Philippa Kaur

Keeling, P. J. & Burki, F. Progress towards the tree of eukaryotes. Curr. Biol. 29, R808–R817 (2019).Article 
CAS 

Google Scholar 
Gawryluk, R. M. R. et al. Non-photosynthetic predators are sister to red algae. Nature 572, 240–243 (2019).Article 
CAS 

Google Scholar 
Janouškovec, J. et al. A new lineage of eukaryotes illuminates early mitochondrial genome reduction. Curr. Biol. 27, 3717–3724 (2017).Article 

Google Scholar 
Lax, G. et al. Hemimastigophora is a novel supra-kingdom-level lineage of eukaryotes. Nature 564, 410–414 (2018).Article 
ADS 
CAS 

Google Scholar 
Oren, A. Prokaryote diversity and taxonomy: current status and future challenges. Philos. Trans. R. Soc. Lond. B 359, 623–638 (2004).Article 
CAS 

Google Scholar 
Shu, W. S. & Huang, L. N. Microbial diversity in extreme environments. Nat. Rev. Microbiol. 20, 219–235 (2022).Article 
CAS 

Google Scholar 
Massana, R., del Campo, J., Sieracki, M. E., Audic, S. & Logares, R. Exploring the uncultured microeukaryote majority in the oceans: reevaluation of ribogroups within stramenopiles. ISME J. 8, 854–866 (2014).Article 

Google Scholar 
de Vargas, C. et al. Eukaryotic plankton diversity in the sunlit ocean. Science 348, 1261605 (2015).Article 

Google Scholar 
Flegontova, O. et al. Extreme diversity of diplonemid eukaryotes in the ocean. Curr. Biol. 26, 3060–3065 (2016).Article 
CAS 

Google Scholar 
Ahlering, M. A. & Carrel, J. E. Predators are rare even when they are small. Oikos 95, 471–475 (2001).Article 

Google Scholar 
Hehenberger, E. et al. Novel predators reshape holozoan phylogeny and reveal the presence of a two-component signaling system in the ancestor of animals. Curr. Biol. 27, 2043–2050 (2017).Article 
CAS 

Google Scholar 
Tikhonenkov, D. V. et al. Description of Colponema vietnamica sp. n. and Acavomonas peruviana n. gen. n. sp., two new alveolate phyla (Colponemidia nom. nov. and Acavomonidia nom. nov.) and their contributions to reconstructing the ancestral state of alveolates and eukaryotes. PLoS ONE 9, e95467 (2014).Article 
ADS 

Google Scholar 
Tikhonenkov, D. V. et al. New lineage of microbial predators adds complexity to reconstructing the evolutionary origin of animals. Curr. Biol. 30, 4500–4509 (2020).Article 
CAS 

Google Scholar 
Mylnikov, A. P. & Tikhonenkov, D. V. The new alveolate carnivorous flagellate Colponema marisrubri sp. n. (Colponemida, Alveolata) from the Red Sea. Zool. Zh. 88, 1163–1169 (2009).
Google Scholar 
Strassert, J. F. H., Irisarri, I., Williams, T. A. & Burki, F. A molecular timescale for eukaryote evolution with implications for the origin of red algal-derived plastids. Nat. Commun. 12, 1879 (2021).Article 
ADS 
CAS 

Google Scholar 
Rodriguez-Ezpeleta, N. et al. Detecting and overcoming systematic errors in genome-scale phylogenies. Syst. Biol. 56, 389–399 (2007).Article 
CAS 

Google Scholar 
Strassert, J. F. H., Jamy, M., Mylnikov, A. P., Tikhonenkov, D. V. & Burki, F. New phylogenomic analysis of the enigmatic phylum Telonemia further resolves the eukaryote tree of life. Mol. Biol. Evol. 36, 757–765 (2019).Article 
CAS 

Google Scholar 
Lanfear, R., Kokko, H. & Eyre-Walker, A. Population size and the rate of evolution. Trends Ecol. Evol. 29, 33–41 (2014).Article 

Google Scholar 
Bahler, M. & Rhoads, A. Calmodulin signaling via the IQ motif. FEBS Lett. 513, 107–113 (2002).Article 
CAS 

Google Scholar 
Schaffer, D. E., Iyer, L. M., Burroughs, A. M. & Aravind, L. Functional innovation in the evolution of the calcium-dependent system of the eukaryotic endoplasmic reticulum. Front. Genet. 11, 34 (2020).Article 

Google Scholar 
Morita-Yamamuro, C. et al. The Arabidopsis gene CAD1 controls programmed cell death in the plant immune system and encodes a protein containing a MACPF domain. Plant Cell Physiol. 46, 902–912 (2005).Article 
CAS 

Google Scholar 
Rosado, C. J. et al. The MACPF/CDC family of pore-forming toxins. Cell. Microbiol. 10, 1765–1774 (2008).Article 
CAS 

Google Scholar 
Ishino, T., Chinzei, Y. & Yuda, M. A Plasmodium sporozoite protein with a membrane attack complex domain is required for breaching the liver sinusoidal cell layer prior to hepatocyte infection. Cell. Microbiol. 7, 199–208 (2005).Article 
CAS 

Google Scholar 
Satoh, H., Oshiro, N., Iwanaga, S., Namikoshi, M. & Nagai, H. Characterization of PsTX-60B, a new membrane-attack complex/perforin (MACPF) family toxin, from the venomous sea anemone Phyllodiscus semoni. Toxicon 49, 1208–1210 (2007).Article 
CAS 

Google Scholar 
Tikhonenkov, D. V., Mazei, Y. A. & Embulaeva, E. A. Degradation succession of heterotrophic flagellate communities in microcosms. Zh. Obs. Biol. 69, 57–64 (2008).CAS 

Google Scholar 
Tikhonenkov, D. V. et al. On the origin of TSAR: morphology, diversity and phylogeny of Telonemia. Open Biol. 12, 210325 (2022).Article 
CAS 

Google Scholar 
Picelli, S. et al. Full-length RNA-seq from single cells using Smart-seq2. Nat. Protoc. 9, 171–181 (2014).Article 
CAS 

Google Scholar 
Keeling, P. J., Poulson, N. & McFadden, G. I. Phylogenetic diversity of parabasalian symbionts from termites, including the phylogenetic position of Pseudotrypanosoma and Trichonympha. J. Eukaryot. Microbiol. 45, 643–650 (1998).Article 
CAS 

Google Scholar 
Medlin, L., Elwood, H. J., Stickel, S. & Sogin, M. L. The characterization of enzymatically amplified eukaryotic 16S-like rRNA-coding regions. Gene 71, 491–499 (1988).Article 
CAS 

Google Scholar 
Tikhonenkov, D. V., Janouškovec, J., Keeling, P. J. & Mylnikov, A. P. The morphology, ultrastructure and SSU rRNA gene sequence of a new freshwater flagellate, Neobodo borokensis n. sp. (Kinetoplastea, Excavata). J. Eukaryot. Microbiol. 63, 220–232 (2016).Article 
CAS 

Google Scholar 
Andrews, S. FastQC: a quality control tool for high throughput sequence data (Babraham Bioinformatics, 2010); https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.Zhang, J., Kobert, K., Flouri, T. & Stamatakis, A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30, 614–620 (2013).Article 

Google Scholar 
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).Article 
CAS 

Google Scholar 
Grabherr, M. G. et al. Full-length transcriptome assembly from RNA-seq data without a reference genome. Nat. Biotechnol. 29, 644–652 (2011).Article 
CAS 

Google Scholar 
Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).Article 
CAS 

Google Scholar 
Laetsch, D. R. & Blaxter, M. L. BlobTools: interrogation of genome assemblies. F1000Research 6, 1287 (2017).Article 

Google Scholar 
Haas, B. J. et al. Denovo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat. Protoc. 8, 1494–1512 (2013).Article 
CAS 

Google Scholar 
Li, W. & Godzik, A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006).Article 
CAS 

Google Scholar 
Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).Article 
CAS 

Google Scholar 
Shen, W. & Ren, H. TaxonKit: a practical and efficient NCBI taxonomy toolkit. J. Genet. Genomics 48, 844–850 (2021).Richter, D. J. et al. EukProt: a database of genome-scale predicted proteins across the diversity of eukaryotes. Peer Community Journal 2, e56 (2022).Simao, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015).Article 
CAS 

Google Scholar 
Kanehisa, M., Furumichi, M., Sato, Y., Ishiguro-Watanabe, M. & Tanabe, M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 49, D545–D551 (2021).Article 
CAS 

Google Scholar 
Moriya, Y., Itoh, M., Okuda, S., Yoshizawa, A. C. & Kanehisa, M. KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 35, W182–W185 (2007).Article 

Google Scholar 
Burki, F. The eukaryotic tree of life from a global phylogenomic perspective. Cold Spring Harb. Perspect. Biol. 6, a016147 (2014).Article 

Google Scholar 
Waskom, M. et al. mwaskom/Seaborn: v0.8.1 (September 2017). Zenodo https://doi.org/10.5281/zenodo.883859 (2017).Eddy, S. R. Accelerated profile HMM searches. PLoS Comput. Biol. 7, e1002195 (2011).Article 
ADS 
MathSciNet 
CAS 

Google Scholar 
Finn, R. D. et al. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res. 44, D279–D285 (2016).Article 
CAS 

Google Scholar 
Letunic, I. & Bork, P. 20 years of the SMART protein domain annotation resource. Nucleic Acids Res. 46, D493–D496 (2018).Article 
CAS 

Google Scholar 
Almagro Armenteros, J. J. et al. SignalP 5.0 improves signal peptide predictions using deep neural networks. Nat. Biotechnol. 37, 420–423 (2019).Article 
CAS 

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

Google Scholar 
Burns, J. A., Pittis, A. A. & Kim, E. Gene-based predictive models of trophic modes suggest Asgard archaea are not phagocytotic. Nat. Ecol. Evol. 2, 697–704 (2018).Article 

Google Scholar 
Emms, D. M. & Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 238 (2019).Article 

Google Scholar 
Altschul, S. F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402 (1997).Article 
CAS 

Google Scholar 
Hall, T. A. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp. Ser. 41, 95–98 (1999).CAS 

Google Scholar 
Minh, B. Q. et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol. 37, 1530–1534 (2020).Article 
CAS 

Google Scholar 
Whelan, S., Irisarri, I. & Burki, F. PREQUAL: detecting non-homologous characters in sets of unaligned homologous sequences. Bioinformatics 34, 3929–3930 (2018).CAS 

Google Scholar 
Capella-Gutierrez, S., Silla-Martinez, J. M. & Gabaldon, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).Article 
CAS 

Google Scholar 
Roure, B., Rodriguez-Ezpeleta, N. & Philippe, H. SCaFoS: a tool for selection, concatenation and fusion of sequences for phylogenomics. BMC Evol. Biol. 7, S2 (2007).Article 

Google Scholar 
Lartillot, N., Rodrigue, N., Stubbs, D. & Richer, J. PhyloBayes MPI: phylogenetic reconstruction with infinite mixtures of profiles in a parallel environment. Syst. Biol. 62, 611–615 (2013).Article 
CAS 

Google Scholar 
Dayhoff, M., Schwartz, R. & Orcutt, B. in Atlas of Protein Sequence and Structure (ed. Dayhoff, M.) 345–352 (National Biomedical Research Foundation, 1978).Susko, E. & Roger, A. J. On reduced amino acid alphabets for phylogenetic inference. Mol. Biol. Evol. 24, 2139–2150 (2007).Article 
CAS 

Google Scholar 
Lartillot, N. & Philippe, H. A Bayesian mixture model for across-site heterogeneities in the amino-acid replacement process. Mol. Biol. Evol. 21, 1095–1109 (2004).Article 
CAS 

Google Scholar 
Quang le, S., Gascuel, O. & Lartillot, N. Empirical profile mixture models for phylogenetic reconstruction. Bioinformatics 24, 2317–2323 (2008).Article 

Google Scholar 
Wang, H. C., Minh, B. Q., Susko, E. & Roger, A. J. Modeling site heterogeneity with posterior mean site frequency profiles accelerates accurate phylogenomic estimation. Syst. Biol. 67, 216–235 (2018).Article 
CAS 

Google Scholar 
Kück, P. & Struck, T. H. BaCoCa—a heuristic software tool for the parallel assessment of sequence biases in hundreds of gene and taxon partitions. Mol. Phylogenet. Evol. 70, 94–98 (2014).Article 

Google Scholar 
Shimodaira, H. An approximately unbiased test of phylogenetic tree selection. Syst. Biol. 51, 492–508 (2002).Article 

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

Google Scholar 
Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).Article 
MathSciNet 
CAS 

Google Scholar 
Dierckxsens, N., Mardulyn, P. & Smits, G. NOVOPlasty: de novo assembly of organelle genomes from whole genome data. Nucleic Acids Res. 45, e18 (2017).
Google Scholar 
Kuznetsov, A. & Bollin, C. J. in Multiple Sequence Alignment (ed. Katoh, K.) 261–295 (Springer, 2021).Lohse, M., Drechsel, O., Kahlau, S. & Bock, R. OrganellarGenomeDRAW—a suite of tools for generating physical maps of plastid and mitochondrial genomes and visualizing expression data sets. Nucleic Acids Res. 41, W575–W581 (2013).Article 

Google Scholar 
Johnson, P. Z., Kasprzak, W. K., Shapiro, B. A. & Simon, A. E. RNA2Drawer: geometrically strict drawing of nucleic acid structures with graphical structure editing and highlighting of complementary subsequences. RNA Biol. 16, 1667–1671 (2019).Article 

Google Scholar 
Burger, G., Gray, M. W., Forget, L. & Lang, B. F. Strikingly bacteria-like and gene-rich mitochondrial genomes throughout jakobid protists. Genome Biol. Evol. 5, 418–438 (2013).Article 

Google Scholar 
Criscuolo, A. & Gribaldo, S. BMGE (Block Mapping and Gathering with Entropy): a new software for selection of phylogenetic informative regions from multiple sequence alignments. BMC Evol. Biol. 10, 210 (2010).Article 

Google Scholar 
Zhang, D. et al. PhyloSuite: an integrated and scalable desktop platform for streamlined molecular sequence data management and evolutionary phylogenetics studies. Mol. Ecol. Resour. 20, 348–355 (2020).Article 

Google Scholar 
Nguyen, L.-T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).Article 
CAS 

Google Scholar 
Ibarbalz, F. M. et al. Global trends in marine plankton diversity across kingdoms of life. Cell 179, 1084–1097 (2019).Article 
CAS 

Google Scholar 
Massana, R. et al. Marine protist diversity in European coastal waters and sediments as revealed by high-throughput sequencing. Environ. Microbiol. 17, 4035–4049 (2015).Article 
CAS 

Google Scholar 
Gendron, E. M. S., Darcy, J. L., Hell, K. & Schmidt, S. K. Structure of bacterial and eukaryote communities reflect in situ controls on community assembly in a high-alpine lake. J. Microbiol. 57, 852–864 (2019).Article 
CAS 

Google Scholar 
Minerovic, A. D. et al. 18S-V9 DNA metabarcoding detects the effect of water-quality impairment. Ecol. Indic. 113, 106225 (2020).Article 
CAS 

Google Scholar 
Pearman, J. K. et al. Cross-shelf investigation of coral reef cryptic benthic organisms reveals diversity patterns of the hidden majority. Sci. Rep. 8, 8090 (2018).Article 
ADS 
CAS 

Google Scholar 
Rodas, A. M. et al. Eukaryotic plankton communities across reef environments in Bocas del Toro Archipelago, Panamá. Coral Reefs 39, 1453–1467 (2020).Article 

Google Scholar 
Schoenle, A. et al. High and specific diversity of protists in the deep-sea basins dominated by diplonemids, kinetoplastids, ciliates and foraminiferans. Commun. Biol. 4, 501 (2021).Article 
CAS 

Google Scholar 
Schulhof, M. A. et al. Sierra Nevada mountain lake microbial communities are structured by temperature, resources and geographic location. Mol. Ecol. 29, 2080–2093 (2020).Article 
CAS 

Google Scholar 
Yi, Z. et al. High-throughput sequencing of microbial eukaryotes in Lake Baikal reveals ecologically differentiated communities and novel evolutionary radiations. FEMS Microbiol. Ecol. 93, fix073 (2017). More

Fernández-Martínez, M. et al. Nutrient availability as the key regulator of global forest carbon balance. Nat. Clim. Chang. 4, 471–476 (2014).Article 
ADS 

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

Google Scholar 
Levy-Varon, J. H. et al. Tropical carbon sink accelerated by symbiotic dinitrogen fixation. Nat. Commun. 10, 5637 (2019).Article 
ADS 
CAS 

Google Scholar 
Batterman, S. A. et al. Key role of symbiotic dinitrogen fixation in tropical forest secondary succession. Nature 502, 224–227 (2013).Article 
ADS 
CAS 

Google Scholar 
Ter Steege, H. et al. Continental-scale patterns of canopy tree composition and function across Amazonia. Nature 443, 444–447 (2006).Article 
ADS 

Google Scholar 
Hedin, L. O., Brookshire, E. N. J., Menge, D. N. L. & Barron, A. R. The nitrogen paradox in tropical forest ecosystems. Annu. Rev. Ecol. Evol. Syst. 40, 613–635 (2009).Article 

Google Scholar 
Menge, D. N. L. et al. Patterns of nitrogen-fixing tree abundance in forests across Asia and America. J. Ecol. 107, 2598–2610 (2019).Article 
CAS 

Google Scholar 
Matson, W. J.Jr Herbivory in relation to plant nitrogen content. Annu. Rev. Ecol. Syst. 11, 119–161 (1980).Article 

Google Scholar 
Coley, P. D., Bateman, M. L. & Kusar, T. A. The effects of plant quality on caterpillar growth and defense against natural enemies. Oikos 115, 219–228 (2006).Article 

Google Scholar 
Wieder, W. R., Cleveland, C. C., Smith, W. K. & Todd-Brown, K. Future productivity and carbon storage limited by terrestrial nutrient availability. Nat. Geosci. 8, 441–444 (2015).Article 
ADS 
CAS 

Google Scholar 
Barron, A. R., Purves, D. W. & Hedin, L. O. Facultative nitrogen fixation by canopy legumes in a lowland tropical forest. Oecologia 165, 511–520 (2011).Article 
ADS 

Google Scholar 
McCulloch, L. A. & Porder, S. Light fuels while nitrogen suppresses symbiotic nitrogen fixation hotspots in neotropical canopy gap seedlings. New Phytol. 231, 1734–1745 (2021).Article 
CAS 

Google Scholar 
Brookshire, E. N. J. et al. Symbiotic N fixation is sufficient to support net aboveground biomass accumulation in a humid tropical forest. Sci Rep. 9, 7571 (2019).Article 
ADS 
CAS 

Google Scholar 
Gei, M. et al. Legume abundance along successional and rainfall gradients in Neotropical forests. Nat. Ecol. Evol. 2, 1104–1111 (2018).Article 

Google Scholar 
Vance, C. P. in Nitrogen-fixing Leguminous Symbioses. Nitrogen Fixation: Origins, Applications, and Research Progress, Vol. 7 (eds Dilworth, M. J. et al.) (Springer, 2008).Vitousek, P. M. & Howarth, R. W. Nitrogen limitation on land and in the sea: how can it occur? Biogeochemistry 13, 87–115 (1991).Article 

Google Scholar 
Menge, D. N. L., Levin, S. A. & Hedin, L. O. Evolutionary tradeoffs can select against nitrogen fixation and thereby maintain nitrogen limitation. Proc. Natl Acad. Sci. USA 105, 1573–1578 (2008).Article 
ADS 
CAS 

Google Scholar 
Sheffer, E., Batterman, S. A., Levin, S. A. & Hedin, L. O. Biome-scale nitrogen fixation strategies selected by climatic constraints on nitrogen cycle. Nat. Plants 1, 15182 (2015).Article 
CAS 

Google Scholar 
Vitousek, P. M. & Field, C. B. Ecosystem constraints to symbiotic nitrogen fixers: a simple model and its implications. Biogeochemistry 46, 179–202 (1999).Article 
CAS 

Google Scholar 
Coley, P. D. & Barone, J. A. Herbivory and plant defenses in tropical forests. Annu. Rev. Ecol. Syst. 27, 305–335 (1996).Article 

Google Scholar 
Fyllas, N. M. et al. Basin-wide variations in foliar properties of Amazonian forest: phylogeny, soils and climate. Biogeosciences 6, 2677–2708 (2009).Article 
ADS 

Google Scholar 
Batterman, S. A. et al. Phosphatase activity and nitrogen fixation reflect species differences, not nutrient trading or nutrient balance, across tropical rainforest trees. Ecol. Lett. 21, 1486–1495 (2018).Article 

Google Scholar 
Menge, D. N. L., Wolf, A. A. & Funk, J. L. Diversity of nitrogen fixation strategies in Mediterranean legumes. Nat. Plants 1, 15064 (2015).Article 
CAS 

Google Scholar 
Ritchie, M. E. & Tilman, D. Responses of legumes to herbivores and nutrients during succession on a nitrogen-poor soil. Ecol. Soc. Am. 76, 2648–2655 (1995).
Google Scholar 
Taylor, B. N. & Ostrowsky, L. R. Nitrogen-fixing and non-fixing trees differ in leaf chemistry and defence but not herbivory in a lowland Costa Rican rain forest. J. Trop. Ecol. 35, 270–279 (2019).Article 

Google Scholar 
Endara, M.-J. et al. Coevolutionary arms race versus host defense chase in a tropical herbivore–plant system. Proc. Natl Acad. Sci. USA 114, E7499–E7505 (2017).Article 
CAS 

Google Scholar 
Kursar, T. A. & Coley, P. D. Convergence in defense syndromes of young leaves in tropical rainforests. Biochem. Syst. Ecol. 31, 929–949 (2003).Article 
CAS 

Google Scholar 
Kursar, T. A. et al. The evolution of antiherbivore defenses and their contribution to species coexistence in the tropical tree genus Inga. Proc. Natl Acad. Sci. USA 106, 18073–18078 (2009).Article 
ADS 
CAS 

Google Scholar 
Taylor, B. N. & Menge, D. N. L. Light regulates tropical symbiotic nitrogen fixation more strongly than soil nitrogen. Nat. Plants 4, 655–661 (2018).Article 
CAS 

Google Scholar 
Adams, M., Turnbull, T., Sprent, J. & Buchmann, N. Legumes are different: leaf nitrogen, photosynthesis, and water use efficiency. Proc. Natl Acad. Sci. USA 113, 4098–4103 (2016).Article 
ADS 
CAS 

Google Scholar 
Coley, P. D. Effects of plant growth rate and leaf lifetime on the amount and type of anti-herbivore defense. Oecologia 74, 531–536 (1988).Article 
ADS 
CAS 

Google Scholar 
Batterman, S. A., Wurzburger, N. & Hedin, L. O. Nitrogen and phosphorus interact to control tropical symbiotic N2 fixation: a test in Inga punctata. J. Ecol. 101, 1400–1408 (2013).Article 
CAS 

Google Scholar 
Eichhorn, M. P., Nilus, R., Compton, S. G., Hartley, S. E. & Burslem, D. F. R. P. Herbivory of tropical rain forest tree seedlings correlates with future mortality. Ecology 91, 1092–1101 (2010).Article 

Google Scholar 
Wink, M. Evolution of secondary metabolites in legumes (Fabaceae). South African J. Bot. 89, 164–175 (2013).Article 
CAS 

Google Scholar 
Currano, E. D. & Jacobs, B. F. Bug-bitten leaves from the early Miocene of Ethiopia elucidate the impacts of plant nutrient concentrations and climate on insect herbivore communities. Glob. Planet. Change 207, 103655 (2021).Article 

Google Scholar 
Wieder, W. R., Cleveland, C. C., Lawrence, D. M. & Bonan, G. B. Effects of model structural uncertainty on carbon cycle projections: biological nitrogen fixation as a case study. Environ. Res. Lett. 10, 044016 (2015).Article 
ADS 

Google Scholar 
Sprent, J. I. Legume Nodulation: A Global Perspective (John Wiley, 2009).Leigh, E. G. Jr Tropical Forest Ecology: A View from Barro Colorado Island (Oxford Univ. Press, 1999).Comita, L. S., Muller-Landau, H. C., Aguilar, S. & Hubbell, S. P. Asymmetric density dependence shapes species abundances in a tropical tree community. Science 329, 330–332 (2010).Article 
ADS 
CAS 

Google Scholar 
Queenborough, S. A., Metz, M. R., Valencia, R. & Wright, S. J. Demographic consequences of chromatic leaf defence in tropical tree communities: do red young leaves increase growth and survival? Ann. Bot. 112, 677–684 (2013).Article 

Google Scholar 
Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671 (2012).Article 
CAS 

Google Scholar 
Pasquini, S. C. & Santiago, L. S. Nutrients limit photosynthesis in seedlings of a lowland tropical forest tree species. Oecologia 168, 311–319 (2012).Article 
ADS 
CAS 

Google Scholar 
Collalti, A. & Prentice, I. C. Is NPP proportional to GPP? Waring’s hypothesis 20 years on. Tree Physiol. 39, 1473–1483 (2019).Article 
CAS 

Google Scholar 
Westbrook, J. W. et al. What makes a leaf tough? Patterns of correlated evolution between leaf toughness traits and demographic rates among 197 shade-tolerant woody species in a Neotropical forest. Am. Nat. 177, 800–811 (2011).Article 

Google Scholar 
Wright, S. J. et al. Functional traits and the growth–mortality trade‐off in tropical trees. Ecology 91, 3664–3674 (2010).Article 

Google Scholar 
Kitajima, K. et al. How cellulose-based leaf toughness and lamina density contribute to long leaf lifespans of shade-tolerant species. New Phytol. 195, 640–652 (2012).Article 

Google Scholar 
Kitajima, K., Wright, S. J. & Westbrook, J. W. Leaf cellulose density as the key determinant of inter- and intra-specific variation in leaf fracture toughness in a species-rich tropical forest. Interface Focus https://doi.org/10.1098/rsfs.2015.0100 (2016).Sedio, B. E., Echeverri, J. C. R., Boya, C. A. & Wright, S. J. Sources of variation in foliar secondary chemistry in a tropical forest tree community. Ecology 98, 616–623 (2017).Article 

Google Scholar 
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9, 378–400 (2017).Article 

Google Scholar 
Smithson, M. & Verkuilen, J. A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables. Psychol. Methods 11, 54–71 (2006).Article 

Google Scholar 
Murphy, S. J., Xu, K. & Comita, L. S. Tree seedling richness, but not neighborhood composition, influences insect herbivory in a temperate deciduous forest community. Ecol. Evol. 6, 6310–6319 (2016).Article 

Google Scholar 
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. Preprint at https://arxiv.org/abs/1406.5823 (2014).Moles, A. T. & Westoby, M. Do small leaves expand faster than large leaves, and do shorter expansion times reduce herbivore damage? Oikos 90, 517–524 (2000).Article 

Google Scholar 
Bürkner, P. C. brms: An R package for Bayesian multilevel models using Stan. J. Stat. Softw. https://doi.org/10.18637/jss.v080.i01 (2017). More

RESEARCH BRIEFINGS
07 December 2022

Ancient environmental DNA from northern Greenland opens a new chapter in genetic research, demonstrating that it is possible to track the ecology and evolution of biological communities two million years ago. The record shows an open boreal-forest ecosystem inhabited by large animals such as mastodons and reindeer. More

Restoring the connection between people and the rest of nature hinges on whole-system science, actions and negotiations.
Those who think about and practise sustainability are constantly looking for holistic interpretations of the world and are trying to understand systemic relations, networks and connections. Biodiversity has all of these things. It shows how every species needs other species to exist and thrive. It shows that all living organisms are part of a sophisticated and fascinating system made up of myriads of links. And humans are undoubtedly a part of it.
Credit: Pulsar Imagens / Alamy Stock PhotoIn the realm of sustainability, experts also ponder about time: how can life exist and thrive over time? Indeed, the above mentioned fascinating system evolves over time. And, over time, it has to adapt to unexpected change. It does that well when it is healthy, and less well when it is ill and constantly disturbed.For a long time, man-made impacts kept accumulating almost completely unchecked by societies, until the consequences for human well-being became untenable. Nowadays, environmental crises make the headlines regularly. They are nothing but the result of a broken connection between people and the rest of nature.Climate change is one major outcome of the broken human–rest of nature connection and has wide ramifications for both people and the planet. We now face imminent disaster, unequally across the world, yet addressing climate change remains an incredibly thorny task. Country representatives from most nations around the world meet regularly at the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCC) — most recently at COP27, which was held in Egypt — to continue the debate on what actions are needed to move the climate agenda forward, all while disasters continue to hit the most vulnerable populations. The world has seen 27 COP meetings to the UNFCC so far; one wonders how many more meetings will be needed to see real change happen.Interestingly, country representatives also meet regularly to discuss biodiversity protection; biodiversity decline — the other major consequence of the broken human–rest of nature connection — is just as worrying, with severe and ramified implications that are still largely underappreciated by decision-makers. These gatherings are the COP meetings to the Convention on Biological Diversity (CBD). Last year, we wrote about the then forthcoming COP15 to the CBD (Nat. Sustain. 4, 189; 2021), the meeting in which the new conservation targets to be met by 2030 were to be agreed. We highlighted the extent to which experts worried that those new targets might not go far enough. The meeting was postponed more than once due to the COVID-19 pandemic, and it is finally happening on 7 December 2022, in Montreal, Canada. The world has already seen 15 COP meetings to the CBD, how many more meetings will be needed for the biodiversity crisis to be averted?But let’s go back to thinking about sustainability. Experts look for holistic visions of the world. Here is an interesting example of what holism means. Biodiversity decline and climate change are both the result of the broken connection between people and the rest of nature, they ultimately have the same, deep roots. They are mutually reinforcing phenomena: unhealthy biodiversity contributes to climate change, and climate change makes biodiversity ill. All this is bad news for human and planetary well-being. The climate–biodiversity conundrum, at least to some degree, has been recognized at a higher level — during COP27, leaders dedicated one day to biodiversity.Yet, given that these issues are highly interconnected and have the same origin, why is the world insisting on discussing them as separate agendas? Why are we still holding two separate COPs? How are these meetings going to promote any fruitful synergy? How will they lead people to reconnect with the rest of nature? Country representatives should be breaking silos, embracing holism and bringing these intertwined issues, and their multiple ramifications, to the same negotiating table.Nature Sustainability welcomes the long-awaited COP15 to the CBD and hopes that countries will agree on feasible yet ambitious 2030 targets to protect and enhance biodiversity. But most of all, we hope that all of the experts and leaders involved in addressing the environmental crises embrace holism to promote meaningful actions across the world aimed at restoring people’s connection with the rest of nature. We are eager to see progress to this end. In the meantime, the collection we started in March 2021 with Nature Ecology & Evolution has been updated to renew our support to the biodiversity community. More

Listen to the latest from the world of science, with Benjamin Thompson.
Your browser does not support the audio element.

Download MP3

In this episode:00:45 World’s oldest DNA shows that mastodons roamed ancient GreenlandDNA recovered from ancient permafrost has been used to reconstruct what an ecosystem might have looked like two million years ago. Their work suggests that Northern Greenland was much warmer than the frozen desert it is today, with a rich ecosystem of plants and animals.Research Article: Kjær et al.Nature Video: The world’s oldest DNA: Extinct beasts of ancient Greenland08:21 Research HighlightsWhy low levels of ‘good’ cholesterol don’t predict heart disease risk in Black people, and how firework displays affect the flights of geese.Research Highlight: ‘Good’ cholesterol readings can lead to bad results for Black peopleResearch Highlight: New Year’s fireworks chase wild geese high into the sky10:31 Modelling the potential emissions of plasticsWhile the global demand for plastics is growing, the manufacturing and disposal of these ubiquitous materials is responsible for significant CO2 emissions each year. This week, a team have modelled how CO2 emissions could vary in the context of different strategies for mitigating climate change. They reveal how under specific conditions the industry could potentially become a carbon sink.Research Article: Stegmann et al.News and Views: Plastics can be a carbon sink but only under stringent conditionsSubscribe to Nature Briefing, an unmissable daily round-up of science news, opinion and analysis free in your inbox every weekday.Never miss an episode. Subscribe to the Nature Podcast on Apple Podcasts, Google Podcasts, Spotify or your favourite podcast app. An RSS feed for Nature Podcast is available too. More

Pristine ecosystems such as mangrove forests protect against the effects of climate change.Credit: Karine Aigner/Nature Picture Library

The Paris climate agreement, signed in December 2015, ranks as one of the most momentous global treaties ever negotiated, setting a crucial goal to seek to limit warming to 1.5–2 °C above pre-industrial levels. At the time, the opening ceremony of the COP21 climate-change conference that led to the agreement also held the record for the largest number of world leaders ever to attend a United Nations event in a single day — more than 150. The two things are probably more than coincidence.Now biodiversity is hoping for its Paris moment. The long-delayed COP15 conference, starting on 7 December in Montreal, Canada, aims to seal a bold new international deal committing countries to precise targets to curb species loss and to protect and restore nature.Many factors suggest the time is ripe. The problem of biodiversity loss is more prominent than ever before. As ecologist Sandra Díaz wrote in Nature last week, researchers have assembled the strongest evidence base yet ahead of COP15, the Fifteenth Conference of the Parties to the Convention on Biological Diversity (S. Díaz Nature 612, 9; 2022). Initiatives such as the Dasgupta Review, commissioned by the UK government, have made plain that the protection of biodiversity is an economic necessity.
COP15 biodiversity plan risks being alarmingly diluted
There is also much greater public awareness of how pollution and habitat destruction threaten the health of ecosystems on which we depend for food, clean water and disease prevention, and a better understanding of nature’s crucial role in mitigating climate change — for example, by storing carbon in soils and trees — as well as in helping us to adapt to its impacts. Mangrove forests, for instance, are hugely effective in stopping influxes of seawater from tsunamis and sea-level rise.But when it comes to getting stalled negotiations motoring again, the scale of support by world leaders that was a feature of climate’s road to Paris is currently lacking.Change cannot come too soon. Nature is on the brink. Of 20 decadal targets to preserve nature that were set in Aichi, Japan, in 2010, not a single one had been fully met by 2020. That, coupled with underfunding and lack of regard for the rights of Indigenous peoples who steward much of the world’s remaining biodiversity, means more species than ever are at risk of extinction. Serious impacts on human wealth and health from biodiversity loss loom ever larger. Yet over the past three years, four difficult rounds of negotiations aiming to agree on a framework to replace Aichi have not yielded results. Hundreds of issues remain unresolved.
COVID delays are frustrating the world’s plans to save biodiversity
Many experts worry that the lacklustre progress made at COP27, the climate summit held last month in Sharm El-Sheikh, Egypt, augur badly for the biodiversity meeting. But there is also reason for hope. The agreement made at COP27 to establish a ‘loss and damage’ fund to compensate low- and middle-income countries (LMICs) for climate impacts indicates that richer nations are open to talking about funding, which has also been a major sticking point in biodiversity negotiations.Global funding for biodiversity is severely in the red. A UN estimate published last week suggests that only US$154 billion per year flows to ‘nature-based solutions’ from all sources, including government aid and private investment — a number the UN says needs to triple by 2030. Many LMICs — which are home to much of the world’s remaining biodiversity — would like rich nations to put fresh finance into a new multilateral fund. One option is that such a fund could compensate LMICs for bio-diversity loss and associated damages driven by the consumption of products in rich nations through international trade.A second major sticking point is how to fairly and equitably share the benefits of digital sequence information — genetic data collected from plants, animals and other organisms. Communities in biodiversity-rich regions where genetic material is collected have little control over the commercialization of the data, and no way to recoup financial or other benefits. A multipurpose fund for bio-diversity could provide a simple and effective way to share the benefits of these data and support other conservation needs of LMICs.Another reason to hope for a breakthrough is the forthcoming change in Brazil’s leadership. Conservation organizations such as the wildlife charity WWF have accused the world’s most biodiverse nation of deliberately obstructing previous negotiations, holding up agreement on targets such as protecting at least 30% of the world’s land and seas by 2030. But Brazil’s incoming president, Luiz Inácio Lula da Silva, has signalled that the environment is one of his top priorities. Although he does not take over until January 2023, he is thought to be sending an interim team of negotiators to Montreal.
Crucial biodiversity summit will go ahead in Canada, not China: what scientists think
All negotiators face a Herculean task to get a deal over the line at COP15, with many issues in the text still unresolved and contested. What’s needed above all is global leadership to empower national negotiators to reach a strong deal, including a new fund of some kind for biodiversity. More than 90 heads of state and heads of government have signed a pledge to tackle the nature crisis. At the time of writing, only Justin Trudeau, the host nation’s prime minster, has confirmed that he is to attend in person.The no-shows send the wrong signal. It’s also true at the time of writing that neither Canada nor China — the original intended host of COP15 and still the meeting’s chair — has issued formal invitations. But leaders have regularly attended climate COPs for more than a decade. This shows in the ambition of climate agreements, if not in their implementation. Research communities and civil society must continue to pressure leaders to engage similarly with the biodiversity agenda. Otherwise, the world risks failing to grasp this opportunity to secure the kind of ambitious deal that nature — and humanity — desperately needs. More

Ray, D. K., Gerber, J. S., Macdonald, G. K. & West, P. C. Climate variation explains a third of global crop yield variability. Nat. Commun. 6, 5989 (2015).Article 

Google Scholar 
Frieler, K. et al. Understanding the weather signal in national crop-yield variability. Earths Future 5, 605–616 (2017).Article 

Google Scholar 
Vogel, E. et al. The effects of climate extremes on global agricultural yields. Environ. Res. Lett. 14, 054010 (2019).Article 

Google Scholar 
Zscheischler, J. et al. A typology of compound weather and climate events. Nat. Rev. Earth Environ. 1, 333–347 (2020).Article 

Google Scholar 
Ridder, N. N., Ukkola, A. M., Pitman, A. J. & Perkins-Kirkpatrick, S. E. Increased occurrence of high impact compound events under climate change. npj Clim. Atmos. Sci. 5, 3 (2022).Article 

Google Scholar 
Lesk, C. & Anderson, W. Decadal variability modulates trends in concurrent heat and drought over global croplands. Environ. Res. Lett. 16, 055024 (2021).Article 

Google Scholar 
Sarhadi, A., Ausín, M. C., Wiper, M. P., Touma, D. & Diffenbaugh, N. S. Multidimensional risk in a nonstationary climate: joint probability of increasingly severe warm and dry conditions. Sci. Adv. 4, eaau3487 (2018).Article 

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

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

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

Google Scholar 
Buckley, T. N. How do stomata respond to water status? New Phytol. 224, 21–36 (2019).Article 

Google Scholar 
Miralles, D. G., Gentine, P., Seneviratne, S. I. & Teuling, A. J. Land–atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges. Ann. NY Acad. Sci. 1436, 19–35 (2019).Article 

Google Scholar 
Mueller, B. & Seneviratne, S. I. Hot days induced by precipitation deficits at the global scale. Proc. Natl Acad. Sci. USA 109, 12398–12403 (2012).Article 

Google Scholar 
Cohen, I., Zandalinas, S. I., Huck, C., Fritschi, F. B. & Mittler, R. Meta-analysis of drought and heat stress combination impact on crop yield and yield components. Physiol. Plant 171, 66–76 (2021).Article 

Google Scholar 
Ostmeyer, T. et al. Impacts of heat, drought, and their interaction with nutrients on physiology, grain yield, and quality in field crops. Plant Physiol. Rep. 25, 549–568 (2020).Article 

Google Scholar 
Matiu, M., Ankerst, D. P. & Menzel, A. Interactions between temperature and drought in global and regional crop yield variability during 1961–2014. PLoS ONE 12, e0178339 (2017).Article 

Google Scholar 
Scheff, J., Mankin, J. S., Coats, S. & Liu, H. CO2-plant effects do not account for the gap between dryness indices and projected dryness impacts in CMIP6 or CMIP5. Environ. Res. Lett. 16, 034018 (2021).Article 

Google Scholar 
Ukkola, A. M., De Kauwe, M. G., Roderick, M. L., Abramowitz, G. & Pitman, A. J. Robust future changes in meteorological drought in CMIP6 projections despite uncertainty in precipitation. Geophys. Res. Lett. 47, e2020GL087820 (2020).Article 

Google Scholar 
Allan, R. P. et al. Advances in understanding large-scale responses of the water cycle to climate change. Ann. NY Acad. Sci. 1472, 49–75 (2020).Article 

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

Google Scholar 
Fowler, H. J. et al. Anthropogenic intensification of short-duration rainfall extremes. Nat. Rev. Earth Environ. 2, 107–122 (2021).Article 

Google Scholar 
Raymond, C. et al. Understanding and managing connected extreme events. Nat. Clim. Change 10, 611–621 (2020).Article 

Google Scholar 
Mills, G. et al. Closing the global ozone yield gap: quantification and cobenefits for multistress tolerance. Glob. Chang. Biol. 24, 4869–4893 (2018).Article 

Google Scholar 
Pandey, P., Irulappan, V., Bagavathiannan, M. V. & Senthil-Kumar, M. Impact of combined abiotic and biotic stresses on plant growth and avenues for crop improvement by exploiting physio-morphological traits. Front. Plant Sci. 8, 537 (2017).Article 

Google Scholar 
Couasnon, A. et al. Measuring compound flood potential from river discharge and storm surge extremes at the global scale. Nat. Hazards Earth Syst. Sci. 20, 489–504 (2020).Article 

Google Scholar 
Nguyen, L. T. T. et al. Flooding and prolonged drought have differential legacy impacts on soil nitrogen cycling, microbial communities and plant productivity. Plant Soil 431, 371–387 (2018).Article 

Google Scholar 
Medrano, H., Escalona, J. M., Bota, J., Gulías, J. & Flexas, J. Regulation of photosynthesis of C3 plants in response to progressive drought: stomatal conductance as a reference parameter. Ann. Bot. 89, 895–905 (2002).Article 

Google Scholar 
Scafaro, A. P. et al. Responses of leaf respiration to heatwaves. Plant Cell Environ. 44, 2090–2101 (2021).Article 

Google Scholar 
Atkin, O. K. & Tjoelker, M. G. Thermal acclimation and the dynamic response of plant respiration to temperature. Trends Plant Sci. 8, 343–351 (2003).Article 

Google Scholar 
Lukac, M., Gooding, M. J., Griffiths, S. & Jones, H. E. Asynchronous flowering and within-plant flowering diversity in wheat and the implications for crop resilience to heat. Ann. Bot. 109, 843–850 (2012).Article 

Google Scholar 
Coast, O., Murdoch, A. J., Ellis, R. H., Hay, F. R. & Jagadish, K. S. V. Resilience of rice (Oryza spp.) pollen germination and tube growth to temperature stress. Plant. Cell Environ. 39, 26–37 (2016).Article 

Google Scholar 
Li, Y., Guan, K., Schnitkey, G. D., Delucia, E. & Peng, B. Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States. Glob. Chang. Biol. https://doi.org/10.1111/gcb.14628 (2019).Article 

Google Scholar 
Tian, L. X. et al. How does the waterlogging regime affect crop yield? A global meta-analysis. Front. Plant Sci. 12, 634898 (2021).Article 

Google Scholar 
Langan, P. et al. Phenotyping for waterlogging tolerance in crops: current trends and future prospects. J. Exp. Bot. https://doi.org/10.1093/jxb/erac243 (2022).Article 

Google Scholar 
Tong, C. et al. Opportunities for improving waterlogging tolerance in cereal crops — physiological traits and genetic mechanisms. Plants 10, 1560 (2021).Article 

Google Scholar 
Colmer, T. D., Cox, M. C. H. & Voesenek, L. A. C. J. Root aeration in rice (Oryza sativa): evaluation of oxygen, carbon dioxide, and ethylene as possible regulators of root acclimatizations. New Phytol. 170, 767–778 (2006).Article 

Google Scholar 
Hattori, Y. et al. The ethylene response factors SNORKEL1 and SNORKEL2 allow rice to adapt to deep water. Nature 460, 1026–1030 (2009).Article 

Google Scholar 
Prasad, P. V. V., Pisipati, S. R., Momčilović, I. & Ristic, Z. Independent and combined effects of high temperature and drought stress during grain filling on plant yield and chloroplast EF-Tu expression in spring wheat. J. Agron. Crop Sci. 197, 430–441 (2011).Article 

Google Scholar 
Suzuki, N., Rivero, R. M., Shulaev, V., Blumwald, E. & Mittler, R. Abiotic and biotic stress combinations. New Phytol. 203, 32–43 (2014).Article 

Google Scholar 
Hussain, H. A. et al. Interactive effects of drought and heat stresses on morpho-physiological attributes, yield, nutrient uptake and oxidative status in maize hybrids. Sci. Rep. 9, 3890 (2019).Article 

Google Scholar 
Mittler, R. Abiotic stress, the field environment and stress combination. Trends Plant Sci. 11, 15–19 (2006).Article 

Google Scholar 
Choudhury, F. K., Rivero, R. M., Blumwald, E. & Mittler, R. Reactive oxygen species, abiotic stress and stress combination. Plant J. 90, 856–867 (2017).Article 

Google Scholar 
Van Der Wiel, K., Selten, F. M., Bintanja, R., Blackport, R. & Screen, J. A. Ensemble climate-impact modelling: extreme impacts from moderate meteorological conditions. Environ. Res. Lett. 15, 034050 (2020).Article 

Google Scholar 
Moore, C. E. et al. The effect of increasing temperature on crop photosynthesis: from enzymes to ecosystems. J. Exp. Bot. 72, 2822–2844 (2021).Article 

Google Scholar 
Fahad, S. et al. Crop production under drought and heat stress: plant responses and management options. Front. Plant Sci. 8, 1147 (2017).Article 

Google Scholar 
Zandalinas, S. I., Fritschi, F. B. & Mittler, R. Signal transduction networks during stress combination. J. Exp. Bot. 71, 1734–1741 (2020).Article 

Google Scholar 
Zhang, H. & Sonnewald, U. Differences and commonalities of plant responses to single and combined stresses. Plant J. 90, 839–855 (2017).Article 

Google Scholar 
Zscheischler, J. & Seneviratne, S. I. Dependence of drivers affects risks associated with compound events. Sci. Adv. 3, e1700263 (2017).Article 

Google Scholar 
Horton, R. M., Mankin, J. S., Lesk, C., Coffel, E. & Raymond, C. A review of recent advances in research on extreme heat events. Curr. Clim. Change Rep. 2, 242–259 (2016).Article 

Google Scholar 
Trenberth, K. E. & Shea, D. J. Relationships between precipitation and surface temperature. Geophys. Res. Lett. 32, L14703 (2005).Article 

Google Scholar 
Miralles, D. G., Teuling, A. J., Van Heerwaarden, C. C. & De Arellano, J. V. G. Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation. Nat. Geosci. 7, 345–349 (2014).Article 

Google Scholar 
Berg, A. et al. Land–atmosphere feedbacks amplify aridity increase over land under global warming. Nat. Clim. Change 6, 869–874 (2016).Article 

Google Scholar 
Seneviratne, S. I. et al. Investigating soil moisture–climate interactions in a changing climate: a review. Earth Sci. Rev. 99, 125–161 (2010).Article 

Google Scholar 
Koster, R. D., Chang, Y., Wang, H. & Schubert, S. D. Impacts of local soil moisture anomalies on the atmospheric circulation and on remote surface meteorological fields during boreal summer: a comprehensive analysis over North America. J. Clim. 29, 7345–7364 (2016).Article 

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

Google Scholar 
Berg, A., Lintner, B., Findell, K. & Giannini, A. Soil moisture influence on seasonality and large-scale circulation in simulations of the West African monsoon. J. Clim. 30, 2295–2317 (2017).Article 

Google Scholar 
Lesk, C. et al. Stronger temperature–moisture couplings exacerbate the impact of climate warming on global crop yields. Nat. Food 2, 683–691 (2021).Article 

Google Scholar 
Wei, Z. et al. Revisiting the contribution of transpiration to global terrestrial evapotranspiration. Geophys. Res. Lett. 44, 2792–2801 (2017).Article 

Google Scholar 
Piao, S. et al. Characteristics, drivers and feedbacks of global greening. Nat. Rev. Earth Environ. 1, 14–27 (2020).Article 

Google Scholar 
Lian, X. et al. Partitioning global land evapotranspiration using CMIP5 models constrained by observations. Nat. Clim. Change 8, 640–646 (2018).Article 

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

Google Scholar 
Raymond, C. et al. Increasing spatiotemporal proximity of heat and precipitation extremes in a warming world quantified by a large model ensemble. Environ. Res. Lett. 17, 035005 (2022).Article 

Google Scholar 
Raymond, C. et al. On the controlling factors for globally extreme humid heat. Geophys. Res. Lett. 48, e2021GL096082 (2021).Article 

Google Scholar 
Speizer, S., Raymond, C., Ivanovich, C. & Horton, R. M. Concentrated and intensifying humid heat extremes in the IPCC AR6 regions. Geophys. Res. Lett. 49, e2021GL097261 (2022).Article 

Google Scholar 
Ning, G. et al. Rising risks of compound extreme heat‐precipitation events in China. Int. J. Climatol. https://doi.org/10.1002/joc.7561 (2022).Article 

Google Scholar 
Thiery, W. et al. Warming of hot extremes alleviated by expanding irrigation. Nat. Commun. 11, 290 (2020).Article 

Google Scholar 
Mueller, N. D. et al. Global relationships between cropland intensification and summer temperature extremes over the last 50 years. J. Clim. 30, 7505–7528 (2017).Article 

Google Scholar 
Siebert, S., Ewert, F., Eyshi Rezaei, E., Kage, H. & Graß, R. Impact of heat stress on crop yield — on the importance of considering canopy temperature. Environ. Res. Lett. 9, 044012 (2014).Article 

Google Scholar 
Singh, D. et al. Distinct influences of land cover and land management on seasonal climate. J. Geophys. Res. Atmos. 123, 12017–12039 (2018).Article 

Google Scholar 
Luan, X. & Vico, G. Canopy temperature and heat stress are increased by compound high air temperature and water stress and reduced by irrigation — a modeling analysis. Hydrol. Earth Syst. Sci. 25, 1411–1423 (2021).Article 

Google Scholar 
Siebert, S., Webber, H., Zhao, G. & Ewert, F. Heat stress is overestimated in climate impact studies for irrigated agriculture. Environ. Res. Lett. 12, 054023 (2017).Article 

Google Scholar 
Sinha, R. et al. Differential regulation of flower transpiration during abiotic stress in annual plants. New Phytol. https://doi.org/10.1111/nph.18162 (2022).Article 

Google Scholar 
He, Y., Lee, E. & Mankin, J. S. Seasonal tropospheric cooling in Northeast China associated with cropland expansion. Environ. Res. Lett. 15, 034032 (2020).Article 

Google Scholar 
Alter, R. E., Douglas, H. C., Winter, J. M. & Eltahir, E. A. B. Twentieth century regional climate change during the summer in the Central United States attributed to agricultural intensification. Geophys. Res. Lett. 45, 1586–1594 (2018).Article 

Google Scholar 
Sánchez, B., Rasmussen, A. & Porter, J. R. Temperatures and the growth and development of maize and rice: a review. Glob. Chang. Biol. 20, 408–417 (2014).Article 

Google Scholar 
Prasad, P. V. V., Bheemanahalli, R. & Jagadish, S. V. K. Field crops and the fear of heat stress — opportunities, challenges and future directions. Field Crops Res. 200, 114–121 (2017).Article 

Google Scholar 
Schauberger, B. et al. Consistent negative response of US crops to high temperatures in observations and crop models. Nat. Commun. 8, 13931 (2017).Article 

Google Scholar 
Lobell, D. B. et al. The critical role of extreme heat for maize production in the United States. Nat. Clim. Change 3, 497–501 (2013).Article 

Google Scholar 
Sadok, W. & Jagadish, S. V. K. The hidden costs of nighttime warming on yields. Trends Plant Sci. 25, 644–651 (2020).Article 

Google Scholar 
Troy, T. J., Kipgen, C. & Pal, I. The impact of climate extremes and irrigation on US crop yields. Environ. Res. Lett. 10, 054013 (2015).Article 

Google Scholar 
Cook, B. I., Shukla, S. P., Puma, M. J. & Nazarenko, L. S. Irrigation as an historical climate forcing. Clim. Dyn. 44, 1715–1730 (2015).Article 

Google Scholar 
Li, Y. et al. Quantifying irrigation cooling benefits to maize yield in the US Midwest. Glob. Chang. Biol. 26, 3065–3078 (2020).Article 

Google Scholar 
Entekhabi, B. D. et al. The Soil Moisture Active Passive (SMAP). IEEE Proc. 98, 704–716 (2010).Article 

Google Scholar 
Ortiz-Bobea, A., Wang, H., Carrillo, C. M. & Ault, T. R. Unpacking the climatic drivers of US agricultural yields. Environ. Res. Lett. 14, 064003 (2019).Article 

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

Google Scholar 
Proctor, J., Rigden, A., Chan, D. & Huybers, P. Accurate specification of water availability shows its importance for global crop production. Preprint at EarthArXiv https://doi.org/10.31223/X5ZS7P (2021).Article 

Google Scholar 
Carter, E. K., Melkonian, J., Riha, S. J. & Shaw, S. B. Separating heat stress from moisture stress: analyzing yield response to high temperature in irrigated maize. Environ. Res. Lett. 11, 094012 (2016).Article 

Google Scholar 
Hamed, R., Van Loon, A. F., Aerts, J. & Coumou, D. Impacts of compound hot-dry extremes on US soybean yields. Earth Syst. Dyn. 12, 1371–1391 (2021).Article 

Google Scholar 
Feng, S., Hao, Z., Zhang, X. & Hao, F. Probabilistic evaluation of the impact of compound dry-hot events on global maize yields. Sci. Total Environ. 689, 1228–1234 (2019).Article 

Google Scholar 
Haqiqi, I., Grogan, D. S., Hertel, T. W. & Schlenker, W. Quantifying the impacts of compound extremes on agriculture. Hydrol. Earth Syst. Sci. 25, 551–564 (2021).Article 

Google Scholar 
Zhu, P., Zhuang, Q., Archontoulis, S. V., Bernacchi, C. & Müller, C. Dissecting the nonlinear response of maize yield to high temperature stress with model-data integration. Glob. Chang. Biol. 25, 2470–2484 (2019).Article 

Google Scholar 
Jin, Z. et al. Do maize models capture the impacts of heat and drought stresses on yield? Using algorithm ensembles to identify successful approaches. Glob. Chang. Biol. 22, 3112–3126 (2016).Article 

Google Scholar 
Filipa Silva Ribeiro, A., Russo, A., Gouveia, C. M., Páscoa, P. & Zscheischler, J. Risk of crop failure due to compound dry and hot extremes estimated with nested copulas. Biogeosciences 17, 4815–4830 (2020).Article 

Google Scholar 
Hsiao, J., Swann, A. L. S. & Kim, S. H. Maize yield under a changing climate: the hidden role of vapor pressure deficit. Agric. For. Meteorol. 279, 107692 (2019).Article 

Google Scholar 
Heinicke, S., Frieler, K., Jägermeyr, J. & Mengel, M. Global gridded crop models underestimate yield responses to droughts and heatwaves. Environ. Res. Lett. 17, 044026 (2022).Article 

Google Scholar 
Cook, B. I. et al. Twenty-first century drought projections in the CMIP6 forcing scenarios. Earths Future 8, e2019EF001461 (2020).Article 

Google Scholar 
He, Y., Hu, X., Xu, W., Fang, J. & Shi, P. Increased probability and severity of compound dry and hot growing seasons over world’s major croplands. Sci. Total Environ. 824, 153885 (2022).Article 

Google Scholar 
Wu, Y. et al. Global observations and CMIP6 simulations of compound extremes of monthly temperature and precipitation. GeoHealth 5, e2021GH000390 (2021).Article 

Google Scholar 
Zhang, Y., Hao, Z., Zhang, X. & Hao, F. Anthropogenically forced increases in compound dry and hot events at the global and continental scales. Environ. Res. Lett. 17, 024018 (2022).Article 

Google Scholar 
Chen, Y., Liao, Z., Shi, Y., Tian, Y. & Zhai, P. Detectable increases in sequential flood-heatwave events across China during 1961–2018. Geophys. Res. Lett. 48, e2021GL092549 (2021).
Google Scholar 
Raymond, C., Matthews, T. & Horton, R. M. The emergence of heat and humidity too severe for human tolerance. Sci. Adv. 6, eaaw1838 (2020).Article 

Google Scholar 
Vogel, M. M. et al. Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture–temperature feedbacks. Geophys. Res. Lett. 44, 1511–1519 (2017).Article 

Google Scholar 
Garcia-Herrera, R., Díaz, J., Trigo, R. M., Luterbacher, J. & Fischer, E. M. A review of the European summer heat wave of 2003. Crit. Rev. Environ. Sci. Technol. 40, 267–306 (2010).Article 

Google Scholar 
Wegren, S. Food security and Russia’s 2010 drought. Eurasian Geogr. Econ. 52, 140–156 (2011).Article 

Google Scholar 
Christian, J. I., Basara, J. B., Hunt, E. D., Otkin, J. A. & Xiao, X. Flash drought development and cascading impacts associated with the 2010 Russian heatwave. Environ. Res. Lett. 15, 094078 (2020).Article 

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

Google Scholar 
Yuan, X., Wang, L. & Wood, E. F. Anthropogenic intensification of southern African flash droughts as exemplified by the 2015/16 season. Bull. Am. Meteorol. Soc. 99, S86–S90 (2018).Article 

Google Scholar 
Ben-Ari, T. et al. Causes and implications of the unforeseen 2016 extreme yield loss in the breadbasket of France. Nat. Commun. 9, 1627 (2018).Article 

Google Scholar 
Gampe, D. et al. Increasing impact of warm droughts on northern ecosystem productivity over recent decades. Nat. Clim. Change 11, 772–779 (2021).Article 

Google Scholar 
Iizumi, T. & Ramankutty, N. Changes in yield variability of major crops for 1981–2010 explained by climate change. Environ. Res. Lett. 11, 034003 (2016).Article 

Google Scholar 
Brás, T. A., Seixas, J., Carvalhais, N. & Jagermeyr, J. Severity of drought and heatwave crop losses tripled over the last five decades in Europe. Environ. Res. Lett. 16, 065012 (2021).Article 

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

Google Scholar 
Seneviratne, S. I. et al. Climate extremes, land–climate feedbacks and land-use forcing at 1.5 °C. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 376, 20160450 (2018).Article 

Google Scholar 
Pfleiderer, P., Schleussner, C. F., Kornhuber, K. & Coumou, D. Summer weather becomes more persistent in a 2 °C world. Nat. Clim. Change 9, 666–671 (2019).Article 

Google Scholar 
Mankin, J. S., Seager, R., Smerdon, J. E., Cook, B. I. & Williams, A. P. Mid-latitude freshwater availability reduced by projected vegetation responses to climate change. Nat. Geosci. 12, 983–988 (2019).Article 

Google Scholar 
Dai, A., Zhao, T. & Chen, J. Climate change and drought: a precipitation and evaporation perspective. Curr. Clim. Chang. Rep. 4, 301–312 (2018).Article 

Google Scholar 
Zhao, C. et al. Temperature increase reduces global yields of major crops in four independent estimates. Proc. Natl Acad. Sci. USA 114, 9326–9331 (2017).Article 

Google Scholar 
Lesk, C., Coffel, E. & Horton, R. Net benefits to US soy and maize yields from intensifying hourly rainfall. Nat. Clim. Change 10, 819–822 (2020).Article 

Google Scholar 
Goulart, H. M. D., Van Der Wiel, K., Folberth, C., Balkovic, J. & Van Den Hurk, B. Weather-induced crop failure events under climate change: a storyline approach. Earth Syst. Dyn. https://doi.org/10.5194/esd-2021-40 (2021).Article 

Google Scholar 
Franke, J. A. et al. Agricultural breadbaskets shift poleward given adaptive farmer behavior under climate change. Glob. Chang. Biol. 28, 167–181 (2022).Article 

Google Scholar 
Jägermeyr, J. et al. Climate impacts on global agriculture emerge earlier in new generation of climate and crop models. Nat. Food 2, 873–885 (2021).Article 

Google Scholar 
Waha, K. et al. Multiple cropping systems of the world and the potential for increasing cropping intensity. Glob. Environ. Chang. 64, 102131 (2020).Article 

Google Scholar 
Zhu, T., Fonseca De Lima, C. F. & De Smet, I. The heat is on: how crop growth, development, and yield respond to high temperature. J. Exp. Bot. 72, 7359–7373 (2021).
Google Scholar 
Lizaso, J. I. et al. Impact of high temperatures in maize: phenology and yield components. Field Crops Res. 216, 129–140 (2018).Article 

Google Scholar 
Rezaei, E. E., Siebert, S. & Ewert, F. Intensity of heat stress in winter wheat — phenology compensates for the adverse effect of global warming. Environ. Res. Lett. 10, 024012 (2015).Article 

Google Scholar 
Liu, K. et al. Climate change shifts forward flowering and reduces crop waterlogging stress. Environ. Res. Lett. 16, 094017 (2021).Article 

Google Scholar 
Bagley, J. et al. The influence of photosynthetic acclimation to rising CO2 and warmer temperatures on leaf and canopy photosynthesis models. Global Biogeochem. Cycles https://doi.org/10.1002/2014GB004848 (2015).Article 

Google Scholar 
Hossain, M. A. et al. Heat or cold priming-induced cross-tolerance to abiotic stresses in plants: key regulators and possible mechanisms. Protoplasma 255, 399–412 (2018).Article 

Google Scholar 
Wolz, K. J., Wertin, T. M., Abordo, M., Wang, D. & Leakey, A. D. B. Diversity in stomatal function is integral to modelling plant carbon and water fluxes. Nat. Ecol. Evol. 1, 1292–1298 (2017).Article 

Google Scholar 
Ainsworth, E. A. & Long, S. P. 30 years of free-air carbon dioxide enrichment (FACE): what have we learned about future crop productivity and its potential for adaptation? Glob. Chang. Biol. 27, 27–49 (2021).Article 

Google Scholar 
Toreti, A. et al. Narrowing uncertainties in the effects of elevated CO2 on crops. Nat. Food 1, 775–782 (2020).Article 

Google Scholar 
Myers, S. S. et al. Climate change and global food systems: potential impacts on food security and undernutrition. Annu. Rev. Public Health 38, 259–277 (2017).Article 

Google Scholar 
Skinner, C. B., Poulsen, C. J. & Mankin, J. S. Amplification of heat extremes by plant CO2 physiological forcing. Nat. Commun. 9, 1094 (2018).Article 

Google Scholar 
Houshmandfar, A., Fitzgerald, G. J., Armstrong, R., Macabuhay, A. A. & Tausz, M. Modelling stomatal conductance of wheat: an assessment of response relationships under elevated CO2. Agric. For. Meteorol. 214–215, 117–123 (2015).Article 

Google Scholar 
Chavan, S. G., Duursma, R. A., Tausz, M. & Ghannoum, O. Elevated CO2 alleviates the negative impact of heat stress on wheat physiology but not on grain yield. J. Exp. Bot. 70, 6447–6459 (2019).Article 

Google Scholar 
Gray, S. B. et al. Intensifying drought eliminates the expected benefits of elevated carbon dioxide for soybean. Nat. Plants 2, 16132 (2016).Article 

Google Scholar 
Coffel, E. D. et al. Future hot and dry years worsen Nile basin water scarcity despite projected precipitation increases. Earths Future 7, 967–977 (2019).Article 

Google Scholar 
Mishra, V., Thirumalai, K., Singh, D. & Aadhar, S. Future exacerbation of hot and dry summer monsoon extremes in India. npj Clim. Atmos. Sci. 3, 10 (2020).Article 

Google Scholar 
Bevacqua, E., Zappa, G., Lehner, F. & Zscheischler, J. Precipitation trends determine future occurrences of compound hot–dry events. Nat. Clim. Change 12, 350–355 (2022).Article 

Google Scholar 
Seager, R. et al. Climate variability and change of Mediterranean-type climates. J. Clim. 32, 2887–2915 (2019).Article 

Google Scholar 
Vogel, M. M., Hauser, M. & Seneviratne, S. I. Projected changes in hot, dry and wet extreme events’ clusters in CMIP6 multi-model ensemble. Environ. Res. Lett. 15, 094021 (2020).Article 

Google Scholar 
Zhou, S. et al. Land–atmosphere feedbacks exacerbate concurrent soil drought and atmospheric aridity. Proc. Natl Acad. Sci. USA 116, 18848–18853 (2019).Article 

Google Scholar 
Byrne, M. P. Amplified warming of extreme temperatures over tropical land. Nat. Geosci. 14, 837–841 (2021).Article 

Google Scholar 
McDermid, S. S. et al. Disentangling the regional climate impacts of competing vegetation responses to elevated atmospheric CO2. J. Geophys. Res. Atmos. 126, e2020JD034108 (2021).Article 

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

Google Scholar 
Ali, H., Fowler, H. J., Lenderink, G., Lewis, E. & Pritchard, D. Consistent large-scale response of hourly extreme precipitation to temperature variation over land. Geophys. Res. Lett. https://doi.org/10.1029/2020GL090317 (2021).Article 

Google Scholar 
Dai, A., Rasmussen, R. M., Liu, C., Ikeda, K. & Prein, A. F. A new mechanism for warm-season precipitation response to global warming based on convection-permitting simulations. Clim. Dyn. 55, 343–368 (2020).Article 

Google Scholar 
Fishman, R. More uneven distributions overturn benefits of higher precipitation for crop yields. Environ. Res. Lett. 11, 024004 (2016).Article 

Google Scholar 
Shortridge, J. Observed trends in daily rainfall variability result in more severe climate change impacts to agriculture. Clim. Chang. 157, 429–444 (2019).Article 

Google Scholar 
Guan, K., Sultan, B., Biasutti, M., Baron, C. & Lobell, D. B. What aspects of future rainfall changes matter for crop yields in West Africa? Geophys. Res. Lett. 42, 8001–8010 (2015).Article 

Google Scholar 
Byrne, M. P. & O’Gorman, P. A. Trends in continental temperature and humidity directly linked to ocean warming. Proc. Natl Acad. Sci. USA 115, 4863–4868 (2018).Article 

Google Scholar 
Coffel, E. D., Horton, R. M. & De Sherbinin, A. Temperature and humidity based projections of a rapid rise in global heat stress exposure during the 21st century. Environ. Res. Lett. 13, 014001 (2018).Article 

Google Scholar 
Matthews, T. Humid heat and climate change. Prog. Phys. Geogr. 42, 391–405 (2018).Article 

Google Scholar 
McKinnon, K. A. & Poppick, A. Estimating changes in the observed relationship between humidity and temperature using noncrossing quantile smoothing splines. J. Agric. Biol. Environ. Stat. 25, 292–314 (2020).Article 

Google Scholar 
Parsons, L. A. et al. Global labor loss due to humid heat exposure underestimated for outdoor workers. Environ. Res. Lett. 17, 014050 (2022).Article 

Google Scholar 
Ridder, N. N., Pitman, A. J. & Ukkola, A. M. Do CMIP6 climate models simulate global or regional compound events skillfully? Geophys. Res. Lett. 48, e2020GL091152 (2021).Article 

Google Scholar 
Hao, Z., Aghakouchak, A. & Phillips, T. J. Changes in concurrent monthly precipitation and temperature extremes. Environ. Res. Lett. 8, 034014 (2013).Article 

Google Scholar 
Zhang, B. & Soden, B. J. Constraining climate model projections of regional precipitation change. Geophys. Res. Lett. 46, 10522–10531 (2019).Article 

Google Scholar 
Ray, D. K., Ramankutty, N., Mueller, N. D., West, P. C. & Foley, J. A. Recent patterns of crop yield growth and stagnation. Nat. Commun. 3, 1293 (2012).Article 

Google Scholar 
Butler, E. E., Mueller, N. D. & Huybers, P. Peculiarly pleasant weather for US maize. Proc. Natl Acad. Sci. USA 115, 11935–11940 (2018).Article 

Google Scholar 
Lombardozzi, D. L. et al. Simulating agriculture in the Community Land Model Version 5. J. Geophys. Res. Biogeosci. 125, e2019JG005529 (2020).Article 

Google Scholar 
Puma, M. J. & Cook, B. I. Effects of irrigation on global climate during the 20th century. J. Geophys. Res. Atmos. 115, D16120 (2010).Article 

Google Scholar 
Coffel, E. D., Lesk, C., Winter, J. M., Osterberg, E. C. & Mankin, J. S. Crop–climate feedbacks boost US maize and soy yields. Environ. Res. Lett. 17, 024012 (2022).Article 

Google Scholar 
Mueller, N. D. et al. Cooling of US Midwest summer temperature extremes from cropland intensification. Nat. Clim. Change 6, 317–322 (2016).Article 

Google Scholar 
Zaveri, E. & B. Lobell, D. The role of irrigation in changing wheat yields and heat sensitivity in India. Nat. Commun. 10, 4144 (2019).Article 

Google Scholar 
DeLucia, E. H. et al. Are we approaching a water ceiling to maize yields in the United States? Ecosphere 10, e02773 (2019).Article 

Google Scholar 
Cook, B. I. et al. Divergent regional climate consequences of maintaining current irrigation rates in the 21st century. J. Geophys. Res. Atmos. 125, e2019JD031814 (2020).Article 

Google Scholar 
Tigchelaar, M., Battisti, D. S., Naylor, R. L. & Ray, D. K. Future warming increases probability of globally synchronized maize production shocks. Proc. Natl Acad. Sci. USA 115, 6644–6649 (2018).Article 

Google Scholar 
Liu, W. et al. Future climate change significantly alters interannual wheat yield variability over half of harvested areas. Environ. Res. Lett. 16, 094045 (2021).Article 

Google Scholar 
Wang, X. et al. Global irrigation contribution to wheat and maize yield. Nat. Commun. 12, 1235 (2021).Article 

Google Scholar 
Rosa, L., Chiarelli, D. D., Rulli, M. C., Dell’Angelo, J. & D’Odorico, P. Global agricultural economic water scarcity. Sci. Adv. 6, eaaz6031 (2020).Article 

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

Google Scholar 
Livneh, B. & Badger, A. M. Drought less predictable under declining future snowpack. Nat. Clim. Change 10, 452–458 (2020).Article 

Google Scholar 
Elliott, J. et al. Constraints and potentials of future irrigation water availability on agricultural production under climate change. Proc. Natl Acad. Sci. USA 111, 3239–3244 (2014).Article 

Google Scholar 
Jägermeyr, J. et al. Integrated crop water management might sustainably halve the global food gap. Environ. Res. Lett. 11, 025002 (2016).Article 

Google Scholar 
Rosa, L. et al. Potential for sustainable irrigation expansion in a 3 °C warmer climate. Proc. Natl Acad. Sci. USA 117, 29526–29534 (2020).Article 

Google Scholar 
Gleeson, T., Wada, Y., Bierkens, M. F. P. & Van Beek, L. P. H. Water balance of global aquifers revealed by groundwater footprint. Nature 488, 197–200 (2012).Article 

Google Scholar 
Bhattarai, N. et al. The impact of groundwater depletion on agricultural production in India. Environ. Res. Lett. 16, 085003 (2021).Article 

Google Scholar 
Nie, W. et al. Irrigation water demand sensitivity to climate variability across the contiguous United States. Water Resour. Res. 57, e2020WR027738 (2021).Article 

Google Scholar 
Wu, W.-Y. et al. Divergent effects of climate change on future groundwater availability in key mid-latitude aquifers. Nat. Commun. 11, 3710 (2020).Article 

Google Scholar 
Jain, M. et al. Groundwater depletion will reduce cropping intensity in India. Sci. Adv. 7, eabd2849 (2021).Article 

Google Scholar 
Kerr, R. B., Hasegawa, T. & Lasco, R. Food, fibre and other ecosystem products. In IPCC WGII Sixth Assessment Report 11–13 Ch. 5 (IPCC, 2022).Zandalinas, S. I. & Mittler, R. Plant responses to multifactorial stress combination. New Phytol. 234, 1161–1167 (2022).Article 

Google Scholar 
Barrett, C. B. et al. Bundling innovations to transform agri-food systems. Nat. Sustain. 3, 974–976 (2020).Article 

Google Scholar 
Peng, B. & Guan, K. Harmonizing climate-smart and sustainable agriculture. Nat. Food 2, 853–854 (2021).Article 

Google Scholar 
Zabel, F. et al. Large potential for crop production adaptation depends on available future varieties. Glob. Chang. Biol. 27, 3870–3882 (2021).Article 

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

Google Scholar 
Renard, D. & Tilman, D. National food production stabilized by crop diversity. Nature 571, 257–260 (2019).Article 

Google Scholar 
Vogel, E. & Meyer, R. Climate Change, Climate Extremes, and Global Food Production — Adaptation in the Agricultural Sector. Resilience: The Science of Adaptation to Climate Change (Elsevier Inc., 2018).Lal, R. Soil health and carbon management. Food Energy Secur. 5, 212–222 (2016).Article 

Google Scholar 
Davis, K. F., Downs, S. & Gephart, J. A. Towards food supply chain resilience to environmental shocks. Nat. Food 2, 54–65 (2021).Article 

Google Scholar 
Baldos, U. L. C. & Hertel, T. W. The role of international trade in managing food security risks from climate change. Food Secur. 7, 275–290 (2015).Article 

Google Scholar 
Deguines, N. et al. Large-scale trade-off between agricultural intensification and crop pollination services. Front. Ecol. Environ. 12, 212–217 (2014).Article 

Google Scholar 
Vyas, S., Dalhaus, T., Kropff, M., Aggarwal, P. & Meuwissen, M. P. M. Mapping global research on agricultural insurance. Environ. Res. Lett. 16, 103003 (2021).Article 

Google Scholar 
Hazell, P. & Varangis, P. Best practices for subsidizing agricultural insurance. Glob. Food Sec. 25, 100326 (2020).Article 

Google Scholar 
Funk, C. et al. Recognizing the famine early warning systems network over 30 years of drought early warning science advances and partnerships promoting global food security. Bull. Am. Meteorol. Soc. 100, 1011–1027 (2019).Article 

Google Scholar 
Reichstein, M., Riede, F. & Frank, D. More floods, fires and cyclones — plan for domino effects on sustainability goals. Nature 592, 347–349 (2021).Article 

Google Scholar 
Müller, C. et al. Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios. Environ. Res. Lett. 16, 034040 (2021).Article 

Google Scholar 
Hao, Z., Hao, F., Xia, Y., Singh, V. P. & Zhang, X. A monitoring and prediction system for compound dry and hot events. Environ. Res. Lett. 14, 114034 (2019).Article 

Google Scholar 
Benami, E. et al. Uniting remote sensing, crop modelling and economics for agricultural risk management. Nat. Rev. Earth Environ. 2, 140–159 (2021).Article 

Google Scholar 
Famine Early Warning System Network. East Africa seasonal monitor. FEWS https://fews.net/sites/default/files/documents/reports/EAST_AFRICA_Seasonal_Monitor_20_May_2022_1.pdf (2022).Becker-Reshef, I. et al. The GEOGLAM crop monitor for AMIS: assessing crop conditions in the context of global markets. Glob. Food Sec. 23, 173–181 (2019).Article 

Google Scholar 
GEOGLAM Crop Monitor. Special report: unprecedented 4th consecutive poor rainfall season for the Horn of Africa. Crop Monitor https://cropmonitor.org/documents/SPECIAL/reports/Special_Report_20220523_East_Africa.pdf (2022).Geange, S. R. et al. The thermal tolerance of photosynthetic tissues: a global systematic review and agenda for future research. New Phytol. 229, 2497–2513 (2021).Article 

Google Scholar 
Reynolds, M. P. et al. Harnessing translational research in wheat for climate resilience. J. Exp. Bot. 72, 5134–5157 (2021).Article 

Google Scholar 
Makondo, C. C. & Thomas, D. S. G. Climate change adaptation: linking indigenous knowledge with western science for effective adaptation. Environ. Sci. Policy 88, 83–91 (2018).Article 

Google Scholar 
Sharafi, L., Zarafshani, K., Keshavarz, M., Azadi, H. & Van Passel, S. Farmers’ decision to use drought early warning system in developing countries. Sci. Total Environ. 758, 142761 (2021).Article 

Google Scholar 
Fischer, K. Why new crop technology is not scale-neutral — A critique of the expectations for a crop-based African Green Revolution. Res. Policy 45, 1185–1194 (2016).Article 

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

Google Scholar 
Glauber, J., Baldwin, K., Antón, J. & Ziebinska, U. Design principles for agricultural risk management policies. OECD Food Agric. Fish. Pap. https://doi.org/10.1787/1048819f-en (2021).Article 

Google Scholar 
Annan, F. & Schlenker, W. Federal crop insurance and the disincentive to adapt to extreme heat. Am. Econ. Rev. 105, 262–266 (2015).Article 

Google Scholar 
Deryugina, T. & Konar, M. Impacts of crop insurance on water withdrawals for irrigation. Adv. Water Resour. 110, 437–444 (2017).Article 

Google Scholar 
Agrimonti, C., Lauro, M. & Visioli, G. Smart agriculture for food quality: facing climate change in the 21st century. Crit. Rev. Food Sci. Nutr. 61, 971–981 (2021).Article 

Google Scholar 
Sloat, L. L. et al. Climate adaptation by crop migration. Nat. Commun. 11, 1243 (2020).Article 

Google Scholar 
Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).Article 

Google Scholar 
Willmott, C. J. & Matsuura, K. Terrestrial Air Temperature and Precipitation: Monthly and Annual Time Series (1950–1999). University of Delaware http://climate.geog.udel.edu/~climate/html_pages/README.ghcn_ts.html (2000).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. Clim. 34, 623–642 (2014).Article 

Google Scholar 
Sheffield, J., Goteti, G. & Wood, E. F. Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. J. Clim. 19, 3088–3111 (2006).Article 

Google Scholar 
Beyer, R. M., Hua, F., Martin, P. A., Manica, A. & Rademacher, T. Relocating croplands could drastically reduce the environmental impacts of global food production. Commun. Earth Environ. 3, 49 (2022).Article 

Google Scholar  More

Parties to the Convention on Biological Diversity will meet this month to finalize the post-2020 Global Biodiversity Framework and the text for the stand-alone target on gender equality (Target 22). This target aims to reshape conservation policy and practice to make them more inclusive, equitable and effective.
Competing Interests
The authors declare no competing interests. More