Ecology

Hoffman P. Stromatolite morphogenesis in Shark Bay, Western Australia. In: Developments in sedimentology. Elsevier; 1976.261–71.Golubic S, Hofmann HJ. Comparison of Holocene and Mid-Precambrian Entophysalidaceae (Cyanophyta) in stromatolitic algal mats: Cell division and degradation. J Paleontol. 1976;50:1074–82.
Google Scholar 
Mlewski EC, Pisapia C, Gomez F, Lecourt L, Rueda ES, Benzerara K, et al. Characterization of pustular mats and related Rivularia-rich laminations in oncoids from the Laguna Negra lake (Argentina). Front Microbiol. 2018;9:1–23.Article 

Google Scholar 
St Kendall C, Skipwith A. Recent algal mats of a Persian Gulf lagoon. SEPM J Sediment Res. 1968;38:1040–58.
Google Scholar 
Golubic S, Abed R. Entophysalis mats as environmental regulators. In: Microbial mats, modern and ancient microorganisms in stratified systems. Dordrecht: Springer; 2010.237–51.Logan BW, Hoffman P, Gebelien CD. Algal mats, cryptalgal fabrics, and structures, Hamelin Pool, Western Australia. Am Assoc Pet Geol. 1974;22:140–94.
Google Scholar 
Jahnert RJ, Collins LB. Controls on microbial activity and tidal flat evolution in Shark Bay, Western Australia. Sedimentology. 2013;60:1071–99.Article 

Google Scholar 
Moore KR, Pajusalu M, Gong J, Sojo V, Matreux T, Braun D, et al. Biologically mediated silicification of marine cyanobacteria and implications for the Proterozoic fossil record. Geology. 2020;48:862–6.CAS 
Article 

Google Scholar 
Decho AW, Visscher PT, Reid RP. Production and cycling of natural microbial exopolymers (EPS) within a marine stromatolite. Geobiology: objectives, concepts, perspectives. 2005;71–86.Visscher PT, Dupont CL, Braissant O, Gallagher KL, Glunk C, Casillas L, et al. Biogeochemistry of carbon cycling in hypersaline mats: Linking the present to the past through biosignatures. In: Microbial mats, modern and ancient microorganisms in stratified systems. Dordrecht: Springer; 2010.443–68.Ruvindy R, White RA, Neilan BA, Burns BP. Unravelling core microbial metabolisms in the hypersaline microbial mats of Shark Bay using high-throughput metagenomics. ISME J. 2016;10:183–96.CAS 
PubMed 
Article 

Google Scholar 
Stuart RK, Mayali X, Lee JZ, Craig Everroad R, Hwang M, Bebout BM, et al. Cyanobacterial reuse of extracellular organic carbon in microbial mats. ISME J. 2016;10:1240–51.CAS 
PubMed 
Article 

Google Scholar 
Wong HL, White RA, Visscher PT, Charlesworth JC, Vázquez-Campos X, Burns BP. Disentangling the drivers of functional complexity at the metagenomic level in Shark Bay microbial mat microbiomes. ISME J. 2018;12:2619–39.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Campbell MA, Coolen MJL, Visscher PT, Morris T, Grice K. Structure and function of Shark Bay microbial communities following tropical cyclone Olwyn: a metatranscriptomic and organic geochemical perspective. Geobiology. 2021;19:642–64.CAS 
PubMed 
Article 

Google Scholar 
Braissant O, Decho AW, Przekop KM, Gallagher KL, Glunk C, Dupraz C, et al. Characteristics and turnover of exopolymeric substances in a hypersaline microbial mat. FEMS Microbiol Ecol. 2009;67:293–307.CAS 
PubMed 
Article 

Google Scholar 
Cutts EM, Baldes MJ, Skoog EJ, Hall J, Gong J, Moore KR, et al. Using molecular tools to understand microbial carbonates. Geosciences 2022;12:185.Moore KR, Gong J, Pajusalu M, Skoog EJ, Xu M, Soto Feliz T, et al. A new model for silicification of cyanobacteria in Proterozoic tidal flats. Geobiology. 2021;19:438–49.CAS 
PubMed 
Article 

Google Scholar 
Pereira S, Zille A, Micheletti E, Moradas-Ferreira P, De Philippis R, Tamagnini P. Complexity of cyanobacterial exopolysaccharides: composition, structures, inducing factors and putative genes involved in their biosynthesis and assembly. FEMS Microbiol Rev. 2009;33:917–41.CAS 
PubMed 
Article 

Google Scholar 
Wingender J, Neu TR, Flemming H-C. Microbial extracellular polymeric substances. In: Microbial extracellular polymeric substances. Berlin, Heidelberg: Springer; 1999.1–19.Sheng GP, Yu HQ, Li XY. Extracellular polymeric substances (EPS) of microbial aggregates in biological wastewater treatment systems: a review. Biotechnol Adv. 2010;28:882–94.CAS 
PubMed 
Article 

Google Scholar 
Bar-Or Y, Shilo M. Characterization of macromolecular flocculants produced by Phormidium sp. Strain J-1 and by Anabaenopsis circularis PCC 6720. Appl Environ Microbiol. 1987;53:2226–30.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Sudo H, Burgess JG, Takemasa H, Nakamura N, Matsunaga T. Sulfated exopolysaccharide production by the halophilic cyanobacterium Aphanocapsa halophytia. Curr Microbiol. 1995;30:219–22.CAS 
Article 

Google Scholar 
Witvrouw M, De Clercq E. Sulfated polysaccharides extracted from sea algae as potential antiviral drugs. Gen Pharmacol: The Vasc Syst. 1997;29:497–511.CAS 
Article 

Google Scholar 
De Philippis R, Vincenzini M. Exocellular polysaccharides from cyanobacteria and their possible applications. FEMS Microbiol Rev. 1998;22:151–75.Article 

Google Scholar 
Chen L, Li T, Guan L, Zhou Y, Li P. Flocculating activities of polysaccharides released from the marine mat-forming cyanobacteria Microcoleus and Lyngbya. Aquat Biol. 2011;11:243–8.CAS 
Article 

Google Scholar 
Wang L, Wang X, Wu H, Liu R. Overview on biological activities and molecular characteristics of sulfated polysaccharides from marine green algae in recent years. Marine Drugs. 2014;12:4984–5020.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hans N, Malik A, Naik S. Antiviral activity of sulfated polysaccharides from marine algae and its application in combating COVID-19: Mini review. Bioresour Technol Rep. 2021;13:100623.2020.PubMed 
Article 

Google Scholar 
Braissant O, Decho AW, Dupraz C, Glunk C, Przekop KM, Visscher PT. Exopolymeric substances of sulfate-reducing bacteria: Interactions with calcium at alkaline pH and implication for formation of carbonate minerals. Geobiology. 2007;5:401–11.CAS 
Article 

Google Scholar 
Barbeyron T, Brillet-Guéguen L, Carré W, Carrière C, Caron C, Czjzek M, et al. Matching the diversity of sulfated biomolecules: Creation of a classification database for sulfatases reflecting their substrate specificity. PLoS ONE. 2016;11:1–33.Article 

Google Scholar 
Allen MA, Goh F, Burns BP, Neilan BA. Bacterial, archaeal and eukaryotic diversity of smooth and pustular microbial mat communities in the hypersaline lagoon of Shark Bay. Geobiology. 2009;7:82–96.CAS 
PubMed 
Article 

Google Scholar 
Goh F, Allen MA, Leuko S, Kawaguchi T, Decho AW, Burns BP, et al. Determining the specific microbial populations and their spatial distribution within the stromatolite ecosystem of Shark Bay. ISME J. 2009;3:383–96.CAS 
PubMed 
Article 

Google Scholar 
Brody SS. New excited state of chlorophyll. Science. 1958;128:838–9.CAS 
PubMed 
Article 

Google Scholar 
Lamb JJ, Røkke G, Hohmann-Marriott MF. Chlorophyll fluorescence emission spectroscopy of oxygenic organisms at 77 K. Photosynthetica. 2018;56:105–24.CAS 
Article 

Google Scholar 
Hahn T, Schulz M, Stadtmüller R, Zayed A, Muffler K, Lang S, et al. Cationic dye for the specific determination of sulfated polysaccharides. Anal Lett. 2016;49:1948–62.CAS 
Article 

Google Scholar 
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Li D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31:1674–6.CAS 
PubMed 
Article 

Google Scholar 
Li D, Luo R, Liu CM, Leung CM, Ting HF, Sadakane K, et al. MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods. 2016;102:3–11.CAS 
PubMed 
Article 

Google Scholar 
Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 2015;3(e1165).Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Chaumeil P-A, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics. 2020;36:1925–7.CAS 

Google Scholar 
Huntemann M, Ivanova NN, Mavromatis K, James Tripp H, Paez-Espino D, Palaniappan K, et al. The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4). Standards in Genomic. Sciences. 2015;10:4–9.
Google Scholar 
Markowitz VM, Ivanova NN, Szeto E, Palaniappan K, Chu K, Dalevi D, et al. IMG/M: a data management and analysis system for metagenomes. Nucleic Acids Res. 2007;36:534–8.SUPPL.1Article 

Google Scholar 
Eren AM, Esen ÖC, Quince C, Vineis JH, Morrison HG, Sogin ML, et al. Anvi’o: an advanced analysis and visualization platform for ‘omics data. PeerJ. 2015;3:e1319.PubMed 
PubMed Central 
Article 

Google Scholar 
Campbell BJ, Yu L, Heidelberg JF, Kirchman DL. Activity of abundant and rare bacteria in a coastal ocean. Proc National Acad Sci USA 2011;108:12776–81.CAS 
Article 

Google Scholar 
Fukuda M, Hiraoka N, Akama TO, Fukuda MN. Carbohydrate-modifying sulfotransferases: Structure, function, and pathophysiology. J Biol Chem. 2001;276:47747–50.CAS 
PubMed 
Article 

Google Scholar 
Roeser D, Preusser-Kunze A, Schmidt B, Gasow K, Wittmann JG, Dierks T, et al. A general binding mechanism for all human sulfatases by the formylglycine-generating enzyme. Proc Natl Acad Sci USA 2006;103:81–6.CAS 
PubMed 
Article 

Google Scholar 
Genicot SM, Groisillier A, Rogniaux H, Meslet-Cladière L, Barbeyron T, Helbert W. Discovery of a novel iota carrageenan sulfatase isolated from the marine bacterium Pseudoalteromonas carrageenovora. Front Chem. 2014;2:1–15.CAS 
Article 

Google Scholar 
Almagro Armenteros JJ, Tsirigos KD, Sønderby CK, Petersen TN, Winther O, Brunak S, et al. SignalP 5.0 improves signal peptide predictions using deep neural networks. Nat Biotechnol. 2019;37:420–3.CAS 
PubMed 
Article 

Google Scholar 
Fernando IPS, Sanjeewa KKA, Samarakoon KW, Lee WW, Kim HS, Kim EA, et al. FTIR characterization and antioxidant activity of water soluble crude polysaccharides of Sri Lankan marine algae. Algae. 2017;32:75–86.CAS 
Article 

Google Scholar 
Papineau D, Walker JJ, Mojzsis SJ, Pace NR. Composition and structure of microbial communities from stromatolites of Hamelin Pool in Shark Bay, Western Australia. Appl Environ Microbiol. 2005;71:4822–32.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wong HL, Smith DL, Visscher PT, Burns BP. Niche differentiation of bacterial communities at a millimeter scale in Shark Bay microbial mats. Sci Rep. 2015;5:1–17. 15607
Google Scholar 
Pereira SB, Mota R, Vieira CP, Vieira J, Tamagnini P. Phylum-wide analysis of genes/proteins related to the last steps of assembly and export of extracellular polymeric substances (EPS) in cyanobacteria. Sci Rep. 2015;5:1–16.CAS 

Google Scholar 
Rossi F, De Philippis R. Role of cyanobacterial exopolysaccharides in phototrophic biofilms and in complex microbial mats. Life. 2015;5:1218–38.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
McCandless EL, Craigie JS. Sulfated polysaccharides in red and brown algae. Ann Rev Plant Physiol. 1979;30:41–53.CAS 
Article 

Google Scholar 
Usov AI, Bilan MI. Fucoidans-sulfated polysaccharides of brown algae. Russ Chem Rev. 2009;78:785–99.CAS 
Article 

Google Scholar 
Jiao G, Yu G, Zhang J, Ewart HS. Chemical structures and bioactivities of sulfated polysaccharides from marine algae. Mar Drugs. 2011;9:196–233.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Al Disi ZA, Zouari N, Dittrich M, Jaoua S, Al-Kuwari HAS, Bontognali TRR. Characterization of the extracellular polymeric substances (EPS) of Virgibacillus strains capable of mediating the formation of high Mg-calcite and protodolomite. Mar Chem. 2019;216:103693.CAS 
Article 

Google Scholar 
Diloreto ZA, Garg S, Bontognali TRR, Dittrich M. Modern dolomite formation caused by seasonal cycling of oxygenic phototrophs and anoxygenic phototrophs in a hypersaline sabkha. Sci Rep. 2021;11:1–13.Article 

Google Scholar 
Richert L, Golubic S, Le Guédès R, Ratiskol J, Payri C, Guezennec J. Characterization of exopolysaccharides produced by cyanobacteria isolated from Polynesian microbial mats. Curr Microbiol. 2005;51:379–84.CAS 
PubMed 
Article 

Google Scholar 
Raguénès G, Moppert X, Richert L, Ratiskol J, Payri C, Costa B, et al. A novel exopolymer-producing bacterium, Paracoccus zeaxanthinifaciens subsp. payriae, isolated from a “kopara” mat located in Rangiroa, an atoll of French Polynesia. Curr Microbiol. 2004;49:145–51.PubMed 
Article 

Google Scholar 
Moppert X, Le Costaouec T, Raguenes G, Courtois A, Simon-Colin C, Crassous P, et al. Investigations into the uptake of copper, iron and selenium by a highly sulphated bacterial exopolysaccharide isolated from microbial mats. J Ind Microbiol Biotechnol. 2009;36:599–604.CAS 
PubMed 
Article 

Google Scholar 
González-Hourcade M, del Campo EM, Braga MR, Salgado A, Casano LM. Disentangling the role of extracellular polysaccharides in desiccation tolerance in lichen-forming microalgae. First evidence of sulfated polysaccharides and ancient sulfotransferase genes. Environ Microbiol. 2020;22:3096–111.PubMed 
Article 

Google Scholar 
De Souza MCR, Marques CT, Dore CMG, Da Silva FRF, Rocha HAO, Leite EL. Antioxidant activities of sulfated polysaccharides from brown and red seaweeds. J Appl Phycol. 2007;19:153–60.Article 

Google Scholar 
Jayawardena TU, Wang L, Asanka Sanjeewa KK, In Kang S, Lee JS, Jeon YJ. Antioxidant potential of sulfated polysaccharides from Padina boryana; protective effect against oxidative stress in in vitro and in vivo zebrafish model. Mar Drugs. 2020;18:1–14.
Google Scholar 
Baba M, Snoeck R, Pauwels R, De Clercq E. Sulfated polysaccharides are potent and selective inhibitors of various enveloped viruses, including herpes simplex virus, cytomegalovirus, vesicular stomatitis virus, and human immunodeficiency virus. Antimicrob Agents Chemother. 1988;32:1742–5.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ghosh T, Chattopadhyay K, Marschall M, Karmakar P, Mandal P, Ray B. Focus on antivirally active sulfated polysaccharides: From structure-activity analysis to clinical evaluation. Glycobiology. 2009;19:2–15.CAS 
PubMed 
Article 

Google Scholar 
Bakunina IY, Nedashkovskaya OI, Alekseeva SA, Ivanova EP, Romanenko LA, Gorshkova NM, et al. Degradation of fucoidan by the marine proteobacterium Pseudoalteromonas citrea. Mikrobiologiya. 2002;71:49–55.
Google Scholar 
Descamps V, Colin S, Lahaye M, Jam M, Richard C, Potin P, et al. Isolation and culture of a marine bacterium degrading the sulfated fucans from marine brown algae. Mar Biotechnol. 2006;8:27–39.CAS 
Article 

Google Scholar 
Mann AJ, Hahnke RL, Huang S, Werner J, Xing P, Barbeyron T, et al. The genome of the alga-associated marine flavobacterium Formosa agariphila KMM 3901T reveals a broad potential for degradation of algal polysaccharides. Appl Environ Microbiol. 2013;79:6813–22.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hehemann JH, Boraston AB, Czjzek M. A sweet new wave: Structures and mechanisms of enzymes that digest polysaccharides from marine algae. Curr Opin Struct Biol. 2014;28:77–86.CAS 
PubMed 
Article 

Google Scholar 
Thomas F, Bordron P, Eveillard D, Michel G. Gene expression analysis of Zobellia galactanivorans during the degradation of algal polysaccharides reveals both substrate-specific and shared transcriptome-wide responses. Front Microbiol. 2017;8:1–14.CAS 
Article 

Google Scholar 
Martinez-Garcia M, Brazel DM, Swan BK, Arnosti C, Chain PSG, Reitenga KG, et al. Capturing single cell genomes of active polysaccharide degraders: an unexpected contribution of verrucomicrobia. PLoS ONE. 2012;7:1–11.
Google Scholar 
Sichert A, Corzett CH, Schechter MS, Unfried F, Markert S, Becher D, et al. Verrucomicrobia use hundreds of enzymes to digest the algal polysaccharide fucoidan. Nat Microbiol. 2020;5:1026–39.CAS 
PubMed 
Article 

Google Scholar 
Bengtsson MM, Øvreås L. Planctomycetes dominate biofilms on surfaces of the kelp Laminaria hyperborea. BMC Microbiol. 2010;10:1–12.Article 

Google Scholar 
Kim JW, Brawley SH, Prochnik S, Chovatia M, Grimwood J, Jenkins J, et al. Genome analysis of Planctomycetes inhabiting blades of the red alga Porphyra umbilicalis. PLoS ONE. 2016;11:1–22.
Google Scholar 
Glöckner FO, Kube M, Bauer M, Teeling H, Lombardot T, Ludwig W, et al. Complete genome sequence of the marine planctomycete Pirellula sp. strain 1. Proc Natl Acad Sci USA 2003;100:8298–303.PubMed 
PubMed Central 
Article 

Google Scholar 
Bayer K, Jahn MT, Slaby BM, Moitinho-Silva L, Hentschel U. Marine sponges as Chloroflexi hot spots: Genomic insights and high-resolution visualization of an abundant and diverse symbiotic clade. mSystems. 2018;3:1–19.Article 

Google Scholar 
Robbins SJ, Song W, Engelberts JP, Glasl B, Slaby BM, Boyd J, et al. A genomic view of the microbiome of coral reef demosponges. ISME J. 2021;15:1641–54.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Salyers AA, O’Brien M. Cellular location of enzymes involved in chondroitin sulfate breakdown by Bacteroides thetaiotaomicron. J Bacteriol. 1980;143:772–80.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Campbell MA, Grice K, Visscher PT, Morris T, Wong HL, White RA, et al. Functional gene expression in Shark Bay hypersaline microbial mats: adaptive responses. Front Microbiol. 2020;11:1–16.Article 

Google Scholar 
Van Vliet DM, Ayudthaya SPN, Diop S, Villanueva L, Stams AJM, Sánchez-Andrea I. Anaerobic degradation of sulfated polysaccharides by two novel Kiritimatiellales strains isolated from black sea sediment. Front Microbiol. 2019;10:1–16.Article 

Google Scholar 
Bäumgen M, Dutschei T, Bornscheuer UT. Marine polysaccharides: occurrence, enzymatic degradation and utilization. ChemBioChem. 2021;22:2247–56.PubMed 
PubMed Central 
Article 

Google Scholar 
Helbert W. Marine polysaccharide sulfatases. Front Mar Sci. 2017;4:1–10.Article 

Google Scholar 
Ficko-Blean E, Préchoux A, Thomas F, Rochat T, Larocque R, Zhu Y, et al. Carrageenan catabolism is encoded by a complex regulon in marine heterotrophic bacteria. Nat Commun. 2017;8:1–7.CAS 
Article 

Google Scholar 
McLean MW, Williamson FB. Glycosulphatase from Pseudomonas carrageenovora, purification and some properties. Eur J Biochem. 1979;101:497–505.CAS 
PubMed 
Article 

Google Scholar 
Mclean MW, Williamson FB Neocarratetraose 4-O-Monosulphate B-Hydrolase from Pseudomonas carrageenovora. 1981;456:447–56.Suarez-Gonzalez P, Reitner J. Ooids forming in situ within microbial mats (Kiritimati atoll, central Pacific). PalZ. 2021;95:809–21.Article 

Google Scholar 
Arp G, Helms G, Karlinska K, Schumann G, Reimer A, Reitner J, et al. Photosynthesis versus exopolymer degradation in the formation of microbialites on the atoll of Kiritimati, Republic of Kiribati, central Pacific. Geomicrobiol J. 2012;29:29–65.CAS 
Article 

Google Scholar  More

New wave: Petar Puškarić used yeast isolated from the Adriatic Sea to make a beer that he named Morski Kukumar (Sea Cucumber).Credit: Marin Ordulj

Petar Puškarić is an engineer, ecologist and head of beer production at LAB Split, a craft brewery in Split, Croatia. He graduated with a master’s degree from the department of marine studies at the University of Split last year, after successfully making a beer from Candida famata, a yeast that can be isolated from sea water. He now hopes to brew this sea-yeast beer commercially. He speaks to Nature about some of the challenges in going from dissertation to commercialization.How did your marine-yeast beer come about?I’ve had an interest in brewing beer for a long time, and started brewing as a hobby when I was a student. During a marine-microbiology lecture as part of my undergraduate degree in ecology, my mentor Marin Ordulj and I started to talk about marine yeasts, and one question led to another. We wondered whether sea yeast could ferment beer.We researched the literature and could not find anyone who had made a beer with a yeast isolated from the sea. Perhaps we could become the first to do so? The idea stayed with me for a few years as I continued my degree and moved on to my master’s course. When I came to choose my dissertation topic, I decided it was time to put the idea to the test. I discussed things with Marin, and he agreed to help me plan an experiment. By then, I was working part-time at the LAB Split brewery, so I had some brewing experience to bring to our investigations.Our first task was to isolate yeasts from the sea. We then tested the fermentation abilities of the isolated yeasts and grew cultures from the most promising samples. Finally, we used those cultures to brew beer.How did you manage your time between brewing and your degree?I wasn’t overorganized, but I always made sure to be disciplined and to do whatever was needed as tasks came along. I kept active outside work as well, continuing to play as a mandolinist in an orchestra, for example.I didn’t think too strictly about my career, and made time to do the things I enjoyed. I’d recommend that other students also try to enjoy life and spend as much time as possible with friends. After all, life is not just about building a career. I was lucky in proposing a graduate topic that I found interesting and that my mentor liked: that helped me through the duller and more difficult moments.What was the hardest part of the process?The biggest problem was created by marine bacteria, which would outgrow the yeast colonies and thus make the isolation of yeast more difficult. We tackled this problem by using selective nutrient media, which inhibit the growth of bacteria. Eventually, this resulted in pure yeast cultures.What did the beer taste like?The first beer tasting after all that research, thinking and anticipation was really exciting. We noted clove and fruit aromas and a slightly sour tone. It didn’t carry the taste of the sea; the flavour was closest to that of sour beer.What impact do you hope this work will have?The beer is an exciting product of my graduate work, but I also hope that my thesis will encourage others to explore in more detail the yeasts in the Adriatic Sea, and to realize their potential in ecology, medicine and nutrition. Split is on the Adriatic coast and I like the idea that we’re contributing in some small way to protecting that coastline.Sea Cucumber, as we’ve named the beer, might not help much directly in that regard, but I do hope that it could raise awareness about how many useful things there are in the sea.Are you planning on taking the sea yeast further in your career?Any experience in microbiology helps in the food industry. Sea yeast might turn out to be useful in brewing, but we have to consider the finances and infrastructure we’d need to support its use commercially. For now, we’re concentrating on brewing more standard beers. In the future, I hope to brew some of my own recipes, whether Sea Cucumber or something else. I would definitely like to combine brewing with the search for new yeasts that can be used not only in beer making, but in other industries as well. More

Komarek, A. M., Thierfelder, C. & Steward, P. R. Conservation agriculture improves adaptive capacity of cropping systems to climate stress in Malawi. Agric. Syst. 190, 103117 (2021).Article 

Google Scholar 
Charles, H., Godfray, H. & Garnett, T. Food security and sustainable intensification. Philos. Trans. R. Soc. B Biol. Sci. 369, 1 (2014).Challinor, A. J. et al. A meta-analysis of crop yield under climate change and adaptation. Nat. Clim. Chang. 4, 287–291 (2014).Article 
ADS 

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

Google Scholar 
Savari, M. & Shokati Amghani, M. SWOT-FAHP-TOWS analysis for adaptation strategies development among small-scale farmers in drought conditions. Int. J. Disaster Risk Reduct. 67, 1 (2022).
Google Scholar 
Savari, M. & Shokati Amghani, M. Factors influencing farmers’ adaptation strategies in confronting the drought in Iran. Environ. Dev. Sustain. 23, 4949–4972 (2020).Article 

Google Scholar 
Savari, M., Eskandari Damaneh, H. & Eskandari Damaneh, H. Drought vulnerability assessment: Solution for risk alleviation and drought management among Iranian farmers. Int. J. Disaster Risk Reduct. 67, (2022).Savari, M. & Zhoolideh, M. The role of climate change adaptation of small-scale farmers on the households food security level in the west of Iran. Dev. Pract. 31, 650–664 (2021).Article 

Google Scholar 
Eder, A., Salhofer, K. & Scheichel, E. Land tenure, soil conservation, and farm performance: An eco-efficiency analysis of Austrian crop farms. Ecol. Econ. 180, 106861 (2021).Article 

Google Scholar 
Keesstra, S. et al. Soil-related sustainable development goals: Four concepts to make land degradation neutrality and restoration work. 7, 133 (2018).Savari, M., Naghibeiranvand, F. & Asadi, Z. Modeling environmentally responsible behaviors among rural women in the forested regions in Iran. Glob. Ecol. Conserv. 35, e02102 (2022).Article 

Google Scholar 
Savari, M., Damaneh, H. E. & Damaneh, H. E. Factors involved in the degradation of mangrove forests in Iran: A mixed study for the management of this ecosystem. J. Nat. Conserv. 66, 1 (2022).Article 

Google Scholar 
Bhan, S. & Behera, U. K. Conservation agriculture in India—Problems, prospects and policy issues. Int. Soil Water Conserv. Res. 2, 1–12 (2014).Article 

Google Scholar 
Savari, M., Ebrahimi-Maymand, R. & Mohammadi-Kanigolzar, F. The factors influencing the application of organic farming operations by farmers in iran. Agris On-line Pap. Econ. Informatics 5, 179–187 (2013).
Google Scholar 
FAO. Conservation agriculture in Central Asia: Status, Policy, Institutional Support, and Strategic Framework for its Promotion. 57 pp (2013).Eskandari Damaneh, H., Khosravi, H., Habashi, K., Eskandari Damaneh, H. & Tiefenbacher, J. P. The impact of land use and land cover changes on soil erosion in western Iran. Nat. Hazards 110, 2185–2205 (2022).Dougill, A. J. et al. Mainstreaming conservation agriculture in Malawi: Knowledge gaps and institutional barriers. J. Environ. Manage. 195, 25–34 (2017).PubMed 
Article 

Google Scholar 
Pannell, D. J., Llewellyn, R. S. & Corbeels, M. The farm-level economics of conservation agriculture for resource-poor farmers. Agric. Ecosyst. Environ. 187, 52–64 (2014).Article 

Google Scholar 
Bajwa, A. A. Sustainable weed management in conservation agriculture. Crop Prot. 65, 105–113 (2014).Article 

Google Scholar 
Lalani, B., Dorward, P., Holloway, G. & Wauters, E. Smallholder farmers’ motivations for using Conservation Agriculture and the roles of yield, labour and soil fertility in decision making. Agric. Syst. 146, 80–90 (2016).Article 

Google Scholar 
Faridi, A. A., Kavoosi-Kalashami, M. & Bilali, H. E. Attitude components affecting adoption of soil and water conservation measures by paddy farmers in Rasht County. Northern Iran. Land Use Policy 99, 1 (2020).
Google Scholar 
Thierfelder, C. et al. Conservation agriculture in Southern Africa: Advances in knowledge. Renew. Agric. Food Syst. 30, 328–348 (2015).Article 

Google Scholar 
Eskandari Damaneh, H. et al. Testing possible scenario-based responses of vegetation under expected climatic changes in Khuzestan Province https://doi.org/10.1177/1178622121101333214 (2021).Article 

Google Scholar 
Ataei, P., Sadighi, H., Chizari, M. & Abbasi, E. Discriminant analysis of the participated farmers’ characteristics in the conservation agriculture project based on the learning transfer system. Environ. Dev. Sustain. 23, 291–307 (2021).Article 

Google Scholar 
Izadi, N., Ataei, P., Karimi-Gougheri, H. & Norouzi, A. Environmental impact assessment of construction of water pumping station in Bacheh Bazar Plain: A case from Iran. EQA – Int. J. Environ. Qual. 35, 13–32 (2019).
Google Scholar 
Mesgaran, M. B., Madani, K., Hashemi, H. & Azadi, P. Iran’s Land Suitability for Agriculture. Sci. Rep. 7, 1–12 (2017).CAS 
Article 

Google Scholar 
Jia, L. et al. Regional differences in the soil and water conservation efficiency of conservation tillage in China. CATENA 175, 18–26 (2019).Article 

Google Scholar 
Kuyvenhoven, A., Ruben, R. & Pender, J. Development strategies for less-favoured areas. Food Policy 29, 295–302 (2004).Article 

Google Scholar 
Hoque, R. & Sorwar, G. Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. Int. J. Med. Inform. 101, 75–84 (2017).PubMed 
Article 

Google Scholar 
Gupta, K. P., Manrai, R. & Goel, U. Factors influencing adoption of payments banks by Indian customers: extending UTAUT with perceived credibility. J. Asia Bus. Stud. 13, 173–195 (2019).Article 

Google Scholar 
Solís, D., Bravo-Ureta, B. E. & Quiroga, R. E. Technical efficiency among peasant farmers participating in natural resource management programmes in Central America. J. Agric. Econ. 60, 202–219 (2009).Article 

Google Scholar 
Amsalu, A. & de Graaff, J. Determinants of adoption and continued use of stone terraces for soil and water conservation in an Ethiopian highland watershed. Ecol. Econ. 61, 294–302 (2007).Article 

Google Scholar 
Solís, D. & Bravo-Ureta, B. E. Economic and Financial Sustainability of Private Agricultural Extension in El Salvador. https://doi.org/10.1300/J064v26n02_0726,81-102 (2008).Article 

Google Scholar 
Bagheri, A. & Teymouri, A. Farmers’ intended and actual adoption of soil and water conservation practices. Agric. Water Manag. 259, 1 (2022).Article 

Google Scholar 
Rodrigo-Comino, J. et al. The potential of straw mulch as a nature-based solution for soil erosion in olive plantation treated with glyphosate: A biophysical and socioeconomic assessment. L. Degrad. Dev. 31, 1877–1889 (2020).Article 

Google Scholar 
Klik, A. & Rosner, J. Long-term experience with conservation tillage practices in Austria: Impacts on soil erosion processes. Soil Tillage Res. 203, 1 (2020).Article 

Google Scholar 
Singh, R. K., Singh, A. & Pandey, C. B. Agro-biodiversity in rice–wheat-based agroecosystems of eastern Uttar Pradesh, India: implications for conservation and sustainable management. 21, 46–59. https://doi.org/10.1080/13504509.2013.869272 (2014).Bijani, M., Ghazani, E., Valizadeh, N. & Fallah Haghighi, N. Pro-environmental analysis of farmers’ concerns and behaviors towards soil conservation in central district of Sari County, Iran. Int. Soil Water Conserv. Res. 5, 43–49 (2017).Raeisi, A., Bijani, M. & Chizari, M. The mediating role of environmental emotions in transition from knowledge to sustainable use of groundwater resources in Iran’s agriculture. Int. Soil Water Conserv. Res. 6, 143–152 (2018).Article 

Google Scholar 
Valizadeh, N., Bijani, M., Hayati, D. & Fallah Haghighi, N. Social-cognitive conceptualization of Iranian farmers’ water conservation behavior. Hydrogeol. J. 27, 1131–1142 (2019).Kassie, M., Jaleta, M., Shiferaw, B., Mmbando, F. & Mekuria, M. Adoption of interrelated sustainable agricultural practices in smallholder systems: Evidence from rural Tanzania. Technol. Forecast. Soc. Change 80, 525–540 (2013).Article 

Google Scholar 
Teklewold, H., Kassie, M. & Shiferaw, B. Adoption of Multiple Sustainable Agricultural Practices in Rural Ethiopia. J. Agric. Econ. 64, 597–623 (2013).Article 

Google Scholar 
Savari, M., Zhoolideh, M. & Khosravipour, B. Explaining pro-environmental behavior of farmers: A case of rural Iran. Curr. Psychol. https://doi.org/10.1007/S12144-021-02093-9 (2021).Article 

Google Scholar 
Tey, Y. S. & Brindal, M. Factors influencing the adoption of precision agricultural technologies: A review for policy implications. Precis. Agric. 13, 713–730 (2012).Article 

Google Scholar 
Savari, M., Abdeshahi, A., Gharechaee, H. & Nasrollahian, O. Explaining farmers’ response to water crisis through theory of the norm activation model: Evidence from Iran. Int. J. Disaster Risk Reduct. 60, 1 (2021).Article 

Google Scholar 
Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211 (1991).Article 

Google Scholar 
Davis, F. D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. Manag. Inf. Syst. 13, 319–339 (1989).Article 

Google Scholar 
Rogers W., R. Cognitive and physiological processes in fear appeals and attitude change: a revised theory of protection motivation. in Social Psychophysiology: A Sourcebook 153–177 (1983).Bandura, A. Health promotion by social cognitive means. Heal. Educ. Behav. 31, 143–164 (2004).Article 

Google Scholar 
Ratten, V. & Ratten, H. Technological innovations and m-Commerce applications. Int. J. Innov. Technol. Manag. 4, 1–14 (2007).Article 

Google Scholar 
Shahangian, S. A., Tabesh, M. & Yazdanpanah, M. Psychosocial determinants of household adoption of water-efficiency behaviors in Tehran capital, Iran: Application of the social cognitive theory. Urban Clim. 39, 1009 (2021).Article 

Google Scholar 
Yazdanpanah, M., Feyzabad, F. R., Forouzani, M., Mohammadzadeh, S. & Burton, R. J. F. Predicting farmers’ water conservation goals and behavior in Iran: A test of social cognitive theory. Land Use Policy 47, 401–407 (2015).Article 

Google Scholar 
Rahimi-Feyzabad, F., Yazdanpanah, M., Burton, R. J. F., Forouzani, M. & Mohammadzadeh, S. The use of a bourdieusian “capitals” model for understanding farmer’s irrigation behavior in Iran. J. Hydrol. 591, 1 (2020).Article 

Google Scholar 
Schwarzer, R. & Luszczynska, A. Predicting and changing health behavior. Heal. action Process approach 252–278 (2015).Gothe, N. P. Correlates of physical activity in urban African American adults and older adults: Testing the social cognitive theory. Ann. Behav. Med. 52, 743–751 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Murphy, D. A., Stein, J. A., Schlenger, W. & Maibach, E. Conceptualizing the multidimensional nature of self-efficacy: Assessment of situational context and level of behavioral challenge to maintain safer sex. Heal. Psychol. 20, 281–290 (2001).CAS 
Article 

Google Scholar 
Valois, R. F., Zullig, K. J. & Revels, A. A. Aggressive and violent behavior and emotional self-efficacy: Is there a relationship for adolescents?. J. Sch. Health 87, 269–277 (2017).PubMed 
Article 

Google Scholar 
Ramirez, E., Kulinna, P. H. & Cothran, D. Constructs of physical activity behaviour in children: The usefulness of Social Cognitive Theory. Psychol. Sport Exerc. 13, 303–310 (2012).Article 

Google Scholar 
Schunk, D. H. & DiBenedetto, M. K. Motivation and social cognitive theory. Contemp. Educ. Psychol. 60, 101832 (2020).Article 

Google Scholar 
Raskauskas, J., Rubiano, S., Offen, I. & Wayland, A. K. Do social self-efficacy and self-esteem moderate the relationship between peer victimization and academic performance?. Soc. Psychol. Educ. 18, 297–314 (2015).Article 

Google Scholar 
Wang, S., Hung, K. & Huang, W.-J. Motivations for entrepreneurship in the tourism and hospitality sector: A social cognitive theory perspective. https://doi.org/10.1016/j.ijhm.2018.11.018 (2018).Article 

Google Scholar 
Zimmerman, B. J. Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. Am. Educ. Res. J. 45, 166–183 (2008).Article 
ADS 

Google Scholar 
Steese, S. et al. Understanding Girls’ Circle as an intervention on perceived social support, body image, self-efficacy, locus of control, and self-esteem. Adolescence 41, 55–74 (2006).PubMed 

Google Scholar 
Komendantova, N. et al. Studying young people’ views on deployment of renewable energy sources in Iran through the lenses of Social Cognitive Theory. AIMS Energy 6, 216–228 (2018).Article 

Google Scholar 
Burton, R. J. F. Reconceptualising the ‘behavioural approach’ in agricultural studies: A socio-psychological perspective. J. Rural Stud. 20, 359–371 (2004).Article 

Google Scholar 
Plotnikoff, R. C., Lippke, S., Courneya, K. S., Birkett, N. & Sigal, R. J. Physical activity and social cognitive theory: A test in a population sample of adults with type 1 or type 2 diabetes. Appl. Psychol. AN Int. Rev. 57, 628–643 (2008).Article 

Google Scholar 
Thøgersen, J. & Grønhøj, A. Electricity saving in households-A social cognitive approach. Energy Policy 38, 7732–7743 (2010).Article 

Google Scholar 
Kaye, S. A., Lewis, I., Forward, S. & Delhomme, P. A priori acceptance of highly automated cars in Australia, France, and Sweden: A theoretically-informed investigation guided by the TPB and UTAUT. Accid. Anal. Prev. 137, 5441 (2020).Article 

Google Scholar 
Savari, M. & Gharechaee, H. Application of the extended theory of planned behavior to predict Iranian farmers’ intention for safe use of chemical fertilizers. J. Clean. Prod. 263, 1 (2020).Article 
CAS 

Google Scholar 
Koohizadeh, M., Mohammad Akhoond-Ali, A. & Arsham, A. The Effect of Soil Moisture Levels on the Threshold Velocity of Wind Erosion in Dust Centers of South and Southeast of Khuzestan Province-Ahwaz. Iran. J. Soil Water Res. 52, 869–885 (2021).Keshavarz, M. & Karami, E. Farmers’ decision-making process under drought. J. Arid Environ. 108, 43–56 (2014).Article 
ADS 

Google Scholar 
Wu, J. Urban sustainability: an inevitable goal of landscape research. Landsc. Ecol. 25, 1–4 (2009).Article 

Google Scholar 
Ullman, J. B. & Bentler, P. M. Structural equation modeling. Handb. Psychol. Second Ed. https://doi.org/10.1002/9781118133880.HOP202023 (2012).Article 

Google Scholar 
Serda, M. Synteza i aktywność biologiczna nowych analogów tiosemikarbazonowych chelatorów żelaza. Uniw. śląski 343–354 (2013).Khoshmaram, M., Shiri, N., Shinnar, R. S. & Savari, M. Environmental support and entrepreneurial behavior among Iranian farmers: The mediating roles of social and human capital. https://doi.org/10.1111/jsbm.1250158,1064-1088 (2020).Article 

Google Scholar 
Kim, T. K. T test as a parametric statistic. Korean J. Anesthesiol. 68, 540–546 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
-The T-test. Source: Adapted from Semenick, (96), p. 37. | Download Scientific Diagram. https://www.researchgate.net/figure/The-T-test-Source-Adapted-from-Semenick-96-p-37_fig2_274192999.Yadav, R. & Pathak, G. S. Intention to purchase organic food among young consumers: Evidences from a developing nation. Appetite 96, 122–128 (2016).PubMed 
Article 

Google Scholar 
Akey, J. E., Rintamaki, L. S. & Kane, T. L. Health Belief Model deterrents of social support seeking among people coping with eating disorders. J. Affect. Disord. 145, 246–252 (2013).PubMed 
Article 

Google Scholar 
Ahmmadi, P., Rahimian, M. & Movahed, R. G. Theory of planned behavior to predict consumer behavior in using products irrigated with purified wastewater in Iran consumer. J. Clean. Prod. 296, 6359 (2021).Article 

Google Scholar 
Bagheri, A., Bondori, A., Allahyari, M. S. & Damalas, C. A. Modeling farmers’ intention to use pesticides: An expanded version of the theory of planned behavior. J. Environ. Manage. 248, 1 (2019).Article 

Google Scholar 
Sarstedt, M., Ringle, C. M. & Hair, J. F. Partial least squares structural equation modeling. Handb. Mark. Res. 1, 1–47. https://doi.org/10.1007/978-3-319-05542-8_15-2 (2021).Article 

Google Scholar 
Mogaka, B. O., Bett, H. K. & Nganga, S. K. Socioeconomic factors influencing the choice of climate-smart soil practices among farmers in western Kenya. J. Agric. Food Res. 5, 1 (2021).
Google Scholar 
Afshan, S., Sharif, A., Waseem, N. & Farooghi, R. Internet banking in Pakistan: An extended technology acceptance perspective. Int. J. Bus. Inf. Syst. 27, 383–410 (2018).
Google Scholar 
Pai, F. Y. & Huang, K. I. Applying the Technology Acceptance Model to the introduction of healthcare information systems. Technol. Forecast. Soc. Change 78, 650–660 (2011).Article 

Google Scholar 
Venkatesh, V., Thong, J. Y. L. & Xu, X. Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Q. Manag. Inf. Syst. 36, 157–178 (2012).Article 

Google Scholar 
Nguru, W. M., Gachene, C. K., Onyango, C. M., Nganga, S. K. & Girvetz, E. H. Factors constraining the adoption of soil organic carbon enhancing technologies among small-scale farmers in Ethiopia. Heliyon 7, 1 (2021).Article 

Google Scholar 
Warner, L. A. Who conserves and who approves? Predicting water conservation intentions in urban landscapes with referent groups beyond the traditional ‘important others’. Urban For. Urban Green. 60, 1 (2021).Article 

Google Scholar  More

Alvarez-Filip, L., Dulvy, N. K., Gill, J. A., Côté, I. M. & Watkinson, A. R. Flattening of Caribbean coral reefs: region-wide declines in architectural complexity. Proc. R. Soc. B: Biol. Sci. 276, 3019–3025 (2009).Article 

Google Scholar 
Hughes, T. P. et al. Global warming transforms coral reef assemblages. Nature 556, 492 (2018).CAS 
PubMed 
Article 

Google Scholar 
Drury, C. & Lirman, D. Genotype by environment interactions in coral bleaching. Proc. R. Soc. B Biol. Sci., https://doi.org/10.1098/rspb.2021.0177 (2021).Kenkel, C. D., Almanza, A. T. & Matz, M. V. Fine-scale environmental specialization of reef-building corals might be limiting reef recovery in the Florida Keys. Ecology 96, 3197–3212 (2015).PubMed 
Article 

Google Scholar 
Howells, E. J., Abrego, D., Meyer, E., Kirk, N. L. & Burt, J. A. Host adaptation and unexpected symbiont partners enable reef‐building corals to tolerate extreme temperatures. Glob. Change Biol. 22, 2702–2714 (2016).Article 

Google Scholar 
Thomas, L. et al. Mechanisms of thermal tolerance in reef-building corals across a fine-grained environmental mosaic: lessons from Ofu, American Samoa. Front. Mar. Sci., https://doi.org/10.3389/fmars.2017.00434 (2018).Thomas, L., López, E. H., Morikawa, M. K. & Palumbi, S. R. Transcriptomic resilience, symbiont shuffling, and vulnerability to recurrent bleaching in reef‐building corals. Mol. Ecol. 28, 3371–3382 (2019).PubMed 
Article 

Google Scholar 
Barshis, D. J. et al. Genomic basis for coral resilience to climate change. Proc. Natl Acad. Sci. USA 110, 1387–1392 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Guest, J. R. et al. Contrasting patterns of coral bleaching susceptibility in 2010 suggest an adaptive response to thermal stress. PLoS ONE 7, e33353 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Matz, M. V., Treml, E. A. & Haller, B. C. Estimating the potential for coral adaptation to global warming across the Indo‐West Pacific. Glob. Chang. Biol. 26, 3473–3481 (2020).Bay, R. A., Rose, N. H., Logan, C. A. & Palumbi, S. R. Genomic models predict successful coral adaptation if future ocean warming rates are reduced. Sci. Adv. 3, e1701413 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Quigley, K. M., Bay, L. K. & van Oppen, M. J. Genome‐wide SNP analysis reveals an increase in adaptive genetic variation through selective breeding of coral. Mol. Ecol. 29, 2176–2188 (2020).Howells, E. J. et al. Enhancing the heat tolerance of reef-building corals to future warming. Sci. Adv. 7, eabg6070 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
LaJeunesse, T. C. et al. Systematic revision of symbiodiniaceae highlights the antiquity and diversity of coral endosymbionts. Curr. Biol. 28, 2570–2580 (2018).CAS 
PubMed 
Article 

Google Scholar 
Rowan, R. Coral bleaching: thermal adaptation in reef coral symbionts. Nature 430, 742 (2004).CAS 
PubMed 
Article 

Google Scholar 
Sampayo, E. M., Ridgway, T., Bongaerts, P. & Hoegh-Guldberg, O. Bleaching susceptibility and mortality of corals are determined by fine-scale differences in symbiont type. Proc. Natl Acad. Sci. USA 105, 10444–10449 (2008).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Maire, J. et al. Intracellular bacteria are common and taxonomically diverse in cultured and in hospite algal endosymbionts of coral reefs. ISME J., 15, 2028–2042 (2021).Ziegler, M., Seneca, F. O., Yum, L. K., Palumbi, S. R. & Voolstra, C. R. Bacterial community dynamics are linked to patterns of coral heat tolerance. Nat. Commun. 8, 14213 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
van Oppen, M. J. & Blackall, L. L. Coral microbiome dynamics, functions and design in a changing world. Nat. Rev. Microbiol. 17, 557–567 (2019).PubMed 
Article 
CAS 

Google Scholar 
Fuller, Z. L. et al. Population genetics of the coral Acropora millepora: Toward genomic prediction of bleaching. Science 369 (2020).Dixon, G. B. et al. Genomic determinants of coral heat tolerance across latitudes. Science 348, 1460–1462 (2015).CAS 
PubMed 
Article 

Google Scholar 
Jin, Y. K. et al. Genetic markers for antioxidant capacity in a reef-building coral. Sci. Adv. 2, e1500842 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Cooke, I. et al. Genomic signatures in the coral holobiont reveal host adaptations driven by Holocene climate change and reef specific symbionts. Sci. Adv. 6, eabc6318 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Bay, R. A. & Palumbi, S. R. Multilocus adaptation associated with heat resistance in reef-building corals. Curr. Biol. 24, 2952–2956 (2014).CAS 
PubMed 
Article 

Google Scholar 
Drury, C. Resilience in reef-building corals: the ecological and evolutionary importance of the host response to thermal stress. Mol. Ecol. 00, 1–18 (2019).CAS 

Google Scholar 
Quigley, K. M., Willis, B. L. & Bay, L. K. Heritability of the Symbiodinium community in vertically-and horizontally-transmitting broadcast spawning corals. Sci. Rep. 7, 8219 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Van Hooidonk, R., Maynard, J. & Planes, S. Temporary refugia for coral reefs in a warming world. Nat. Clim. Change 3, 508 (2013).Article 
CAS 

Google Scholar 
Quigley, K. M., Warner, P. A., Bay, L. K. & Willis, B. L. Unexpected mixed-mode transmission and moderate genetic regulation of Symbiodinium communities in a brooding coral. Heredity, 121, 524–536 (2018).Cunning, R., Ritson-Williams, R. & Gates, R. D. Patterns of bleaching and recovery of Montipora capitata in Kāne’ohe Bay, Hawai’i, USA. Mar. Ecol. Prog. Ser. 551, 131–139 (2016).CAS 
Article 

Google Scholar 
Dilworth, J., Caruso, C., Kahkejian, V. A., Baker, A. C. & Drury, C. Host genotype and stable differences in algal symbiont communities explain patterns of thermal stress response of Montipora capitata following thermal pre-exposure and across multiple bleaching events. Coral Reefs, https://doi.org/10.1007/s00338-020-02024-3 (2020).Rocha de Souza, M. et al. Community composition of coral-associated Symbiodiniaceae is driven by fine-scale environmental gradients. bioRxiv https://doi.org/10.1101/2021.11.10.468165 (2021).Innis, T., Cunning, R., Ritson-Williams, R., Wall, C. & Gates, R. Coral color and depth drive symbiosis ecology of Montipora capitata in Kāne’ohe Bay, O’ahu, Hawai’i. Coral Reefs 37, 423–430 (2018).Article 

Google Scholar 
Shore-Maggio, A., Runyon, C. M., Ushijima, B., Aeby, G. S. & Callahan, S. M. Differences in bacterial community structure in two color morphs of the Hawaiian reef coral Montipora capitata. Appl. Environ. Microbiol. 81, 7312–7318 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Roach, T. N., Dilworth, J., Jones, A. D., Quinn, R. A. & Drury, C. Metabolomic signatures of coral bleaching history. Nat. Ecol. Evol., 5, 495–503 (2021).Baird, A. H., Guest, J. R. & Willis, B. L. Systematic and biogeographical patterns in the reproductive biology of scleractinian corals. Annu. Rev. Ecol., Evolution, Syst. 40, 551–571 (2009).Article 

Google Scholar 
Caruso, C. et al. Genetic patterns in Montipora capitata across an environmental mosaic in Kāne’ohe Bay. bioRxiv https://doi.org/10.1101/2021.10.07.463582 (2021).Rose, N. H., Bay, R. A., Morikawa, M. K. & Palumbi, S. R. Polygenic evolution drives species divergence and climate adaptation in corals. Evolution 72, 82–94 (2017).PubMed 
Article 

Google Scholar 
Rose, N. H. et al. Genomic analysis of distinct bleaching tolerances among cryptic coral species. Proc. R. Soc. B 288, 20210678 (2021).PubMed 
Article 

Google Scholar 
Forsman, Z. H. et al. Ecomorph or endangered coral? DNA and microstructure reveal Hawaiian species complexes: Montipora dilatata/flabellata/turgescens & M. patula/verrilli. PLoS ONE 5, e15021 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Dixon, G., Abbott, E. & Matz, M. Meta‐analysis of the coral environmental stress response: Acropora corals show opposing responses depending on stress intensity. Mol. Ecol. 29, 2855–2870 (2020).CAS 
PubMed 
Article 

Google Scholar 
Lim, S., Kim, D. G. & Kim, S. ERK-dependent phosphorylation of the linker and substrate-binding domain of HSP70 increases folding activity and cell proliferation. Exp. Mol. Med. 51, 1–14 (2019).CAS 
PubMed 
Article 

Google Scholar 
Yancey, P. H. et al. Betaines and dimethylsulfoniopropionate as major osmolytes in cnidaria with endosymbiotic dinoflagellates. Physiol. Biochem. Zool. 83, 167–173 (2010).CAS 
PubMed 
Article 

Google Scholar 
Hill, R., Li, C., Jones, A., Gunn, J. & Frade, P. Abundant betaines in reef-building corals and ecological indicators of a photoprotective role. Coral Reefs 29, 869–880 (2010).Article 

Google Scholar 
Ngugi, D. K., Ziegler, M., Duarte, C. M. & Voolstra, C. R. Genomic blueprint of glycine betaine metabolism in coral metaorganisms and their contribution to reef nitrogen budgets. iScience 23, 101120 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Williams, A. et al. Metabolome shift associated with thermal stress in coral holobionts. bioRxiv https://doi.org/10.1101/2020.06.04.134619 (2021).Sakamoto, A. & Murata, N. The role of glycine betaine in the protection of plants from stress: clues from transgenic plants. Plant, Cell Environ. 25, 163–171 (2002).CAS 
Article 

Google Scholar 
Burg, M. B. & Ferraris, J. D. Intracellular organic osmolytes: function and regulation. J. Biol. Chem. 283, 7309–7313 (2008).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Chen, T. H. & Murata, N. Glycinebetaine protects plants against abiotic stress: mechanisms and biotechnological applications. Plant Cell Environ. 34, 1–20 (2011).PubMed 
Article 
CAS 

Google Scholar 
Petronini, P., De Angelis, E., Borghetti, A. & Wheeler, K. Effect of betaine on HSP70 expression and cell survival during adaptation to osmotic stress. Biochem. J. 293, 553–558 (1993).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Padilla-Gamiño, J. L., Pochon, X., Bird, C., Concepcion, G. T. & Gates, R. D. From parent to gamete: vertical transmission of Symbiodinium (Dinophyceae) ITS2 sequence assemblages in the reef building coral Montipora capitata. PLoS ONE 7, e38440 (2012).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Cunning, R. & Baker, A. C. Thermotolerant coral symbionts modulate heat stress‐responsive genes in their hosts. Mol. Ecol. 29, 2940–2950 (2020).CAS 
PubMed 
Article 

Google Scholar 
Buerger, P. et al. Heat-evolved microalgal symbionts increase coral bleaching tolerance. Sci. Adv. 6, eaba2498 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Mayfield, A. B. & Gates, R. D. Osmoregulation in anthozoan–dinoflagellate symbiosis. Comp. Biochem. Physiol. A Mol. Integr. Physiol. 147, 1–10 (2007).PubMed 
Article 
CAS 

Google Scholar 
Chan, W. Y., Peplow, L. M., Menéndez, P., Hoffmann, A. A. & van Oppen, M. J. Interspecific hybridization may provide novel opportunities for coral reef restoration. Front. Mar. Sci. 5, 160 (2018).Article 

Google Scholar 
Rose, N. H., Seneca, F. O. & Palumbi, S. R. Gene networks in the wild: identifying transcriptional modules that mediate coral resistance to experimental heat stress. Genome Biol. Evolution 8, 243–252 (2016).CAS 
Article 

Google Scholar 
Ruiz-Jones, L. J. & Palumbi, S. R. Tidal heat pulses on a reef trigger a fine-tuned transcriptional response in corals to maintain homeostasis. Sci. Adv. 3, e1601298 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Chakravarti, L. J., Beltran, V. H. & van Oppen, M. J. Rapid thermal adaptation in photosymbionts of reef‐building corals. Glob. Change Biol. 23, 4675–4688 (2017).Article 

Google Scholar 
Little, A. F., Van Oppen, M. J. & Willis, B. L. Flexibility in algal endosymbioses shapes growth in reef corals. Science 304, 1492–1494 (2004).CAS 
PubMed 
Article 

Google Scholar 
Quigley, K., Randall, C., van Oppen, M. & Bay, L. Assessing the role of historical temperature regime and algal symbionts on the heat tolerance of coral juveniles. Biol. Open 9, bio047316 (2020).Matsuda, S. et al. Coral bleaching susceptibility is predictive of subsequent mortality within but not between coral species. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2020.00178 (2020).Ritson-Williams, R. & Gates, R. D. Coral community resilience to successive years of bleaching in Kane ‘ohe Bay, Hawai ‘i. Coral Reefs. 39, 757–769 (2020).Hancock, J. et al. Coral husbandry for ocean futures: leveraging abiotic factors to increase survivorship, growth and resilience in juvenile Montipora capitata. Mar. Ecol. Prog. Ser., https://doi.org/10.3354/meps13534 (2020).Falconer, D. S. Introduction To Quantitative Genetics (Pearson, 1960).Cunning, R. & Baker, A. C. Excess algal symbionts increase the susceptibility of reef corals to bleaching. Nat. Clim. Change 3, 259–262 (2012).Article 

Google Scholar 
Cunning, R., Gillette, P., Capo, T., Galvez, K. & Baker, A. Growth tradeoffs associated with thermotolerant symbionts in the coral Pocillopora damicornis are lost in warmer oceans. Coral Reefs 34, 155–160 (2015).Article 

Google Scholar 
Alonge, M. et al. RaGOO: fast and accurate reference-guided scaffolding of draft genomes. Genome Biol. 20, 1–17 (2019).Article 

Google Scholar 
Shumaker, A. et al. Genome analysis of the rice coral Montipora capitata. Sci. Rep. 9, 2571 (2019).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 17, 10–12 (2011).Article 

Google Scholar 
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Korneliussen, T. S., Albrechtsen, A. & Nielsen, R. ANGSD: analysis of next generation sequencing data. BMC Bioinforma. 15, 356 (2014).Article 

Google Scholar 
Skotte, L., Korneliussen, T. S. & Albrechtsen, A. Estimating individual admixture proportions from next generation sequencing data. Genetics 195, 693–702 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Oksanen, J. et al. vegan: Community Ecology Package. R package version 1.17-2. R Development Core Team. R: A language and environment for statistical computing (R Foundation for Statistical Computing, 2010).
Google Scholar 
Wright, R. M., Aglyamova, G. V., Meyer, E. & Matz, M. V. Gene expression associated with white syndromes in a reef building coral, Acropora hyacinthus. BMC Genomics 16, 371 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Hivert, V., Leblois, R., Petit, E. J., Gautier, M. & Vitalis, R. Measuring genetic differentiation from Pool-seq data. Genetics 210, 315–330 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Yi, X. et al. Sequencing of 50 human exomes reveals adaptation to high altitude. Science 329, 75–78 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Pluskal, T., Castillo, S., Villar-Briones, A. & Orešič, M. MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinforma. 11, 1–11 (2010).Article 
CAS 

Google Scholar 
Wang, M. et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat. Biotechnol. 34, 828–837 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Nothias, L.-F. et al. Feature-based molecular networking in the GNPS analysis environment. Nat. Methods 17, 905–908 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Dührkop, K. et al. SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information. Nat. methods 16, 299–302 (2019).PubMed 
Article 
CAS 

Google Scholar 
Ludwig, M., Fleischauer, M., Dührkop, K., Hoffmann, M. A. & Böcker, S. in Computational Methods and Data Analysis for Metabolomics 185–207 (Springer, 2020).Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinforma. 9, 1–13 (2008).Article 
CAS 

Google Scholar 
Pedersen, H. K. et al. A computational framework to integrate high-throughput ‘-omics’ datasets for the identification of potential mechanistic links. Nat. Protoc. 13, 2781–2800 (2018).CAS 
PubMed 
Article 

Google Scholar 
Pei, G., Chen, L. & Zhang, W. in Methods in enzymology 585 135–158 (Elsevier, 2017).Sumner, L. W. et al. Proposed minimum reporting standards for chemical analysis. Metabolomics 3, 211–221 (2007).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar  More

DataAll data was processed and analyzed using R (R Core Team, Version 4.0.3).Dengue case data were collected and shared by the Alcaldía de Medellín, Secretaría de Salud. In Medellin, dengue case surveillance is conducted by public health institutions that classify and report all cases that meet the WHO clinical dengue case criteria for a probable case to Medellin’s Secretaría de Salud through SIVIGILA (“el Sistema Nacional de Vigilancia en Salud Publica). All case data were de-identified and aggregated to the SIT Zone level.Human public transit usage and movement data were collected and shared by the Área Metropolitana del Valle de Aburrá for 50–200 respondents per SIT Zone. The “Encuestas Origen Destino” (Origen Destination Surveys) were conducted in 2005, 2011, and 2016 and published in 2006, 2012, and 2017, with survey methods described by the Área Metropolitana del Valle de Aburrá25. Survey respondents include a randomly selected subset of all Medellin residents in each SIT zone regardless of whether they use public transit or not. Survey respondents reported the start and end locations, purpose for travel, and mode of travel for all movement over the last 24 h from the time the survey was administered. Respondents reported all modes of movement, including public transit, private transit, and movement on foot. The results of the survey published in 2017 are published online by the Área Metropolitana del Valle de Aburrá26, and select data are available through the geodata-Medellin open data portal27. The results and data of the survey published in 2012 are not publicly available and were obtained directly from the Área Metropolitana del Valle de Aburrá.The public transit usage survey data were also used to extract socioeconomic data to the SIT zone; surveyors also reported basic demographic data including household Estrato, which was averaged per SIT zone to estimate zone socioeconomic status. “Estrato” measures socioeconomic status on a scale from 1 (lowest) to 6 (highest). This system is used by the government of Colombia to allocate public services and subsidies (Law 142, 1994). Data from the public transit usage survey were used to extract socioeconomic status data because it is the only location available where the spatial scale of the data matched the spatial scale of the SIT zone.Data on the location of Medellín public transit lines was downloaded as shape files from the geodata-Medellín open data portal27 and subset for each year to the set of transit lines that was available in that year. Data on the opening date of each Medellín public transit line was taken from the Medellín metro website28.Because census data at the zone level were not available for this study and only exists for 2005 and 2018, we used population estimates for each year downloaded from the WorldPop project29 and aggregated by SIT zone. The accuracy of WorldPop estimates were checked against available census data for 2005 and 2018 at the comuna level, accessed via the geodata- Medellín open data portal27.Ethical considerationsNo human subjects research was conducted. All data used was de-identified, and the analysis was conducted on a database of cases meeting the clinical criteria for dengue with no intervention or modification of biological, physical, psychological, or social variables. All methods were performed in accordance with the relevant guidelines and regulations.Data analysisQuantifying public transit usage and distance from nearest transit lineTo quantify public transit usage, we determined if each respondent reported using the metro, metroplus, or ruta alimentadora (supplementary bus route system integrated with the metro system) in the last 24 h. We then calculated the percent of respondents using the public transit system at least once for each SIT zone.To quantify the distance to the nearest public transit line, we calculated the distance from the center point of each zone to the closest metro, metroplus, tranvía, metrocable, ruta alimentadora, or escalera eléctrica. This was recalculated for each year, including new transit lines that were added within that year.Spatial autoregressive models of dengue incidenceDengue incidence per year at the level of the SIT zone was modeled using a fixed effects spatial panel model by maximum likelihood (R package splm30) as described in31. Our fixed effects were socioeconomic status, distance from public transit, a two-way interaction between these factors, and year. To weight dengue cases by population per SIT zone, the model contained a log offset of population per zone per year. Dengue case counts were log transformed after adding one to account for zones with zero dengue cases in a given year. Year was analyzed as a categorical variable to avoid smoothing epidemic years. All continuous variables were scaled to enable comparison of effect size. Because these panel models require balanced data across time, data was truncated to SIT zones that had data for all years available (247 remaining of 291). Spatial dependency was evaluated, and the model was selected using the Hausman specification test and locally robust panel Lagrange Multiplier tests for spatial dependence. Based on a significant Hausman specification test result, which indicates a poor specification of the random effect model, a fixed effect model was chosen. This result is supported by the fact that we had a nearly exhaustive sample of SIT zones in the Medellin metro area. Lagrange multiplier tests were used to determine the most appropriate spatial dependency specifications. Based on the results of the Lagrange multiplier tests, a Spatial Autoregressive (SAR) model was the most appropriate to incorporate spatial dependency; a SAR model considers that the number of dengue cases in a SIT zone depends on the number in neighboring zones.Because public transit usage was a measurement taken during just two of the study years, we constructed an additional fixed effects spatial panel model by maximum likelihood model of dengue incidence in just 2011 and 2016 that included ridership as an additional predictor variable. Our fixed effects were year, socioeconomic status, distance from public transit, a two-way interaction between socioeconomic status and distance from public transit, percent utilizing public transit, and a two-way interaction between socioeconomic status and percent utilizing public transit. As in our model of all years, the model contained a log offset of population per zone per year and dengue case counts were log transformed after adding one to account for zones with zero dengue cases in a given year, year was analyzed as a categorical variable, and all continuous variables were scaled to enable comparison of effect size. The data was truncated to SIT zones that had data for all years available (251 remaining of 291). We used the same model selection process, and again a fixed effect model was chosen, and based on the results of the Lagrange multiplier tests, a Spatial Autoregressive (SAR) model was determined the most appropriate to incorporate spatial dependency. More

Kelly, A. E. & Goulden, M. L. Rapid shifts in plant distribution with recent climate change. Proc. Natl. Acad. Sci. U.S.A. 105, 11823–11826. https://doi.org/10.1073/pnas.0802891105 (2008).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Wiens, J. J. Climate-related local extinctions are already widespread among plant and animal species. PLoS Biol. 14, e2001104. https://doi.org/10.1371/journal.pbio.2001104 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Swinnen, J., Burkitbayeva, S., Schierhorn, F., Prishchepov, A. V. & Müller, D. Production potential in the “bread baskets” of Eastern Europe and Central Asia. Global Food Secur. 14, 38–53. https://doi.org/10.1016/j.gfs.2017.03.005 (2017).Article 

Google Scholar 
Henry, R. J. Innovations in plant genetics adapting agriculture to climate change. Curr. Opin. Plant Biol. 56, 168–173. https://doi.org/10.1016/j.pbi.2019.11.004 (2020).Article 
PubMed 

Google Scholar 
Stokes, C. & Howden, M. Adapting Agriculture to Climate Change: Preparing Australian Agriculture, Forestry and Fisheries for the Future (Csiro Publishing, 2010).Book 

Google Scholar 
Bräutigam, K. et al. Epigenetic regulation of adaptive responses of forest tree species to the environment. Ecol. Evol. 3, 399–415. https://doi.org/10.1002/ece3.461 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Yaish, M. W., Colasanti, J. & Rothstein, S. J. The role of epigenetic processes in controlling flowering time in plants exposed to stress. J. Exp. Bot. 62, 3727–3735. https://doi.org/10.1093/jxb/err177 (2011).CAS 
Article 
PubMed 

Google Scholar 
Yaish, M. W. DNA methylation-associated epigenetic changes in stress tolerance of plants. In Molecular Stress Physiology of Plants (eds Rout, G. R. & Das, A. B.) 427–440 (Springer India, 2013).Chapter 

Google Scholar 
Suji, K. K. & Joel, A. J. An epigenetic change in rice cultivars underwater stress conditions. Electron. J. Plant Breed. 1, 1142–1143 (2010).
Google Scholar 
Peng, H. & Zhang, J. Plant genomic DNA methylation in response to stresses: Potential applications and challenges in plant breeding. Prog. Nat. Sci. 19, 1037–1045. https://doi.org/10.1016/j.pnsc.2008.10.014 (2009).CAS 
Article 

Google Scholar 
Baduel, P. & Colot, V. The epiallelic potential of transposable elements and its evolutionary significance in plants. Philos. Trans. R. Soc. B 376, 20200123. https://doi.org/10.1098/rstb.2020.0123 (2021).CAS 
Article 

Google Scholar 
Labra, M. et al. Analysis of cytosine methylation pattern in response to water deficit in pea root tips. Plant Biol. 4, 694–699. https://doi.org/10.1055/s-2002-37398 (2002).CAS 
Article 

Google Scholar 
Wang, W.-S. et al. Drought-induced site-specific DNA methylation and its association with drought tolerance in rice (Oryza sativa L.). J. Exp. Bot. 62, 1951–1960. https://doi.org/10.1093/jxb/erq391 (2011).CAS 
Article 
PubMed 

Google Scholar 
Šmarda, P., Bureš, P., Horová, L., Foggi, B. & Rossi, G. Genome size and GC content evolution of Festuca: Ancestral expansion and subsequent reduction. Ann. Bot. 101, 421–433. https://doi.org/10.1093/aob/mcm307 (2008).CAS 
Article 
PubMed 

Google Scholar 
Tomczyk, P. P., Kiedrzyński, M., Jedrzejczyk, I., Rewers, M. & Wasowicz, P. The transferability of microsatellite loci from a homoploid to a polyploid hybrid complex: An example from fine-leaved Festuca species (Poaceae). PeerJ 8, e9227. https://doi.org/10.7717/peerj.9227 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Piękoś-Mirkowa, H. & Mirek, Z. Distribution patterns and habitats of endemic vascular plants in the Polish Carpathians. Acta Soc. Bot. Pol. 78, 321–326 (2009).Article 

Google Scholar 
Kiedrzyński, M., Zielińska, K. M., Rewicz, A. & Kiedrzyńska, E. Habitat and spatial thinning improve the Maxent models performed with incomplete data. J. Geophys. Res. Biogeosci. 122(6), 1359–1370. https://doi.org/10.1002/2016JG003629 (2017).Article 

Google Scholar 
Rewicz, A. et al. Morphometric traits in the fine-leaved fescues depend on ploidy level: The case of Festuca amethystina L. PeerJ 6, e5576. https://doi.org/10.7717/peerj.5576 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Kiedrzyński, M. et al. Tetraploids expanded beyond the mountain niche of their diploid ancestors in the mixed-ploidy grass Festuca amethystina L. Sci. Rep. 11, 18735 (2021).ADS 
Article 

Google Scholar 
Mounger, J. et al. Epigenetics and the success of invasive plants. Philos. Trans. R. Soc. B 376, 20200117. https://doi.org/10.1098/rstb.2020.0117 (2021).CAS 
Article 

Google Scholar 
Bewick, A. J. & Schmitz, R. J. Epigenetics in the wild. Elife 4, e07808. https://doi.org/10.7554/eLife.07808 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Sahu, P. P. et al. Epigenetic mechanisms of plant stress responses and adaptation. Plant Cell Rep. 32(8), 1151–1159. https://doi.org/10.1007/s00299-013-1462-x (2013).CAS 
Article 
PubMed 

Google Scholar 
Alonso, C. et al. Interspecific variation across angiosperms in global DNA methylation: Phylogeny, ecology and plant features in tropical and Mediterranean communities. New Phytol. 224(2), 949–960. https://doi.org/10.1111/nph.16046 (2019).CAS 
Article 
PubMed 

Google Scholar 
Angers, B., Castonguay, E. & Massicotte, R. Environmentally induced phenotypes and DNA methylation: How to deal with unpredictable conditions until the next generation and after. Mol. Ecol. 19(7), 1283–1295. https://doi.org/10.1111/j.1365-294X.2010.04580.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Batog, J. & Wawro, A. Process of obtaining bioethanol from sorghum biomass using genome shuffling. Cellul. Chem. Technol. 53, 459–467 (2019).CAS 
Article 

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

Google Scholar 
Li, N. et al. DNA methylation repatterning accompanying hybridization, whole genome doubling and homoeolog exchange in nascent segmental rice allotetraploids. New Phytol. 223(2), 979–992. https://doi.org/10.1111/nph.15820 (2019).CAS 
Article 
PubMed 

Google Scholar 
Róis, A. S. et al. Epigenetic rather than genetic factors may explain phenotypic divergence between coastal populations of diploid and tetraploid Limonium spp. (Plumbaginaceae) in Portugal. BMC Plant Biol. 13(1), 205. https://doi.org/10.1186/1471-2229-13-205 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Li, A. et al. DNA methylation in genomes of several annual herbaceous and woody perennial plants of varying ploidy as detected by MSAP. Plant Mol. Biol. Rep. 29, 784–793. https://doi.org/10.1007/s11105-010-0280-3 (2011).ADS 
CAS 
Article 

Google Scholar 
Sokolova, D. A., Vengzhen, G. S. & Kravets, A. P. An Analysis of the correlation between the changes in satellite DNA methylation patterns and plant cell responses to the stress. Cell Bio 2, 163–171. https://doi.org/10.4236/cellbio.2013.23018 (2013).CAS 
Article 

Google Scholar 
Johnson, L. I. & Tricker, P. J. Epigenomic plasticity within populations: Its evolutionary significance and potential. Heredity 105, 113–121. https://doi.org/10.1038/hdy.2010.25 (2010).CAS 
Article 
PubMed 

Google Scholar 
Zheng, X. et al. Transgenerational variations in DNA methylation induced by drought stress in two rice varieties with distinguished difference to drought resistance. PLoS One 8(11), e80253. https://doi.org/10.1371/journal.pone.0080253 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Karan, R., DeLeon, T., Biradar, H. & Subudhi, P. K. Salt Stress induced variation in DNA methylation pattern and its influence on gene expression in contrasting rice genotypes. PLoS One 7(6), e40203. https://doi.org/10.1371/journal.pone.0040203 (2012).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Richards, C. L. & Pigliucci, M. Epigenetic inheritance. A decade into the extended evolutionary synthesis. Paradigmi 38, 463–494. https://doi.org/10.30460/99624 (2020).Article 

Google Scholar 
Chelaifa, H., Monnier, A. & Ainouche, M. Transcriptomic changes following recent natural hybridization and allopolyploidy in the salt marsh species Spartina × townsendii and Spartina anglica (Poaceae). New Phytol. 186(1), 161–174. https://doi.org/10.1111/j.1469-8137.2010.03179.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Al-Lawati, A., Al-Bahry, S., Victor, R., Al-Lawati, A. H. & Yaish, M. W. Salt stress alters DNA methylation levels in alfalfa (Medicago spp.). Genet. Mol. Res. 15, 15018299. https://doi.org/10.4238/gmr.15018299 (2016).CAS 
Article 
PubMed 

Google Scholar 
Lewandowska-Gnatowska, E. et al. Is DNA methylation modulated by wounding-induced oxidative burst in maize?. Plant Physiol. Biochem. 82, 202–208. https://doi.org/10.1016/j.plaphy.2014.06.003 (2014).CAS 
Article 
PubMed 

Google Scholar 
Marfil, C. et al. Changes in grapevine DNA methylation and polyphenols content induced by solar ultraviolet-B radiation, water deficit and abscisic acid spray treatments. Plant Physiol. Biochem. 135, 287–294. https://doi.org/10.1016/j.plaphy.2018.12.021 (2019).CAS 
Article 
PubMed 

Google Scholar 
Zedek, F. et al. Endopolyploidy is a common response to UV-B stress in natural plant populations, but its magnitude may be affected by chromosome type. Ann. Bot. 126(5), 883–889. https://doi.org/10.1093/aob/mcaa109 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Pandey, N. & Pandey-Rai, S. Deciphering UV-B-induced variation in DNA methylation pattern and its influence on regulation of DBR2 expression in Artemisia annua L. Planta 242(4), 869–879. https://doi.org/10.1007/s00425-015-2323-3 (2015).CAS 
Article 
PubMed 

Google Scholar 
Molinier, J. Genome and epigenome surveillance processes underlying UV exposure in plants. Genes 8(11), 316. https://doi.org/10.3390/genes8110316 (2017).CAS 
Article 
PubMed Central 

Google Scholar 
Niederhuth, C. E. et al. Widespread natural variation of DNA methylation within angiosperms. Genome Biol. 17, 194. https://doi.org/10.1186/s13059-016-1059-0 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Lira-Medeiros, C. F. et al. Epigenetic variation in mangrove plants occurring in contrasting natural environment. PLoS One 5, e10326. https://doi.org/10.1371/journal.pone.0010326 (2010).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Richards, C. L., Verhoeven, K. J. F. & Bossdorf, O. Evolutionary significance of epigenetic variation. In Plant Genome Diversity Vol. 1 (eds Wendel, J. F. et al.) 257–274 (Springer Vienna, 2012).Chapter 

Google Scholar 
Paun, O. et al. Stable epigenetic effects impact adaptation in allopolyploid orchids (Dactylorhiza: Orchidaceae). Mol. Biol. Evol. 27, 2465–2473. https://doi.org/10.1093/molbev/msq150 (2010).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Xie, H. et al. Global DNA methylation patterns can play a role in defining terroir in grapevine (Vitis vinifera cv. Shiraz). Front. Plant Sci. 8, 130398. https://doi.org/10.3389/fpls.2017.01860 (2017).Article 

Google Scholar 
Herrera, C. M. & Bazaga, P. Epigenetic differentiation and relationship to adaptive genetic divergence in discrete populations of the violet Viola cazorlensis. New Phytol. 187(3), 867–876. https://doi.org/10.1111/j.1469-8137.2010.03298.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Portis, E., Acquadro, A., Comino, C. & Lanteri, S. Analysis of DNA methylation during germination of pepper (Capsicum annuum L.) seeds using methylation-sensitive amplification polymorphism (MSAP). Plant Sci. 166, 169–178. https://doi.org/10.1016/j.plantsci.2003.09.004 (2004).CAS 
Article 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. http://www.R-project.org (R Foundation for Statistical Computing, 2013).Schloerke, B. et al. GGally: Extension to “ggplot2” R package version 2.1.0. https://CRAN.R-project.org/package=GGally (2021).StatSoft, Inc. STATISTICA (Data Analysis Software System), Version 10. http://www.statsoft.com (2011).Tomczyk, P. Phenotypic measurement of inbreeding depression in grasses—An overview of traits (Fenotypowe miary depresji wsobnej u traw—przegląd cech). Wiad. Bot. https://doi.org/10.5586/wb.2019.005 (2019).Article 

Google Scholar 
Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37(12), 4302–4315. https://doi.org/10.1002/joc.5086 (2017).Article 

Google Scholar 
Fox, J. & Weisberg, S. An {R} Companion to Applied Regression (Sage Publications, 2019).
Google Scholar  More

Yeo, D. C. J. et al. Global diversity of crabs (Crustacea: Decapoda: Brachyura). In Freshwater Animal Diversity Assessment (eds Balian, E. V. et al.). Hydrobiologia Vol. 595, 275–286 (2008).Álvarez, F. et al. Revision of the higher taxonomy of Neotropical freshwater crabs of the family Pseudothelphusidae, based on multigene and morphological analyses. Zool. J. Linn. Soc. 193, 973–1001 (2021).Article 

Google Scholar 
Ng, D. J. J. & Yeo, D. C. J. Terrestrial scavenging behaviour of the Singapore freshwater crab, Johora singaporensis (Crustacea: Brachyura: Potamidae). Nat. Singap. 6, 207–210 (2013).
Google Scholar 
Dobson, M. Freshwater crabs in Africa. Freshw. Forum 21, 3–26 (2004).
Google Scholar 
Dobson, M., Magana, A. M., Mathooko, J. M. & Ndegwa, F. K. Distribution and abundance of freshwater crabs (Potamonautes spp.) in rivers draining Mt Kenya, East Africa. Fundam. Appl. Limnol. 168, 271–279 (2007).Article 

Google Scholar 
Cumberlidge, N. et al. Freshwater crabs and the biodiversity crisis: Importance, threats, status, and conservation challenges. Biol. Conserv. 142, 1665–1673 (2009).Article 

Google Scholar 
Jouladeh-Roudbar, A., Ghanavi, H. R. & Doadrio, I. Ichthyofauna from Iranian freshwater: Annotated checklist, diagnosis, taxonomy, distribution and conservation. Assessment 21, 1–303 (2020).
Google Scholar 
Brandis, D., Storch, V. & Türkay, M. Taxonomy and zoogeography of the freshwater crabs of Europe, North Africa, and the Middle East (Crustacea, Decapoda, Potamidae). Senckenberg. Biol. 80, 5–56 (2000).
Google Scholar 
Keikhosravi, A. & Schubart, C. D. Description of a new freshwater crab species of the genus Potamon (Decapoda, Brachyura, Potamidae) from Iran, based on morphological and genetic characters. In Advances in Freshwater Decapod Systematics and Biology 115–133 (BRILL, 2014). https://doi.org/10.1163/9789004207615_008.Keikhosravi, A. & Schubart, C. D. Revalidation and redescription of Potamon elbursi Pretzmann, 1976 (Brachyura, Potamidae) from Iran, based on morphology and genetics. Open Life Sci. 9, 114–123 (2014).Article 

Google Scholar 
Keikhosravi, A., Naderloo, R. & Schubart, C. D. Morphological and molecular diversity in the freshwater crab Potamon ruttneri-P. gedrosianum species complex (Decapoda, Brachyura) indicate the need for taxonomic revision. Crustaceana 89, 129–139 (2016).Article 

Google Scholar 
Parvizi, E., Naderloo, R., Keikhosravi, A., Solhjouy-Fard, S. & Schubart, C. D. Multiple Pleistocene refugia and repeated phylogeographic breaks in the southern Caspian Sea region: Insights from the freshwater crab Potamon ibericum. J. Biogeogr. 45, 1234–1245 (2018).Article 

Google Scholar 
Folmer, O., Black, M., Hoeh, W., Lutz, R. & Vrijenhoek, R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Aust. J. Zool. https://doi.org/10.1071/ZO9660275 (1994).Article 

Google Scholar 
Kearse, M. et al. Geneious basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28, 1647–1649 (2012).Article 

Google Scholar 
Katoh, K. MAFFT: A novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066 (2002).CAS 
Article 

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

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

Google Scholar 
Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A. & Jermiin, L. S. ModelFinder: Fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).CAS 
Article 

Google Scholar 
Felsenstein, J. Confidence limits on phylogenies: An approach using the bootstrap. Evolution 39, 783 (1985).Article 

Google Scholar 
Zhang, J., Kapli, P., Pavlidis, P. & Stamatakis, A. A general species delimitation method with applications to phylogenetic placements. Bioinformatics 29, 2869–2876 (2013).CAS 
Article 

Google Scholar 
Tamura, K., Stecher, G. & Kumar, S. MEGA11: Molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 38, 3022–3027 (2021).CAS 
Article 

Google Scholar 
Masters, B. C., Fan, V. & Ross, H. A. Species delimitation—A geneious plugin for the exploration of species boundaries. Mol. Ecol. Resour. 11, 154–157 (2011).Article 

Google Scholar  More

Our study combining field data and aerial imagery analysis clearly showed that the spotted souslik avoids close coexistence with another burrowing species, i.e. the European mole, in the period of low population abundance. This is the first study on this subject described in the available literature, as attention has been paid mainly to other parameters of the habitat so far14,18,20. The present results can (1) make a new contribution to the knowledge of the ecology of burrowing mammals and their interspecies relationships, (2) contribute to better designs of conservation and assessment of the quality of habitats of endangered burrowing mammals, and (3) indicate new possibilities of using remote sensing and deep learning methods in ecology and conservation. Below we will try to address each of these issues.The interaction between underground animals is not a new idea in ecology (e.g.22); however, this issue has not been analyzed for the mole and the souslik so far. This was probably related to the fact that the potential negative or positive relationships between these species are not intuitively obvious. The spatial distribution of underground tunnels of these animals is completely different: the mole builds an extensive network of horizontal tunnels close to the ground surface, while the souslik usually builds one deep nest burrow with a vertical entrance and possibly a small number of shallow safety burrows near the nest burrow. Moreover, the food preferences of the souslik and the mole differ, i.e. the former is mainly a herbivore, while the latter is an obligatory predator. There are also clear differences in the annual cycle: the mole is active all year round, and the souslik hibernates in an underground nest for about half a year from October to March. Thus, it seems that the emergence of competitive relationships between these two species is unlikely. Our study shows, however, that these species avoid each other in space, which raises the question of the mechanism of this relationship. Based on the knowledge of the biology of both species, some hypothetical mechanisms can be proposed.Although they are colonial animals, sousliks inhabit burrows alone (except for mother and offspring) and they have a strong behavioural trait of a negative reaction to the presence of other animals in their burrows and their close vicinity14,23. The negative reaction to other sousliks is a reflection of the intraspecific competition in the population and the territoriality of individuals. It is regulated by odour signals and the social structure of the population30,31. Koshev32 described aggressive reactions of free-ranging European sousliks to other vertebrate species that appeared near burrows: towards the reptile Lacerta trilineata, the bird Corvus frugilegus, and the mammal Mustela nivalis. Theoretically, the mole can get into the souslik’s burrow unintentionally when digging new tunnels. For souslik, the presence of moles in their nest burrow means a violation of its strictly defended territory and is probably a highly stressful episode. It can therefore be assumed that sousliks should choose places outside areas of frequent occurrence of other burrowing mammals to set up a nest burrow.It remains an open question whether avoidance of areas where the mole is often present may be important for the souslik during winter hibernation. Theoretically, the presence of moles in souslik burrows during hibernation may disturb this process and cause waking up and energy-consuming increases in metabolism, which may reduce winter survival. It is also unknown whether the mole can be a predator for the souslik during winter hibernation. Remains of rodent species were found in the digestive tracts of moles33; therefore, at least theoretically, the mole may use such a food source. On the other hand, remains of vertebrates, including the remains of moles, were sometimes found in the stomachs of sousliks18. The relationship between the souslik and the mole may therefore be more complex and require further research focused on this issue. It is possible that the moles can avoid the souslik colonies as well. This scenario seems also realistic, since the moles home ranges are likely much more dynamic than that of sousliks, that likely benefit from dwelling within an existing colony of the conspecifics.The spotted souslik protection requires the designation of special areas of conservation16. A number of various conservation activities are also routinely undertaken for this species, including regular monitoring of the population size, habitat monitoring, mowing, reduction of predation risk, and application of more invasive methods such as reintroduction. Similar activities are also performed for a closely related species, i.e. the European souslik Spermophilus citellus, in Europe. Importantly, in the current guidelines of souslik conservation, the issue of the competition with other species and its impact on spatial distribution is not considered. In turn, there is evidence in the literature that interspecies interactions may be important for the souslik population21. In periods of low abundance, when the survival of the population is at risk, the sousliks may have different habitat preferences than in periods of the abundant population20. It seems, therefore, that nowadays, when the souslik most often forms small populations, more attention should be paid to a wider range of factors and threats that may determine longer term population trends or the health condition, survival, and abundance of their colonies.Our study indicates that, in the period of low population abundance, the presence of other burrowing species may be an important factor determining the distribution of sousliks. This observation shows that in addition to the assessment of the area and condition of the habitat the presence of other potentially competitive species should also be taken into account in the analysis of population survival. In such a case, the actual area of habitats suitable for sousliks in a given location may turn out to be much lower than assumed. In our study area, the habitat suitable for the souslik was reduced from 105 ha to approx. 65 ha, i.e. by nearly 38%, but it probably is even smaller (compare Fig. 8). This observation has consequences for improvement of the reintroduction methods of sousliks (or other burrowing mammals), which are constantly of scientific interest20,34,35. Our results indicate that the reintroduction of sousliks should be carried out in places where there is the lowest probability of competition for resources including even shelter or space with other burrowing species and where adequate space for the settlement of the population is ensured.So far, investigations of the distribution of small burrowing mammals have been based on laborious field studies involving site inspections by trained observers (e.g.36,37,38). Our results show that, in certain conditions, high-resolution imagery can be successfully used to support studies of the distribution of such animals. As reported by other authors (e.g.7,10,12), however, such animals must produce clear signs of their presence in the environment. Evidence of the presence of the European mole, i.e. mounds of soil, in short vegetation habitats has shown that remote sensing can detect moles and their area of occupancy successfully. The advantage of these markers of the presence of moles is that the mounds are redundant and quite durable and can be visible in the environment for up to several months.By combining field research and remote sensing, it is also possible to study more sophisticated ecological issues, e.g. interspecies interactions. In this work, the remote estimation of the distribution of moles facilitated estimation of the actual habitat available to the souslik and excluded areas with the lowest probability of its occurrence. As a result, the population may be monitored more economically. Since the conservation guidelines recommend monitoring souslik populations by means of laborious inspections of transects, the indication of areas with no burrows may significantly reduce the amount of fieldwork without negative consequences for the accuracy of results. Some areas of the souslik occurrence are large, e.g. Świdnik (105 ha) or Pastwiska nad Huczwą (150 ha), and every 10 ha to be monitored means one day’s work for one observer (according to the calculations presented in the results). Our study showed that when the area of the occurrence of moles is excluded from the monitoring (Fig. 8), the error in estimating the size of the souslik population will be relatively small (0.9–8.7%). At the same time, the time devoted to the research can be limited by 14% or 38%, respectively. This suggests that our method can contribute to improved monitoring and management of these protected species, especially that souslik monitoring requires considerable research effort and has to be carried out twice a year.However, mole mounds may be underestimated by remote sensing, which can be seen in Fig. 7. Small mole mounds that are easily identified during field research may not be noticed by remote sensing. Such underestimation does not constitute a critical threat to the determination of the mole area according to the scheme shown in Fig. 8, since its marks are highly redundant. However, since there is currently little research on this subject, we recommend combining field research and remote sensing in assessments similar to ours. Finally, it is worth noting that, for a better understanding of the issue of the interactions between souslik and other burrowing species, it is advisable to use another remote sensing technique—telemetry. Telemetry studies are successfully conducted in Bulgarian souslik populations34 and their combination with studies of habitat selectivity dependent on other burrowing species may provide new and valuable insight into this issue. More