More stories

  • in

    Selection, drift and community interactions shape microbial biogeographic patterns in the Pacific Ocean

    Nelson G. From Candolle to croizat: comments on the history of biogeography. J Hist Biol. 1978;11:269–305.PubMed 
    Article 
    CAS 

    Google Scholar 
    Lomolino MV, Riddle BR, Whittaker RJ, Brown JH. Biogeography. Sunderland, MA: Sinauer Associates; 2005. p. 752Wang J, Soininen J, Zhang Y, Wang B, Yang X, Shen J. Contrasting patterns in elevational diversity between microorganisms and macroorganisms. J Biogeogr. 2011;38:595–603.Article 

    Google Scholar 
    Treseder KK, Maltz MR, Hawkins BA, Fierer N, Stajich JE, Mcguire KL. Evolutionary histories of soil fungi are reflected in their large-scale biogeography. Ecol Lett. 2014;17:1086–93.PubMed 
    Article 

    Google Scholar 
    Meyer KM, Memiaghe H, Korte L, Kenfack D, Alonso A, Bohannan BJM. Why do microbes exhibit weak biogeographic patterns? ISME J. 2018;12:1404–13.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lindström ES, Langenheder S. Local and regional factors influencing bacterial community assembly. Environ Microbiol Rep. 2012;4:1–9.PubMed 
    Article 

    Google Scholar 
    Ghiglione JF, Galand PE, Pommier T, Pedrós-Alió C, Maas EW, Bakker K, et al. Pole-to-pole biogeography of surface and deep marine bacterial communities. Proc Natl Acad Sci USA 2012;109:17633–8.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Sul WJ, Oliver TA, Ducklow HW, Amaral-Zettlera LA, Sogin ML. Marine bacteria exhibit a bipolar distribution. Proc Natl Acad Sci USA 2013;110:2342–7.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Sunagawa S, Coelho LP, Chaffron S, Kultima JR, Labadie K, Salazar G, et al. Structure and function of the global ocean microbiome. Science. 2015;348:1261359.PubMed 
    Article 
    CAS 

    Google Scholar 
    de Vargas C, Audic S, Henry N, Decelle J, Mahé F, Logares R, et al. Eukaryotic plankton diversity in the sunlit ocean. Science. 2015;348:1261605.PubMed 
    Article 
    CAS 

    Google Scholar 
    Milici M, Tomasch J, Wos-Oxley ML, Decelle J, Jáuregui R, Wang H. et al. Bacterioplankton biogeography of the Atlantic ocean: a case study of the distance-decay relationship. Front Microbiol. 2016;7:Article 590.PubMed 

    Google Scholar 
    Raes EJ, Bodrossy L, Van De Kamp J, Bissett A, Ostrowski M, Brown MV, et al. Oceanographic boundaries constrain microbial diversity gradients in the south pacific ocean. Proc Natl Acad Sci USA 2018;115:8266–75.Article 
    CAS 

    Google Scholar 
    Wu W, Lu HP, Sastri A, Yeh YC, Gong GC, Chou WC, et al. Contrasting the relative importance of species sorting and dispersal limitation in shaping marine bacterial versus protist communities. ISME J. 2018;12:485–94.PubMed 
    Article 

    Google Scholar 
    Vellend M. Conceptual synthesis in community ecology. Q Rev Biol. 2010;85:183–206.PubMed 
    Article 

    Google Scholar 
    Hanson CA, Fuhrman JA, Horner-Devine MC, Martiny JBH. Beyond biogeographic patterns: Processes shaping the microbial landscape. Nat Rev Microbiol. 2012;10:497–506.PubMed 
    Article 
    CAS 

    Google Scholar 
    Nemergut DR, Schmidt SK, Fukami T, O’Neill SP, Bilinski TM, Stanish LF, et al. Patterns and processes of microbial community assembly. Microbiol Mol Biol Rev. 2013;77:342–56.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Stegen JC, Lin X, Fredrickson JK, Chen X, Kennedy DW, Murray CJ, et al. Quantifying community assembly processes and identifying features that impose them. ISME J. 2013;7:2069–79.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Schmidt TSB, Matias Rodrigues JF, Von Mering C. A family of interaction-adjusted indices of community similarity. ISME J. 2017;11:791–807.PubMed 
    Article 

    Google Scholar 
    Zhou J, Ning D. Stochastic community assembly: does it matter in microbial ecology? Microbiol Mol Biol Rev. 2017;81:1–32.Article 

    Google Scholar 
    Djurhuus A, Port J, Closek CJ, Yamahara KM, Romero-maraccini O, Walz KR. et al. Evaluation of filtration and DNA extraction methods for environmental DNA biodiversity assessments across multiple trophic levels. Front Mar Sci. 2017;4:Article 314.Article 

    Google Scholar 
    Wang ZB, Sun YY, Li Y, Chen XL, Wang P, Ding HT, et al. Significant bacterial distance-decay relationship in continuous, well-connected southern ocean surface water. Micro Ecol. 2020;80:73–80.Article 
    CAS 

    Google Scholar 
    Dlugosch L, Pohlein A, Wemheuer B, Pfeiffer B, Badewien T, Daniel R, et al. Significance of gene variants for the functional biogeography of the near-surface Atlantic Ocean microbiome. Nat Commun. 2022;13:456.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Lozupone C, Knight R. UniFrac: A new phylogenetic method for comparing microbial communities. Appl Environ Microbiol. 2005;71:8228–35.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Logares R, Deutschmann IM, Junger PC, Giner CR, Krabberød AK, Schmidt TSB, et al. Disentangling the mechanisms shaping the surface ocean microbiota. Microbiome. 2020;8:55.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Doblin MA, Petrou K, Sinutok S, Seymour JR, Messer LF, Brown MV, et al. Nutrient uplift in a cyclonic eddy increases diversity, primary productivity and iron demand of microbial communities relative to a western boundary current. PeerJ. 2016;4:e1973.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Polovina JJ, Howell E, Kobayashi DR, Seki MP. The transition zone chlorophyll front, a dynamic global feature defining migration and forage habitat for marine resources. Prog Oceanogr. 2001;49:469–83.Article 

    Google Scholar 
    Karl DM, Church MJ. Ecosystem structure and dynamics in the north pacific subtropical gyre: new views of an old ocean. Ecosystems. 2017;20:433–57.Article 

    Google Scholar 
    Mestre M, Ruiz-González C, Logares R, Duarte CM, Gasol JM, Sala MM. Sinking particles promote vertical connectivity in the ocean microbiome. Proc Natl Acad Sci USA 2018;115:6799–807.Article 
    CAS 

    Google Scholar 
    Balmonte JP, Simon M, Giebel HA, Arnosti C. A sea change in microbial enzymes: Heterogeneous latitudinal and depth-related gradients in bulk water and particle-associated enzymatic activities from 30°S to 59°N in the Pacific Ocean. Limnol Oceanogr. 2021;66:3489–507.Article 
    CAS 

    Google Scholar 
    Giebel H-A, Arnosti C, Badewien TH, Bakenhus I, Balmonte JP, Billerbeck S. et al. Microbial growth and organic matter cycling in the Pacific Ocean along a latitudinal transect between subarctic and subantarctic waters. Front Mar Sci. 2021;8:Article 764383.Article 

    Google Scholar 
    Milici M, Tomasch J, Wos-Oxley ML, Wang H, Jáuregui R, Camarinha-Silva A, et al. Low diversity of planktonic bacteria in the tropical ocean. Sci Rep. 2016;6:19054.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Longhurst AR. Ecological geography of the sea. San Diego, USA: Academic Press; 2007.Parada AE, Needham DM, Fuhrman JA. Every base matters: Assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ Microbiol. 2016;18:1403–14.PubMed 
    Article 
    CAS 

    Google Scholar 
    Milke F, Sanchez-Garcia S, Dlugosch L, McNichol J, Fuhrman J, Simon M. et al. Composition and biogeography of pro- and eukaryotic communities in the Atlantic Ocean: primer choice matters. Front Microbiol. 2022;13:Article 895875.PubMed 
    Article 

    Google Scholar 
    Vaulot D, Geisen S, Mahé F, Bass D. pr2-primers: An 18S rRNA primer database for protists. Mol Ecol Resour. 2022;22:168–79.PubMed 
    Article 
    CAS 

    Google Scholar 
    Yeh YC, McNichol J, Needham DM, Fichot EB, Berdjeb L, Fuhrman JA. Comprehensive single-PCR 16S and 18S rRNA community analysis validated with mock communities, and estimation of sequencing bias against 18S. Environ Microbiol. 2021;23:3240–50.PubMed 
    Article 
    CAS 

    Google Scholar 
    Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013;41:590–6.Article 
    CAS 

    Google Scholar 
    Guillou L, Bachar D, Audic S, Bass D, Berney C, Bittner L, et al. The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy. Nucleic Acids Res. 2013;41:597–604.Article 
    CAS 

    Google Scholar 
    Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 (Nature Biotechnology, (2019), 37, 8, (852-857), 10.1038/s41587-019-0209-9). Nat Biotechnol. 2019;37:1091.PubMed 
    Article 
    CAS 

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

    Google Scholar 
    Friedman J, Alm EJ. Inferring correlation networks from genomic survey data. PLoS Comput Biol. 2012;8:e1002687.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Bodenhofer U, Bonatesta E, Horejš-Kainrath C, Hochreiter S. Msa: an R package for multiple sequence alignment. Bioinformatics. 2015;31:3997–9.PubMed 
    CAS 

    Google Scholar 
    Kaufman L, Rousseeuw PJ. Finding groups in data: an introduction to cluster analysis. Hoboken NJ, USA: John Wiley & Sons; 2009.Pruesse E, Peplies J, Glöckner FO. SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics. 2012;28:1823–9.PubMed 
    PubMed Central 
    Article 
    CAS 

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

    Google Scholar 
    Losos JB. Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among species. Ecol Lett. 2008;11:995–1003.PubMed 
    Article 

    Google Scholar 
    Stegen JC, Lin X, Konopka AE, Fredrickson JK. Stochastic and deterministic assembly processes in subsurface microbial communities. ISME J. 2012;6:1653–64.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Fine PVA, Kembel SW. Phylogenetic community structure and phylogenetic turnover across space and edaphic gradients in western Amazonian tree communities. Ecography. 2011;34:552–65.Article 

    Google Scholar 
    Chase JM, Kraft NJB, Smith KG, Vellend M, Inouye BD. Using null models to disentangle variation in community dissimilarity from variation in α-diversity. Ecosphere. 2011;2:1–11.Article 

    Google Scholar 
    NASA Goddard Space Flight Center, Ocean Ecology Laboratory OBPG. Moderate-resolution Imaging Spectroradiometer (MODIS) aqua chlorophyll data. https://oceancolor.gsfc.nasa.gov/data/10.5067/AQUA/MODIS/L3B/CHL/2018/. Accessed 13 Nov 2020.Pommier T, Douzery EJP, Mouillot D. Environment drives high phylogenetic turnover among oceanic bacterial communities. Biol Lett. 2012;8:562–6.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Giovannoni SJ, Cameron Thrash J, Temperton B. Implications of streamlining theory for microbial ecology. ISME J. 2014;8:1553–65.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Sañudo-Wilhelmy SA, Gómez-Consarnau L, Suffridge C, Webb EA. The role of B vitamins in marine biogeochemistry. Ann Rev Mar Sci. 2014;6:339–67.PubMed 
    Article 

    Google Scholar 
    Morris JJ, Lenski RE, Zinser ER. The black queen hypothesis: evolution of dependencies through adaptive gene loss. MBio. 2012;3:e00036–12.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Carini P, Campbell EO, Morré J, Sañudo-Wilhelmy SA, Cameron Thrash J, Bennett SE, et al. Discovery of a SAR11 growth requirement for thiamin’s pyrimidine precursor and its distribution in the Sargasso Sea. ISME J. 2014;8:1727–38.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Wienhausen G, Bruns S, Sultana S, Dlugosch L, Groon L, Wilkes H, et al. The overlooked role of a biotin precursor for marine bacteria – desthiobiotin as an escape route for biotin auxotrophy. ISME J. 2022. https://doi.org/10.1038/s41396-022-01304-w.Biller SJ, Coe A, Chisholm SW. Torn apart and reunited: Impact of a heterotroph on the transcriptome of Prochlorococcus. ISME J. 2016;10:2831–43.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Sokolovskaya OM, Shelton AN, Taga ME. Sharing vitamins: cobamides unveil microbial interactions. Science. 2020;369:eaba0165.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Wienhausen G, Dlugosch L, Jarling R, Wilkes H, Giebel H-A, Simon M. Availability of vitamin B12 and its lower ligand intermediate a-ribazole impact prokaryotic and protist communities in oceanic systems. ISME J. 2022;16:2002–14.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Reintjes G, Arnosti C, Fuchs B, Amann R. Selfish, sharing and scavenging bacteria in the Atlantic Ocean: a biogeographical study of bacterial substrate utilisation. ISME J. 2019;13:1119–32.PubMed 
    Article 
    CAS 

    Google Scholar 
    Bertrand EM, McCrow JP, Moustafa A, Zheng H, McQuaid JB, Delmont TO, et al. Phytoplankton-bacterial interactions mediate micronutrient colimitation at the coastal Antarctic sea ice edge. Proc Natl Acad Sci USA 2015;112:9938–43.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Amin SA, Hmelo LR, Van Tol HM, Durham BP, Carlson LT, Heal KR, et al. Interaction and signalling between a cosmopolitan phytoplankton and associated bacteria. Nature. 2015;522:98–101.PubMed 
    Article 
    CAS 

    Google Scholar 
    Shibl AA, Isaac A, Ochsenkühn MA, Cárdenas A, Fei C, Behringer G, et al. Diatom modulation of select bacteria through use of two unique secondary metabolites. Proc Natl Acad Sci USA 2020;117:27445–55.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Villarino E, Watson JR, Chust G, Woodill AJ, Klempay B, Jonsson B, et al. Global beta diversity patterns of microbial communities in the surface and deep ocean. Glob Ecol Biogeogr. 2022;00:1–14.
    Google Scholar 
    Cravatte S, Kestenare E, Marin F, Dutrieux P, Firing E. Subthermocline and intermediate zonal currents in the tropical Pacific Ocean: Paths and vertical structure. J Phys Oceanogr. 2017;47:2305–24.Article 

    Google Scholar 
    Cho BC, Azam F. Major role of bacteria in biogeochemical fluxes in the ocean’s interior. Nature. 1988;332:441–3.Article 
    CAS 

    Google Scholar 
    Salazar G, Cornejo-Castillo FM, Benítez-Barrios V, Fraile-Nuez E, Álvarez-Salgado XA, Duarte CM, et al. Global diversity and biogeography of deep-sea pelagic prokaryotes. ISME J. 2016;10:596–608.PubMed 
    Article 

    Google Scholar 
    Delmont TO, Kiefl E, Kilinc O, Esen OC, Uysal I, Rappé MS, et al. Single-amino acid variants reveal evolutionary processes that shape the biogeography of a global SAR11 subclade. Elife. 2019;8:e46497.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hillebrand H. On the generallity of the latutinal diversity gradient. Am Nat. 2004;163:192–211.PubMed 
    Article 

    Google Scholar  More

  • in

    Synthesis of optically active through-space conjugated polymers consisting of planar chiral pseudo-meta-disubstituted [2.2]paracyclophane

    Vögtle, F. Cyclophane Chemistry: Synthesis, Structures and Reactions. John Wiley & Sons: Chichester; 1993.Gleiter, R, Hopf H. Modern Cyclophane Chemistry. Wiley-VCH: Weinheim; 2004.Hopf H. [2.2]Paracyclophanes in Polymer Chemistry and Materials Science. Angew Chem Int Ed. 2008;47:9808–12.CAS 

    Google Scholar 
    Brown CJ, Farthing AC. Preparation and structure of Di-p-Xylylene. Nature. 1949;164:915–6.CAS 

    Google Scholar 
    Cram DJ, Steinberg H. Macro Rings. I. Preparation and spectra of the paracyclophanes. J Am Chem Soc. 1951;73:5691–704.CAS 

    Google Scholar 
    Wang S, Bazan GC, Tretiak S, Mukamel S. Oligophenylenevinylene Phane Dimers: probing the effect of contact site on the optical properties of bichromophoric pairs. J Am Chem Soc. 2000;122:1289–97.CAS 

    Google Scholar 
    Bartholomew GP, Bazan GC. Bichromophoric paracyclophanes: models for interchromophore delocalization. Acc Chem Res. 2001;34:30–9.CAS 
    PubMed 

    Google Scholar 
    Bartholomew GP, Bazan GC. Strategies for the Synthesis of ‘Through-space’ Chromophore Dimers Based on [2.2]Paracyclophane. Synthesis. 2002;1245–55.Hong JW, Woo HY, Bazan GC. Solvatochromism of distyrylbenzene pairs bound together by [2.2]Paracyclophane: evidence for a polarizable “Through-space” delocalized state. J Am Chem Soc. 2005;127:7435–43.CAS 
    PubMed 

    Google Scholar 
    Bazan GC. Novel organic materials through control of multichromophore interactions. J Org Chem. 2007;72:8615–35.CAS 
    PubMed 

    Google Scholar 
    Cram DJ, Allinger NL. Macro Rings. XII stereochemical consequences of steric compression in the smallest paracyclophane. J Am Chem Soc. 1955;77:6289–94.CAS 

    Google Scholar 
    Rozenberg V, Sergeeva E, Hopf H. Cyclophanes as templates in stereoselective synthesis. In Gleiter R, Hopf H, editors. Modern Cyclophane Chemistry. Wiley-VCH: Weinheim; 2004, p. 435–62.Rowlands GJ. The synthesis of enantiomerically pure [2.2]paracyclophane derivatives. Org Biomol Chem. 2008;6:1527–34.CAS 
    PubMed 

    Google Scholar 
    Gibson SE, Knight JD. [2.2]Paracyclophane derivatives in asymmetric catalysis. Org Biomol Chem. 2003;1:1256–69.CAS 
    PubMed 

    Google Scholar 
    Aly AA, Brown AB. Asymmetric and fused heterocycles based on [2.2]Paracyclophane. Tetrahedron. 2009;65:8055–89.CAS 

    Google Scholar 
    Paradies J. [2.2]Paracyclophane derivatives: synthesis and application in catalysis. Synthesis. 2011;3749–66.Delcourt M-L, Felder S, Turcaud S, Pollok CH, Merten C, Micouin L, et al. Highly enantioselective asymmetric transfer hydrogenation: a practical and scalable method to efficiently access planar chiral [2.2]paracyclophanes. J Org Chem. 2019;84:5369–82.CAS 
    PubMed 

    Google Scholar 
    Vorontsova NV, Rozenberg VI, Sergeeva EV, Vorontsov EV, Starikova ZA, Lyssenko KA, et al. Symmetrically tetrasubstituted [2.2]Paracyclophanes: their systematization and regioselective synthesis of several types of bis-bifunctional derivatives by double electrophilic substitution. Chem Eur J. 2008;14:4600–17.CAS 
    PubMed 

    Google Scholar 
    David ORP. Syntheses and applications of disubstituted [2.2]Paracyclophanes. Tetrahedron. 2012;68:8977–93.CAS 

    Google Scholar 
    Hassan Z, Spluling E, Knoll DM, Lahann J, Bräse S. Planar Chiral [2.2]Paracyclophanes: from synthetic curiosity to applications in asymmetric synthesis and materials. Chem Soc Rev. 2018;47:6947–63.CAS 
    PubMed 

    Google Scholar 
    Hassan Z, Spuling E, Knoll DM, Bräse S. Regioselective functionalization of [2.2]Paracyclophanes: recent synthetic progress and perspectives. Angew Chem Int Ed. 2020;59:2156–70.CAS 

    Google Scholar 
    Felder S, Wu S, Brom J, Micouin L, Benedetti E. Enantiopure Planar Chiral [2.2]Paracyclophanes: synthesis and applications in asymmetric organocatalysis. Chirality. 2021;33:506–27.CAS 
    PubMed 

    Google Scholar 
    Morisaki Y. Circularly Polarized Luminescence from Planar Chiral Compounds Based on [2.2]Paracyclophane. In: Mori T, editor. Circularly Polarized Luminescence of Isolated Small Organic Molecules. Springer: Singapore; 2020, p. 31–52.Morisaki, Y. Circularly Polarized Luminescence (CPL) Based on Planar Chiral [2.2]Paracyclophane. In: Ooyama Y, Yagi S, editors. Progress in the Science of Functional Dyes. Springer: Singapore; 2021, p. 343–74.Morisaki Y, Chujo Y. Planar Chiral [2.2]Paracyclophanes: optical resolution and transformation to optically active π-stacked molecules. Bull Chem Soc Jpn. 2019;92:265–74.CAS 

    Google Scholar 
    Maeda H, Kameda M, Hatakeyama T, Morisaki Y. π-Stacked polymer consisting of a Pseudo-meta-[2.2]Paracyclophane skeleton. Polymers. 2018;10:1140. https://doi.org/10.3390/polym10101140.PubMed Central 

    Google Scholar 
    Gon M, Sawada R, Morisaki Y, Chujo Y. Enhancement and controlling the signal of circularly polarized luminescence based on a Planar Chiral Tetrasubstituted [2.2]Paracyclophane Framework in Aggregation System. Macromolecules. 2017;50:1790–802.CAS 

    Google Scholar 
    Gon M, Morisaki Y, Sawada R, Chujo Y. Synthesis of optically active X-shaped conjugated compounds and dendrimers based on Planar Chiral [2.2]Paracyclophane, leading to highly emissive circularly Polarized Luminescence. Chem Eur J. 2016;22:2291–8.CAS 
    PubMed 

    Google Scholar 
    Morisaki Y, Inoshita K, Shibata S, Chujo Y. Synthesis of optically active through-space conjugated polymers consisting of Planar Chiral [2.2]Paracyclophane and Quaterthiophene. Polym J. 2015;47:278–81.CAS 

    Google Scholar 
    Morisaki Y, Hifumi R, Lin L, Inoshita K, Chujo Y. Through-space conjugated polymers consisting of Planar Chiral Pseudo-ortho-linked [2.2]Paracyclophane. Polym Chem. 2012;3:2727–30.CAS 

    Google Scholar 
    Liao C, Zhang Y, Ye S-H, Zheng W-H. Planar Chiral [2.2]Paracyclophane-based thermally activated delayed fluorescent materials for circularly polarized electroluminescence. ACS Appl Mater Int. 2021;13:25186–92.CAS 

    Google Scholar 
    Zhang M-Y, Li Z-Y, Lu B, Wang Y, Ma Y-D, Zhao C-H. Solid-state emissive triarylborane-based [2.2]Paracyclophanes displaying circularly polarized luminescence and thermally activated delayed fluorescence. Org Lett. 2018;20:6868–71.CAS 
    PubMed 

    Google Scholar 
    Morisaki Y, Hifumi R, Lin L, Inoshita K, Chujo Y. Practical optical resolution of Planar Chiral Pseudo-ortho-disubstituted [2.2]Paracyclophane. Chem Lett. 2012;41:990–2.CAS 

    Google Scholar 
    Tsuchiya M, Maeda H, Inoue R, Morisaki Y. Construction of Helical Structures with Planar Chiral [2.2]Paracyclophane: fusing helical and planar chiralities. Chem Commun. 2021;57:9256–9.CAS 

    Google Scholar 
    Kikuchi K, Nakamura J, Nagata Y, Tsuchida H, Kakuta T, Ogoshi T, et al. Control of circularly polarized luminescence by orientation of stacked π-Electron Systems. Chem Asian J. 2019;14:1681–5.CAS 
    PubMed 

    Google Scholar 
    Morisaki Y, Sawada R, Gon M, Chujo Y. New Type of Planar Chiral [2.2]Paracyclophanes and construction of one-handed double Helices. Chem Asian J. 2016;11:2524–7.CAS 
    PubMed 

    Google Scholar 
    Sawada R, Gon M, Nakamura J, Morisaki Y, Chujo Y. Synthesis of Enantiopure Planar Chiral Bis-(para)-Pseudo-meta-Type [2.2]Paracyclophanes. Chirality. 2018;30:1109–14.CAS 
    PubMed 

    Google Scholar 
    Morisaki Y, Gon M, Sasamori T, Tokitoh N, Chujo Y. Planar Chiral Tetrasubstituted [2.2]Paracyclophane: optical resolution and functionalization. J Am Chem Soc. 2014;136:3350–3.CAS 
    PubMed 

    Google Scholar 
    Sonogashira K, Tohda Y, Hagihara N. A convenient synthesis of acetylenes: catalytic substitutions of acetylenic hydrogen with bromoalkenes, iodoarenes and bromopyridines. Tetrahedron Lett. 1975;16:4467–70.
    Google Scholar 
    Sonogashira K. Palladium-Catalyzed Alkynylation: Sonogashira Alkyne Synthesis. In: Negishi E, editor. Handbook of Organopalladium Chemistry for Organic Synthesis. Wiley-Interscience: New York; 2002, p. 493–529.Meyer-Epler G, Sure R, Schneider A, Schnakenburg G, Grimme S, Lützen A. Synthesis, Chiral Resolution, and absolute configuration of dissymmetric 4,15-Difunctionalized [2.2]Paracyclophanes. J Org Chem. 2014;79:6679–87.
    Google Scholar 
    Miki N, Maeda H, Inoue R, Morisaki Y. Syntheses and Chiroptical properties of optically active V-shaped molecules based on Planar Chiral [2.2]Paracyclophane. ChemistrySelect. 2021;6:12970–4.CAS 

    Google Scholar 
    Bondarenko L, Dix I, Hinrichs H, Hopf H. Cyclophanes. Part LII: Ethynyl[2.2]paracyclophanes – New Building Blocks for Molecular Scaffolding. Synthesis. 2004;2751–9.Tanaka Y, Ozawa T, Inagaki A, Akita M. Redox-active Polyiron Complexes with Tetra(ethynylphenyl)ethene and [2,2]Paracyclophane spacers containing ethynylphenyl units: extension to higher dimensional molecular wire. Dalton Trans. 2007;928–33.Morisaki Y, Ueno S, Saeki A, Asano A, Seki S, Chujo Y. π-Electron-system-layered Polymer: through-space conjugation and properties as a single molecular wire. Chem Eur J. 2012;18:4216–24.CAS 
    PubMed 

    Google Scholar 
    Morisaki Y, Inoshita K, Chujo Y. Planar Chiral through-space conjugated oligomers: synthesis and characterization of Chiroptical Properties. Chem Eur J. 2014;20:8386–90.CAS 
    PubMed 

    Google Scholar 
    Saeki A. Evaluation-oriented exploration of photo energy conversion systems: from fundamental optoelectronics and material screening to the combination with Data Science. Polym J. 2020;52:1307–21.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Miki N, Inoue R, Morisaki Y. Synthesis of optically active V-shaped molecules: studies on the orientation of the Stacked π-Electron Systems and Their Chiroptical Properties. Bull Chem Soc Jpn. 2021;94:451–3.CAS 

    Google Scholar 
    Tabata D, Inoue R, Sasai Y, Morisaki Y. Synthesis of optically active V(120°)- and (60°)-shaped molecules comprising different π-electron systems. Bull Chem Soc Jpn. 2022;95:595–601.CAS 

    Google Scholar 
    Asakawa R, Tabata D, Miki N, Tsuchiya M, Inoue R, Morisaki Y. Syntheses of optically active V-shaped molecules: relationship between their Chiroptical Properties and the Orientation of the Stacked π-Electron System. Eur J Org Chem. 2021;2021:5725–31.Berova N, Nakanishi K, Woody RW. Circular Dichroism 2nd ed. Wiley-VCH: Toronto; 2000.Riehl JP, Richardson FS. Circularly polarized luminescence spectroscopy. Chem Rev. 1986;86:1–16.CAS 

    Google Scholar 
    Riehl JP, Muller F. Comprehensive Chiroptical Spectroscopy. Wiley and Sons: New York; 2012. More

  • in

    Tailored pathways toward revived farmland biodiversity can inspire agroecological action and policy to transform agriculture

    Benton, T. G. & Bailey, R. The paradox of productivity: agricultural productivity promotes food system inefficiency. Glob. Sustain. 2, (2019).IPBES Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. S. Diaz, et al. (eds.). IPBES secretariat, Bonn, Germany, 56 p, (2019).Beckmann, M. et al. Conventional land-use intensification reduces species richness and increases production: a global meta-analysis. Glob. Chang. Biol. 25, 1941–1956 (2019).Article 

    Google Scholar 
    Jones, S. K. et al. Agrobiodiversity Index scores show agrobiodiversity is underutilized in national food systems. Nat. Food 2, 712–723 (2021).Article 

    Google Scholar 
    Butler, S. J., Vickery, J. A. & Norris, K. Farmland biodiversity and the footprint of agriculture. Science 315, 381–384 (2007).CAS 
    Article 

    Google Scholar 
    Tscharntke, T. et al. Landscape moderation of biodiversity patterns and processes – eight hypotheses. Biol. Rev. 87, 661–685 (2012).Article 

    Google Scholar 
    Meyfroidt, P. et al. Ten facts about land systems for sustainability. Proc. Nat. Acad. Sci. 119, e2109217118 (2022).CAS 
    Article 

    Google Scholar 
    Diaz, S. et al. Pervasive human-driven decline of life on Earth points to the need for transformative change. Science 366, eaax3100 (2019).CAS 
    Article 

    Google Scholar 
    Pilling, D., Bélanger, J. & Hoffmann, I. Declining biodiversity for food and agriculture needs urgent global action. Nat. Food 1, 144–147 (2020).Article 

    Google Scholar 
    Wanger, T. C. et al. Integrating agroecological production in a robust post-2020 Global Biodiversity Framework. Nat. Ecol. Evol .4, 1150–1152 (2020).Article 

    Google Scholar 
    Altieri, M. A. Agroecology: the science of natural resource management for poor farmers in marginal environments. Agric. Ecosyst. Environ. 93, 1–24 (2002).Article 

    Google Scholar 
    HLPE. Agroecological and Other Innovative Approaches for Sustainable Agriculture and Food Systems That Enhance Food Security and Nutrition, Food and Agriculture Organization (FAO). (2019).Barrios, E. et al. The 10 Elements of Agroecology: enabling transitions towards sustainable agriculture and food systems through visual narratives. Ecosyst. People 16, 230–247 (2020).Article 

    Google Scholar 
    FAO. Catalysing dialogue and cooperation to scale up agroecology: outcomes of the FAO regional seminars on agroecology. Food and Agriculture Organization of the United Nations, Rome, Italy, http://www.fao.org/3/I8992EN/i8992en.pdf (2018).Wezel, A. et al. Agroecological principles and elements and their implications for transitioning to sustainable food systems. A review. Agron. Sustain. Dev. 40, 40 (2020).Article 

    Google Scholar 
    FAO. Building a common vision for sustainable food and agriculture, Principles, and approaches. Food and Agriculture Organization of the United Nations, Rome, Italy, https://www.fao.org/3/i3940e/i3940e.pdf, (2014).Kleijn, D., Rundlof, M., Scheper, J., Smith, H. G. & Tscharntke, T. Does conservation on farmland contribute to halting the biodiversity decline? Trends Ecol. Evol. 26, 474–481 (2011).Article 

    Google Scholar 
    Seppelt, R. et al. Harmonizing biodiversity conservation and productivity in the context of increasing demands on landscapes. BioScience 66, 890–896 (2016).Article 

    Google Scholar 
    Tscharntke, T., Klein, A. M., Kruess, A., Steffan-Dewenter, I. & Thies, C. Landscape perspectives on agricultural intensification and biodiversity-ecosystem service management. Ecol Lett. 8, 857–874 (2005).Article 

    Google Scholar 
    EEA High nature value farmland Characteristics, trends, and policy challenges. EEA report No 1/2004, European Environment Agency, Luxembourg, Office for Official Publications of the European Communities, 32 pp (2004).Ichikawa, K. & Toth, G. G. The Satoyama Landscape of Japan: The Future of an Indigenous Agricultural System in an Industrialized Society. In: Nair, P., Garrity, D. (eds) Agroforestry-The Future of Global Land Use. Advances in Agroforestry, 9. Springer, Dordrecht. 341–358. (2012).Navarro, L. M. & Pereira, H. M. Rewilding abandoned landscapes in Europe. Ecosystem 15, 900–912 (2012).Article 

    Google Scholar 
    Willett, W. et al. Food in the Anthropocene: the EAT-Lancet Commission on healthy diets from sustainable food systems. Lancet 393, 447–492 (2019).Article 

    Google Scholar 
    Garibaldi, L. A. et al. Working landscapes need at least 20% native habitat. Conserv. Lett. 14, e12773 (2021).Article 

    Google Scholar 
    Tscharntke, T., Grass, I., Wanger, T. C., Westphal, C. & Batáry, P. Beyond organic farming–harnessing biodiversity-friendly landscapes. Trends Ecol. Evol. 36, 919–930 (2021).CAS 
    Article 

    Google Scholar 
    Bommarco, R., Kleijn, D. & Potts, S. G. Ecological intensification: harnessing ecosystem services for food security. Trends Ecol. Evol. 28, 230–238 (2013).Article 

    Google Scholar 
    Suding, K. N. & Hobbs, R. J. Threshold models in restoration and conservation: a developing framework. Trends Ecol. Evol. 24, 271–279 (2009).Article 

    Google Scholar 
    Sietz, D., Fleskens, L. & Stringer, L. C. Learning from non-linear ecosystem dynamics is vital for achieving Land Degradation Neutrality. Land Degrad. Dev. 28, 2308–2314 (2017).Article 

    Google Scholar 
    Van den Elsen, E. et al. Advances in understanding and managing catastrophic shifts in Mediterranean ecosystems. Front. Ecol. Evol. 8:561101, Section Conservation, https://doi.org/10.3389/fevo.2020.561101. (2020).Brussaard, L. et al. Reconciling biodiversity conservation and food security: scientific challenges for a new agriculture. Curr. Opin. Environ. Sustain. 2, 34–42 (2010).Article 

    Google Scholar 
    Tougiani, A., Guero, C. & Rinaudo, T. Community mobilisation for improved livelihoods through tree crop management in Niger. GeoJournal 74, 377 (2009).Article 

    Google Scholar 
    Baumhardt, R. L. Dust Bowl Era. Encyclopedia of Water Science, pp. 187 – 191, New York, USA. (2003).Hein, L. et al. Progress in natural capital accounting for ecosystems. Science 367, 514–515 (2020).CAS 
    Article 

    Google Scholar 
    SER The SER International Primer on Ecological Restoration, Society for Ecological Restoration International Science & Policy Working Group, www.ser.org & Tucson, Society for Ecological Restoration International (2004).Kremen, C., Iles, A. & Bacon, C. Diversified farming systems: an agroecological, systems-based alternative to modern industrial agriculture. Ecol. Soc. 17, 44 (2012).
    Google Scholar 
    Kleijn, D. et al. Ecological intensification: bridging the gap between science and practice. Trends Ecol. Evol. 34, 154–166 (2019).Article 

    Google Scholar 
    Lomba, A. et al. Back to the future: rethinking socioecological systems underlying high nature value farmlands. Front. Ecol. Environ. 18, 36–42 (2020).Article 

    Google Scholar 
    Pretty, J. et al. Global assessment of agricultural system redesign for sustainable intensification. Nat. Sustain. 1, 441–446 (2018).Article 

    Google Scholar 
    Basso, B. & Antle, J. Digital agriculture to design sustainable agricultural systems. Nat. Sustain. 3, 254–256 (2020).Article 

    Google Scholar 
    Teixeira, H. M. et al. Understanding farm diversity to promote agroecological transitions. Sustainability 10, 4337 (2018).Article 

    Google Scholar 
    Fraser, M. D., Moorby, J. M., Vale, J. E. & Evans, D. M. Mixed grazing systems benefit both upland biodiversity and livestock production. PLOS ONE 9, e89054 (2014).Article 
    CAS 

    Google Scholar 
    Reganold, J. & Wachter, J. Organic agriculture in the twenty-first century. Nat. Plants 2, 15221 (2016).Article 

    Google Scholar 
    Niggli, U., Slabe, A., Schmid, O., Halberg, N. & Schlüter, M. Vision for an Organic Food and Farming Research Agenda 2025. Organic Knowledge for the Future. Technology Platform Organics. IFOAM Regional Group European Union (IFOAM EU Group), Brussels and International Society of Organic Agriculture Research (ISOFAR), Bonn, Germany (2008).Badgley, C. et al. Organic agriculture and the global food supply. Renew. Agric. Food Syst. 22, 86–108 (2007).Article 

    Google Scholar 
    Boddey, R. M., de Moraes, J. C., Alves, B. J. R. & Urquiaga, S. The contribution of biological nitrogen fixation for sustainable agriculture in the tropics. Soil Biol. Biochem. 29, 787–799 (1997).CAS 
    Article 

    Google Scholar 
    Sharifi, O. et al. Barriers to conversion to organic farming: a case study in Babol County in Iran. Afr. J. Agr. Res. 5, 2260–2267 (2010).
    Google Scholar 
    Peetsmann, E. et al. Organic marketing in Estonia. Agron. Res. 7, 706–711 (2009).
    Google Scholar 
    Palsova, L., Schwarczova, L., Schwarcz, P. & Bandlerova, A. The support of implementation of organic farming in the Slovak Republic in the context of sustainable development. Procedia—Soc. Behav. Sci. 110, 520–529 (2014).Article 

    Google Scholar 
    Konstantinidis, C. Capitalism in green disguise: the political economy of organic farming in the European Union. Rev. Radic. Polit. Econ. 50, 830–852 (2018).Article 

    Google Scholar 
    Ponisio, L. C. et al. Diversification practices reduce organic to conventional yield gap. Proc. R. Soc. B. 282, 20141396 (2015).Article 

    Google Scholar 
    Willer, H., Trávníček, J., Meier, C. & Schlatter, B. (Eds.) The World of Organic Agriculture: Statistics and Emerging Trends 2021. Research Institute of Organic Agriculture FiBL, Frick and IFOAM Organics International, Bonn, Germany (2021).Rosset, P. M., Sosa, B. M., Roque Jaime, A. M. & Ávila Lozano, D. A. The Campesino-to-Campesino agroecology movement of ANAP in Cuba: social process methodology in the construction of sustainable peasant agriculture and food sovereignty. J. Peasant Stud. 38, 161–191 (2011).Article 

    Google Scholar 
    Lechenet, M., Dessaint, F., Py, G., Makowski, D. & Munier-Jolain, N. Reducing pesticide use while preserving crop productivity and profitability on arable farms. Nat. Plants 3, 17008 (2017).Article 

    Google Scholar 
    Beillouin, D., Ben-Ari, T., Malézieux, E., Seufert, V. & Makowski, D. Positive but variable effects of crop diversification on biodiversity and ecosystem services. Glob. Chang. Biol. 27, 4697–4710 (2021).CAS 
    Article 

    Google Scholar 
    Pywell, R. F. et al. Wildlife‐friendly farming increases crop yield: Evidence for ecological intensification. Proc. Royal Soc. B Biol. Sci. 282, 20151740 (2015).Article 

    Google Scholar 
    Gurr, G. M. et al. Multi-country evidence that crop diversification promotes ecological intensification of agriculture. Nat. Plants 2, 16014 (2016).Article 

    Google Scholar 
    Garnett, T. et al. Sustainable intensification in agriculture: Premises and policies. Science 341, 33–34 (2013).CAS 
    Article 

    Google Scholar 
    Daum, T. Farm robots: ecological utopia or dystopia? Trends Ecol. Evol. 36, 774–777 (2021).Article 

    Google Scholar 
    Neethirajan, S. & Kemp, B. Digital Livestock Farming. Sens. Bio-Sens. Res. 32, 100408 (2021).Article 

    Google Scholar 
    Mota, J. F., Peñas, J., Castro, H., Cabelllo, J. & Guirado, J. S. Agricultural development vs. biodiversity conservation: The Mediterranean semiarid vegetation in El Ejido (Almería, Southeastern Spain). Biodivers. Conserv. 5, 1597–1616 (1996).Article 

    Google Scholar 
    Giagnocavo, C. et al. Reconnecting farmers with nature through agroecological transitions: interacting niches and experimentation and the role of agricultural knowledge and innovation systems. Agriculture 12, 137 (2022).Article 

    Google Scholar 
    Shaffer, M. L. Minimum population sizes for species conservation. BioScience 31, 131–134 (1981).Article 

    Google Scholar 
    Shaffer, M. L. Minimum Viable Populations: coping with uncertainty. In: Soulé M. E., editor. Viable populations for conservation. Cambridge: Cambridge University Press. pp. 69-86. (1987).Sendzimir, J., Reij, C. P. & Magnuszewski, P. Rebuilding resilience in the Sahel: regreening in the Maradi and Zinder regions of Niger. Ecol. Soc. 16, 1 (2011).Article 

    Google Scholar 
    Weston, P., Hong, R., Kaboré, C. & Kull, C. A. Farmer-managed natural regeneration enhances rural livelihoods in dryland west Africa. Environ. Manage. 55, 1402–1417 (2015).Article 

    Google Scholar 
    De Souza, H. N. et al. Protective shade, tree diversity and soil properties in coffee agroforestry systems in the Atlantic Rainforest biome. Agric. Ecosyst. Environ. 146, 179–196 (2012).Article 

    Google Scholar 
    WWF (2021) Plowprint report. World Wildlife Fund, Washington, DC, USA.Senapathi, D. et al. Pollinator conservation—The difference between managing for pollination services and preserving pollinator diversity. Curr. Opin. Insect Sci. 12, 93–101 (2015).Article 

    Google Scholar 
    Sietz, D. & Feola, G. Resilience in the rural Andes: critical dynamics, constraints and emerging opportunities. Reg. Environ. Change 16, 2163–2169 (2016).Article 

    Google Scholar 
    Kleijn, D. et al. On the relationship between farmland biodiversity and land-use intensity in Europe. Proc. Biol. Sci. Royal Soc. 276, 903–909 (2009).CAS 

    Google Scholar 
    Tittonell, P. Assessing resilience and adaptability in agroecological transitions. Agric Syst 184, 102862 (2020).Article 

    Google Scholar 
    Jia, G. et al. Land–climate interactions. In: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems [P. R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M., Belkacemi, J. Malley, (eds.)]. Intergovernmental Panel on Climate Change. (2019).Tittonell, P. et al. Ecological Intensification: Local Innovation to Address Global Challenges. In: Lichtfouse, E. (eds) Sustainable Agriculture Reviews. Sustainable Agriculture Reviews, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-319-26777-7_1. (2016).Beyer, R. M. et al. Relocating croplands could drastically reduce the environmental impacts of global food production. Commun. Earth Environ. 3, 49 (2022).Article 

    Google Scholar 
    Jeanneret, P. et al. An increase in food production in Europe could dramatically affect farmland biodiversity. Commun. Earth Environ. 2, 183 (2021).Article 

    Google Scholar 
    Tamburino, L., Bravo, G., Clough, Y. & Nicholas, K. A. From population to production: 50 years of scientific literature on how to feed the world. Glob. Food Secur. 24, 100346 (2020).Article 

    Google Scholar 
    Grassini, P., Eskridge, K. & Cassman, K. Distinguishing between yield advances and yield plateaus in historical crop production trends. Nat. Commun. 4, 2918 (2013).Article 
    CAS 

    Google Scholar 
    U. N. Transforming Our World: The 2030 Agenda for Sustainable Development. United Nations, New York (2015).EC Farm to Fork strategy for a fair, healthy, and environmentally-friendly food system, European Commission, Brussels, https://ec.europa.eu/food/horizontal-topics/farm-fork-strategy_de (2020).UNCBD First draft of the post-2020 global biodiversity framework. CBD/WG2020/3/3, https://www.cbd.int/doc/c/abb5/591f/2e46096d3f0330b08ce87a45/wg2020-03-03-en.pdf (2021)Lacoste, M. et al. On-Farm Experimentation to transform global agriculture. Nat. Food 3, 11–18 (2022).Article 

    Google Scholar 
    Runhaar, H. Governing the transformation towards ‘nature-inclusive’ agriculture: insights from the Netherlands. Int. J. Agric. Sustain. 15, 340–349 (2017).Article 

    Google Scholar 
    Ferguson, R. S. & Lovell, S. T. Permaculture for agroecology: design, movement, practice, and worldview. A review. Agron. Sustain. Dev. 34, 251–274 (2014).Article 

    Google Scholar 
    Oberlack, C. et al. Archetype analysis in sustainability research: Meanings, motivations, and evidence-based policy making. Special feature: archetype analysis in sustainability research. Ecology and Society 24, 26 (2019).Article 

    Google Scholar 
    Sietz, D. et al. Archetype analysis in sustainability research: Methodological portfolio and analytical frontiers. Special Feature: Archetype Analysis in Sustainability Research. Ecol. Soc. 24, 34 (2019).Article 

    Google Scholar 
    Piemontese, L. et al. Validity and validation in archetype analysis: Practical assessment framework and guidelines. Environ. Res. Lett. 17, 025010 (2022).Article 

    Google Scholar 
    Sietz, D. et al. Nested archetypes of vulnerability in African drylands: Where lies potential for sustainable agricultural intensification? Environ. Res. Lett. 12, 095006 (2017).Article 

    Google Scholar 
    Alexandridis, N. et al. Archetype models upscale understanding of natural pest control response to land-use change. Ecological Applications. Accepted Author Manuscript e2696. https://doi.org/10.1002/eap.2696. (2022).Piñeiro, V. et al. A scoping review on incentives for adoption of sustainable agricultural practices and their outcomes. Nat. Sustain. 3, 809–820 (2020).Article 

    Google Scholar 
    Jack, B. K., Kousky, C. & Sims, K. R. E. Designing payments for ecosystem services: Lessons from previous experience with incentive-based mechanisms. Proc. Natl Acad Sci. 105, 9465–9470 (2008).CAS 
    Article 

    Google Scholar  More

  • in

    Fungi are more transient than bacteria in caterpillar gut microbiomes

    Futuyma, D. J. & Agrawal, A. A. Macroevolution and the biological diversity of plants and herbivores. Proc. Natl. Acad. Sci. 106, 18054–18061 (2009).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Frago, E., Dicke, M. & Godfray, H. C. J. Insect symbionts as hidden players in insect–plant interactions. Trends Ecol. Evol. 27, 705–711 (2012).PubMed 
    Article 

    Google Scholar 
    Gurung, K., Wertheim, B. & Salles, J. F. The microbiome of pest insects: It is not just bacteria. Entomol. Exp. Appl. 167, 156–170 (2019).Article 

    Google Scholar 
    Douglas, A. E. Multiorganismal insects: Diversity and function of resident microorganisms. Annu. Rev. Entomol. 60, 17–34 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Engel, P. & Moran, N. A. The gut microbiota of insects—diversity in structure and function. FEMS Microbiol. Rev. 37, 699–735 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Giron, D. et al. Chapter seven—influence of microbial symbionts on plant-insect interactions. In Advances in Botanical Research Vol. 81 (eds Sauvion, N. et al.) 225–257 (Academic Press, 2017).
    Google Scholar 
    Chen, B. et al. Biodiversity and activity of the gut microbiota across the life history of the insect herbivore Spodoptera littoralis. Sci. Rep. 6, 29505 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Vacher, C. et al. The phyllosphere: Microbial jungle at the plant–climate interface. Annu. Rev. Ecol. Evol. Syst. 47, 1–24 (2016).Article 

    Google Scholar 
    Griffin, E. A. & Carson, W. P. Tree endophytes: cryptic drivers of tropical forest diversity. In Endophytes of Forest Trees: Biology and Applications (eds Pirttilä, A. M. & Frank, A. C.) 63–103 (Springer International Publishing, 2018). https://doi.org/10.1007/978-3-319-89833-9_4.Chapter 

    Google Scholar 
    Peñuelas, J., Rico, L., Ogaya, R., Jump, A. S. & Terradas, J. Summer season and long-term drought increase the richness of bacteria and fungi in the foliar phyllosphere of Quercus ilex in a mixed Mediterranean forest. Plant Biol. 14, 565–575 (2012).PubMed 
    Article 

    Google Scholar 
    Laforest-Lapointe, I., Paquette, A., Messier, C. & Kembel, S. W. Leaf bacterial diversity mediates plant diversity and ecosystem function relationships. Nature 546, 145–147 (2017).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Kembel, S. W. et al. Relationships between phyllosphere bacterial communities and plant functional traits in a neotropical forest. Proc. Natl. Acad. Sci. USA. 111, 13715–13720 (2014).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kembel, S. W. & Mueller, R. C. Plant traits and taxonomy drive host associations in tropical phyllosphere fungal communities. Botany 92, 303–311 (2014).Article 

    Google Scholar 
    Faeth, S. H. & Hammon, K. E. Fungal endophytes in oak trees: Long-term patterns of abundance and associations with leafminers. Ecology 78, 810–819 (1997).Article 

    Google Scholar 
    Broderick, N. A., Raffa, K. F., Goodman, R. M. & Handelsman, J. Census of the bacterial community of the gypsy moth larval midgut by using culturing and culture-independent methods. Appl. Environ. Microbiol. 70, 293–300 (2004).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pinto-Tomás, A. A. et al. Comparison of midgut bacterial diversity in tropical caterpillars (Lepidoptera: Saturniidae) fed on different diets. Environ. Entomol. 40, 1111–1122 (2011).PubMed 
    Article 

    Google Scholar 
    Ravenscraft, A., Berry, M., Hammer, T., Peay, K. & Boggs, C. Structure and function of the bacterial and fungal gut microbiota of Neotropical butterflies. Ecol. Monogr. 89, e01346 (2019).Article 

    Google Scholar 
    Hammer, T. J., Sanders, J. G. & Fierer, N. Not all animals need a microbiome. FEMS Microbiol. Lett. 366, 117 (2019).Article 
    CAS 

    Google Scholar 
    Mason, C. J. et al. Diet influences proliferation and stability of gut bacterial populations in herbivorous lepidopteran larvae. PLoS ONE 15, e0229848 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Montagna, M. et al. Evidence of a bacterial core in the stored products pest Plodia interpunctella: The influence of different diets. Environ. Microbiol. 18, 4961–4973 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Phalnikar, K., Kunte, K. & Agashe, D. Disrupting butterfly caterpillar microbiomes does not impact their survival and development. Proc. R. Soc. B Biol. Sci. 286, 20192438 (2019).CAS 
    Article 

    Google Scholar 
    Somerville, J., Zhou, L. & Raymond, B. Aseptic rearing and infection with gut bacteria improve the fitness of transgenic diamondback moth, Plutella xylostella. Insects 10, 89 (2019).PubMed Central 
    Article 

    Google Scholar 
    González-Serrano, F. et al. The gut microbiota composition of the moth brithys crini reflects insect metamorphosis. Microb. Ecol. 79, 960–970 (2020).PubMed 
    Article 
    CAS 

    Google Scholar 
    Goharrostami, M. & JalaliSendi, J. Investigation on endosymbionts of Mediterranean flour moth gut and studying their role in physiology and biology. J. Stored Prod. Res. 75, 10–17 (2018).Article 

    Google Scholar 
    Vilanova, C., Baixeras, J., Latorre, A. & Porcar, M. The generalist inside the specialist: Gut bacterial communities of two insect species feeding on toxic plants are dominated by Enterococcus sp. Front. Microbiol. 7, 1005 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Minard, G., Tikhonov, G., Ovaskainen, O. & Saastamoinen, M. The microbiome of the Melitaea cinxia butterfly shows marked variation but is only little explained by the traits of the butterfly or its host plant. Environ. Microbiol. 21, 4253–4269 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Shapira, M. Gut microbiotas and host evolution: Scaling up symbiosis. Trends Ecol. Evol. 31, 539–549 (2016).PubMed 
    Article 

    Google Scholar 
    Chen, B. et al. Gut bacterial and fungal communities of the domesticated silkworm (Bombyx mori) and wild mulberry-feeding relatives. ISME J. 12, 2252–2262 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mason, C. J. & Raffa, K. F. Acquisition and structuring of midgut bacterial communities in gypsy moth (Lepidoptera: Erebidae) larvae. Environ. Entomol. 43, 595–604 (2014).PubMed 
    Article 

    Google Scholar 
    Paniagua Voirol, L. R., Frago, E., Kaltenpoth, M., Hilker, M. & Fatouros, N. E. Bacterial symbionts in Lepidoptera: Their diversity, transmission, and impact on the host. Front. Microbiol. 9, 556 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Laforest-Lapointe, I., Messier, C. & Kembel, S. W. Host species identity, site and time drive temperate tree phyllosphere bacterial community structure. Microbiome 4, 27 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Meyer, K. M. & Leveau, J. H. J. Microbiology of the phyllosphere: A playground for testing ecological concepts. Oecologia 168, 621–629 (2012).ADS 
    PubMed 
    Article 

    Google Scholar 
    Gomes, T., Pereira, J. A., Benhadi, J., Lino-Neto, T. & Baptista, P. Endophytic and epiphytic phyllosphere fungal communities are shaped by different environmental factors in a Mediterranean ecosystem. Microb. Ecol. 76, 668–679 (2018).PubMed 
    Article 

    Google Scholar 
    Rastogi, G. et al. Leaf microbiota in an agroecosystem: Spatiotemporal variation in bacterial community composition on field-grown lettuce. ISME J. 6, 1812–1822 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Whitaker, M. R. L., Salzman, S., Sanders, J., Kaltenpoth, M. & Pierce, N. E. Microbial communities of lycaenid butterflies do not correlate with larval diet. Front. Microbiol. 7, 1920 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zheng, Y. et al. Midgut microbiota diversity of potato tuber moth associated with potato tissue consumed. BMC Microbiol. 20, 58 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Griffin, E. A., Harrison, J. G., McCormick, M. K., Burghardt, K. T. & Parker, J. D. Tree diversity reduces fungal endophyte richness and diversity in a large-scale temperate forest experiment. Diversity 11, 234 (2019).Article 

    Google Scholar 
    Kim, M. et al. Distinctive phyllosphere bacterial communities in tropical trees. Microb. Ecol. 63, 674–681 (2012).PubMed 
    Article 

    Google Scholar 
    Hammer, T. J., Janzen, D. H., Hallwachs, W., Jaffe, S. P. & Fierer, N. Caterpillars lack a resident gut microbiome. Proc. Natl. Acad. Sci. 114, 9641–9646 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Višňovská, D. et al. Caterpillar gut and host plant phylloplane mycobiomes differ: A new perspective on fungal involvement in insect guts. FEMS Microbiol. Ecol. 96, fiaa116 (2020).PubMed 
    Article 
    CAS 

    Google Scholar 
    Voříšková, J. & Baldrian, P. Fungal community on decomposing leaf litter undergoes rapid successional changes. ISME J. 7, 477–486 (2013).PubMed 
    Article 
    CAS 

    Google Scholar 
    Pochon, X., Zaiko, A., Fletcher, L. M., Laroche, O. & Wood, S. A. Wanted dead or alive? Using metabarcoding of environmental DNA and RNA to distinguish living assemblages for biosecurity applications. PLoS ONE 12, e0187636 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Schlechter, R. O., Miebach, M. & Remus-Emsermann, M. N. P. Driving factors of epiphytic bacterial communities: A review. J. Adv. Res. 19, 57–65 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Seabloom, E. W. et al. Effects of nutrient supply, herbivory, and host community on fungal endophyte diversity. Ecology 100, e02758 (2019).PubMed 
    Article 

    Google Scholar 
    Berlec, A. Novel techniques and findings in the study of plant microbiota: Search for plant probiotics. Plant Sci. 193–194, 96–102 (2012).PubMed 
    Article 
    CAS 

    Google Scholar 
    Unterseher, M., Reiher, A., Finstermeier, K., Otto, P. & Morawetz, W. Species richness and distribution patterns of leaf-inhabiting endophytic fungi in a temperate forest canopy. Mycol. Prog. 6, 201–212 (2007).Article 

    Google Scholar 
    Gilbert, G. S., Reynolds, D. R. & Bethancourt, A. The patchiness of epifoliar fungi in tropical forests: Host range, host abundance, and environment. Ecology 88, 575–581 (2007).PubMed 
    Article 

    Google Scholar 
    Stone, B. W. G. & Jackson, C. R. Canopy position is a stronger determinant of bacterial community composition and diversity than environmental disturbance in the phyllosphere. FEMS Microbiol. Ecol. 95, fiz032 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Copeland, J. K., Yuan, L., Layeghifard, M., Wang, P. W. & Guttman, D. S. Seasonal community succession of the phyllosphere microbiome. Mol. Plant. Microbe Interact. 28, 274–285 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Stone, B. W. G. & Jackson, C. R. Seasonal patterns contribute more towards phyllosphere bacterial community structure than short-term perturbations. Microb. Ecol. https://doi.org/10.1007/s00248-020-01564-z (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Truchado, P., Gil, M. I., Reboleiro, P., Rodelas, B. & Allende, A. Impact of solar radiation exposure on phyllosphere bacterial community of red-pigmented baby leaf lettuce. Food Microbiol. 66, 77–85 (2017).PubMed 
    Article 

    Google Scholar 
    Wang, X. et al. Variability of gut microbiota across the life cycle of Grapholita molesta (Lepidoptera: Tortricidae). Front. Microbiol. 11, 1366 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Toju, H. & Fukatsu, T. Diversity and infection prevalence of endosymbionts in natural populations of the chestnut weevil: Relevance of local climate and host plants. Mol. Ecol. 20, 853–868 (2011).PubMed 
    Article 

    Google Scholar 
    Yun, J.-H. et al. Insect gut bacterial diversity determined by environmental habitat, diet, developmental stage, and phylogeny of host. Appl. Environ. Microbiol. 80, 5254–5264 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Sánchez, N. E., Pereyra, P. C. & Luna, M. G. Spatial patterns of parasitism of the solitary parasitoid Pseudapanteles dignus (Hymenoptera: Braconidae) on Tuta absoluta (Lepidoptera: Gelechiidae). Environ. Entomol. 38, 365–374 (2009).PubMed 
    Article 

    Google Scholar 
    Santos, A. M. C. & Quicke, D. L. J. Large-scale diversity patterns of parasitoid insects. Entomol. Sci. 14, 371–382 (2011).Article 

    Google Scholar 
    Mereghetti, V., Chouaia, B. & Montagna, M. New insights into the microbiota of moth pests. Int. J. Mol. Sci. 18, 2450 (2017).PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Floater, G. J. Estimating movement of the processionary caterpillar Ochrogaster zunifer Herrich-Schäffer (Lepidoptera: Thaumetopoeidae) between discrete resource patches. Aust. J. Entomol. 35, 279–283 (1996).Article 

    Google Scholar 
    Turčáni, M. & Patočka, J. Does intraguild predation of Cosmia trapezina L. (Lep.: Noctuidae) influence the abundance of other Lepidoptera forest pests?. J. For. Sci. 57, 472–482 (2011).Article 

    Google Scholar 
    Hikisz, J. & Soszynska-Maj, A. What moths fly in winter? The assemblage of moths active in a temperate deciduous forest during the cold season in Central Poland. J. Entomol. Res. Soc. 17, 59–71 (2015).
    Google Scholar 
    Bell, J. R., Bohan, D. A., Shaw, E. M. & Weyman, G. S. Ballooning dispersal using silk: World fauna, phylogenies, genetics and models. Bull. Entomol. Res. 95, 69–114 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Griffin, E. A. & Carson, W. P. The ecology and natural history of foliar bacteria with a focus on tropical forests and agroecosystems. Bot. Rev. 81, 105–149 (2015).Article 

    Google Scholar 
    Qian, X. et al. Mainland and island populations of Mussaenda kwangtungensis differ in their phyllosphere fungal community composition and network structure. Sci. Rep. 10, 952 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Herren, C. M. & McMahon, K. D. Keystone taxa predict compositional change in microbial communities. Environ. Microbiol. 20, 2207–2217 (2018).PubMed 
    Article 

    Google Scholar 
    Humphrey, P. T. & Whiteman, N. K. Insect herbivory reshapes a native leaf microbiome. Nat. Ecol. Evol. 4, 221–229 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Müller, T., Müller, M., Behrendt, U. & Stadler, B. Diversity of culturable phyllosphere bacteria on beech and oak: The effects of lepidopterous larvae. Microbiol. Res. 158, 291–297 (2003).PubMed 
    Article 

    Google Scholar 
    Hrcek, J., Miller, S. E., Quicke, D. L. J. & Smith, M. A. Molecular detection of trophic links in a complex insect host-parasitoid food web. Mol. Ecol. Resour. 11, 786–794 (2011).PubMed 
    Article 

    Google Scholar 
    Bateman, C., Šigut, M., Skelton, J., Smith, K. E. & Hulcr, J. Fungal associates of the Xylosandrus compactus (Coleoptera: Curculionidae, Scolytinae) are spatially segregated on the insect body. Environ. Entomol. 45, 883–890 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Toju, H., Tanabe, A. S., Yamamoto, S. & Sato, H. High-coverage ITS primers for the DNA-based identification of ascomycetes and basidiomycetes in environmental samples. PLoS ONE 7, e40863 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chelius, M. K. & Triplett, E. W. The diversity of archaea and bacteria in association with the roots of Zea mays L. Microb. Ecol. 41, 252–263 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Redford, A. J., Bowers, R. M., Knight, R., Linhart, Y. & Fierer, N. The ecology of the phyllosphere: Geographic and phylogenetic variability in the distribution of bacteria on tree leaves. Environ. Microbiol. 12, 2885–2893 (2010).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bolyen, E. et al. QIIME 2: Reproducible, Interactive, Scalable, and Extensible Microbiome Data Science https://peerj.com/preprints/27295 (2018) https://doi.org/10.7287/peerj.preprints.27295v2.Rivers, A. R., Weber, K. C., Gardner, T. G., Liu, S. & Armstrong, S. D. ITSxpress: Software to rapidly trim internally transcribed spacer sequences with quality scores for marker gene analysis. F1000Research 7, 1418 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 90 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).CAS 
    PubMed 
    Article 

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

    Google Scholar 
    UNITE Community. UNITE QIIME Release for Fungi 2. (2019).Davis, N. M., Proctor, D. M., Holmes, S. P., Relman, D. A. & Callahan, B. J. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome 6, 226 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).Ter Braak, C. J. F. ter & Smilauer, P. Canoco reference manual and user’s guide: software for ordination, version 5.0. (2012).Ondov, B. D., Bergman, N. H. & Phillippy, A. M. Interactive metagenomic visualization in a Web browser. BMC Bioinform. 12, 385 (2011).Article 

    Google Scholar 
    Chrostek, E., Pelz-Stelinski, K., Hurst, G. D. D. & Hughes, G. L. Horizontal transmission of intracellular insect symbionts via plants. Front. Microbiol. 8, 2237 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Fox, J. & Weisberg, S. An R Companion to Applied Regression (SAGE Publications, 2018).
    Google Scholar 
    Oksanen, J. et al. vegan: Community Ecology Package. (2020).Anderson, M. J. Distance-based tests for homogeneity of multivariate dispersions. Biometrics 62, 245–253 (2006).MathSciNet 
    PubMed 
    MATH 
    Article 

    Google Scholar 
    Renkonen, O. Statistisch-ökologische Untersuchungen über die terrestrische Käferwelt der finnischen Bruchmoore. Ann. Zool. Soc. Zool.-Bot. Fenn. Vanamo 6, 1–231 (1938).
    Google Scholar 
    Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

    Google Scholar 
    Roberts, D. W. labdsv: Ordination and Multivariate Analysis for Ecology (2019).Cáceres, M. D. & Legendre, P. Associations between species and groups of sites: Indices and statistical inference. Ecology 90, 3566–3574 (2009).PubMed 
    Article 

    Google Scholar 
    Dufrêne, M. & Legendre, P. Species assemblages and indicator species: The need for a flexible asymmetrical approach. Ecol. Monogr. 67, 345–366 (1997).
    Google Scholar 
    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Methodol. 57, 289–300 (1995).MathSciNet 
    MATH 

    Google Scholar  More

  • in

    Coral conservation in a warming world must harness evolutionary adaptation

    Logan, C. A., Dunne, J. P., Ryan, J. S., Baskett, M. L. & Donner, S. D. Nat. Clim. Chang. 11, 537–542 (2021).Article 

    Google Scholar 
    Cook, C. N. & Sgrò, C. M. Conserv. Biol. 31, 501–512 (2017).Article 

    Google Scholar 
    Gonzalez, A., Ronce, O., Ferriere, R. & Hochberg, M. E. Phil. Trans. R. Soc. Lond. B 368, 1–8 (2013).
    Google Scholar 
    Kovach, R. P., Gharrett, A. J. & Tallmon, D. A. Proc. R. Soc. Lond. B 279, 3870–3878 (2012).
    Google Scholar 
    Bonnet, T. et al. Science 376, 1012–1016 (2022).CAS 
    Article 

    Google Scholar 
    Norberg, J. et al. Nat. Clim. Chang. 2, 747–751 (2012).Article 

    Google Scholar 
    Torda, G. et al. Nat. Clim. Chang. 7, 627–636 (2017).Article 

    Google Scholar 
    Catullo, R. A., Llewelyn, J., Phillips, B. L. & Moritz, C. C. Curr. Biol. 29, R996–R1007 (2019).CAS 
    Article 

    Google Scholar 
    Keppel, G. et al. Glob. Ecol. Biogeogr. 21, 393–404 (2012).Article 

    Google Scholar 
    Vos, C. C. et al. J. Appl. Ecol. 45, 1722–1731 (2008).Article 

    Google Scholar 
    Isaak, D. J. et al. Glob. Change Biol. 21, 2540–2553 (2015).Article 

    Google Scholar 
    Beyer, H. L. et al. Conserv. Lett. 11, e12587 (2018).Article 

    Google Scholar 
    Tingley, M. W., Estes, L. D. & Wilcove, D. S. Nature 500, 271–272 (2013).CAS 
    Article 

    Google Scholar 
    Schindler, D. E., Armstrong, J. B. & Reed, T. E. Front. Ecol. Environ. 13, 257–263 (2015).Article 

    Google Scholar 
    Cornwell, B. et al. eLife 10, e64790 (2021).CAS 
    Article 

    Google Scholar 
    National Academies. of Sciences Engineering & Medicine. A Decision Framework for Interventions to Increase the Persistence and Resilience of Coral Reefs. (The National Academies Press, 2019).Palumbi, S. R., Barshis, D. J., Traylor-Knowles, N. & Bay, R. A. Science 344, 895–898 (2014).CAS 
    Article 

    Google Scholar 
    Matz, M. V., Treml, E. A. & Haller, B. C. Glob. Change Biol. 26, 3473–3481 (2020).Article 

    Google Scholar 
    Bay, R. A. & Palumbi, S. R. Curr. Biol. 24, 2952–2956 (2014).CAS 
    Article 

    Google Scholar 
    Donovan, M. K. et al. Science 372, 977–980 (2021).CAS 
    Article 

    Google Scholar 
    Anthony, K. et al. Nat. Ecol. Evol. 1, 1420–1422 (2017).Article 

    Google Scholar 
    Morrison, T. H. et al. Nature 573, 333–336 (2019).CAS 
    Article 

    Google Scholar 
    van Oppen, M. J. H., Oliver, J. K., Putnam, H. M. & Gates, R. D. Proc. Natl Acad. Sci. USA 112, 2307–2313 (2015).Article 

    Google Scholar 
    DeFilippo, L. B. et al. Ecol. Appl. https://doi.org/10.1002/eap.2650 (2022).Steneck, R. S. et al. Front. Mar. Sci. 6, 265 (2019).Article 

    Google Scholar 
    Dixon, G. B. et al. Science 348, 1460–1462 (2015).CAS 
    Article 

    Google Scholar 
    McManus, L. C. et al. Glob. Change Biol. 27, 4307–4321 (2021).CAS 
    Article 

    Google Scholar 
    Kleypas, J. A. et al. Glob. Change Biol. 22, 3539–3549 (2016).Article 

    Google Scholar 
    McManus, L. C. et al. Ecology 102, e03381 (2021).Article 

    Google Scholar 
    Walsworth, T. E. et al. Nat. Clim. Chang. 9, 632–636 (2019).Article 

    Google Scholar  More

  • in

    Characteristics of urine spraying and scraping the ground with hind paws as scent-marking of captive cheetahs (Acinonyx jubatus)

    Urine spraying and scraping as potential scent-markingThe urine spraying and the scraping were reported in other felids6,20,21. In this study, only half of the other excretion instances were accompanied by sniffing, whereas almost all urine spraying and scraping events were accompanied by sniffing, indicating that these are scent-markings. The sniffing was also often observed immediately before urine spraying and scraping. Given the significant association of sniffing before excretion, especially with regard to the scraping, the presence or absence of a scent on the object was thought to be a trigger.Furthermore, during the scraping, liquid secretions thought to originate from the anal glands, were released. Domestic cats have scent glands in the anal sac22. The presence of secretions from the anal sac has also been confirmed in not only tigers, lions (Panthera leo), and bobcats (Lynx rufus), but also in cheetahs1,6,23; however, this study was the first to investigate their role in excretion. Generally, secretions are considered to be caused by health problems or estrus, but in this study, none of the individuals had health problems, and all secretions were observed only in males. Therefore, it was thought that the secretion was produced by the scent glands and contributed to a stronger smell than only urine and feces.Variations based on sexUrine spraying was observed only in adult males and females, and was more frequent in males, as reported in other felids4,5,6,9,24. In wild cheetahs, although urine spraying and scraping have been observed as scent-making, the frequency of scent-marking is known to be substantially higher in territorial than in non-territorial males and in females15,16,25, and the marking locations are concentrated in the core area of the male territories16. The territories of a single male cheetah or a male group are relatively small and exclusive, whereas the relatively large home ranges of non-territorial males (also known as “floaters”) overlap with each other and with those of females15,16. A male’s home range is also larger than that of a female15,16,26,27. Male cheetahs rarely encounter other males because they communicate via marking posts28. Given these reports, the frequent urine spraying by males may help prevent encounters between males. In addition, observations of captive cheetahs have shown a significantly positive correlation between urinary spraying frequency and fecal estradiol content in female cheetahs19. Therefore, as Cornhill and Kerley24 mentioned, female urine spraying is caused by estrus, and male urine spraying is intended as a home range marker for other males or as a sign for females.The action of scraping using the hind paws has been reported to occur in both males and females in servals, lions, tigers, black-footed cats, etc.2,5,6,7,29; however, this behavior was only observed in adult males in this study. Sunquist and Sunquist3 reported that female cheetahs also perform the scraping. In this study, we only recorded observations when the cheetahs were released in the outdoor enclosures, and not when they were in the indoor facilities. In 43.6% of the scraping events, the males excreted feces. During the observation period, the females defecated in the indoor facilities, and no defecation was observed in the outdoor enclosures. It is possible that no scraping action was observed among the females because defecation was not observed in the outdoor enclosure. In indoor facilities, the cheetahs were in a completely monopolized enclosure; hence, the females defecated in their own spaces. There was a difference in the defecation sites and frequency of scraping between the males and females; this was attributed to the sex difference in scent-marking.Differences in target height for each behaviorUrine spraying was frequently done on objects approximately 170 cm or higher, such as walls or fences, standing trees, and stumps, whereas scraping was observed on low-lying objects on the ground, such as a straw pile approximately 3 cm high and a fallen tree that was 10–50 cm high. In other words, the cheetah engaged in urine spraying and scraping depending on the object nearby. This might indicate the functional role of these behaviors. This is consistent with previous findings of urine spraying by tigers being more frequent in wooded forests than in grasslands, with few prominent objects, and scraping being more common in the latter6. In addition, in a study that investigated the place where the smell of the urine of domestic cats is likely to remain, the smell persisted for a long time on rough surfaces, areas covered with moss, and overhanging slopes30. Even for cheetahs living in the savanna woodlands, where there are comparatively fewer upright objects than in the habitat of felids living in the forest, increasing the chances of transmitting information via not only urine spraying but also by the scraping might be more important. On the other hand, in their natural habitat, there are some large carnivores like lions and leopards (Panthera pardus). Wild cheetahs tend not to visit the sites where such carnivores’ scent-mark is present31, suggesting that they might confine their marking to specific sites devoid of other carnivores’ scent. Further research is needed to determine how wild cheetahs use urine spraying and scraping. In this study, scraping was frequently observed even on tall stumps and rocks if they were within the cheetahs’ reach. Scraping by wild cheetahs has been also observed on trees32. Zoos other than Zoo C had few prominent horizontal objects. Therefore, the presence of straw piles, fallen trees, stumps, and rocks may have elicited the scraping.Differences in housing conditionsIn zoos C and D, where animals shared enclosures, the frequency of both urine spraying and scraping by males was higher than in the males in the monopolized enclosures. They possibly showed a more frequent scent-marking to strengthen their home range claims when sharing the exhibition space15. Regarding the scraping, Zoo C had at least four low and horizontal objects (straw piles, fallen tree, stones, and rocks), and scraping was frequently observed. As mentioned above, the placement of objects might have elicited the scraping.In this study, the frequency of urine spraying decreased when the submissive individual (Male 17) was released in the enclosure where the dominant individual (Male 13) was previously released. Among wild cheetahs, territorial males have been reported to mark their territories more often than non-territorial males17,25. Therefore, the difference in the number of markings is considered to be related to whether or not the target individual is within the territory, and it is highly possible that the dominant/submissive relationship between males at that location has an effect on marking.Function of scraping using hind pawsOther felid studies have reported scraping in tigers, pumas, jaguars, clouded leopards, and small felids6,10,20,21,32,33; however, there are fewer studies on different types of scraping. In certain species, such as jaguars and pumas, scraping using hind paws is more frequent than urine spraying33. From this study, the use of secretions was confirmed in the scraping, and it was considered to be a significant marking of the cheetah.The possible functions of scraping include: (1) dispersing the smell of excrement, (2) placing the smell of excrement on the hindlegs, (3) smearing the objects with excrement, and (4) adding the scent of the hind paws. Domestic cats are known to cover their feces with soil34; however, in this study, the cheetahs did not cover the feces with soil and were not observed to scrap only after excretion. Therefore, scraping using hind paws was not meant for concealing urine and/or feces. The results of this study suggest that the scrapings were mostly performed during and after excretion for any of the aforementioned functions. However, 43.2% of the observed scraping events were performed before excretion, and in these cases, the functions 1–3 did not apply, since we did not observe the feces being crushed by scraping the hind paws. As for function 4, domestic cats have sweat glands on the soles of their feet that are thought to retain their smell35. Therefore, the sweat glands on the soles of the feet of the cheetahs possible retain the smell of the hind paws as well. Schaller36 reported that among tigers, scraping on the grassland was exhibited by scratches in the grass and exposure of the ground, creating a visual effect. In the case of cheetahs, scraping may have the function of creating grooves and ridges on the ground to enhance the visual effect; however, the formation of grooves and ridges were not observed in this study. In certain cases, they scraped against trees and stones. Because trees and stones are not easily deformed, it is hard to say whether the visual effect was enhanced by scraping with their hind paws.Scraping has been reported in other felids; however, the movement of the hindlimbs is not uniform. For example, in the case of bobcats, behaviors such as kicking back on the ground with no surrounding objects and scattering of soil have been observed during scrapings20. The snow leopard slowly moves its hindlimbs on the ground near the rocks, exposing the ground; in fact, Schaller29 observed a tiger scraping its hind paws to create a pile of soil [37; Kinoshita, personal communication: Online Resource 3; Scraping of snow leopard]. The movement of urine spraying also varies among species. For example, bobcats sometimes squat and urinate on the ground20, and snow leopards rub their cheeks against the target object and then spray urine9, but cheetahs do not rub their face before urine spraying. Hence, even in the same behavior of “spraying/scraping,” the actions differ. Because felids are widely distributed in various environments, such differences in movements are possibly related to differences in habitat and behavioral functions.In conclusion, urine spraying and scraping using hind paws were considered scent-markings because they were more strongly associated with sniffing than other excretion. Both behaviors were also observed only in adults; however, urine spraying was confirmed in both sexes and was more frequent in males than in females, whereas scraping was observed only in males. Also, the frequencies of both behaviors were significantly higher in males kept in shared enclosures containing other individuals than in males kept in monopolized enclosures, while there was no difference in the frequencies among females. Hence, there were sex differences in these scent-markings possibly because of the difference in the sociality between the sexes even in captivity; the frequency of scent-markings was affected by the living environment including the number of target objects; urine spraying was frequently done on tall objects such as walls or fences, whereas scraping was more commonly done on low-lying objects near the ground, such as straw piles. To our knowledge, this study is the first to confirm that during the scraping a liquid other than feces and urine was secreted, presumably from the anal glands. Taken together, the results can serve to enhance our knowledge regarding the behavior of cheetahs, help improve management of these animals in captivity as well as breeding and animal welfare ex situ conservation, and help elucidate the kind of habitat that should be preserved for the in situ conservation of cheetahs. More

  • in

    Time-series RNA-Seq transcriptome profiling reveals novel insights about cold acclimation and de-acclimation processes in an evergreen shrub of high altitude

    Plants increase their freezing resistance upon exposure to low temperatureThe freezing resistance (LT50 values) was found to vary ranging from − 6.9 °C (14-August-2017) to − 31.7 °C (04-November-2018) over the course of study period. The freezing resistance of leaves recorded during the 12 sampling time-points has been provided in Table 1 (also see39). The overlap of confidence intervals around the mean was examined for comparison of LT50 values for the different sampling time-points. Significant differences in freezing resistance were observed across the sampling time-points (Table 1). Leaves of R. anthopogon collected during summer [July and August (Air temperature and photoperiod was about 9.6 °C and 13 h day−1 respectively)] showed marginal resistance to freezing (LT50: − 7 °C) and thus, are more susceptible to freezing damage. Further, as the ambient air temperature and photoperiod decreased towards the end of growing season (i.e., October and November 2017 with air temperature and photoperiod of about − 1.1 °C and 10.5 h day−1 respectively), the plants acquired the highest freezing resistance (LT50: − 30 °C). Interestingly, a sharp increase in freezing resistance (− 29.4 °C) was observed in September 2018, when the daily mean air temperature decreased below 0 °C due to sudden snowfall (Supplementary Fig. S2). Comparison of LT50 values of all the leaf samples of R. anthopogon showed that cold de-acclimation occurred after the snowmelt during early spring in June (LT50: − 13.4 °C) with an increase in air temperature and photoperiod. These results demonstrated that R. anthopogon plants exhibit lowered freezing resistance during the warmer months [hence, these time-periods were referred as non-acclimation (NA)], progressively develop greater freezing resistance during the onset of winter season (hence, referred as cold acclimation) followed by an intermediate level of freezing resistance during the spring [hence, these time-periods were referred as de-acclimation (DA)].Table 1 The estimates of LT50, calculated by fitting sigmoidal curve to electrolyte leakage values of temperature treatments, recorded for leaves collected during the different sampling time-points (from August 22, 2017 to September 18, 2018).Full size tableDuring the acclimation period (i.e., late in the growing season), plants acquired the highest resistance to freezing (Fig. 1). The low electrolyte leakage (= high freezing resistance) observed during this period might be due to changes in cell wall properties (such as increase in lignification and suberization of cell walls), which provide resistance to diffusion of electrolytes from cells of the leaves to the extracellular water47. Moreover, high freezing resistance may also be attributed to high leaf toughness and sclerophyllous habit of this evergreen species48. Further, it was found that freezing resistance was the lowest during mid-summer period. This pattern could be explained by a trade-of between plant growth rates and freezing resistance, where warmer temperatures favour plant allocation to growth49. These observations corroborated well with earlier reports that showed a rapid increase in ‘freezing resistance’ during the transition from summer to early winter and vice versa50.Figure 1LT50 [black point (with solid fill) on the curve] calculated by fitting sigmoidal curve to relative electrolyte leakage (REL %) values recorded during the three different acclimation phases. GOF indicates ‘goodness of fit’ test values for the fitted sigmoidal curves.Full size imagePhotosynthetic rates are higher during non-acclimation and de-acclimation periodIt was found that PN of R. anthopogon varied in the range from 8.336 to 17.64 μmol(CO2)m−2 s−1 and E from 2.281 to 4.912 mol(H2O)m−2 s−1, throughout its growing season. The Gs of leaves was estimated to be in the range from 0.110 to 0.265 mol (H2O) m−2 s−1. WUE, a ratio of PN and E, varied between 52.21 and 87.68 (Table 2). The gas exchange parameters of R. anthopogon varied significantly among the sampling time-points [referred to here as different acclimation phases of the growing period of evergreen shrub (Fig. 2, Table 3)]. In particular, PN was significantly lower on 18-September-2018 (referred as cold acclimation phase), whereas it was higher on 31-August-2018 and 15-June-2018 (referred as NA and DA phases, respectively). Similarly, Gs of leaves was significantly lower during cold acclimation in comparison to the rest of the acclimation phases (i.e., NA and DA). Further, WUE was significantly higher during cold acclimation, while it was lower during both NA and DA (p ≤ 0.05) (Fig. 2).Table 2 Variability in leaf gas exchange parameters of R. anthopogon during the different acclimation phases (NA = Non-acclimation, LA = Late cold acclimation and DA = De-acclimation).Full size tableFigure 2Variability in leaf gas exchange parameters of R. anthopogon during the three acclimation phases [i.e., Non-acclimation (31 August, 2018), Cold acclimation (18 September, 2018) and De-acclimation (15 June, 2018)]. Different alphabets (a, b, c) represent statistically significant values (p  More

  • in

    Background climate conditions regulated the photosynthetic response of Amazon forests to the 2015/2016 El Nino-Southern Oscillation event

    Costanza, R. et al. Changes in the global value of ecosystem services. Glob. Environ. Change 26, 152–158 (2014).Article 

    Google Scholar 
    Mittermeier, R. A. et al. Wilderness and biodiversity conservation. Proc. Natl. Acad. Sci. USA 100, 10309–10313 (2003).CAS 
    Article 

    Google Scholar 
    Dirzo, R. & Raven, P. H. Global state of biodiversity and loss. Annu. Rev. Env. Resour. 28, 137–167 (2003).Article 

    Google Scholar 
    Marengo, J. A. et al. Changes in climate and land use over the amazon region: current and future variability and trends. Front. Earth Sci. 6, 1–21 (2018).Article 

    Google Scholar 
    Anderson-Teixeira, K. J. et al. Climate-regulation services of natural and agricultural ecoregions of the Americas. Nat. Clim. Change 2, 177–181 (2012).Article 

    Google Scholar 
    Marengo, J. A. et al. The drought of Amazonia in 2005. J. Clim. 21, 495–516 (2008).Article 

    Google Scholar 
    Lewis, S. L., Brando, P. M., Phillips, O. L., Van Der Heijden, G. M. F. & Nepstad, D. The 2010 Amazon drought. Science 331, 554 (2011).CAS 
    Article 

    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, 33130 (2016).Article 
    CAS 

    Google Scholar 
    Phillips, O. L. et al. Drought sensitivity of the amazon rainforest. Science 323, 1344–1347 (2009).Koren, G. et al. Widespread reduction in sun-induced fluorescence from the Amazon during the 2015/2016 El Niño. Philos. Trans. R. Soc. Lond. B Biol. Sci 373, 20170408 (2018).Article 
    CAS 

    Google Scholar 
    Feldpausch, T. R. et al. Amazon forest response to repeated droughts. Glob. Biogeochem. Cycles 30, 964–982 (2016).CAS 
    Article 

    Google Scholar 
    Sousa, T. R. et al. Palms and trees resist extreme drought in Amazon forests with shallow water tables. J. Ecol. 108, 2070–2082 (2020).CAS 
    Article 

    Google Scholar 
    Barros, F. et al. Hydraulic traits explain differential responses of Amazonian forests to the 2015 El Niño-induced drought. New Phytol. 223, 1253–1266 (2019).CAS 
    Article 

    Google Scholar 
    Magney, T. S. et al. Mechanistic evidence for tracking the seasonality of photosynthesis with solar-induced fluorescence. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.1900278116 (2019).Ciemer, C. et al. Higher resilience to climatic disturbances in tropical vegetation exposed to more variable rainfall. Nat. Geosci. 12, 174–179 (2019).CAS 
    Article 

    Google Scholar 
    Gloor, E. et al. Tropical land carbon cycle responses to 2015/16 El Niño as recorded by atmospheric greenhouse gas and remote sensing data. Philos. Trans. R. Soc. B 373, 20170302 (2018).Article 
    CAS 

    Google Scholar 
    Jiménez-Muñoz, J. C., Sobrino, J. A., Mattar, C. & Malhi, Y. Spatial and temporal patterns of the recent warming of the Amazon forest. J. Geophys. Res. Atmos. 118, 5204–5215 (2013).Article 

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

    Google Scholar 
    Esquivel-Muelbert, A. et al. Seasonal drought limits tree species across the Neotropics. Ecography 60, 12 (2016).
    Google Scholar 
    Fisher, R. A., Williams, M., de Lourdes Ruivo, M., de Costa, A. L. & Meir, P. Evaluating climatic and soil water controls on evapotranspiration at two Amazonian rainforest sites. Agric. For. Meteorol. 148, 850–861 (2008).Article 

    Google Scholar 
    Marthews, T. R. et al. High-resolution hydraulic parameter maps for surface soils in tropical South America. Geosci. Model Dev. 7, 711–723 (2014).Article 

    Google Scholar 
    Esteban, E. J. L., Castilho, C. V., Melgaço, K. L. & Costa, F. R. C. The other side of droughts: wet extremes and topography as buffers of negative drought effects in an Amazonian forest. New. Phytol. 229, 1995–2006 (2021).CAS 
    Article 

    Google Scholar 
    Castro, A. O. et al. OCO-2 solar-induced chlorophyll fluorescence variability across ecoregions of the amazon basin and the extreme drought effects of El Niño (2015–2016). Remote Sens. 12, 1202 (2020).Article 

    Google Scholar 
    Sullivan, M. J. P. et al. Long-term thermal sensitivity of Earth’s tropical forests. Science 368, 869–874 (2020).CAS 
    Article 

    Google Scholar 
    Sombroek, W. Spatial and temporal patterns of amazon rainfall. Ambio 30, 388–396 (2001).CAS 
    Article 

    Google Scholar 
    Quesada, C. A. et al. Basin-wide variations in Amazon forest structure and function are mediated by both soils and climate. Biogeosciences 9, 2203–2246 (2012).Fan, Y., Li, H. & Miguez-Macho, G. Global patterns of groundwater table depth. Science 339, 940–943 (2013).CAS 
    Article 

    Google Scholar 
    Joetzjer, E., Douville, H., Delire, C. & Ciais, P. Present-day and future Amazonian precipitation in global climate models: CMIP5 versus CMIP3. Clim. Dyn. 41, 2921–2936 (2013).Article 

    Google Scholar 
    Schietti, J. et al. Vertical distance from drainage drives floristic composition changes in an Amazonian rainforest. Plant. Ecol. Divers. 7, 241–253 (2014).Oliveira, R. S. et al. Embolism resistance drives the distribution of Amazonian rainforest tree species along hydro‐topographic gradients. New Phytol. 221, 1457–1465 (2018).Fyllas, N. M. et al. Basin-wide variations in foliar properties of Amazonian forest: phylogeny, soils and climate. Biogeosciences 6, 2677–2708 (2009).Sterck, F., Markesteijn, L., Schieving, F. & Poorter, L. Functional traits determine trade-offs and niches in a tropical forest community. PNAS 108, 20627–20632 (2011).CAS 
    Article 

    Google Scholar 
    Oliveira, R. S. et al. Linking plant hydraulics and the fast–slow continuum to understand resilience to drought in tropical ecosystems. New Phytol. 230, 904–923 (2021).Article 

    Google Scholar 
    Guillemot, J. et al. Small and slow is safe: On the drought tolerance of tropical tree species. Glob. Chang. Biol. 28, 2622–2638 (2022).CAS 
    Article 

    Google Scholar 
    DeSoto, L. et al. Low growth resilience to drought is related to future mortality risk in trees. Nat. Commun. 11, 545 (2020).CAS 
    Article 

    Google Scholar 
    Rowland, L. et al. Death from drought in tropical forests is triggered by hydraulics not carbon starvation. Nature 528, 119–122 (2015).CAS 
    Article 

    Google Scholar 
    de Almeida Castanho, A. D. et al. Changing Amazon biomass and the role of atmospheric CO2 concentration, climate, and land use. Glob. Biogeochem. Cycles 30, 18–39 (2016).Article 
    CAS 

    Google Scholar 
    Friedlingstein, P. et al. Global carbon budget 2020. Earth Syst. Sci. Data 12, 3269–3340 (2020).Article 

    Google Scholar 
    Sitch, S. et al. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob. Chang. Biol. 9, 161–185 (2003).Article 

    Google Scholar 
    Lathière, J. et al. Impact of climate variability and land use changes on global biogenic volatile organic compound emissions. Atmos. Chem. Phys. 6, 2129–2146 (2006).Article 

    Google Scholar 
    Galbraith, D. et al. Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change. New Phytol. 187, 647–65 (2010).Article 

    Google Scholar 
    Johnson, M. O. et al. Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models. Glob. Chang. Biol. 22, 3996–4013 (2016).Article 

    Google Scholar 
    Thonicke, K. et al. Simulating functional diversity of European natural forests along climatic gradients. J. Biogeogr. 47, 1069–1085 (2020).Article 

    Google Scholar 
    Feldpausch, T. R. et al. Height-diameter allometry of tropical forest trees. Biogeosciences 8, 1081–1106 (2011).Article 

    Google Scholar 
    Feldpausch, T. R. et al. Tree height integrated into pantropical forest biomass estimates. Biogeosciences 9, 3381–3403 (2012).Article 

    Google Scholar 
    Potapov, P. et al. The last frontiers of wilderness: tracking loss of intact forest landscapes from 2000 to 2013. Sci. Adv. 3, 1–14 (2017).Article 

    Google Scholar 
    Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth. BioScience 51, 933–938 (2001).Article 

    Google Scholar 
    Running, Steve, Mu, Qiaozhen & Zhao, Maosheng. MOD16A2 MODIS/Terra net evapotranspiration 8-day L4 global 500m. https://doi.org/10.5067/MODIS/MOD16A2.006 (2017).van Schaik, E. et al. Improved SIFTER v2 algorithm for long-term GOME-2A satellite retrievals of fluorescence with a correction for instrument degradation. https://doi.org/10.5194/amt-2019-384 (2020).Kooreman, M. L. et al. GOME-2A SIFTER v2 (2007-2018) [Data set]. SIFTER sun-induced vegetation fluorescence data from GOME-2A (Version 2.0) [Data set]. Royal Netherlands Meteorological Institute (KNMI). https://doi.org/10.21944/gome2a-sifter-v2-sun-induced-fluorescence.Hoese, D. et al. pytroll/pyresample: Version 1.23.0. Zenodo, https://doi.org/10.5281/zenodo.6375741 (2022).Kooreman, M., Tuinder, O., Boersma, K. F. & van Schaik, E. Algorithm Theoretical Basis Document for the GOME-2 NRT, Offline and Data Record Sun-Induced Fluorescence Products. (2019).Wigneron, J.-P. et al. Tropical forests did not recover from the strong 2015–2016 El Niño event. Sci. Adv. 6, eaay4603 (2020).CAS 
    Article 

    Google Scholar 
    Gatti, L. V. et al. Drought sensitivity of Amazonian carbon balance revealed by atmospheric measurements. Nature 506, 76–80 (2014).CAS 
    Article 

    Google Scholar 
    Doughty, R. et al. TROPOMI reveals dry-season increase of solar-induced chlorophyll fluorescence in the Amazon forest. Proc. Natl. Acad. Sci. USA 116, 22393–22398 (2019).CAS 
    Article 

    Google Scholar 
    Porcar-Castell, A. et al. Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science. Nat. Plants 7, 998–1009 (2021).CAS 
    Article 

    Google Scholar 
    Sun, Y. et al. OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence. Science 358, eaam5747 (2017).Article 
    CAS 

    Google Scholar 
    Wood, J. D. et al. Multiscale analyses of solar-induced florescence and gross primary production. Geophys. Res. Lett. 44, 533–541 (2017).Article 

    Google Scholar 
    Verma, M. et al. Effect of environmental conditions on the relationship between solar-induced fluorescence and gross primary productivity at an OzFlux grassland site. J. Geophys. Res. Biogeosci. 122, 716–733 (2017).Article 

    Google Scholar 
    Parazoo, N. C. et al. Terrestrial gross primary production inferred from satellite fluorescence and vegetation models. Glob. Chang Biol. 20, 3103–3121 (2014).Article 

    Google Scholar 
    Copernicus Climate Change Service (C3S). ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate. https://cds.climate.copernicus.eu/cdsapp#!/home (2017).Goddard Earth Sciences Data and Information Services Center (GES DISC). Tropical Rainfall Measuring Mission (TRMM) – TRMM (TMPA/3B43) Rainfall Estimate L3 1 month 0.25 degree x 0.25 degree V7. https://doi.org/10.5067/TRMM/TMPA/MONTH/7 (2011).Aragão, L. E. O. C. et al. Spatial patterns and fire response of recent Amazonian droughts. Geophys. Res. Lett. 34 (2007).Paca, V. H. et al. The spatial variability of actual evapotranspiration across the Amazon River Basin based on remote sensing products validated with flux towers. Ecol. Process. 8, 6 (2019).Phillips, O. L. et al. Drought–mortality relationships for tropical forests. New Phytol. 187, 631–646 (2010).Article 

    Google Scholar 
    Maeda, E. E. et al. Evapotranspiration seasonality across the Amazon Basin. Earth Syst. Dyn. 8, 439–454 (2017).Article 

    Google Scholar 
    Hengl, T. et al. SoilGrids250m: Global gridded soil information based on machine learning. PLoS One 12, e0169748 (2017).Article 
    CAS 

    Google Scholar 
    Costa, F. R. C., Schietti, J., Stark, S. C. & Smith, M. N. The other side of tropical forest drought: do shallow water table regions of Amazonia act as large-scale hydrological refugia from drought? New Phytol. https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.17914 .Walsh, R. P. D. & Lawler, D. M. Rainfall seasonality: description, spatial patterns and change through time. Weather 36, 201–208 (1981).Article 

    Google Scholar 
    Gorelick, N. et al. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ. https://doi.org/10.1016/j.rse.2017.06.031 (2017).Heinze, G., Wallisch, C. & Dunkler, D. Variable selection – a review and recommendations for the practicing statistician. Biom. J. 60, 431–449 (2018).Article 

    Google Scholar 
    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag New York, 2016).QGIS.org. QGIS Geographic Information System (QGIS Association, 2022).Fancourt, M. Repository for Code, Data and Figures. https://zenodo.org/badge/latestdoi/514231211 (2022). More