More stories

  • in

    Strain-specific transcriptional responses overshadow salinity effects in a marine diatom sampled along the Baltic Sea salinity cline

    Lozupone CA, Knight R. Global patterns in bacterial diversity. Proc Natl Acad Sci USA. 2007;104:11436–40.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Logares R, Bråte J, Bertilsson S, Clasen JL, Shalchian-Tabrizi K, Rengefors K. Infrequent marine-freshwater transitions in the microbial world. Trends Microbiol. 2009;17:414–22.CAS 
    PubMed 

    Google Scholar 
    Cavalier-Smith T. Megaphylogeny, cell body plans, adaptive zones: causes and timing of eukaryote basal radiations. J Eukaryot Microbiol. 2009;56:26–33.PubMed 

    Google Scholar 
    Nakov T, Beaulieu JM, Alverson AJ. Diatoms diversify and turn over faster in freshwater than marine environments. Evolution. 2019;73:2497–511.PubMed 

    Google Scholar 
    Dittami SM, Heesch S, Olsen JL, Collén J. Transitions between marine and freshwater environments provide new clues about the origins of multicellular plants and algae. J Phycol. 2017;53:731–45.PubMed 

    Google Scholar 
    Dickson B, Yashayaev I, Meincke J, Turrell B, Dye S, Holfort J. Rapid freshening of the deep North Atlantic Ocean over the past four decades. Nature. 2002;416:832–7.CAS 
    PubMed 

    Google Scholar 
    Aretxabaleta AL, Smith KW, Kalra TS. Regime changes in global sea surface salinity trend. J Mar Sci Eng. 2017;5:57.
    Google Scholar 
    López-Maury L, Marguerat S, Bähler J. Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation. Nat Rev Genet. 2008;9:583–93.PubMed 

    Google Scholar 
    Björck S. A review of the history of the Baltic Sea, 13.0-8.0 ka BP. Quat Int. 1995;27:19–40.
    Google Scholar 
    Krauss W. Baltic sea circulation. In: Steele JH, editor. Encyclopedia of ocean sciences. Oxford: Academic Press; 2001. p. 236–44.Telesh I, Schubert H, Skarlato S. Life in the salinity gradient: discovering mechanisms behind a new biodiversity pattern. Estuar Coast Shelf Sci. 2013;135:317–27.
    Google Scholar 
    Johannesson K, Le Moan A, Perini S, André C. A Darwinian laboratory of multiple contact zones. Trends Ecol Evol. 2020;35:1021–36.PubMed 

    Google Scholar 
    Olofsson M, Hagan JG, Karlson B, Gamfeldt L. Large seasonal and spatial variation in nano- and microphytoplankton diversity along a Baltic Sea-North Sea salinity gradient. Sci Rep. 2020;10:17666.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sjöqvist C, Godhe A, Jonsson PR, Sundqvist L, Kremp A. Local adaptation and oceanographic connectivity patterns explain genetic differentiation of a marine diatom across the North Sea-Baltic Sea salinity gradient. Mol Ecol. 2015;24:2871–85.PubMed 
    PubMed Central 

    Google Scholar 
    Jochem F. Distribution and importance of autotrophic ultraplankton in a boreal inshore area (Kiel Bight, Western Baltic). Mar Ecol Prog Ser. 1989;53:153–68.
    Google Scholar 
    Wasmund N, Nausch G, Gerth M, Busch S, Burmeister C, Hansen R, et al. Extension of the growing season of phytoplankton in the western Baltic Sea in response to climate change. Mar Ecol Prog Ser. 2019;622:1–16.CAS 

    Google Scholar 
    van Wirdum F, Andrén E, Wienholz D, Kotthoff U, Moros M, Fanget A-S, et al. Middle to Late Holocene variations in salinity and primary productivity in the Central Baltic Sea: a multiproxy study from the Landsort Deep. Front Mar Sci. 2019;6:51.
    Google Scholar 
    Alverson AJ. Timing marine–freshwater transitions in the diatom order Thalassiosirales. Paleobiology. 2014;40:91–101.
    Google Scholar 
    Nakov T, Beaulieu JM, Alverson AJ. Insights into global planktonic diatom diversity: the importance of comparisons between phylogenetically equivalent units that account for time. ISME J. 2018;12:2807–10.PubMed 
    PubMed Central 

    Google Scholar 
    Kremp A, Godhe A, Egardt J, Dupont S, Suikkanen S, Casabianca S, et al. Intraspecific variability in the response of bloom-forming marine microalgae to changed climate conditions. Ecol Evol. 2012;2:1195–207.PubMed 
    PubMed Central 

    Google Scholar 
    Olofsson M, Kourtchenko O, Zetsche E-M, Marchant HK, Whitehouse MJ, Godhe A, et al. High single-cell diversity in carbon and nitrogen assimilations by a chain-forming diatom across a century. Environ Microbiol. 2019;21:142–51.CAS 
    PubMed 

    Google Scholar 
    Olofsson M, Almén A-K, Jaatinen K, Scheinin M. Temporal escape – adaptation to eutrophication by Skeletonema marinoi. FEMS Microbiol Lett. 2022;fnac011. https://pubmed.ncbi.nlm.nih.gov/35137038/.Godhe A, Härnström K. Linking the planktonic and benthic habitat: genetic structure of the marine diatom Skeletonema marinoi. Mol Ecol. 2010;19:4478–90.PubMed 

    Google Scholar 
    Dobin A, Gingeras TR. Mapping RNA-seq reads with STAR. Curr Protoc Bioinform. 2015;51:11.14.1–11.14.19.
    Google Scholar 
    Anders S, Pyl PT, Huber W. HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jones P, Binns D, Chang H-Y, Fraser M, Li W, McAnulla C, et al. InterProScan 5: genome-scale protein function classification. Bioinformatics. 2014;30:1236–40.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Aramaki T, Blanc-Mathieu R, Endo H, Ohkubo K, Kanehisa M, Goto S, et al. KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold. Bioinformatics. 2020;36:2251–2.CAS 
    PubMed 

    Google Scholar 
    Emms DM, Kelly S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 2019;20:238.PubMed 
    PubMed Central 

    Google Scholar 
    Almagro Armenteros JJ, Salvatore M, Emanuelsson O, Winther O, von Heijne G, Elofsson A, et al. Detecting sequence signals in targeting peptides using deep learning. Life Sci Alliance. 2019;2:e201900429.PubMed 
    PubMed Central 

    Google Scholar 
    Gruber A, Rocap G, Kroth PG, Armbrust EV, Mock T. Plastid proteome prediction for diatoms and other algae with secondary plastids of the red lineage. Plant J. 2015;81:519–28.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bendtsen JD, Nielsen H, von Heijne G, Brunak S. Improved prediction of signal peptides: SignalP 3.0. J Mol Biol. 2004;340:783–95.PubMed 

    Google Scholar 
    Gschloessl B, Guermeur Y, Cock JM. HECTAR: a method to predict subcellular targeting in heterokonts. BMC Bioinforma. 2008;9:393.
    Google Scholar 
    Claros MG. MitoProt, a Macintosh application for studying mitochondrial proteins. Comput Appl Biosci. 1995;11:441–7.CAS 
    PubMed 

    Google Scholar 
    Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40.CAS 

    Google Scholar 
    Van den Berge K, Soneson C, Robinson MD, Clement L. stageR: a general stage-wise method for controlling the gene-level false discovery rate in differential expression and differential transcript usage. Genome Biol. 2017;18:151.PubMed 
    PubMed Central 

    Google Scholar 
    Heller R, Manduchi E, Grant GR, Ewens WJ. A flexible two-stage procedure for identifying gene sets that are differentially expressed. Bioinformatics. 2009;25:1019–25.CAS 
    PubMed 

    Google Scholar 
    Alexa A, and Rahnenfuhrer J. topGO: Enrichment Analysis for GeneOntology. R package version 2.44.0. 2021. https://bioconductor.org/packages/release/bioc/html/topGO.html.Wu D, Smyth GK. Camera: a competitive gene set test accounting for inter-gene correlation. Nucleic Acids Res. 2012;40:e133.CAS 
    PubMed 
    PubMed Central 

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

    Google Scholar 
    Bussard A, Corre E, Hubas C, Duvernois-Berthet E, Le Corguillé G, Jourdren L, et al. Physiological adjustments and transcriptome reprogramming are involved in the acclimation to salinity gradients in diatoms. Environ Microbiol. 2017;19:909–25.CAS 
    PubMed 

    Google Scholar 
    Matthijs M, Fabris M, Obata T, Foubert I, Franco-Zorrilla JM, Solano R, et al. The transcription factor bZIP14 regulates the TCA cycle in the diatom Phaeodactylum tricornutum. EMBO J. 2017;36:1559–76.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kong L, Price NM. Transcriptomes of an oceanic diatom reveal the initial and final stages of acclimation to copper deficiency. Environ Microbiol. 2021;24:951–66.Amato A, Sabatino V, Nylund GM, Bergkvist J, Basu S, Andersson MX, et al. Grazer-induced transcriptomic and metabolomic response of the chain-forming diatom Skeletonema marinoi. ISME J. 2018;12:1594–604.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Maumus F, Allen AE, Mhiri C, Hu H, Jabbari K, Vardi A, et al. Potential impact of stress activated retrotransposons on genome evolution in a marine diatom. BMC Genomics. 2009;10:624.PubMed 
    PubMed Central 

    Google Scholar 
    Pargana A, Musacchia F, Sanges R, Russo MT, Ferrante MI, Bowler C, et al. Intraspecific diversity in the cold stress response of transposable elements in the diatom Leptocylindrus aporus. Genes. 2019;11:9.PubMed Central 

    Google Scholar 
    Smith SR, Dupont CL, McCarthy JK, Broddrick JT, Oborník M, Horák A, et al. Evolution and regulation of nitrogen flux through compartmentalized metabolic networks in a marine diatom. Nat Commun. 2019;10:4552.PubMed 
    PubMed Central 

    Google Scholar 
    Kageyama H, Tanaka Y, Shibata A, Waditee-Sirisattha R, Takabe T. Dimethylsulfoniopropionate biosynthesis in a diatom Thalassiosira pseudonana: Identification of a gene encoding MTHB-methyltransferase. Arch Biochem Biophys. 2018;645:100–6.CAS 
    PubMed 

    Google Scholar 
    Nakov T, Judy KJ, Downey KM, Ruck EC, Alverson AJ. Transcriptional response of osmolyte synthetic pathways and membrane transporters in a euryhaline diatom during long-term acclimation to a salinity gradient. J Phycol. 2020;56:1712–28.CAS 
    PubMed 

    Google Scholar 
    Kageyama H, Tanaka Y, Takabe T. Biosynthetic pathways of glycinebetaine in Thalassiosira pseudonana; functional characterization of enzyme catalyzing three-step methylation of glycine. Plant Physiol Biochem. 2018;127:248–55.CAS 
    PubMed 

    Google Scholar 
    Krell A, Funck D, Plettner I, John U, Dieckmann G. Regulation of proline metabolism under salt stress in the psychrophilic diatom Fragilariopsis cylindrus (Bacillariophyceae). J Phycol. 2007;43:753–62.CAS 

    Google Scholar 
    Latta LC, Weider LJ, Colbourne JK, Pfrender ME. The evolution of salinity tolerance in Daphnia: a functional genomics approach. Ecol Lett. 2012;15:794–802.PubMed 

    Google Scholar 
    Ferrante MI, Entrambasaguas L, Johansson M, Töpel M, Kremp A, Montresor M, et al. Exploring molecular signs of sex in the marine diatom Skeletonema marinoi. Genes. 2019;10:494.Kroth PG. The biodiversity of carbon assimilation. J Plant Physiol. 2015;172:76–81.CAS 
    PubMed 

    Google Scholar 
    Obata T, Fernie AR, Nunes-Nesi A. The central carbon and energy metabolism of marine diatoms. Metabolites. 2013;3:325–46.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Smith SR, Abbriano RM, Hildebrand M. Comparative analysis of diatom genomes reveals substantial differences in the organization of carbon partitioning pathways. Algal Res. 2012;1:2–16.CAS 

    Google Scholar 
    Kroth PG, Chiovitti A, Gruber A, Martin-Jezequel V, Mock T, Parker MS, et al. A model for carbohydrate metabolism in the diatom Phaeodactylum tricornutum deduced from comparative whole genome analysis. PLoS ONE. 2008;3:e1426.PubMed 
    PubMed Central 

    Google Scholar 
    Furumoto T, Yamaguchi T, Ohshima-Ichie Y, Nakamura M, Tsuchida-Iwata Y, Shimamura M, et al. A plastidial sodium-dependent pyruvate transporter. Nature. 2011;476:472–5.CAS 
    PubMed 

    Google Scholar 
    Chen G-Q, Jiang Y, Chen F. Salt-induced alterations in lipid composition of diatom Nitzschia laevis (Bacillariophyceae) under heterotrophic culture condition. J Phycol. 2008;44:1309–14.CAS 
    PubMed 

    Google Scholar 
    Sayanova O, Mimouni V, Ulmann L, Morant-Manceau A, Pasquet V, Schoefs B, et al. Modulation of lipid biosynthesis by stress in diatoms. Philos Trans R Soc Lond B Biol Sci. 2017;372:20160407.PubMed 
    PubMed Central 

    Google Scholar 
    Vårum KM, Myklestad S. Effects of light, salinity and nutrient limitation on the production of β-1,3-d-glucan and exo-d-glucanase activity in Skeletonema costatum (Grev.) Cleve. J Exp Mar Bio Ecol. 1984;83:13–25.
    Google Scholar 
    Radchenko IG, Il’yash LV. Growth and photosynthetic activity of diatom Thalassiosira weissflogii at decreasing salinity. Biol Bull. 2006;33:242–7.CAS 

    Google Scholar 
    Adams C, Bugbee B. Enhancing lipid production of the marine diatom Chaetoceros gracilis: synergistic interactions of sodium chloride and silicon. J Appl Phycol. 2014;26:1351–7.CAS 

    Google Scholar 
    Shetty P, Gitau MM, Maróti G. Salinity stress responses and adaptation mechanisms in eukaryotic green microalgae. Cells. 2019;8:1657.Jacob A, Kirst GO, Wiencke C, Lehmann H. Physiological responses of the Antarctic green alga Prasiola crispa ssp. antarctica to salinity stress. J Plant Physiol. 1991;139:57–62.CAS 

    Google Scholar 
    Bazzani E, Lauritano C, Mangoni O, Bolinesi F, Saggiomo M. Chlamydomonas responses to salinity stress and possible biotechnological exploitation. J Mar Sci Eng. 2021;9:1242.
    Google Scholar 
    Cheng R-L, Feng J, Zhang B-X, Huang Y, Cheng J, Zhang C-X. Transcriptome and gene expression analysis of an oleaginous diatom under different salinity conditions. Bioenergy Res. 2014;7:192–205.CAS 

    Google Scholar 
    Stock W, Blommaert L, Daveloose I, Vyverman W, Sabbe K. Assessing the suitability of imaging-PAM fluorometry for monitoring growth of benthic diatoms. J Exp Mar Bio Ecol. 2019;513:35–41.
    Google Scholar 
    Reichmann D, Voth W, Jakob U. Maintaining a healthy proteome during oxidative stress. Mol Cell. 2018;69:203–13.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Latowski D, Kuczyńska P, Strzałka K. Xanthophyll cycle-a mechanism protecting plants against oxidative stress. Redox Rep. 2011;16:78–90.CAS 
    PubMed 

    Google Scholar 
    Chen D, Shao Q, Yin L, Younis A, Zheng B. Polyamine function in plants: metabolism, regulation on development, and roles in abiotic stress responses. Front Plant Sci. 2018;9:1945.PubMed 

    Google Scholar 
    Liu Q, Nishibori N, Imai I, Hollibaugh JT. Response of polyamine pools in marine phytoplankton to nutrient limitation and variation in temperature and salinity. Mar Ecol Prog Ser. 2016;544:93–105.CAS 

    Google Scholar 
    Scoccianti V, Penna A, Penna N, Magnani M. Effect of heat stress on polyamine content and protein pattern in Skeletonema costatum. Mar Biol. 1995;121:549–54.CAS 

    Google Scholar 
    Alscher RG, Erturk N, Heath LS. Role of superoxide dismutases (SODs) in controlling oxidative stress in plants. J Exp Bot. 2002;53:1331–41.CAS 
    PubMed 

    Google Scholar 
    Kumar M, Kumari P, Gupta V, Reddy CRK, Jha B. Biochemical responses of red alga Gracilaria corticata (Gracilariales, Rhodophyta) to salinity induced oxidative stress. J Exp Mar Bio Ecol. 2010;391:27–34.CAS 

    Google Scholar 
    von Alvensleben N, Magnusson M, Heimann K. Salinity tolerance of four freshwater microalgal species and the effects of salinity and nutrient limitation on biochemical profiles. J Appl Phycol. 2016;28:861–76.
    Google Scholar 
    Rijstenbil JW, Wijnholds JA, Sinke JJ. Implications of salinity fluctuation for growth and nitrogen metabolism of the marine diatom Ditylum brightwellii in comparison with Skeletonema costatum. Mar Biol. 1989;101:131–41.CAS 

    Google Scholar 
    Mansour MMF. Nitrogen containing compounds and adaptation of plants to salinity stress. Biol Plant. 2000;43:491–500.CAS 

    Google Scholar 
    Garcia N, Lopez Elias JA, Miranda A, Martinez Porchas M, Huerta N, Garcia A. Effect of salinity on growth and chemical composition of the diatom Thalassiosira weissflogii at three culture phases. Lat Am J Aquat Res. 2012;40:435–40.
    Google Scholar 
    Van den Berge K, Hembach KM, Soneson C, Tiberi S, Clement L, Love MI, et al. RNA sequencing data: Hitchhiker’s guide to expression analysis. Annu Rev Biomed Data Sci. 2019;2:139–73.
    Google Scholar 
    Kremp A. Effects of cyst resuspension on germination and seeding of two bloom-forming dinoflagellates in the Baltic Sea. Mar Ecol Prog Ser. 2001;216:57–66.
    Google Scholar 
    Juneau P, Barnett A, Méléder V, Dupuy C, Lavaud J. Combined effect of high light and high salinity on the regulation of photosynthesis in three diatom species belonging to the main growth forms of intertidal flat inhabiting microphytobenthos. J Exp Mar Bio Ecol. 2015;463:95–104.CAS 

    Google Scholar 
    Vargas C, Argandoña M, Reina-Bueno M, Rodríguez-Moya J, Fernández-Aunión C, Nieto JJ. Unravelling the adaptation responses to osmotic and temperature stress in Chromohalobacter salexigens, a bacterium with broad salinity tolerance. Saline Syst. 2008;4:14.PubMed 
    PubMed Central 

    Google Scholar 
    Khmelenina VN, Sakharovskii VG, Reshetnikov AS, Trotsenko YA. Synthesis of osmoprotectants by halophilic and alkaliphilic methanotrophs. Microbiology. 2000;69:381–6.CAS 

    Google Scholar 
    Fenizia S, Thume K, Wirgenings M, Pohnert G. Ectoine from bacterial and algal origin is a compatible solute in microalgae. Mar Drugs. 2020;18:42.CAS 
    PubMed Central 

    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.CAS 
    PubMed 

    Google Scholar 
    Krell A, Beszteri B, Dieckmann G, Glöckner G, Valentin K, Mock T. A new class of ice-binding proteins discovered in a salt-stress-induced cDNA library of the psychrophilic diatom Fragilariopsis cylindrus (Bacillariophyceae). Eur J Phycol. 2008;43:423–33.CAS 

    Google Scholar 
    Helliwell KE, Kleiner FH, Hardstaff H, Chrachri A, Gaikwad T, Salmon D, et al. Spatiotemporal patterns of intracellular Ca2+ signalling govern hypo-osmotic stress resilience in marine diatoms. N Phytol. 2021;230:155–70.CAS 

    Google Scholar 
    Kaczmarska I, Poulíčková A, Sato S, Edlund MB, Idei M, Watanabe T, et al. Proposals for a terminology for diatom sexual reproduction, auxospores and resting stages. Diatom Res. 2013;28:263–94.
    Google Scholar 
    Godhe A, Kremp A, Montresor M. Genetic and microscopic evidence for sexual reproduction in the centric diatom Skeletonema marinoi. Protist. 2014;165:401–16.PubMed 

    Google Scholar 
    Annunziata R, Mele BH, Marotta P, Volpe M, Entrambasaguas L, Mager S, et al. Trade-off between sex and growth in diatoms: Molecular mechanisms and demographic implications. Sci Adv. 2022;8:eabj9466.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ajani PA, Petrou K, Larsson ME, Nielsen DA, Burke J, Murray SA. Phenotypic trait variability as an indication of adaptive capacity in a cosmopolitan marine diatom. Environ Microbiol. 2021;23:207–23.CAS 
    PubMed 

    Google Scholar 
    Sjöqvist CO, Kremp A. Genetic diversity affects ecological performance and stress response of marine diatom populations. ISME J. 2016;10:2755–66.PubMed 
    PubMed Central 

    Google Scholar 
    Godhe A, Rynearson T. The role of intraspecific variation in the ecological and evolutionary success of diatoms in changing environments. Philos Trans R Soc Lond B Biol Sci. 2017;372:20160399.PubMed 
    PubMed Central 

    Google Scholar 
    Bulankova P, Sekulić M, Jallet D, Nef C, van Oosterhout C, Delmont TO, et al. Mitotic recombination between homologous chromosomes drives genomic diversity in diatoms. Curr Biol. 2021;31:3221–32. e9CAS 
    PubMed 

    Google Scholar 
    Pinseel E, Janssens SB, Verleyen E, Vanormelingen P, Kohler TJ, Biersma EM, et al. Global radiation in a rare biosphere soil diatom. Nat Commun. 2020;11:2382.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Savchuk OP. Large-scale nutrient dynamics in the Baltic sea, 1970–2016. Front Mar Sci. 2018;5:95.
    Google Scholar 
    Gomez-Mestre I, Jovani R. A heuristic model on the role of plasticity in adaptive evolution: plasticity increases adaptation, population viability and genetic variation. Proc Biol Sci. 2013;280:20131869.PubMed 
    PubMed Central 

    Google Scholar 
    Lambert BS, Groussman RD, Schatz MJ, Coesel SN, Durham BP, Alverson AJ, et al. The dynamic trophic architecture of open-ocean protist communities revealed through machine-guided metatranscriptomics. Proc Natl Acad Sci USA. 2022;119:e2100916119.Harrison PF, Pattison AD, Powell DR, Beilharz TH. Topconfects: a package for confident effect sizes in differential expression analysis provides a more biologically useful ranked gene list. Genome Biol. 2019;20:67.PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Biological trade-offs underpin coral reef ecosystem functioning

    Welti, N. et al. Bridging food webs, ecosystem metabolism, and biogeochemistry using ecological stoichiometry theory. Front. Microbiol. 8, 1298 (2017).Article 

    Google Scholar 
    Ceballos, G. et al. Accelerated modern human-induced species losses: entering the sixth mass extinction. Sci. Adv. 1, e14002 (2015).Hughes, T. P. et al. Global warming and recurrent mass bleaching of corals. Nature 543, 373–377 (2017).CAS 
    Article 

    Google Scholar 
    Pauly, D. et al. Towards sustainability in world fisheries. Nature 418, 689–695 (2002).Bellwood, D. R., Streit, R. P., Brandl, S. J. & Tebbett, S. B. The meaning of the term ‘function’ in ecology: a coral reef perspective. Funct. Ecol. 33, 948–961 (2019).Williams, G. J. et al. Coral reef ecology in the Anthropocene. Funct. Ecol. 33, 1014–1022 (2019).Article 

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

    Google Scholar 
    Cinner, J. E. et al. Meeting fisheries, ecosystem function, and biodiversity goals in a human-dominated world. Science 368, 307–311 (2020).CAS 
    Article 

    Google Scholar 
    Mouillot, D. et al. Functional over-redundancy and high functional vulnerability in global fish faunas on tropical reefs. Proc. Natl Acad. Sci. USA 111, 13757–13762 (2014).CAS 
    Article 

    Google Scholar 
    Mora, C. et al. Global human footprint on the linkage between biodiversity and ecosystem functioning in reef fishes. PLoS Biol. 9, e1000606 (2011).CAS 
    Article 

    Google Scholar 
    Barneche, D. R. et al. Scaling metabolism from individuals to reef-fish communities at broad spatial scales. Ecol. Lett. 17, 1067–1076 (2014).CAS 
    Article 

    Google Scholar 
    McIntyre, P. B. et al. Fish distributions and nutrient cycling in streams: can fish create biogeochemical hotspots? Ecology 89, 2335–2346 (2008).Article 

    Google Scholar 
    Allgeier, J. E., Layman, C. A., Mumby, P. J. & Rosemond, A. D. Consistent nutrient storage and supply mediated by diverse fish communities in coral reef ecosystems. Glob. Change Biol. 20, 2459–2472 (2014).Article 

    Google Scholar 
    Morais, R. A. & Bellwood, D. R. Pelagic subsidies underpin fish productivity on a degraded coral reef. Curr. Biol. 29, 1521–1527.e6 (2019).CAS 
    Article 

    Google Scholar 
    Morais, R. A., Connolly, S. R. & Bellwood, D. R. Human exploitation shapes productivity–biomass relationships on coral reefs. Glob. Change Biol. 26, 1295–1305 (2020).Article 

    Google Scholar 
    Barneche, D. R. et al. Body size, reef area and temperature predict global reef-fish species richness across spatial scales. Glob. Ecol. Biogeogr. 28, 315–327 (2019).Article 

    Google Scholar 
    Schiettekatte, N. M. D. et al. Nutrient limitation, bioenergetics and stoichiometry: a new model to predict elemental fluxes mediated by fishes. Funct. Ecol. 34, 1857–1869 (2020).Article 

    Google Scholar 
    Schramski, J. R., Dell, A. I., Grady, J. M., Sibly, R. M. & Brown, J. H. Metabolic theory predicts whole-ecosystem properties. Proc. Natl Acad. Sci. USA 112, 2617–2622 (2015).CAS 
    Article 

    Google Scholar 
    Morais, R. A. & Bellwood, D. R. Global drivers of reef fish growth. Fish Fish. 19, 874–889 (2018).Article 

    Google Scholar 
    Hood, J. M., Vanni, M. J. & Flecker, A. S. Nutrient recycling by two phosphorus-rich grazing catfish: the potential for phosphorus-limitation of fish growth. Oecologia 146, 247–257 (2005).Article 

    Google Scholar 
    Barneche, D. R. & Allen, A. P. The energetics of fish growth and how it constrains food-web trophic structure. Ecol. Lett. 21, 836–844 (2018).Article 

    Google Scholar 
    Brandl, S. J. et al. Demographic dynamics of the smallest marine vertebrates fuel coral reef ecosystem functioning. Science 364, 1189–1192 (2019).CAS 
    Article 

    Google Scholar 
    Lefcheck, J. S. et al. Tropical fish diversity enhances coral reef functioning across multiple scales. Sci. Adv. 5, eaav6420 (2019).Topor, Z. M., Rasher, D. B., Duffy, J. E. & Brandl, S. J. Marine protected areas enhance coral reef functioning by promoting fish biodiversity. Conserv. Lett. 12, e12638 (2019).Article 

    Google Scholar 
    Bellwood, D. R., Hughes, T. P. & Hoey, A. S. Sleeping functional group drives coral-reef recovery. Curr. Biol. 16, 2434–2439 (2006).CAS 
    Article 

    Google Scholar 
    Darling, E. S. & D’agata, S. Coral reefs: fishing for sustainability. Curr. Biol. 27, R65–R68 (2017).CAS 
    Article 

    Google Scholar 
    Graham, N. A. J. et al. Human disruption of coral reef trophic structure. Curr. Biol. 27, 231–236 (2017).CAS 
    Article 

    Google Scholar 
    Graham, N. A. J. et al. Dynamic fragility of oceanic coral reef ecosystems. Proc. Natl Acad. Sci. USA 103, 8425–8429 (2006).CAS 
    Article 

    Google Scholar 
    Stuart-Smith, R. D., Brown, C. J., Ceccarelli, D. M. & Edgar, G. J. Ecosystem restructuring along the great barrier reef following mass coral bleaching. Nature 560, 92–96 (2018).CAS 
    Article 

    Google Scholar 
    Burkepile, D. E. et al. Nutrient supply from fishes facilitates macroalgae and suppresses corals in a Caribbean coral reef ecosystem. Sci. Rep. 3, 1493 (2013).CAS 
    Article 

    Google Scholar 
    Graham, N. A. J. et al. Changing role of coral reef marine reserves in a warming climate. Nat. Commun. 11, 2000 (2020).Reynolds, R. W. et al. Daily high-resolution-blended analyses for sea surface temperature. J. Clim. 20, 5473–5496 (2007).Article 

    Google Scholar 
    Froese, R., Thorson, J. T. & Reyes, R. B. A Bayesian approach for estimating length–weight relationships in fishes. J. Appl. Ichthyol. 30, 78–85 (2014).Article 

    Google Scholar 
    Froese, R. & Pauly, D. FishBase (2018); https://www.fishbase.in/home.htmParravicini, V. et al. Delineating reef fish trophic guilds with global gut content data synthesis and phylogeny. PLoS Biol. 18, e3000702 (2020).CAS 
    Article 

    Google Scholar 
    Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. & West, G. B. Toward a metabolic theory of ecology. Ecology 85, 1771–1789 (2004).Article 

    Google Scholar 
    Bürkner, P.-C. brms: an R package for Bayesian multilevel models using Stan. J. Stat. Softw. 80, 1–28 (2017).Article 

    Google Scholar 
    Carpenter, B. et al. Stan: a probabilistic programming language. J. Stat. Softw. 76, 1–31 (2017).Article 

    Google Scholar  More

  • in

    Influence of yellow gypsum on nutrient uptake and yield of groundnut in different acid soils of Southern India

    Seasonal conditions during crop growthThe groundnut crop produces optimum yield in the regions receiving rainfall between 200 to 1000 mm8. The total rainfall during groundnut growing season was 257.10 mm and 403.10 mm at Baljigapade in 2018 and 2019, respectively, wherein Pavagada (2018) total rainfall was 53.90 mm (Fig. 1). In 2018, both Pavagada and Baljigapade received very low and negligible rainfall during the reproduction and harvest stage of groundnut. Optimum temperature for groundnut production ranges between 20 to 30 °C and growth and pod formation limited below 16 °C and above 32 °C9. The monthly mean atmospheric temperature was ranged from 23 to 27 °C and 21 to 26 °C at Baljigapade in 2018 and 2019, respectively, wherein Pavagada ranged from 25 to 28 °C. At all three locations, the monthly mean atmospheric temperature was slightly high during the early vegetative growth of groundnut and it was progressively decreased as the crop reaches its maturity stage (Fig. 1). All three locations recorded higher and lower mean monthly sunshine hours (hours day−1) during peg initiation to pod filling stage (September and October) and early vegetative growth of groundnut (July and August), respectively.Growth parameters of groundnutAnalysis of variance revealed that treatment, location, and their interaction had a significant effect on plant height and number of branches at harvest (P  More

  • in

    Drawing the borders of the mesophotic zone of the Mediterranean Sea using satellite data

    Hoegh-Guldberg, O. & Bruno, J. F. The impact of climate change on the World’s Marine Ecosystems. Science 328, 1523–1528 (2010).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Hewitt, J. E., Ellis, J. I. & Thrush, S. F. Multiple stressors, nonlinear effects and the implications of climate change impacts on marine coastal ecosystems. Glob. Change Biol. 22, 2665–2675 (2016).ADS 

    Google Scholar 
    Sweetman, A. K. et al. Major impacts of climate change on deep-sea benthic ecosystems. Elementa Sci. Anthropocene. https://doi.org/10.1525/elementa.203 (2017).Article 

    Google Scholar 
    Leslie, H. M. A synthesis of marine conservation planning approaches. Conserv. Biol. 19, 1701–1713 (2005).
    Google Scholar 
    Oppel, S. et al. Spatial scales of marine conservation management for breeding seabirds. Mar. Policy 98, 37–46 (2018).
    Google Scholar 
    Manea, E., Bianchelli, S., Fanelli, E., Danovaro, R. & Gissi, E. Towards an ecosystem-based marine spatial planning in the deep Mediterranean Sea. Sci. Total Environ. 715, 136884 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Aylesworth, L., Phoonsawat, R., Suvanachai, P. & Vincent, A. C. J. Generating spatial data for marine conservation and management. Biodivers. Conserv. 26, 383–399 (2017).
    Google Scholar 
    Lesser, M. P., Slattery, M. & Leichter, J. J. Ecology of mesophotic coral reefs. J. Exp. Mar. Biol. Ecol. 375, 1–8 (2009).
    Google Scholar 
    James, N. P., Ginsburg, R. N. & Ginsburg, R. N. The Seaward Margin of Belize Barrier and Atoll Reefs: Morphology, Sedimentology, Organism Distribution, and Late Quaternary History (Blackwell Scientific, 1979).
    Google Scholar 
    Ginsburg, R. N., Harris, P. M., Eberli, G. P. & Swart, P. K. The growth potential of a bypass margin, Great Bahama Bank. J. Sediment. Res. 61, 976–987 (1991).
    Google Scholar 
    Pyle, R. L. & Copus, J. M. Mesophotic coral ecosystems: Introduction and overview. In Mesophotic Coral Ecosystems. Coral Reefs of the World (eds Loya, Y. et al.) 3–27 (Springer International Publishing, 2019). https://doi.org/10.1007/978-3-319-92735-0_1.Chapter 

    Google Scholar 
    Kahng, S. E. et al. Community ecology of mesophotic coral reef ecosystems. Coral Reefs 29, 255–275 (2010).
    Google Scholar 
    Hinderstein, L. M. et al. Theme section on “Mesophotic coral ecosystems: Characterization, ecology, and management”. Coral Reefs 29, 247–251 (2010).ADS 

    Google Scholar 
    J. A. Turner, D. A. Andradi-Brown, A. Gori, P. Bongaerts, H. L. Burdett, C. Ferrier-Pagès, C. R. Voolstra, D. K. Weinstein, T. C. L. Bridge, F. Costantini, E. Gress, J. Laverick, Y. Loya, G. Goodbody-Gringley, S. Rossi, M. L. Taylor, N. Viladrich, J. D. Voss, J. Williams, L. C. Woodall, G. Eyal. in Mesophotic Coral Ecosystems, Coral Reefs of the World, 989–1003 (Y. Loya, K. A. Puglise, T. C. L. Bridge, Eds). (Springer International Publishing, 2019). https://doi.org/10.1007/978-3-319-92735-0_52.Baker, E. K., Puglise, K. A., Harris, P. T., United Nations Environment Programme, GRID-Arendal. Mesophotic Coral Ecosystems: A Lifeboat for Coral Reefs? (United Nations Environment Programme and GRID-Arendal, 2016).
    Google Scholar 
    Lang, J. C. Biological Zonation at the Base of a Reef: Observations from the submersible Nekton Gamma have led to surprising revelations about the deep fore-reef and island slope at Discovery Bay, Jamaica. Am. Scientist. 62, 272–281 (1974).ADS 

    Google Scholar 
    J. K. Reed. Deepest distribution of Atlantic hermatypic corals discovered in the Bahamas. in Proceedings of the 5th International Coral Reef Symposium (1985), Vol. 6, 249–254.Hanisak, M. D. & Blair, S. M. The deep-water macroalgal community of the East Florida continental shelf (USA). Helgolander Meeresunters. 42, 133–163 (1988).
    Google Scholar 
    Aponte, N. E. & Ballantine, D. L. Depth distribution of algal species on the deep insular fore reef at Lee Stocking Island, Bahamas. Deep Sea Res. Part I 48, 2185–2194 (2001).
    Google Scholar 
    Fricke, H. W., Vareschi, E. & Schlichter, D. Photoecology of the coral Leptoseris fragilis in the Red Sea twilight zone (an experimental study by submersible). Oecologia 73, 371–381 (1987).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Kahng, S. & Maragos, J. The deepest, zooxanthellate scleractinian corals in the world?. Coral Reefs 25, 254–254 (2006).ADS 

    Google Scholar 
    Maragos, J. E. & Jokiel, P. L. Reef corals of Johnston Atoll: One of the world’s most isolated reefs. Coral Reefs 4, 141–150 (1986).ADS 

    Google Scholar 
    Bridge, T. C. L. et al. Variability in mesophotic coral reef communities along the Great Barrier Reef, Australia. Mar. Ecol. Progress Series 428, 63–75 (2011).ADS 

    Google Scholar 
    Lesser, M. P. & Slattery, M. Phase shift to algal dominated communities at mesophotic depths associated with lionfish (Pterois volitans) invasion on a Bahamian coral reef. Biol. Invasions 13, 1855–1868 (2011).
    Google Scholar 
    Slattery, M. & Lesser, M. P. The Bahamas and Cayman Islands. In Mesophotic Coral Ecosystems (eds Loya, Y. et al.) 47–56 (Springer International Publishing, 2019). https://doi.org/10.1007/978-3-319-92735-0_3.Chapter 

    Google Scholar 
    Slattery, M., Lesser, M. P., Brazeau, D., Stokes, M. D. & Leichter, J. J. Connectivity and stability of mesophotic coral reefs. J. Exp. Mar. Biol. Ecol. 408, 32–41 (2011).
    Google Scholar 
    Lesser, M. P., Slattery, M., Laverick, J. H., Macartney, K. J. & Bridge, T. C. Global community breaks at 60 m on mesophotic coral reefs. Glob. Ecol. Biogeogr. 28, 1403–1416 (2019).
    Google Scholar 
    Tamir, R., Eyal, G., Kramer, N., Laverick, J. H. & Loya, Y. Light environment drives the shallow-to-mesophotic coral community transition. Ecosphere 10, e02839 (2019).
    Google Scholar 
    Laverick, J. H., Green, T. K., Burdett, H. L., Newton, J. & Rogers, A. D. Depth alone is an inappropriate proxy for physiological change in the mesophotic coral Agaricia lamarcki. J. Mar. Biol. Assoc. UK 99, 1535–1546 (2019).
    Google Scholar 
    Lesser, M. P., Mobley, C. D., Hedley, J. D. & Slattery, M. Incident light on mesophotic corals is constrained by reef topography and colony morphology. Mar. Ecol. Prog. Ser. 670, 49–60 (2021).ADS 

    Google Scholar 
    Cerrano, C. et al. Temperate mesophotic ecosystems: Gaps and perspectives of an emerging conservation challenge for the Mediterranean Sea. Eur. Zool. J. 86, 370–388 (2019).
    Google Scholar 
    Idan, T. et al. Shedding light on an East-Mediterranean mesophotic sponge ground community and the regional sponge fauna. Mediterr. Mar. Sci. 19, 84–106 (2018).
    Google Scholar 
    Idan, T., Goren, L., Shefer, S., Brickner, I. & Ilan, M. Does depth matter? Reproduction pattern plasticity in two common sponge species found in both mesophotic and shallow waters. Front. Mar. Sci. 7, 1078 (2020).
    Google Scholar 
    Enrichetti, F. et al. Megabenthic communities of the Ligurian deep continental shelf and shelf break (NW Mediterranean Sea). PLoS ONE 14, e0223949 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kahng, S. E. et al. Coral reefs of the world. In Mesophotic Coral Ecosystems (eds Loya, Y. et al.) 47–56 (Springer International Publishing, 2019). https://doi.org/10.1007/978-3-319-92735-0_42 (801–828).Chapter 

    Google Scholar 
    D’Ortenzio, F. & Ribera d’Alcalà, M. On the trophic regimes of the Mediterranean Sea: A satellite analysis. Biogeosciences 6, 139–148 (2009).ADS 

    Google Scholar 
    Christaki, U. et al. Microbial food webs and metabolic state across oligotrophic waters of the Mediterranean Sea during summer. Biogeosciences 8, 1839–1852 (2011).ADS 
    CAS 

    Google Scholar 
    Rossi, V., Ser-Giacomi, E., López, C. & Hernández-García, E. Hydrodynamic provinces and oceanic connectivity from a transport network help designing marine reserves. Geophys. Res. Lett. 41, 2883–2891 (2014).ADS 

    Google Scholar 
    Basterretxea, G., Font-Muñoz, J. S., Salgado-Hernanz, P. M., Arrieta, J. & Hernández-Carrasco, I. Patterns of chlorophyll interannual variability in Mediterranean biogeographical regions. Remote Sens. Environ. 215, 7–17 (2018).ADS 

    Google Scholar 
    Tanhua, T. et al. Repeat hydrography in the Mediterranean Sea, data from the Meteor cruise 84/3 in 2011. Earth Syst. Sci. Data 5, 289–294 (2013).ADS 

    Google Scholar 
    Bethoux, J. P. Budgets of the Mediterranean Sea-their dependance on the local climate and on the characteristics of the Atlantic waters. Oceanol. Acta 2, 157–163 (1979).
    Google Scholar 
    Azov, Y. Eastern Mediterranean—A marine desert?. Mar. Pollut. Bull. 23, 225–232 (1991).
    Google Scholar 
    Pinardi, N., Zavatarelli, M., Arneri, E., Crise, A. & Ravaioli, M. The physical, sedimentary and ecological structure and variability of shelf areas in the Mediterranean Sea. The Sea 14, 1243–1330 (2006).
    Google Scholar 
    Rodolfo-Metalpa, R. et al. Calcification is not the Achilles’ heel of cold-water corals in an acidifying ocean. Glob. Change Biol. 21, 2238–2248 (2015).ADS 

    Google Scholar 
    Bo, M. et al. Fishing impact on deep Mediterranean rocky habitats as revealed by ROV investigation. Biol. Cons. 171, 167–176 (2014).
    Google Scholar 
    Cau, A. et al. Deepwater corals biodiversity along roche du large ecosystems with different habitat complexity along the south Sardinia continental margin (CW Mediterranean Sea). Mar. Biol. 162, 1865–1878 (2015).
    Google Scholar 
    L. Bramanti, M. C. Benedetti, R. Cupido, S. Cocito, C. Priori, F. Erra, M. Iannelli, G. Santangelo. in Marine Animal Forests: The Ecology of Benthic Biodiversity Hotspots, 529–548 (S. Rossi, L. Bramanti, A. Gori, C. Orejas Eds.) (Springer International Publishing, 2017). https://doi.org/10.1007/978-3-319-21012-4_13.Capdevila, P., Linares, C., Aspillaga, E., Riera, J. L. & Hereu, B. Effective dispersal and density-dependence in mesophotic macroalgal forests: Insights from the Mediterranean species Cystoseira zosteroides. PLoS ONE 13, e0191346 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Angeletti, L. et al. A brachiopod biotope associated with rocky bottoms at the shelf break in the central Mediterranean Sea: Geobiological traits and conservation aspects. Aquat. Conserv. Mar. Freshwat. Ecosyst. 30, 402–411 (2020).
    Google Scholar 
    Angeletti, L. & Taviani, M. Offshore Neopycnodonte Oyster Reefs in the Mediterranean Sea. Diversity 12, 92 (2020).
    Google Scholar 
    Castellan, G., Angeletti, L., Taviani, M. & Montagna, P. The yellow coral Dendrophyllia cornigera in a warming ocean. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00692 (2019).Article 

    Google Scholar 
    Corriero, G. et al. A Mediterranean mesophotic coral reef built by non-symbiotic scleractinians. Sci. Rep. 9, 3601 (2019).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Chimienti, G. Vulnerable Forests of the Pink Sea Fan Eunicella verrucosa in the Mediterranean Sea. Diversity 12, 176 (2020).
    Google Scholar 
    Gori, A. et al. Animal forests in deep coastal bottoms and continental shelf of the Mediterranean Sea. In Marine Animal Forests: The Ecology of Benthic Biodiversity Hotspots (eds Rossi, S. et al.) 1–28 (Springer International Publishing, 2017). https://doi.org/10.1007/978-3-319-17001-5_5-2.Chapter 

    Google Scholar 
    Goren, L., Idan, T., Shefer, S. & Ilan, M. Macrofauna inhabiting massive demosponges from shallow and mesophotic habitats along the Israeli Mediterranean Coast. Front. Mar. Sci. 7, 1245 (2021).
    Google Scholar 
    Santín, A. et al. Sponge assemblages on the deep Mediterranean continental shelf and slope (Menorca Channel, Western Mediterranean Sea). Deep Sea Res. Part I 131, 75–86 (2018).
    Google Scholar 
    Martin, C. S. et al. Coralligenous and maërl habitats: predictive modelling to identify their spatial distributions across the Mediterranean Sea. Sci. Rep. 4, 5073 (2014).CAS 

    Google Scholar 
    D. Basso, L. Babbini, A. A. Ramos-Esplá, M. Salomidi. in Rhodolith/Maërl Beds: A Global Perspective, Coastal Research Library, 281–298 (R. Riosmena-Rodríguez, W. Nelson, J. Aguirre, Eds.) (Springer International Publishing, 2017). https://doi.org/10.1007/978-3-319-29315-8_11.Foster, M. M., Amado Filho, G. M., Kamenos, N. A., Riosmena-Rodríguez, R. & Steller, D. L. Rhodoliths and rhodolith beds. Res. Discoveries Revolut. Sci. Through Scuba. 39, 143–155 (2013).
    Google Scholar 
    Littler, M. M., Littler, D. S. & Dennis Hanisak, M. Deep-water rhodolith distribution, productivity, and growth history at sites of formation and subsequent degradation. J. Exp. Mar. Biol. Ecol. 150, 163–182 (1991).
    Google Scholar 
    Ballesteros, E. Mediterranean coralligenous assemblages: a synthesis of present knowledge. Oceanogr. Mar. Biol. Annu. Rev. 44, 123–195 (2006).
    Google Scholar 
    Smith, T. B. et al. Benthic structure and cryptic mortality in a Caribbean mesophotic coral reef bank system, the Hind Bank Marine Conservation District, U. S. Virgin Islands. Coral Reefs 29, 289–308 (2010).ADS 

    Google Scholar 
    Markager, S. & Sand-Jensen, K. Light requirements and depth zonation of marine macroalgae. Mar. Ecol. Prog. Ser. 88, 83–92 (1992).ADS 

    Google Scholar 
    Runcie, J. W., Gurgel, C. F. D. & Mcdermid, K. J. In situ photosynthetic rates of tropical marine macroalgae at their lower depth limit. Eur. J. Phycol. 43, 377–388 (2008).CAS 

    Google Scholar 
    Bindoff, N. L., et al. Chapter 5: Changing ocean, marine ecosystems, and dependent communities. Intergovernmental panel of climate change. in IPCC Special Report on the Ocean and Cryosphere in a Changing Climate 447–587 (2019).Tweedley, J. R., Warwick, R. M. & Potter, I. C. The contrasting ecology of temperate macrotidal and microtidal estuaries. In Oceanography and Marine Biology: An Annual Review (eds Hughes, R. N. et al.) 73–171 (CRC Press, 2016).
    Google Scholar 
    Arias-Ortiz, A. et al. A marine heatwave drives massive losses from the world’s largest seagrass carbon stocks. Nat. Clim. Change. 8, 338–344 (2018).ADS 
    CAS 

    Google Scholar 
    Chen, N., Krom, M. D., Wu, Y., Yu, D. & Hong, H. Storm induced estuarine turbidity maxima and controls on nutrient fluxes across river-estuary-coast continuum. Sci. Total Environ. 628–629, 1108–1120 (2018).ADS 
    PubMed 

    Google Scholar 
    Agusti, S., Lubián, L. M., Moreno-Ostos, E., Estrada, M. & Duarte, C. M. Projected changes in photosynthetic picoplankton in a warmer subtropical ocean. Front. Mar. Sci. 5, 506 (2019).
    Google Scholar 
    Lesser, M. P. & Slattery, M. Will coral reef sponges be winners in the Anthropocene?. Glob. Change Biol. 26, 3202–3211 (2020).ADS 

    Google Scholar 
    Ponti, M., Turicchia, E., Ferro, F., Cerrano, C. & Abbiati, M. The understorey of gorgonian forests in mesophotic temperate reefs. Aquat. Conserv. Mar. Freshwat. Ecosyst. 28, 1153–1166 (2018).
    Google Scholar 
    Enrichetti, F. et al. Assessing the environmental status of temperate mesophotic reefs: A new, integrated methodological approach. Ecol. Ind. 102, 218–229 (2019).
    Google Scholar 
    Soares, M. O., Tavares, T. C. L. & Carneiro, P. B. M. Mesophotic ecosystems: Distribution, impacts and conservation in the South Atlantic. Diversity Distributions. 25, 255–268 (2019).
    Google Scholar 
    Mobley, C. D. & Mobley, C. D. Light and Water: Radiative Transfer in Natural Waters (Academic Press, 1994).
    Google Scholar 
    Marty, J.-C. & Chiavérini, J. Seasonal and interannual variations in phytoplankton production at DYFAMED time-series station, northwestern Mediterranean Sea. Deep Sea Res. Part II 49, 2017–2030 (2002).ADS 
    CAS 

    Google Scholar 
    Morel, A. & André, J.-M. Pigment distribution and primary production in the western Mediterranean as derived and modeled from coastal zone color scanner observations. J. Geophys. Res. Oceans. 96, 12685–12698 (1991).ADS 

    Google Scholar 
    Antoine, D., Morel, A. & André, J.-M. Algal pigment distribution and primary production in the eastern Mediterranean as derived from coastal zone color scanner observations. J. Geophys. Res. Oceans. 100, 16193–16209 (1995).ADS 

    Google Scholar 
    Mayot, N., D’Ortenzio, F., Ribera d’Alcalà, M., Lavigne, H. & Claustre, H. Interannual variability of the Mediterranean trophic regimes from ocean color satellites. Biogeosciences 13, 1901–1917 (2016).ADS 
    CAS 

    Google Scholar 
    S. Kahng, J. M. Copus, D. Wagner. in Marine Animal Forests: The Ecology of Benthic Biodiversity Hotspots, 185–206 (S. Rossi, L. Bramanti, A. Gori, C. Orejas, Eds.) (Springer International Publishing, 2017). https://doi.org/10.1007/978-3-319-21012-4_4.Chimienti, G. et al. Effects of global warming on Mediterranean coral forests. Sci. Rep. 11, 20703 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lesser, M. P., Slattery, M. & Mobley, C. D. Incident light and morphology determine coral productivity along a shallow to mesophotic depth gradient. Ecol. Evol. 11, 13445–13454 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Spalding, M. D. et al. Marine ecoregions of the world: A bioregionalization of coastal and shelf areas. Bioscience 57, 573–583 (2007).
    Google Scholar 
    Danovaro, R. et al. Towards a marine strategy for the deep Mediterranean Sea: Analysis of current ecological status. Mar. Policy. 112, 103781 (2020).
    Google Scholar 
    Saulquin, B. et al. Estimation of the diffuse attenuation coefficient KdPAR using MERIS and application to seabed habitat mapping. Remote Sens. Environ. 128, 224–233 (2013).ADS 

    Google Scholar 
    Grinyó, J. et al. Soft corals assemblages in deep environments of the Menorca Channel (Western Mediterranean Sea). Progress Oceanogr. 188, 102435 (2020).
    Google Scholar 
    Artegiani, A. et al. The Adriatic Sea general circulation. Part I: Air–sea interactions and water mass structure. J. Phys. Oceanogr. 27, 1492–1514 (1997).ADS 

    Google Scholar 
    Morel, A. et al. Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach. Remote Sens. Environ. 111, 69–88 (2007).ADS 

    Google Scholar 
    Davies, A. J. & Guinotte, J. M. Global habitat suitability for framework-forming cold-water corals. PLoS ONE 6, e18483 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Georgian, S. E. et al. Habitat suitability modelling to predict the spatial distribution of cold-water coral communities affected by the Deepwater Horizon oil spill. J. Biogeogr. 47, 1455–1466 (2020).
    Google Scholar 
    R. C. Team, R: A language and environment for statistical computing (3. 5. 1)[Computer software]. R Foundation for Statistical Computing (2020). More

  • in

    Net benefit: using a turtle excluder device in the Adriatic Sea

    Download PDF

    I’m from a fishing family. My grandfather was a fisherman when he was a young man, working out of Fano, the Italian town where I grew up and still live. I’m used to the smell of fish.I’m pictured during an overnight shift on the fishing boat RIMAS. I work from 5 p.m. until 9 a.m. with fishermen from nearby Cesenatico on the north Adriatic Sea. It’s a small boat: there’s only six or so of us on board. At night, the fish are most active and we can avoid other vessels.The nets scrape the sea bed for the catch but sometimes they also catch turtles who often die in the nets or on board. That’s where I come in. The net I’m holding is designed to allow turtles to escape: it has a hole at the top they can swim out of. We call it TED — short for ‘turtle excluder device’. The TED is made from a high-strength plastic, and is based on decades of work and research aimed at reducing the bycatch of turtles from trawling. Turtles and some larger fish can leave through the escape hatch, but the current holds most of the catch in the net.I ensure that the net is working, and that the fishermen we’re collaborating with can still catch enough for their livelihoods while protecting turtles. The work is part of research by the Cetacea Foundation, based in Riccione, Italy, in collaboration with the University of Pisa, where I’m a field researcher. It is financed by the LIFE programme, the European Union’s funding instrument for the environment and climate action.I love this work. It means I’m not stuck in an office all day and instead can enjoy the ocean and work closely with people who live by the sea. I get to be a researcher who works outside, rather than being hunched over a microscope.When my grandfather was fishing in the 1970s, there were more fish and more turtles around. At the foundation, we save 50–60 turtles a year, most of them harmed because of fishing. If we can protect turtles by rolling out this device to fishermen all across the Adriatic, I’d see this work as a success.

    Nature 604, 210 (2022)
    doi: https://doi.org/10.1038/d41586-022-00930-w

    Related Articles

    Protector of giant salamander

    A photo celebration of scientists at work

    Gut feeling: building a picture of Latin American microbiomes

    Subjects

    Careers

    Climate change

    Conservation biology

    Latest on:

    Careers

    How and why to say ‘no’ to colleagues and collaborators
    Career Column 28 MAR 22

    Afghanistan’s girls’ schools can — and must — stay open. There is no alternative
    Editorial 28 MAR 22

    The marine biologist whose photography pastime became a profession
    Career Column 25 MAR 22

    Climate change

    Tropical forests have big climate benefits beyond carbon storage
    News 01 APR 22

    Funding battles stymie ambitious plan to protect global biodiversity
    News 31 MAR 22

    Trends in Europe storm surge extremes match the rate of sea-level rise
    Article 30 MAR 22

    Jobs

    Postdoctoral Fellow

    LSU Health Sciences Center New Orleans (LSUHSC-NO)
    New Orleans, LA, United States

    Associate Research Scientist

    Columbia University Medical Center (CUMC), CU
    New York, NY, United States

    Experimental Postdoctoral Research Associate in Optical/Quantum Metasurfaces

    Los Alamos National Laboratory (LANL)
    Los Alamos, NM, United States

    Theory Postdoctoral Research Associate in Optical/Quantum Metasurfaces

    Los Alamos National Laboratory (LANL)
    Los Alamos, NM, United States More

  • in

    Restructuring of plankton genomic biogeography in the surface ocean under climate change

    Field, C. B., Behrenfeld, M. J., Randerson, J. T. & Falkowski, P. Primary production of the biosphere: integrating terrestrial and oceanic components. Science https://doi.org/10.1126/science.281.5374.237 (1998).Guidi, L. et al. Plankton networks driving carbon export in the oligotrophic ocean. Nature https://doi.org/10.1038/nature16942 (2016).Henson, S. A., Sanders, R. & Madsen, E. Global patterns in efficiency of particulate organic carbon export and transfer to the deep ocean. Glob. Biogeochem. Cycles https://doi.org/10.1029/2011GB004099 (2012).Azam, F. et al. The ecological role of water-column microbes in the sea. Mar. Ecol. Prog. Ser. https://doi.org/10.3354/meps010257 (1983).Saab, M. A. Day-to-day variation in phytoplankton assemblages during spring blooming in a fixed station along the Lebanese coastline. J. Plankton Res. https://doi.org/10.1093/plankt/14.8.1099 (1992).Djurhuus, A. et al. Environmental DNA reveals seasonal shifts and potential interactions in a marine community. Nat. Commun. https://doi.org/10.1038/s41467-019-14105-1 (2020).Kavanaugh, M. T. et al. Seascapes as a new vernacular for pelagic ocean monitoring, management and conservation. ICES J. Mar. Sci. https://doi.org/10.1093/icesjms/fsw086 (2016).Longhurst, A. R. Ecological Geography of the Sea (Elsevier, 2007).Fay, A. R. & McKinley, G. A. Global open-ocean biomes: mean and temporal variability. Earth Syst. Sci. Data https://doi.org/10.5194/essd-6-273-2014 (2014).Reygondeau, G. et al. Dynamic biogeochemical provinces in the global ocean. Glob. Biogeochem. Cycles https://doi.org/10.1002/gbc.20089 (2013).Richter, D. J. et al. Genomic evidence for global ocean plankton biogeography shaped by large-scale current systems. Preprint at bioRxiv https://doi.org/10.1101/867739 (2020).Dutkiewicz, S. et al. Dimensions of marine phytoplankton diversity. Biogeosciences https://doi.org/10.5194/bg-17-609-2020 (2020).Hellweger, F. L., Van Sebille, E. & Fredrick, N. D. Biogeographic patterns in ocean microbes emerge in a neutral agent-based model. Science https://doi.org/10.1126/science.1254421 (2014).Laso-Jadart, R. et al. Investigating population-scale allelic differential expression in wild populations of Oithona similis (Cyclopoida, Claus, 1866). Ecol. Evol. https://doi.org/10.1002/ece3.6588 (2020).Delmont, T. O. et al. Single-amino acid variants reveal evolutionary processes that shape the biogeography of a global SAR11 subclade. eLife https://doi.org/10.7554/eLife.46497 (2019).Carradec, Q. et al. A global ocean atlas of eukaryotic genes. Nat. Commun. https://doi.org/10.1038/s41467-017-02342-1 (2018).Salazar, G. et al. Gene expression changes and community turnover differentially shape the global ocean metatranscriptome. Cell https://doi.org/10.1016/j.cell.2019.10.014 (2019).Alberti, A. et al. Viral to metazoan marine plankton nucleotide sequences from the Tara Oceans expedition. Sci. Data https://doi.org/10.1038/sdata.2017.93 (2017).Pesant, S. et al. Open science resources for the discovery and analysis of Tara Oceans data. Sci. Data https://doi.org/10.1038/sdata.2015.23 (2015).Karsenti, E. et al. A holistic approach to marine eco-systems biology. PLoS Biol. https://doi.org/10.1371/journal.pbio.1001177 (2011).Duarte, C. M. Seafaring in the 21st century: the Malaspina 2010 circumnavigation expedition. Limnol. Oceanogr. Bull. https://doi.org/10.1002/lob.10008 (2015).Barton, A. D., Irwin, A. J., Finkel, Z. V. & Stock, C. A. Anthropogenic climate change drives shift and shuffle in North Atlantic phytoplankton communities. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.1519080113 (2016).Benedetti, F., Guilhaumon, F., Adloff, F. & Ayata, S. D. Investigating uncertainties in zooplankton composition shifts under climate change scenarios in the Mediterranean Sea. Ecography https://doi.org/10.1111/ecog.02434 (2018).Beaugrand, G. et al. Prediction of unprecedented biological shifts in the global ocean. Nat. Clim. Change 9, 237–243 (2019).Article 

    Google Scholar 
    Pinsky, M. L., Worm, B., Fogarty, M. J., Sarmiento, J. L. & Levin, S. A. Marine taxa track local climate velocities. Science https://doi.org/10.1126/science.1239352 (2013).Bopp, L. et al. Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models. Biogeosciences https://doi.org/10.5194/bg-10-6225-2013 (2013).Thomas, M. K., Kremer, C. T., Klausmeier, C. A. & Litchman, E. A global pattern of thermal adaptation in marine phytoplankton. Science https://doi.org/10.1126/science.1224836 (2012).Ibarbalz, F. M. et al. Global trends in marine plankton diversity across kingdoms of life. Cell https://doi.org/10.1016/j.cell.2019.10.008 (2019).Busseni, G. et al. Large scale patterns of marine diatom richness: drivers and trends in a changing ocean. Glob. Ecol. Biogeogr. https://doi.org/10.1111/geb.13161 (2020).Hutchinson, G. E. Concluding remarks. Cold Spring Harb. Symp. Quant. Biol. 22, 415–427 (1957).Article 

    Google Scholar 
    Delmont, T. O. et al. Functional repertoire convergence of distantly related eukaryotic plankton lineages revealed by genome-resolved metagenomics. Preprint at bioRxiv https://doi.org/10.1101/2020.10.15.341214 (2020).Delmont, T. O. et al. Heterotrophic bacterial diazotrophs are more abundant than their cyanobacterial counterparts in metagenomes covering most of the sunlit ocean. ISME J. https://doi.org/10.1038/s41396-021-01135-1 (2021).Boyer, et al. World Ocean Database 2013, NOAA Atlas NESDIS 72 (National Oceanic and Atmospheric Administration, 2013); https://doi.org/10.7289/V5NZ85MTSunagawa, S. et al. Tara Oceans: towards global ocean ecosystems biology. Nat. Rev. Microbiol. https://doi.org/10.1038/s41579-020-0364-5 (2020).Moon, K. R. et al. Visualizing structure and transitions in high-dimensional biological data. Nat. Biotechnol. https://doi.org/10.1038/s41587-019-0336-3 (2019).van Vuuren, D. P. et al. The representative concentration pathways: an overview. Climatic Change https://doi.org/10.1007/s10584-011-0148-z (2011).Polovina, J. J., Dunne, J. P., Woodworth, P. A. & Howell, E. A. Projected expansion of the subtropical biome and contraction of the temperate and equatorial upwelling biomes in the North Pacific under global warming. ICES J. Mar. Sci. https://doi.org/10.1093/icesjms/fsq198 (2011).Flombaum, P., Wang, W. L., Primeau, F. W. & Martiny, A. C. Global picophytoplankton niche partitioning predicts overall positive response to ocean warming. Nat. Geosci. https://doi.org/10.1038/s41561-019-0524-2 (2020).Richardson, A. J. In hot water: zooplankton and climate change. ICES J. Mar. Sci. 65, 279–295 (2008).Article 

    Google Scholar 
    Wrightson, L. & Tagliabue, A. Quantifying the impact of climate change on marine diazotrophy: insights from Earth system models. Front. Mar. Sci. 7, 635 (2020).Article 

    Google Scholar 
    Zehr, J. P. & Capone, D. G. Changing perspectives in marine nitrogen fixation. Science 368, eaay9514 (2020).CAS 
    Article 

    Google Scholar 
    Luo, Y.-W. et al. Database of diazotrophs in global ocean: abundance, biomass and nitrogen fixation rates. Earth Syst. Sci. Data 4, 47–73 (2012).Article 

    Google Scholar 
    Eppley, R. W. & Peterson, B. J. Particulate organic matter flux and planktonic new production in the deep ocean. Nature 282, 677–680 (1979).Article 

    Google Scholar 
    Laws, E. A., Falkowski, P. G., Smith, W. O., Ducklow, H. & McCarthy, J. J. Temperature effects on export production in the open ocean. Glob. Biogeochem. Cycles 14, 1231–1246 (2000).CAS 
    Article 

    Google Scholar 
    Agrawal, R. & Srikant, R. in Proceedings of the 20th International Conference on Very Large Data Bases (eds Bocca, J. B. et al.) 487–499 (Morgan Kaufmann, 1994).Laufkötter, C. et al. Projected decreases in future marine export production: the role of the carbon flux through the upper ocean ecosystem. Biogeosciences 13, 4023–4047 (2016).Article 

    Google Scholar 
    Iudicone, D. Some may like it hot. Nat. Geosci. https://doi.org/10.1038/s41561-020-0535-z (2020).Gorsky, G. et al. Expanding Tara Oceans protocols for underway, ecosystemic sampling of the ocean–atmosphere interface during Tara Pacific expedition (2016–2018). Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00750 (2019).Istace, B. et al. de novo assembly and population genomic survey of natural yeast isolates with the Oxford Nanopore MinION sequencer. Gigascience https://doi.org/10.1093/gigascience/giw018 (2017).Grand, M. M. et al. Developing autonomous observing systems for micronutrient trace metals. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00035 (2019).Becker, R. A., Wilks, A. R., Brownrigg, R., Minka, T. P. & Deckmyn, A. maps: Draw geographical maps. R version 3.5.0 https://cran.r-project.org/web/packages/maps/index.html (2021).Jaccard, P. Distribution comparée de la flore alpine dans quelques régions des Alpes occidentales et orientales. Bull. Murith. 31, 81–92 (1902).
    Google Scholar 
    Watson, R. A. A database of global marine commercial, small-scale, illegal and unreported fisheries catch 1950–2014. Sci. Data https://doi.org/10.1038/sdata.2017.39 (2017).Maritime Boundaries Geodatabase: Maritime Boundaries and Exclusive Economic Zones (200NM), version 11 (Flanders Marine Institute, 2019); https://doi.org/10.14284/386Aumont, O., Ethé, C., Tagliabue, A., Bopp, L. & Gehlen, M. PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies. Geosci. Model Dev. https://doi.org/10.5194/gmd-8-2465-2015 (2015).Bibby, T. S. & Moore, C. M. Silicate:nitrate ratios of upwelled waters control the phytoplankton community sustained by mesoscale eddies in sub-tropical North Atlantic and Pacific. Biogeosciences https://doi.org/10.5194/bg-8-657-2011 (2011).Brun, P., Kiørboe, T., Licandro, P. & Payne, M. R. The predictive skill of species distribution models for plankton in a changing climate. Glob. Change Biol. https://doi.org/10.1111/gcb.13274 (2016).Redfield, A. C. in James Johnstone Memorial Volume (ed. Daniel, R. J.) 176–192 (Liverpool Univ. Press, 1934).Michelangeli, P. A., Vrac, M. & Loukos, H. Probabilistic downscaling approaches: application to wind cumulative distribution functions. Geophys. Res. Lett. https://doi.org/10.1029/2009GL038401 (2009).Ridgeway, G. gbm: Generalized boosted regression models. R version 1.6–3.1 https://cran.r-project.org/web/packages/gbm/gbm.pdf (2010).Breiman, L. & Cutler, A. randomForest: Breiman and Cutler’s random forests for classification and regression. R package 4.1.0 https://www.stat.berkeley.edu/~breiman/RandomForests/ (2012).Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S 4th edn (Springer, 2002).Wood, S. N. Stable and efficient multiple smoothing parameter estimation for generalized additive models. J. Am. Stat. Assoc. https://doi.org/10.1198/016214504000000980 (2004).Fawcett, T. An introduction to ROC analysis. Pattern Recognit. Lett. https://doi.org/10.1016/j.patrec.2005.10.010 (2006).Biecek, P. DALEX: explainers for complex predictive models. J. Mach. Learn. Res. 19, 1–5 (2018).
    Google Scholar 
    Jones, M. C. & Cheung, W. W. L. Multi-model ensemble projections of climate change effects on global marine biodiversity. ICES J. Mar. Sci. https://doi.org/10.1093/icesjms/fsu172 (2015).Vallejos, C. A. Exploring a world of a thousand dimensions. Nat. Biotechnol. https://doi.org/10.1038/s41587-019-0330-9 (2019).Kaufman, L. and Rousseeuw, P.J. in Statistical Data Analysis Based on the L1 Norm and Related Methods (ed. Dodge, Y.) 405–416 (North-Holland, 1987).Rousseeuw, P. J. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. https://doi.org/10.1016/0377-0427(87)90125-7 (1987).Orsi, A. H., Whitworth, T. & Nowlin, W. D. On the meridional extent and fronts of the Antarctic Circumpolar Current. Deep Sea Res. Part I https://doi.org/10.1016/0967-0637(95)00021-W (1995).Hubert, L. & Arabie, P. Comparing partitions. J. Classif. https://doi.org/10.1007/BF01908075 (1985).Somerfield, P. J. Identification of the Bray–Curtis similarity index: comment on Yoshioka (2008). Mar. Ecol. Prog. Ser. https://doi.org/10.3354/meps07841 (2008).Bloom, S. Similarity indices in community studies: potential pitfalls. Mar. Ecol. Prog. Ser. https://doi.org/10.3354/meps005125 (1981).Welch, B. L. The generalisation of student’s problems when several different population variances are involved. Biometrika 34, 28–35 (1947).CAS 

    Google Scholar 
    Holm, S. A simple sequentially rejective multiple test procedure. Scand. J. Stat. 6, 65–70 (1979).
    Google Scholar 
    Mann, H. B. & Whitney, D. R. On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 18, 50–60 (1947).Article 

    Google Scholar 
    Sthle, L. & Wold, S. Analysis of variance (ANOVA). Chemom. Intell. Lab. Syst. 6, 259–272 (1989).Article 

    Google Scholar 
    Bozdogan, H. Model selection and Akaike’s Information Criterion (AIC): the general theory and its analytical extensions. Psychometrika 52, 345–370 (1987).Article 

    Google Scholar 
    Frémont, P. et al. Biogeographies of genomic provinces from ‘Restructuring of plankton genomic biogeography in the surface ocean under climate change’. figshare. https://figshare.com/articles/dataset/Biogeographies_genomic_provinces/19071620 (2022). More

  • in

    Latitudinal gradients in avian colourfulness

    Darwin, C. R. On the Origin of Species, or the Preservation of Favoured Races in the Struggle for Life (John Murray, 1859).Wallace, A. R. Natural Selection and Tropical Nature: Essays on Descriptive and Theoretical Biology 2nd edn (Macmillan, 1895).Darwin, C. R. A Naturalist’s Voyage Round the World (John Murray, 1913).Wallace, A. R. Colour in nature. Nature 19, 580–581 (1879).
    Google Scholar 
    Dalrymple, R. L. et al. Abiotic and biotic predictors of macroecological patterns in bird and butterfly coloration. Ecol. Monogr. 88, 204–224 (2018).
    Google Scholar 
    Adams, J. M., Kang, C. & June-Wells, M. Are tropical butterflies more colorful? Ecol. Res. 29, 685–691 (2014).
    Google Scholar 
    Bailey, S. F. Latitudinal gradients in colors and patterns of passerine birds. Condor 80, 372–381 (1978).
    Google Scholar 
    Wilson, M. F. & Von Neaumann, R. A. Why are neotropical birds more colourful than North American birds? Avicultural Mag. 78, 141–147 (1972).
    Google Scholar 
    Dalrymple, R. L. et al. Birds, butterflies and flowers in the tropics are not more colourful than those at higher latitudes. Glob. Ecol. Biogeogr. 24, 1424–1432 (2015).
    Google Scholar 
    Friedman, N. R. & Remeš, V. Ecogeographical gradients in plumage coloration among Australasian songbird clades. Glob. Ecol. Biogeogr. 26, 261–274 (2017).
    Google Scholar 
    Dale, J., Dey, C. J., Delhey, K., Kempenaers, B. & Valcu, M. The effects of life history and sexual selection on male and female plumage colouration. Nature 527, 367–370 (2015).CAS 

    Google Scholar 
    Dunn, P. O., Armenta, J. K. & Whittingham, L. A. Natural and sexual selection act on different axes of variation in avian plumage color. Sci. Adv. 1, e1400155 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Stoddard, M. C. & Prum, R. O. How colorful are birds? Evolution of the avian plumage color gamut. Behav. Ecol. 22, 1042–1052 (2011).
    Google Scholar 
    Renoult, J. P., Kelber, A. & Schaefer, H. M. Colour spaces in ecology and evolutionary biology. Biol. Rev. 92, 292–315 (2017).
    Google Scholar 
    Stoddard, M. C. & Prum, R. O. Evolution of avian plumage color in a tetrahedral color space: a phylogenetic analysis of New World buntings. Am. Nat. 171, 755–776 (2008).
    Google Scholar 
    Delhey, K. The colour of an avifauna: a quantitative analysis of the colour of Australian birds. Sci. Rep. 5, 18514 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51, 933–938 (2001).
    Google Scholar 
    Rabosky, D. L. et al. An inverse latitudinal gradient in speciation rate for marine fishes. Nature 559, 392–395 (2018).CAS 

    Google Scholar 
    Lynch, M. Methods for the analysis of comparative data in evolutionary biology. Evolution 45, 1065–1080 (1991).PubMed 
    PubMed Central 

    Google Scholar 
    Delhey, K. A review of Gloger’s rule, an ecogeographical rule of colour: definitions, interpretations and evidence. Biol. Rev. Camb. Phil. Soc. 94, 1294–1316 (2019).
    Google Scholar 
    Marchetti, K. Dark habitats and bright birds illustrate the role of the environment in species divergence. Nature 362, 149–152 (1993).
    Google Scholar 
    Endler, J. A. The color of light in forests and its implications. Ecol. Monogr. 63, 1–27 (1993).
    Google Scholar 
    Schemske, D. W. in Speciation and Patterns of Diversity Vol. 12 (eds Butlin, R. et al.) 219–239 (Cambridge Univ. Press, 2009).Schemske, D. W., Mittelbach, G. G., Cornell, H. V., Sobel, J. M. & Roy, K. Is there a latitudinal gradient in the importance of biotic interactions? Annu. Rev. Ecol. Evol. Syst. 40, 245–269 (2009).
    Google Scholar 
    MacArthur, R. H. Patterns of communities in the tropics. Biol. J. Linn. Soc. 1, 19–30 (1969).
    Google Scholar 
    Hadfield, J. D. & Nakagawa, S. General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi-trait models for continuous and categorical characters. J. Evol. Biol. 23, 494–508 (2010).CAS 

    Google Scholar 
    Cooney, C. R. et al. Sexual selection predicts the rate and direction of colour divergence in a large avian radiation. Nat. Commun. 10, 1773 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Cooney, C. R., MacGregor, H. E. A., Seddon, N. & Tobias, J. A. Multi-modal signal evolution in birds: re-assessing a standard proxy for sexual selection. Proc. R. Soc. B 285, 20181557 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    van der Bijl, W. et al. Butterfly dichromatism primarily evolved via Darwin’s, not Wallace’s, model. Evol. Lett. 4, 545–555 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Darwin, C. R. The Descent of Man, and Selection in Relation to Sex (John Murray, 1871).Tobias, J. A., Montgomerie, R. & Lyon, B. E. The evolution of female ornaments and weaponry: social selection, sexual selection and ecological competition. Phil. Trans. R. Soc. B 367, 2274–2293 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    Galván, I., Negro, J. J., Rodríguez, A. & Carrascal, L. M. On showy dwarfs and sober giants: body size as a constraint for the evolution of bird plumage colouration. Acta Ornithol. 48, 65–80 (2013).
    Google Scholar 
    Kiltie, R. A. Scaling of visual acuity with body size in mammals and birds. Funct. Ecol. 14, 226–234 (2000).
    Google Scholar 
    Zahavi, A. & Zahavi, A. The Handicap Principle (Oxford Univ. Press, 1997).Badyaev, A. V. & Hill, G. E. Avian sexual dichromatism in relation to phylogeny and ecology. Annu. Rev. Ecol. Evol. Syst. 34, 27–49 (2003).
    Google Scholar 
    Simpson, R. K., Johnson, M. A. & Murphy, T. G. Migration and the evolution of sexual dichromatism: evolutionary loss of female coloration with migration among wood-warblers. Proc. R. Soc. B 282, 20150375 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Helferich, G. Humboldt’s Cosmos (Tantor eBooks, 2011).Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    He, Y. et al. Segmenting biological specimens from photos to understand the evolution of UV plumage in passerine birds. Preprint at bioRxiv https://doi.org/10.1101/2021.07.22.453339 (2021).Chen, L. C., Zhu, Y., Papandreou, G., Schroff, F. & Adam, H. Encoder–decoder with atrous separable convolution for semantic image segmentation. Preprint at arXiv https://doi.org/10.48550/arXiv.1802.02611 (2018).Hussein, B. R., Malik, O. A., Ong, W.-H. & Slik, J. W. F. in Computational Science and Technology Lecture Notes in Electrical Engineering (eds Alfred, R. et al.) 321–330 (Springer Singapore, 2020).Troscianko, J. & Stevens, M. Image calibration and analysis toolbox—a free software suite for objectively measuring reflectance, colour and pattern. Methods Ecol. Evol. 6, 1320–1331 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Hijmans, R. J. raster: Geographic Data Analysis and Modeling. R package version 3.5-15 https://CRAN.R-project.org/package=raster (2022).Maia, R., Gruson, H., Endler, J. A., White, T. E. & O’Hara, R. B. pavo 2: new tools for the spectral and spatial analysis of colour in R. Methods Ecol. Evol. 10, 1097–1107 (2019).
    Google Scholar 
    Stoddard, M. C. et al. Wild hummingbirds discriminate nonspectral colors. Proc. Natl Acad. Sci. USA 117, 15112–15122 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gomez, D. & Théry, M. Simultaneous crypsis and conspicuousness in color patterns: comparative analysis of a neotropical rainforest bird community. Am. Nat. 169, S42–S61 (2007).
    Google Scholar 
    Blonder, B. Do hypervolumes have holes? Am. Nat. 187, E93–E105 (2016).
    Google Scholar 
    Schliep, K. P. phangorn: phylogenetic analysis in R. Bioinformatics 27, 592–593 (2011).CAS 

    Google Scholar 
    Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).
    Google Scholar 
    Beckmann, M. et al. glUV: a global UV-B radiation data set for macroecological studies. Methods Ecol. Evol. 5, 372–383 (2014).
    Google Scholar 
    Running, S. W. et al. A continuous satellite-derived measure of global terrestrial primary production. Bioscience 54, 547–560 (2004).
    Google Scholar 
    Tobias, J. A. & Pigot, A. L. Integrating behaviour and ecology into global biodiversity conservation strategies. Phil. Trans. R. Soc. B 374, 20190012 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Dunn, P. O., Whittingham, L. A. & Pitcher, T. E. Mating systems, sperm competition, and the evolution of sexual dimorphism in birds. Evolution 55, 161–175 (2001).CAS 

    Google Scholar 
    Bivand, R. S. & Wong, D. W. S. Comparing implementations of global and local indicators of spatial association. TEST 27, 716–748 (2018).
    Google Scholar 
    Hawkins, B. A. et al. Structural bias in aggregated species-level variables driven by repeated species co-occurrences: a pervasive problem in community and assemblage data. J. Biogeogr. 44, 1199–1211 (2017).
    Google Scholar 
    Hadfield, J. D. MCMC methods for multi-response generalised linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, 1–22 (2010).
    Google Scholar 
    Healy, K. et al. Ecology and mode-of-life explain lifespan variation in birds and mammals. Proc. R. Soc. B 281, 20140298 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021); https://www.R-project.org/ More

  • in

    Functional trade-offs in fish communities

    Eddy, T. D. et al. One Earth 4, 1278–1285 (2021).Article 

    Google Scholar 
    Mumby, P. J. et al. Science 311, 98–101 (2006).CAS 
    Article 

    Google Scholar 
    Maire, E. et al. Proc. R. Soc. Lond. B 285, 20181167 (2018).
    Google Scholar 
    Schiettekatte, N. M. D. et al. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-022-0-01710-5 (2022).Article 

    Google Scholar 
    Woodhead, A. J., Hicks, C. C., Norström, A. V., Williams, G. J. & Graham, N. A. J. Funct. Ecol. 33, 1023–1034 (2019).
    Google Scholar 
    Naeem, S., Bunker, D. E., Hector, A., Loreau, M. & Perrings, C. Biodiversity, Ecosystem Functioning, and Human Wellbeing: An Ecological and Economic Perspective (Oxford Univ. Press, 2009).Villéger, S., Brosse, S., Mouchet, M., Mouillot, D. & Vanni, M. J. Aquat. Sci. 79, 783–801 (2017).Article 

    Google Scholar 
    Bascompte, J., Melián, C. J. & Sala, E. Proc. Natl Acad. Sci. USA 102, 5443–5447 (2005).CAS 
    Article 

    Google Scholar 
    Houk, P. & Musburger, C. Mar. Ecol. Prog. Ser. 488, 23–34 (2013).Article 

    Google Scholar 
    Allgeier, J. E., Burkepile, D. E. & Layman, C. A. Glob. Change Biol. 23, 2166–2178 (2017).Article 

    Google Scholar 
    Meyer, J. L., Schultz, E. T. & Helfman, G. S. Science 220, 1047–1049 (1983).CAS 
    Article 

    Google Scholar 
    Brandl, S. J. et al. Science 364, 1189–1192 (2019).CAS 
    Article 

    Google Scholar 
    Morais, R. A., Siqueira, A. C., Smallhorn-West, P. F. & Bellwood, D. R. PLoS Biol. 19, e3001435 (2021).CAS 
    Article 

    Google Scholar 
    Larned, S. T. Mar. Biol. 132, 409–421 (1998).Article 

    Google Scholar 
    McClanahan, T. R., Carreiro-Silva, M. & DiLorenzo, M. Mar. Pollut. Bull. 54, 1947–1957 (2007).CAS 
    Article 

    Google Scholar 
    McLean, M. et al. Proc. Natl Acad. Sci. USA 118, e2012318118 (2021).CAS 
    Article 

    Google Scholar  More