling of drought-induced tree death. Trends Plant Sci. 17, 693–700 (2012).CAS 
    PubMed 

    Google Scholar 
    Wang, J., Zeng, N. & Wang, M. Interannual variability of the atmospheric CO2growth rate: Roles of precipitation and temperature. Biogeosciences 13, 2339–2352 (2016).ADS 
    CAS 

    Google Scholar 
    Tan, Z. H. et al. Optimum air temperature for tropical forest photosynthesis: Mechanisms involved and implications for climate warming. Environ. Res. Lett. 12, 054022 (2017).Green, J. K., Berry, J., Ciais, P., Zhang, Y. & Gentine, P. Amazon rainforest photosynthesis increases in response to atmospheric dryness. Sci. Adv. 6, 1–10 (2020).
    Google Scholar 
    Guan, K. et al. Photosynthetic seasonality of global tropical forests constrained by hydroclimate. Nat. Geosci. 8, 284–289 (2015).ADS 
    CAS 

    Google Scholar 
    Jiménez-Muñoz, J. C. et al. Record-breaking warming and extreme drought in the Amazon rainforest during the course of El Niño 2015-2016. Sci. Rep. 6, 1–7 (2016).
    Google Scholar 
    Lyon, B. The strength of El Niño and the spatial extent of tropical drought. Geophys. Res. Lett. 31, 1–4 (2004).
    Google Scholar 
    Ciais, P. et al. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437, 529–533 (2005).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Zscheischler, J., Mahecha, M. D. & Buttlar, J. Von. A few extreme events dominate global interannual variability in gross primary production. Environ. Res. Lett. 9, 035001 (2014).Zscheischler, J. et al. Impact of large-scale climate extremes on biospheric carbon fluxes: An intercomparison based on MsTMIP data. Glob. Biogeochem. Cycles 28, 585–600 (2014).ADS 
    CAS 

    Google Scholar 
    Saatchi, S. et al. Persistent effects of a severe drought on Amazonian forest canopy. Proc. Natl Acad. Sci. U. S. A. 110, 565–570 (2013).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Williams, I. N., Torn, M. S., Riley, W. J. & Wehner, M. F. Impacts of climate extremes on gross primary production under global warming. Environ. Res. Lett. 9, 094011 (2014).Keenan, T. F., Luo, X., Zhang, Y. & Zhou, S. Ecosystem aridity and atmospheric CO2. Sci. (80-.). 368, 251.2–252 (2020).
    Google Scholar 
    Schuldt, B. et al. Change in hydraulic properties and leaf traits in a tall rainforest tree species subjected to long-term throughfall exclusion in the perhumid tropics. Biogeosciences 8, 2179–2194 (2011).ADS 

    Google Scholar 
    Hawkins, L., Kumar, J., Luo, X., Sihi, D. & Zhou, S. Measuring, Monitoring, and Modeling Ecosystem Cycling. Eos (Washington. DC). 101, (2020).Jung, M. et al. Scaling carbon fluxes from eddy covariance sites to globe: Synthesis and evaluation of the FLUXCOM approach. Biogeosciences 17, 1343–1365 (2020).ADS 
    CAS 

    Google Scholar 
    Besnard, S. et al. Memory effects of climate and vegetation affecting net ecosystem CO2 fluxes in global forests. PLoS One 14, 1–22 (2019).
    Google Scholar 
    Masarie, K. A. & Tans, P. P. Extension and integration of atmospheric carbon dioxide data into a globally consistent measurement record. J. Geophys. Res. 100, 11593 (1995).ADS 
    CAS 

    Google Scholar 
    Le Quéré, C. et al. Global Carbon Budget 2018. Earth Syst. Sci. Data 10, 2141–2194 (2018).ADS 

    Google Scholar 
    Keeling, C. D. et al. Atmospheric carbon dioxide variations at Mauna Loa Observatory, Hawaii. Tellus 28, 538–551 (1976).ADS 
    CAS 

    Google Scholar 
    Ballantyne, A. P., Alden, C. B., Miller, J. B., Trans, P. P. & White, J. W. C. Increase in observed net carbon dioxide uptake by land and oceans during the past 50 years. Nature 488, 70–73 (2012).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Harris, I., Jones, P. D., Osborn, T. J. & Lister, D. H. Updated high-resolution grids of monthly climatic observations – the CRU TS3.10 Dataset. Int. J. Climatol. 34, 623–642 (2014).
    Google Scholar 
    Davis, T. W. et al. Simple process-led algorithms for simulating habitats (SPLASH v.1.0): Robust indices of radiation, evapotranspiration and plant-available moisture. Geosci. Model Dev. 10, 689–708 (2017).ADS 

    Google Scholar 
    Priestley, C. H. B. & Taylor, R. J. On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters. Mon. Weather Rev. 100, 81–92 (1972).ADS 

    Google Scholar 
    Muller, A., Rohde, R., Jacobsen, R., R., Muller, E. & Wickham, C. A New Estimate of the Average Earth Surface Land Temperature Spanning 1753 to 2011. Geoinformatics Geostatistics Overv. 01, 1–7 (2013).
    Google Scholar 
    Brohan, P., Kennedy, J. J., Harris, I., Tett, S. F. B. & Jones, P. D. Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850. J. Geophys. Res. Atmos. 111, 1–21 (2006).
    Google Scholar 
    Hansen, J., Ruedy, R., Sato, M. & Lo, K. Global surface temperature change. Rev. Geophys. 48, 1–29 (2010).
    Google Scholar 
    Willmott, C. J. & Matsuura, K. Smart interpolation of annually averaged air temperature in the United States. J. Appl. Meteorol. 34, 2577–2586 (1995).ADS 

    Google Scholar 
    Schneider, U. et al. Evaluating the hydrological cycle over land using the newly-corrected precipitation climatology from the Global Precipitation Climatology Centre (GPCC). Atmosphere (Basel). 8, 30052 (2017).Chen, M., Xie, P. & Janowiak, J. E. Global land precipitation: A 50-yr monthly analysis based on gauge observations. J. Hydrometeorol. 3, 249–266 (2002).ADS 

    Google Scholar 
    Friedl, M. A. et al. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sens. Environ. 114, 168–182 (2010).ADS 

    Google Scholar 
    Trenberth, K. E. et al. Global warming and changes in drought. Nat. Clim. Chang. 4, 17–22 (2014).ADS 

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

    Google Scholar 
    Seneviratne, S. I. et al. Changes in climate extremes and their impacts on the natural physical environment. Manag. Risks Extrem. Events Disasters Adv. Clim. Chang. Adapt. Spec. Rep. Intergov. Panel Clim. Chang. 9781107025, 109–230 (2012).
    Google Scholar 
    Baccini, A. et al. Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science 358, 230–234 (2017).ADS 
    MathSciNet 
    CAS 
    PubMed 
    MATH 

    Google Scholar  More

  • in

    Increasing terrestrial ecosystem carbon release in response to autumn cooling and warming

    Climate dataMonthly climate data (air temperature at 2 m and cloudiness) with a spatial resolution of 0.5° were obtained from the CRU Time Series 4.0.15 We extracted data from 1982 to 2018 to match the time series of satellite vegetation observations. The VPD was calculated as the difference between saturated water-vapour pressure and actual water-vapour pressure31. Temperature and vapour-pressure data used for the VPD calculation were obtained from CRU.Soil moisture dataThe daily root-zone soil moisture with a spatial resolution of 0.25° for the period 1980–2018 was obtained from the Global Land Evaporation Amsterdam Model (GLEAM v.3.3a)32. The dataset is based on radiation and air temperature from a reanalysis, a combination of gauge-based, reanalysis-based and satellite-based precipitation and satellite-based vegetation optical depth.Fire emission dataMonthly carbon emissions from biomass burning were obtained from the fourth-generation Global Fire Emission Database33. This dataset has a spatial resolution of 0.25° and provides global data on the burning area and emissions on three-hourly, daily and monthly timescales and estimates the contributions of different fire types. Emissions data can be obtained for different substances, such as carbon (C), dry matter (DM), carbon dioxide (CO2), carbon monoxide (CO) and methane (CH4).Satellite vegetation greenness dataThe satellite-based NDVI archived from the MODIS NDVI dataset with a spatial resolution of 0.5° and a temporal resolution of 16 days was used here to detect vegetation greenness changes. In addition, the solar-induced chlorophyll fluorescence product was used as a proxy of vegetation photosynthesis. We furthermore used the four-day clear-sky CSIF time series (2000–2019) with a spatial resolution of 0.05° × 0.05° from ref. 34 (https://osf.io/8xqy6/).GPP based on NIRvThe NIRv is a newly developed satellite vegetation index combining NDVI and near-infrared band reflectivity of vegetation and is recognized as a proxy of GPP35,36. We obtained the 0.05° NIRv_GPP from 1982 to 2018 from ref. 37. This product was produced by upscaling the relationships between NIRv and observed GPP to the global scale and was judged to perform well in capturing interannual trends of GPP37.Atmospheric CO2 dataIn situ observations of daily CO2 concentration at Point Barrow were obtained from the National Oceanic and Atmospheric Administration/Earth System Research Laboratory network. According to analyses of atmospheric transport and mixing processes, the CO2 signals detected at Barrow are suggested to be an integrated measure of carbon fluxes over both the high latitudes and the middle latitudes20.Ecosystem carbon fluxesSimulations of ecosystem carbon fluxes (GPP, TER and NEE) derived from process-based model simulations (TRENDY), empirical models based on flux tower observations (FLUXCOM) and atmospheric CO2 inversion models were jointly used for the investigation of net ecosystem carbon exchange over the northern middle and high latitudes.The TRENDY dataset is an ensemble of dynamic global vegetation model (DGVM) simulations that are forced by CRU–National Centers for Environmental Prediction historical climate and CO2 inputs38. The DGVMs use a bottom‐up approach to simulate terrestrial CO2 fluxes (for example, GPP, TER and NEE), and were extensively used to explore the mechanisms driving changes in carbon uptake and fluxes. The simulated GPP, TER and NEE from nine models of TRENDYv.8 (Supplementary Table 1) were used in this study. The S2 experiment, which considered the effect of both observed changes of CO2 and climate on ecosystem carbon fluxes, was selected for studying the changes of ecosystem carbon fluxes before and after the temperature shift.The FLUXCOM dataset is an upscaling product using empirical models forced by eddy-covariance data from 224 flux towers, remote sensing data and climate data8,9,10. It provides estimates of global energy and carbon fluxes (http://www.fluxcom.org/). The empirical models were trained by three machine learning algorithms, including Random Forests, Artificial Neural Networks and Multivariate Adaptive Regression Spline, and thus provide a series of estimates of global carbon fluxes. We used the FLUXCOM carbon fluxes data driven by the European Centre for Medium-Range Weather Forecasts Reanalysis v.5 (ERA5) climate reanalysis from 1979 to 2018.The atmospheric CO2 inversion datasets provide estimates of NEE over land from long-term atmospheric CO2 measurements using atmospheric transport models. Three atmospheric CO2 inversion products were used here: monthly net biome production with a spatial resolution of 3.75° × 2.5° from the JENA CarboScope (version s76_vo2020) for the period 1976–2019, long-term global CO2 fluxes estimated by the NICAM-based Inverse Simulation for Monitoring CO2 (NISMON-CO2) between 1990 and 2019 and the Copernicus Atmosphere Monitoring Service12 (CAMS v.19r1) dataset between 1979 and 2019.Eddy-covariance CO2 observation dataThe eddy-covariance measurements of carbon fluxes from tower sites were obtained from the Integrated Carbon Observation System 2018 and the FLUXNET Network 2015. We selected 48 eddy-covariance CO2 observation sites with 10 yr continuous data (Supplementary Table 2) located north of 25° N and extracted temperature and NEE data from September to November to explore the change of ecosystem carbon exchange in autumn.NEE estimationThe monthly NEE was estimated as the difference between TER and GPP. The autumn (September to November) GPP and TER derived from TRENDY and FLUXCOM over the study region were obtained by aggregating GPP and TER from each grid cell weighted by the grid-cell area. The NEE derived from atmospheric CO2 inversions was directly used and compared against those from TRENDY and FLUXCOM. To compare the NEE before and after the temperature turning point, we divided the NEE time series into two periods: 1982–2003 and 2004–2018.Calculation of the AZCWe used observations of CO2 from Point Barrow to characterize the trends in the zero-crossing date of CO2 (downward in spring and upward in autumn). These trends roughly correspond to the beginning of net carbon uptake in spring and the beginning of net carbon release in autumn. According to the method of ref. 39, we obtained the detrended seasonal CO2 curve by separating the seasonal cycle from the long-term trend and short-term variations, fitting a function consisting of a quadratic polynomial for the long-term trend and four harmonics for the annual cycle to the daily data. The residuals from this function fit are then obtained. A 1.5-month and a 390-day full-width half-maximum-value averaging filter were used for the digital filtering of residuals to remove the short-term variations and the long-term trend, respectively. Then we got the zero-crossing dates when the detrended seasonal CO2 curve crosses the zero line from positive to negative and negative to positive, respectively.The autumn carbon release is calculated as the amount of CO2 released between the autumn zero-crossing date and the first week of September following ref. 21.Identification of turning point of temperatureWe used the piecewise linear regression method to determine the turning point of the mean autumn (September to November) temperature during 1982–2018 over the area north of 25° N. In addition, a moving t-test method was used to verify the turning-point identification. Then, the temporal trends of the mean autumn temperature before and after the turning point were calculated using the Mann–Kendall non-parametric trend test method, and the confidence intervals were determined using Sen’s slope statistics. According to the temperature trends before and after the turning point, we further identified the CAs as where the autumn temperature shows a decreasing trend after the turning point (2004) relative to that before the turning point, and WAs as regions outside the CAs. To maintain spatial integrity and continuity, we ignored the significance of the temperature trend when dividing the CAs and WAs.To verify that our analysis is not affected by the division of the time period and regions, we also identified the temperature turning point at each grid point using the piecewise linear regression method and then extracted those grid points with significant temperature change and significant NEE change (P  More

  • in

    Experimental manipulation of microbiota reduces host thermal tolerance and fitness under heat stress in a vertebrate ectotherm

    Paaijmans, K. P. et al. Temperature variation makes ectotherms more sensitive to climate change. Glob. Change Biol. 19, 2373–2380 (2013).
    Google Scholar 
    Clusella-Trullas, S., Blackburn, T. M. & Chown, S. L. Climatic predictors of temperature performance curve parameters in ectotherms imply complex responses to climate change. Am. Nat. 177, 738–751 (2011).PubMed 

    Google Scholar 
    Pounds, J. A. et al. Widespread amphibian extinctions from epidemic disease driven by global warming. Nature 439, 161–167 (2006).CAS 
    PubMed 

    Google Scholar 
    Sinervo, B. et al. Erosion of lizard diversity by climate change and altered thermal niches. Science 328, 894–899 (2010).CAS 
    PubMed 

    Google Scholar 
    Pacifici, M. et al. Assessing species vulnerability to climate change. Nat. Clim. Change 5, 215–224 (2015).
    Google Scholar 
    Angilletta, M. J. Jr Thermal Adaptation: A Theoretical and Empirical Synthesis (Oxford Univ. Press, 2009).Sunday, J. M., Bates, A. E. & Dulvy, N. K. Global analysis of thermal tolerance and latitude in ectotherms. Proc. R. Soc. B 278, 1823–1830 (2011).PubMed 

    Google Scholar 
    Jørgensen, L. B., Malte, H. & Overgaard, J. How to assess Drosophila heat tolerance: unifying static and dynamic tolerance assays to predict heat distribution limits. Funct. Ecol. 33, 629–642 (2019).
    Google Scholar 
    Pörtner, H.-O., Bock, C. & Mark, F. C. Oxygen- and capacity-limited thermal tolerance: bridging ecology and physiology. J. Exp. Biol. 220, 2685–2696 (2017).PubMed 

    Google Scholar 
    Gangloff, E. J. & Telemeco, R. S. High temperature, oxygen, and performance: insights from reptiles and amphibians. Integr. Comp. Biol. 58, 9–24 (2018).CAS 
    PubMed 

    Google Scholar 
    Perry, G. M., Danzmann, R. G., Ferguson, M. M. & Gibson, J. P. Quantitative trait loci for upper thermal tolerance in outbred strains of rainbow trout (Oncorhynchus mykiss). Heredity 86, 333–341 (2001).CAS 
    PubMed 

    Google Scholar 
    Healy, T. M. & Schulte, P. M. Factors affecting plasticity in whole-organism thermal tolerance in common killifish (Fundulus heteroclitus). J. Comp. Physiol. B 182, 49–62 (2012).PubMed 

    Google Scholar 
    Hu, X. P. & Appel, A. G. Seasonal variation of critical thermal limits and temperature tolerance in Formosan and eastern subterranean termites (Isoptera: Rhinotermitidae). Environ. Entomol. 33, 197–205 (2004).CAS 

    Google Scholar 
    Nyamukondiwa, C. & Terblanche, J. S. Thermal tolerance in adult Mediterranean and Natal fruit flies (Ceratitis capitata and Ceratitis rosa): effects of age, gender and feeding status. J. Therm. Biol. 34, 406–414 (2009).
    Google Scholar 
    Greenspan, S. E. et al. Infection increases vulnerability to climate change via effects on host thermal tolerance. Sci. Rep. 7, 9349 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Padfield, D., Castledine, M. & Buckling, A. Temperature-dependent changes to host–parasite interactions alter the thermal performance of a bacterial host. ISME J. 14, 389–398 (2020).PubMed 

    Google Scholar 
    Hooper, L. V., Littman, D. R. & Macpherson, A. J. Interactions between the microbiota and the immune system. Science 336, 1268–1273 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Goodrich, J. K. et al. Human genetics shape the gut microbiome. Cell 159, 789–799 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Alberdi, A., Aizpurua, O., Bohmann, K., Zepeda-Mendoza, M. L. & Gilbert, M. T. P. Do vertebrate gut metagenomes confer rapid ecological adaptation? Trends Ecol. Evol. 31, 689–699 (2016).PubMed 

    Google Scholar 
    Kohl, K. D. & Carey, H. V. A place for host–microbe symbiosis in the comparative physiologist’s toolbox. J. Exp. Biol. 219, 3496–3504 (2016).PubMed 

    Google Scholar 
    Fontaine, S. S. & Kohl, K. D. Optimal integration between host physiology and functions of the gut microbiome. Phil. Trans. R. Soc. B 375, 20190594 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Velagapudi, V. R. et al. The gut microbiota modulates host energy and lipid metabolism in mice. J. Lipid Res. 51, 1101–1112 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Donohoe, D. R. et al. The microbiome and butyrate regulate energy metabolism and autophagy in the mammalian colon. Cell Metab. 13, 517–526 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ziegler, M., Seneca, F. O., Yum, L. K., Palumbi, S. R. & Voolstra, C. R. Bacterial community dynamics are linked to patterns of coral heat tolerance. Nat. Commun. 8, 14213 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Russell, J. A. & Moran, N. A. Costs and benefits of symbiont infection in aphids: variation among symbionts and across temperatures. Proc. R. Soc. B 273, 603–610 (2006).PubMed 

    Google Scholar 
    Montllor, C. B., Maxmen, A. & Purcell, A. H. Facultative bacterial endosymbionts benefit pea aphids Acyrthosiphon pisum under heat stress. Ecol. Entomol. 27, 189–195 (2002).
    Google Scholar 
    Herrera, M. et al. Unfamiliar partnerships limit cnidarian holobiont acclimation to warming. Glob. Change Biol. 26, 5539–5553 (2020).
    Google Scholar 
    Jaramillo, A. & Castaneda, L. E. Gut microbiota of Drosophila subobscura contributes to its heat tolerance and is sensitive to transient thermal stress. Front. Microbiol. 12, 886 (2021).
    Google Scholar 
    Moghadam, N. N. et al. Strong responses of Drosophila melanogaster microbiota to developmental temperature. Fly 12, 1–12 (2018).PubMed 

    Google Scholar 
    Fontaine, S. S., Novarro, A. J. & Kohl, K. D. Environmental temperature alters the digestive performance and gut microbiota of a terrestrial amphibian. J. Exp. Biol. 221, 187559 (2018).
    Google Scholar 
    Kohl, K. D. & Yahn, J. Effects of environmental temperature on the gut microbial communities of tadpoles. Environ. Microbiol. 18, 1561–1565 (2016).PubMed 

    Google Scholar 
    Fontaine, S. S. & Kohl, K. D. The gut microbiota of invasive bullfrog tadpoles responds more rapidly to temperature than a non‐invasive congener. Mol. Ecol. 29, 2449–2462 (2020).PubMed 

    Google Scholar 
    Bestion, E. et al. Climate warming reduces gut microbiota diversity in a vertebrate ectotherm. Nat. Ecol. Evol. 1, 0161 (2017).
    Google Scholar 
    Zhu, L. et al. Environmental temperatures affect the gastrointestinal microbes of the Chinese giant salamander. Front. Microbiol. 12, 493 (2021).
    Google Scholar 
    Moeller, A. H. et al. The lizard gut microbiome changes with temperature and is associated with heat tolerance. Appl. Environ. Microbiol. 86, e01181-20 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Kokou, F. et al. Host genetic selection for cold tolerance shapes microbiome composition and modulates its response to temperature. eLife 7, e36398 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Hanage, W. P. Microbiology: microbiome science needs a healthy dose of scepticism. Nature 512, 247–248 (2014).CAS 
    PubMed 

    Google Scholar 
    Pascoe, E. L., Hauffe, H. C., Marchesi, J. R. & Perkins, S. E. Network analysis of gut microbiota literature: an overview of the research landscape in non-human animal studies. ISME J. 11, 2644–2651 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Mykles, D. L., Ghalambor, C. K., Stillman, J. H. & Tomanek, L. Grand challenges in comparative physiology: integration across disciplines and across levels of biological organization. Integr. Comp. Biol. 50, 6–16 (2010).PubMed 

    Google Scholar 
    Kohl, K. D. A microbial perspective on the grand challenges in comparative animal physiology. mSystems 3, e00146-17 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Gray, K. T., Escobar, A. M., Schaeffer, P. J., Mineo, P. M. & Berner, N. J. Thermal acclimatization in overwintering tadpoles of the green frog, Lithobates clamitans (Latreille, 1801). J. Exp. Zool. A 325, 285–293 (2016).
    Google Scholar 
    Brattstrom, B. H. & Lawrence, P. The rate of thermal acclimation in anuran amphibians. Physiol. Zool. 35, 148–156 (1962).
    Google Scholar 
    Knutie, S. A., Wilkinson, C. L., Kohl, K. D. & Rohr, J. R. Early-life disruption of amphibian microbiota decreases later-life resistance to parasites. Nat. Commun. 8, 86 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Warne, R. W., Kirschman, L. & Zeglin, L. Manipulation of gut microbiota during critical developmental windows affects host physiological performance and disease susceptibility across ontogeny. J. Anim. Ecol. 88, 845–856 (2019).PubMed 

    Google Scholar 
    Morgun, A. et al. Uncovering effects of antibiotics on the host and microbiota using transkingdom gene networks. Gut 64, 1732–1743 (2015).CAS 
    PubMed 

    Google Scholar 
    Kohl, K. D., Cary, T. L., Karasov, W. H. & Dearing, M. D. Restructuring of the amphibian gut microbiota through metamorphosis. Environ. Microbiol. Rep. 5, 899–903 (2013).PubMed 

    Google Scholar 
    Vences, M. et al. Gut bacterial communities across tadpole ecomorphs in two diverse tropical anuran faunas. Sci. Nat. 103, 25 (2016).
    Google Scholar 
    Fontaine, S. S., Mineo, P. M. & Kohl, K. D. Changes in the gut microbial community of the eastern newt (Notophthalmus viridescens) across its three distinct life stages. FEMS Microbiol. Ecol. 97, fiab021 (2021).CAS 
    PubMed 

    Google Scholar 
    Anderson, M. J. & Walsh, D. C. PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: what null hypothesis are you testing? Ecol. Monogr. 83, 557–574 (2013).
    Google Scholar 
    Sepulveda, J. & Moeller, A. H. The effects of temperature on animal gut microbiomes. Front. Microbiol. 11, 384 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Arango, R. A., Schoville, S. D., Currie, C. R. & Carlos-Shanley, C. Experimental warming reduces survival, cold tolerance, and gut prokaryotic diversity of the eastern subterranean termite, Reticulitermes flavipes (Kollar). Front. Microbiol. 12, 1116 (2021).
    Google Scholar 
    Stothart, M. R. et al. Stress and the microbiome: linking glucocorticoids to bacterial community dynamics in wild red squirrels. Biol. Lett. 12, 20150875 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Zaneveld, J. R., McMinds, R. & Thurber, R. V. Stress and stability: applying the Anna Karenina principle to animal microbiomes. Nat. Microbiol. 2, 17121 (2017).CAS 
    PubMed 

    Google Scholar 
    Orrock, J. L. & Watling, J. I. Local community size mediates ecological drift and competition in metacommunities. Proc. R. Soc. B 277, 2185–2191 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    Deeg, C. M. et al. Chromulinavorax destructans, a pathogen of microzooplankton that provides a window into the enigmatic candidate phylum Dependentiae. PLoS Pathog. 15, e1007801 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kaboré, O. D., Godreuil, S. & Drancourt, M. Planctomycetes as host-associated bacteria: a perspective that holds promise for their future isolations, by mimicking their native environmental niches in clinical microbiology laboratories. Front. Cell. Infect. Microbiol. 10, 729 (2020).
    Google Scholar 
    Sheremet, A. et al. Ecological and genomic analyses of candidate phylum WPS‐2 bacteria in an unvegetated soil. Environ. Microbiol. 22, 3143–3157 (2020).CAS 
    PubMed 

    Google Scholar 
    Correa, D. T. et al. Multilevel community assembly of the tadpole gut microbiome. Preprint at bioRxiv https://doi.org/10.1101/2020.07.05.188698 (2020).Contijoch, E. J. et al. Gut microbiota density influences host physiology and is shaped by host and microbial factors. eLife 8, e40553 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Warne, R. W., Kirschman, L. & Zeglin, L. Manipulation of gut microbiota reveals shifting community structure shaped by host developmental windows in amphibian larvae. Integr. Comp. Biol. 57, 786–794 (2017).PubMed 

    Google Scholar 
    Trevelline, B. K., Fontaine, S. S., Hartup, B. K. & Kohl, K. D. Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices. Proc. R. Soc. B 286, 20182448 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Lutterschmidt, W. I. & Hutchison, V. H. The critical thermal maximum: history and critique. Can. J. Zool. 75, 1561–1574 (1997).
    Google Scholar 
    Gosner, K. L. A simplified table for staging anuran embryos and larvae with notes on identification. Herpetologica 16, 183–190 (1960).
    Google Scholar 
    Daloso, D. M. The ecological context of bilateral symmetry of organ and organisms. Nat. Sci. 6, 43340 (2014).
    Google Scholar 
    Goldstein, J. A., Hoff, K. v. S. & Hillyard, S. D. The effect of temperature on development and behaviour of relict leopard frog tadpoles. Conserv. Physiol. 5, cow075 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Harkey, G. A. & Semlitsch, R. D. Effects of temperature on growth, development, and color polymorphism in the ornate chorus frog Pseudacris ornata. Copeia 1998, 1001–1007 (1988).
    Google Scholar 
    Marian, M. & Pandian, T. Effect of temperature on development, growth and bioenergetics of the bullfrog tadpole Rana tigrina. J. Therm. Biol. 10, 157–161 (1985).
    Google Scholar 
    Alvarez, D. & Nicieza, A. Effects of temperature and food quality on anuran larval growth and metamorphosis. Funct. Ecol. 16, 640–648 (2002).
    Google Scholar 
    Kohl, K. D., Brun, A., Bordenstein, S. R., Caviedes‐Vidal, E. & Karasov, W. H. Gut microbes limit growth in house sparrow nestlings (Passer domesticus) but not through limitations in digestive capacity. Integr. Zool. 13, 139–151 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Potti, J. et al. Bacteria divert resources from growth for Magellanic penguin chicks. Ecol. Lett. 5, 709–714 (2002).
    Google Scholar 
    Coates, M. E., Fuller, R., Harrison, G., Lev, M. & Suffolk, S. A comparison of the growth of chicks in the Gustafsson germ-free apparatus and in a conventional environment, with and without dietary supplements of penicillin. Br. J. Nutr. 17, 141–150 (1963).CAS 
    PubMed 

    Google Scholar 
    Gaskins, H., Collier, C. & Anderson, D. Antibiotics as growth promotants: mode of action. Anim. Biotechnol. 13, 29–42 (2002).CAS 
    PubMed 

    Google Scholar 
    Gitsels, A., Sanders, N. & Vanrompay, D. Chlamydial infection from outside to inside. Front. Microbiol. 10, 2329 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Denver, R. J. Proximate mechanisms of phenotypic plasticity in amphibian metamorphosis. Am. Zool. 37, 172–184 (1997).CAS 

    Google Scholar 
    Chevalier, C. et al. Gut microbiota orchestrates energy homeostasis during cold. Cell 163, 1360–1374 (2015).CAS 
    PubMed 

    Google Scholar 
    Khakisahneh, S., Zhang, X.-Y., Nouri, Z. & Wang, D.-H. Gut microbiota and host thermoregulation in response to ambient temperature fluctuations. mSystems 5, e00514–e00520 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Xie, B. et al. Chlamydomonas reinhardtii thermal tolerance enhancement mediated by a mutualistic interaction with vitamin B12-producing bacteria. ISME J. 7, 1544–1555 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gutiérrez‐Pesquera, L. M. et al. Testing the climate variability hypothesis in thermal tolerance limits of tropical and temperate tadpoles. J. Biogeogr. 43, 1166–1178 (2016).
    Google Scholar 
    Litmer, A. R. & Murray, C. M. Critical thermal tolerance of invasion: comparative niche breadth of two invasive lizards. J. Therm. Biol. 86, 102432 (2019).PubMed 

    Google Scholar 
    Semlitsch, R. D. Effects of body size, sibship, and tail injury on the susceptibility of tadpoles to dragonfly predation. Can. J. Zool. 68, 1027–1030 (1990).
    Google Scholar 
    Cabrera-Guzmán, E., Crossland, M. R., Brown, G. P. & Shine, R. Larger body size at metamorphosis enhances survival, growth and performance of young cane toads (Rhinella marina). PLoS ONE 8, e70121 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Tejedo, M. Effects of body size and timing of reproduction on reproductive success in female natterjack toads (Bufo calamita). J. Zool. 228, 545–555 (1992).
    Google Scholar 
    Warne, R. W., Crespi, E. J. & Brunner, J. L. Escape from the pond: stress and developmental responses to ranavirus infection in wood frog tadpoles. Funct. Ecol. 25, 139–146 (2011).
    Google Scholar 
    Urban, M. C. Accelerating extinction risk from climate change. Science 348, 571–573 (2015).CAS 
    PubMed 

    Google Scholar 
    Pearce, T. A. & Paustian, M. E. Are temperate land snails susceptible to climate change through reduced altitudinal ranges? A Pennsylvania example. Am. Malacol. 31, 213–224 (2013).
    Google Scholar 
    Wolfe, D. W. et al. Projected change in climate thresholds in the northeastern US: implications for crops, pests, livestock, and farmers. Mitig. Adapt. Strateg. Glob. Change 13, 555–575 (2008).
    Google Scholar 
    Huey, R. B. & Kingsolver, J. G. Evolution of thermal sensitivity of ectotherm performance. Trends Ecol. Evol. 4, 131–135 (1989).CAS 
    PubMed 

    Google Scholar 
    Bennett, A. F. Thermal dependence of locomotor capacity. Am. J. Physiol. 259, R253–R258 (1990).CAS 
    PubMed 

    Google Scholar 
    Seebacher, F. & Walter, I. Differences in locomotor performance between individuals: importance of parvalbumin, calcium handling and metabolism. J. Exp. Biol. 215, 663–670 (2012).CAS 
    PubMed 

    Google Scholar 
    Husak, J. F., Fox, S. F., Lovern, M. B. & Bussche, R. A. V. D. Faster lizards sire more offspring: sexual selection on whole‐animal performance. Evolution 60, 2122–2130 (2006).CAS 
    PubMed 

    Google Scholar 
    Mineo, P. M., Waldrup, C., Berner, N. J. & Schaeffer, P. J. Differential plasticity of membrane fatty acids in northern and southern populations of the eastern newt (Notophthalmus viridescens). J. Comp. Physiol. B 189, 249–260 (2019).CAS 
    PubMed 

    Google Scholar 
    Chung, D. J., Sparagna, G. C., Chicco, A. J. & Schulte, P. M. Patterns of mitochondrial membrane remodeling parallel functional adaptations to thermal stress. J. Exp. Biol. 221, 174458 (2018).
    Google Scholar 
    Gladwell, R., Bowler, K. & Duncan, C. Heat death in crayfish Austropotamobius pallipes: ion movements and their effects on excitable tissues during heat death. J. Therm. Biol. 1, 79–94 (1976).CAS 

    Google Scholar 
    Wang, Z. et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature 472, 57–63 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pörtner, H. Climate change and temperature-dependent biogeography: oxygen limitation of thermal tolerance in animals. Naturwissenschaften 88, 137–146 (2001).PubMed 

    Google Scholar 
    Gräns, A. et al. Aerobic scope fails to explain the detrimental effects on growth resulting from warming and elevated CO2 in Atlantic halibut. J. Exp. Biol. 217, 711–717 (2014).PubMed 

    Google Scholar 
    Jutfelt, F. et al. Oxygen- and capacity-limited thermal tolerance: blurring ecology and physiology. J. Exp. Biol. 221, 169615 (2018).
    Google Scholar 
    St-Pierre, J., Charest, P.-M. & Guderley, H. Relative contribution of quantitative and qualitative changes in mitochondria to metabolic compensation during seasonal acclimatisation of rainbow trout Oncorhynchus mykiss. J. Exp. Biol. 201, 2961–2970 (1998).CAS 

    Google Scholar 
    Grim, J., Miles, D. & Crockett, E. Temperature acclimation alters oxidative capacities and composition of membrane lipids without influencing activities of enzymatic antioxidants or susceptibility to lipid peroxidation in fish muscle. J. Exp. Biol. 213, 445–452 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    LeMoine, C. M., Genge, C. E. & Moyes, C. D. Role of the PGC-1 family in the metabolic adaptation of goldfish to diet and temperature. J. Exp. Biol. 211, 1448–1455 (2008).CAS 
    PubMed 

    Google Scholar 
    McClelland, G. B., Craig, P. M., Dhekney, K. & Dipardo, S. Temperature‐ and exercise‐induced gene expression and metabolic enzyme changes in skeletal muscle of adult zebrafish (Danio rerio). J. Physiol. 577, 739–751 (2006).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pichaud, N. et al. Cardiac mitochondrial plasticity and thermal sensitivity in a fish inhabiting an artificially heated ecosystem. Sci. Rep. 9, 17832 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Seebacher, F., Guderley, H., Elsey, R. M. & Trosclair, P. L. Seasonal acclimatisation of muscle metabolic enzymes in a reptile (Alligator mississippiensis). J. Exp. Biol. 206, 1193–1200 (2003).CAS 
    PubMed 

    Google Scholar 
    Berner, N. J. & Bessay, E. P. Correlation of seasonal acclimatization in metabolic enzyme activity with preferred body temperature in the eastern red spotted newt (Notophthalmus viridescens viridescens). Comp. Biochem. Physiol. A 144, 429–436 (2006).
    Google Scholar 
    Vigelsø, A., Andersen, N. B. & Dela, F. The relationship between skeletal muscle mitochondrial citrate synthase activity and whole body oxygen uptake adaptations in response to exercise training. Int. J. Physiol. Pathophysiol. Pharmacol. 6, 84–101 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Li, Y., Park, J.-S., Deng, J.-H. & Bai, Y. Cytochrome c oxidase subunit IV is essential for assembly and respiratory function of the enzyme complex. J. Bioenerg. Biomembr. 38, 283–291 (2006).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pryor, G. S. & Bjorndal, K. A. Symbiotic fermentation, digesta passage, and gastrointestinal morphology in bullfrog tadpoles (Rana catesbeiana). Physiol. Biochem. Zool. 78, 201–215 (2005).PubMed 

    Google Scholar 
    Clark, A. & Mach, N. The crosstalk between the gut microbiota and mitochondria during exercise. Front. Physiol. 8, 319 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Payne, N. L. et al. Temperature dependence of fish performance in the wild: links with species biogeography and physiological thermal tolerance. Funct. Ecol. 30, 903–912 (2016).
    Google Scholar 
    Van Dijk, P., Tesch, C., Hardewig, I. & Portner, H. Physiological disturbances at critically high temperatures: a comparison between stenothermal Antarctic and eurythermal temperate eelpouts (Zoarcidae). J. Exp. Biol. 202, 3611–3621 (1999).PubMed 

    Google Scholar 
    Schulte, P. M. The effects of temperature on aerobic metabolism: towards a mechanistic understanding of the responses of ectotherms to a changing environment. J. Exp. Biol. 218, 1856–1866 (2015).PubMed 

    Google Scholar 
    Gillooly, J. F., Brown, J. H., West, G. B., Savage, V. M. & Charnov, E. L. Effects of size and temperature on metabolic rate. Science 293, 2248–2251 (2001).CAS 
    PubMed 

    Google Scholar 
    Hoppeler, H. & Weibel, E. R. Scaling functions to body size: theories and facts. J. Exp. Biol. 208, 1573–1574 (2005).PubMed 

    Google Scholar 
    Hopkins, W. A., Rowe, C. L. & Congdon, J. D. Elevated trace element concentrations and standard metabolic rate in banded water snakes (Nerodia fasciata) exposed to coal combustion wastes. Environ. Toxicol. Chem. 18, 1258–1263 (1999).CAS 

    Google Scholar 
    Sokolova, I. Bioenergetics in environmental adaptation and stress tolerance of aquatic ectotherms: linking physiology and ecology in a multi-stressor landscape. J. Exp. Biol. 224, 236802 (2021).
    Google Scholar 
    Sokolova, I. M. & Lannig, G. Interactive effects of metal pollution and temperature on metabolism in aquatic ectotherms: implications of global climate change. Clim. Res. 37, 181–201 (2008).
    Google Scholar 
    Peralta-Maraver, I. & Rezende, E. L. Heat tolerance in ectotherms scales predictably with body size. Nat. Clim. Change 11, 58–63 (2021).
    Google Scholar 
    Bahrndorff, S., Alemu, T., Alemneh, T. & Lund Nielsen, J. The microbiome of animals: implications for conservation biology. Int. J. Genomics 2016, 5304028 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Hauffe, H. C. & Barelli, C. Conserve the germs: the gut microbiota and adaptive potential. Conserv. Genet. 20, 19–27 (2019).
    Google Scholar 
    Jiménez, R. R. & Sommer, S. The amphibian microbiome: natural range of variation, pathogenic dysbiosis, and role in conservation. Biodivers. Conserv. 26, 763–786 (2017).
    Google Scholar 
    Swaddle, J. P. Fluctuating asymmetry, animal behavior, and evolution. Adv. Study Behav. 32, 169–205 (2003).
    Google Scholar 
    R Core Team R: A Language and Environment for Statistical Computing v.3.4.3 (R Foundation for Statistical Computing, 2019).Bates, D., Machler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. Preprint at https://arxiv.org/abs/1406.5823 (2014).Pinheiro, J. et al. nlme: Linear and Nonlinear Mixed Effects Models. R package version 3 (2017).Hulbert, A., Pamplona, R., Buffenstein, R. & Buttemer, W. Life and death: metabolic rate, membrane composition, and life span of animals. Physiol. Rev. 87, 1175–1213 (2007).CAS 
    PubMed 

    Google Scholar 
    Oksanen, J. et al. vegan: Community Ecology Package. R package version 2 (2013).Mary-Huard, T., Daudin, J.-J., Baccini, M., Biggeri, A. & Bar-Hen, A. Biases induced by pooling samples in microarray experiments. Bioinformatics 23, i313–i318 (2007).CAS 
    PubMed 

    Google Scholar 
    Singer, J. D. & Willett, J. B. It’s about time: using discrete-time survival analysis to study duration and the timing of events. J. Educ. Stat. 18, 155–195 (1993).
    Google Scholar 
    Mallick, H. et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput. Biol. 17, e100442 (2021).
    Google Scholar  More

  • in

    Vegetation increases abundances of ground and canopy arthropods in Mediterranean vineyards

    Hallmann, C. A. et al. More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE 12, e0185809 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Lister, B. C. & Garcia, A. Climate-driven declines in arthropod abundance restructure a rainforest food web. Proc. Natl. Acad. Sci. 115, E10397–E10406 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cardoso, P. et al. Scientists’ warning to humanity on insect extinctions. Biol. Conserv. 242, 108426 (2020).
    Google Scholar 
    Habel, J. C., Samways, M. J. & Schmitt, T. Mitigating the precipitous decline of terrestrial European insects: Requirements for a new strategy. Biodivers. Conserv. 28, 1343–1360 (2019).
    Google Scholar 
    Brühl, C. A. & Zaller, J. G. Biodiversity decline as a consequence of an inappropriate environmental risk assessment of pesticides. Front. Environ. Sci. 7, 2013–2016 (2019).
    Google Scholar 
    Seastedt, T. R. & Crossley, D. A. The influence of arthropods on ecosystems. Bioscience 34, 157–161 (1984).
    Google Scholar 
    Brussaard, L. et al. Biodiversity and ecosystem functioning in soil. Ambio 26, 563–570 (1997).
    Google Scholar 
    Symondson, W. O. C., Sunderland, K. D. & Greenstone, M. H. Can generalist predators be effective biocontrol agents?. Annu. Rev. Entomol. 47, 561–594 (2002).CAS 
    PubMed 

    Google Scholar 
    Goulson, D. The insect apocalypse, and why it matters. Curr. Biol. 29, R967–R971 (2019).CAS 
    PubMed 

    Google Scholar 
    Kremen, C. et al. Pollination and other ecosystem services produced by mobile organisms: A conceptual framework for the effects of land-use change. Ecol. Lett. 10, 299–314 (2007).PubMed 

    Google Scholar 
    Schowalter, T. D., Noriega, J. A. & Tscharntke, T. Insect effects on ecosystem services: Introduction. Basic Appl. Ecol. 26, 1–7 (2018).
    Google Scholar 
    Dangles, O. & Casas, J. Ecosystem services provided by insects for achieving sustainable development goals. Ecosyst. Serv. 35, 109–115 (2019).
    Google Scholar 
    van der Sluijs, J. P. Insect decline, an emerging global environmental risk. Curr. Opin. Environ. Sustain. 46, 39–42 (2020).
    Google Scholar 
    Metcalfe, H., Hassall, K. L., Boinot, S. & Storkey, J. The contribution of spatial mass effects to plant diversity in arable fields. J. Appl. Ecol. 56, 1560–1574 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Winter, S. et al. Effects of vegetation management intensity on biodiversity and ecosystem services in vineyards: A meta-analysis. J. Appl. Ecol. 55, 2484–2495 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Blaise, C. et al. The key role of inter-row vegetation and ants on predation in Mediterranean organic vineyards. Agric. Ecosyst. Environ. 311, 107237 (2021).
    Google Scholar 
    Hoffmann, C. et al. Can flowering greencover crops promote biological control in German vineyards?. Insects 8, 121 (2017).PubMed Central 

    Google Scholar 
    Eckert, M., Mathulwe, L. L., Gaigher, R., der Merwe, L. J. & Pryke, J. S. Native cover crops enhance arthropod diversity in vineyards of the Cape Floristic Region. J. Insect Conserv. 24, 133–149 (2019).
    Google Scholar 
    Sáenz-Romo, M. G. et al. Ground cover management in a Mediterranean vineyard: Impact on insect abundance and diversity. Agric. Ecosyst. Environ. 283, 106571 (2019).
    Google Scholar 
    Capó-Bauçà, S., Marqués, A., Llopis-Vidal, N., Bota, J. & Baraza, E. Long-term establishment of natural green cover provides agroecosystem services by improving soil quality in a Mediterranean vineyard. Ecol. Eng. 127, 285–291 (2019).
    Google Scholar 
    Garcia, L. et al. Management of service crops for the provision of ecosystem services in vineyards: A review. Agric. Ecosyst. Environ. 251, 158–170 (2018).
    Google Scholar 
    Nicholls, C. I., Altieri, M. A. & Ponti, L. Enhancing plant diversity for improved insect pest management in Northern California organic vineyards. Acta Hortic. 785, 263–278 (2008).
    Google Scholar 
    Franin, K., Barić, B. & Kuštera, G. The role of ecological infrastructure on beneficial arthropods in vineyards. Spanish J. Agric. Res. 14, e303 (2016).
    Google Scholar 
    Shapira, I. et al. Habitat use by crop pests and natural enemies in a Mediterranean vineyard agroecosystem. Agric. Ecosyst. Environ. 267, 109–118 (2018).
    Google Scholar 
    Judt, C. et al. Diverging effects of landscape factors and inter-row management on the abundance of beneficial and herbivorous arthropods in andalusian vineyards (Spain). Insects 10, 320 (2019).PubMed Central 

    Google Scholar 
    Geldenhuys, M., Gaigher, R., Pryke, J. S. & Samways, M. J. Diverse herbaceous cover crops promote vineyard arthropod diversity across different management regimes. Agric. Ecosyst. Environ. 307, 107222 (2021).CAS 

    Google Scholar 
    Medail, F. & Quezel, P. Biodiversity hotspots in the Mediterranean Basin: Setting global conservation priorities. Conserv. Biol. https://doi.org/10.1046/j.1523-1739.1999.98467.x (1999).Article 

    Google Scholar 
    Carrère, P. La structure du vignoble du Vaucluse. Etudes Conjonct. 9, 931–949 (1957).
    Google Scholar 
    Nentwig, W. et al. Spiders of Europe. (2020). www.araneae.nmbe.ch.Tronquet, M. Catalogue des coléoptères de France. Rev. l’Assoc. Roussillonnaise d’Entomol. 23, 1–10 (2014).
    Google Scholar 
    Rosseel, Y. Lavaan: An R package for structural equation modeling. J. Stat. Softw. 48, 2 (2012).
    Google Scholar 
    Grace, J. B. Structural equation modeling and natural systems. Struct. Equ. Model. Nat. Syst. https://doi.org/10.1017/CBO9780511617799 (2006).Article 

    Google Scholar 
    Fiera, C. et al. Effects of vineyard inter-row management on the diversity and abundance of plants and surface-dwelling invertebrates in Central Romania. J. Insect Conserv. 24, 175–185 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    de Pedro, L., Perera-Fernández, L. G., López-Gallego, E., Pérez-Marcos, M. & Sanchez, J. A. The effect of cover crops on the ciodiversity and abundance of ground-dwelling arthropods in a Mediterranean pear orchard. Agrono 10, 580 (2020).
    Google Scholar 
    Ebeling, A. et al. Plant diversity impacts decomposition and herbivory via changes in aboveground arthropods. PLoS ONE 9, e106529 (2014).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cobb, T. P., Langor, D. W. & Spence, J. R. Biodiversity and multiple disturbances: Boreal forest ground beetle (Coleoptera: Carabidae) responses to wildfire, harvesting, and herbicide. Can. J. For. Res. 37, 1310–1323 (2007).
    Google Scholar 
    Hendrickx, F. et al. How landscape structure, land-use intensity and habitat diversity affect components of total arthropod diversity in agricultural landscapes. J. Appl. Ecol. 44, 340–351 (2007).
    Google Scholar 
    Melbourne, B. A. Bias in the effect of habitat structure on pitfall traps: An experimental evaluation. Aust. J. Ecol. 24, 228–239 (1999).
    Google Scholar 
    Welti, E. A. R., Prather, R. M., Sanders, N. J., de Beurs, K. M. & Kaspari, M. Bottom-up when it is not top-down: Predators and plants control biomass of grassland arthropods. J. Anim. Ecol. 89, 1286–1294 (2020).PubMed 

    Google Scholar 
    Gonçalves, F. et al. Do soil management practices affect the activity density, diversity, and stability of soil arthropods in vineyards?. Agric. Ecosyst. Environ. 294, 106863 (2020).
    Google Scholar 
    Muscas, E. et al. Effects of vineyard floor cover crops on grapevine vigor, yield, and fruit quality, and the development of the vine mealybug under a Mediterranean climate. Agric. Ecosyst. Environ. 237, 203–212 (2017).
    Google Scholar 
    Nicholls, C. I., Parrella, M. P. & Altieri, M. A. Reducing the abundance of leafhoppers and thrips in a northern California organic vineyard through maintenance of full season floral diversity with summer cover crops. Agric. For. Entomol. 2, 107–113 (2000).
    Google Scholar 
    Vogelweith, F. & Thiéry, D. Cover crop differentially affects arthropods, but not diseases, occurring on grape leaves in vineyards. Aust. J. Grape Wine Res. 23, 426–431 (2017).
    Google Scholar 
    Hanna, R., Zalom, F. G. & Roltsch, W. J. Relative impact of spider predation and cover crop on population dynamics of Erythroneura variabilis in a raisin grape vineyard. Entomol. Exp. Appl. 107, 177–191 (2003).
    Google Scholar 
    Burgio, G. et al. Habitat management of organic vineyard in Northern Italy: the role of cover plants management on arthropod functional biodiversity. Bull. Entomol. Res. 106, 759–768 (2016).CAS 
    PubMed 

    Google Scholar 
    Wisniewska, J. & Prokopy, R. Do spiders (Araneae) feed on rose leafhopper (Edwardsiana rosae; Auchenorrhyncha: Cicadellidae) pests of apple trees? (2013).Malumbres-Olarte, J., Vink, C. J., Ross, J. G., Cruickshank, R. H. & Paterson, A. M. The role of habitat complexity on spider communities in native alpine grasslands of New Zealand. Insect Conserv. Divers. 6, 124–134 (2013).
    Google Scholar 
    Wilson, H. et al. Summer flowering cover crops support wild bees in vineyards. Environ. Entomol. 47, 63–69 (2018).PubMed 

    Google Scholar 
    Kratschmer, S. et al. Tillage intensity or landscape features: What matters most for wild bee diversity in vineyards?. Agric. Ecosyst. Environ. 266, 142–152 (2018).
    Google Scholar 
    Gardarin, A., Pigot, J. & Valantin-Morison, M. The hump-shaped effect of plant functional diversity on the biological control of a multi-species pest community. Sci. Rep. 11, 1–14 (2021).
    Google Scholar 
    Serra, G., Lentini, A., Verdinelli, M. & Delrio, G. Effects of cover crop management on grape pests in a Mediterranean environment. IOBC/WPRS Bull. (2006).Sáenz-Romo, M. G. et al. Effects of ground cover management on insect predators and pests in a Mediterranean vineyard. Insects 10, 421 (2019).PubMed Central 

    Google Scholar 
    Barry, J. P., Baxter, C. H., Sagarin, R. D. & Gilman, S. E. Climate-related, long-term faunal changes in a California rocky intertidal community. Science 267, 672–675 (1995).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Ewald, J. A. et al. Influences of extreme weather, climate and pesticide use on invertebrates in cereal fields over 42 years. Glob. Chang. Biol. 21, 3931–3950 (2015).ADS 
    PubMed 

    Google Scholar 
    Celette, F., Findeling, A. & Gary, C. Competition for nitrogen in an unfertilized intercropping system: The case of an association of grapevine and grass cover in a Mediterranean climate. Eur. J. Agron. https://doi.org/10.1016/j.eja.2008.07.003 (2009).Article 

    Google Scholar 
    Ruiz-Colmenero, M., Bienes, R. & Marques, M. J. Soil and water conservation dilemmas associated with the use of green cover in steep vineyards. Soil Tillage Res. 117, 211–223 (2011).
    Google Scholar  More