Ecology

Nayfach S, Roux S, Seshadri R, Udwary D, Varghese N, Schulz F, et al. A genomic catalog of Earth’s microbiomes. Nat Biotechnol. 2021;39:499–509.CAS 
PubMed 

Google Scholar 
Fierer N. Embracing the unknown: disentangling the complexities of the soil microbiome. Nat Rev Microbiol. 2017;15:579–90.CAS 
PubMed 

Google Scholar 
Cordovez V, Dini-Andreote F, Carrión VJ, Raaijmakers JM. Ecology and evolution of plant microbiomes. Annu Rev Microbiol. 2019;73:69–88.CAS 
PubMed 

Google Scholar 
Trivedi P, Leach JE, Tringe SG, Sa T, Singh BK. Plant–microbiome interactions: from community assembly to plant health. Nat Rev Microbiol. 2020;18:607–21.CAS 
PubMed 

Google Scholar 
Fitzpatrick CR, Salas-González I, Conway JM, Finkel OM, Gilbert S, Russ D, et al. The plant microbiome: From ecology to reductionism and beyond. Annu Rev Microbiol. 2020;74:81–100.CAS 
PubMed 

Google Scholar 
Schmidt R, Ulanova D, Wick LY, Bode HB, Garbeva P. Microbe-driven chemical ecology: past, present and future. ISME J. 2019;13:2656–63.PubMed 
PubMed Central 

Google Scholar 
Tyc O, Song C, Dickschat JS, Vos M, Garbeva P. The ecological role of volatile and soluble secondary metabolites produced by soil bacteria. Trends Microbiol. 2017;25:280–92.CAS 
PubMed 

Google Scholar 
Romero D, Traxler MF, López D, Kolter R. Antibiotics as signal molecules. Chem Rev. 2011;111:5492–505.CAS 
PubMed 
PubMed Central 

Google Scholar 
Traxler MF, Seyedsayamdost MR, Clardy J, Kolter R. Interspecies modulation of bacterial development through iron competition and siderophore piracy. Mol Microbiol. 2012;86:628–44.CAS 
PubMed 
PubMed Central 

Google Scholar 
Bernal P, Llamas MA, Filloux A. Type VI secretion systems in plant-associated bacteria. Environ Microbiol. 2018;20:1–15.PubMed 

Google Scholar 
Okada BK, Seyedsayamdost MR. Antibiotic dialogues: induction of silent biosynthetic gene clusters by exogenous small molecules. FEMS Microbiol Rev. 2017;41:19–33.CAS 
PubMed 

Google Scholar 
Zhang C, Straight PD. Antibiotic discovery through microbial interactions. Curr Opin Microbiol. 2019;51:64–71.CAS 
PubMed 

Google Scholar 
Traxler MF, Kolter R. Natural products in soil microbe interactions and evolution. Nat Prod Rep. 2015;32:956–70.CAS 
PubMed 

Google Scholar 
Müller DB, Vogel C, Bai Y, Vorholt JA. The plant microbiota: systems-level insights and perspectives. Annu Rev Genet. 2016;50:211–34.PubMed 

Google Scholar 
Anckaert A, Arias AA, Hoff G, Calonne-Salmon M, Declerck S, Ongena M. The use of Bacillus spp. as bacterial biocontrol agents to control plant diseases. In: Köhl J, Ravensberg W, editors. Microbial bioprotectants for plant disease management. Cambridge, UK: Burleigh Dodds Science Publishing; 2022. p. 1–54.Dunlap CA. Taxonomy of registered Bacillus spp. strains used as plant pathogen antagonists. Biol Control. 2019;134:82–86.
Google Scholar 
Ye M, Tang X, Yang R, Zhang H, Li F, Tao F, et al. Characteristics and application of a novel species of Bacillus: Bacillus velezensis. ACS Chem Biol. 2018;13:500–5.CAS 
PubMed 

Google Scholar 
Grubbs KJ, Bleich RM, Santa Maria KC, Allen SE, Farag S, Shank EA, et al. Large-scale bioinformatics analysis of Bacillus genomes uncovers conserved roles of natural products in bacterial physiology. mSystems 2017;2:e00040–17.CAS 
PubMed 
PubMed Central 

Google Scholar 
Harwood CR, Mouillon J-MM, Pohl S, Arnau J. Secondary metabolite production and the safety of industrially important members of the Bacillus subtilis group. FEMS Microbiol Rev. 2018;42:721–38.CAS 
PubMed 
PubMed Central 

Google Scholar 
Köhl J, Kolnaar R, Ravensberg WJ. Mode of action of microbial biological control agents against plant diseases: Relevance beyond efficacy. Front Plant Sci. 2019;10:1–19.
Google Scholar 
Li Y, Rebuffat S. The manifold roles of microbial ribosomal peptide-based natural products in physiology and ecology. J Biol Chem. 2020;295:34–54.Andrić S, Meyer T, Ongena M. Bacillus responses to plant-associated fungal and bacterial communities. Front Microbiol. 2020;11:1350.PubMed 
PubMed Central 

Google Scholar 
Zhang L, Sun C. Fengycins, cyclic lipopeptides from marine Bacillus subtilis strains, kill the plant-pathogenic fungus Magnaporthe grisea by inducing reactive oxygen species production and chromatin condensation. Appl Environ Microbiol. 2018;84:e00445–18.CAS 
PubMed 
PubMed Central 

Google Scholar 
Molina-Santiago C, Vela-Corcía D, Petras D, Díaz-Martínez L, Pérez-Lorente AI, Sopeña-Torres S, et al. Chemical interplay and complementary adaptative strategies toggle bacterial antagonism and co-existence. Cell Rep. 2021;36:109449.CAS 
PubMed 
PubMed Central 

Google Scholar 
Molina-Santiago C, Pearson JR, Navarro Y, Berlanga-Clavero MV, Caraballo-Rodriguez AM, Petras D, et al. The extracellular matrix protects Bacillus subtilis colonies from Pseudomonas invasion and modulates plant co-colonization. Nat Commun. 2019;10:1919.PubMed 
PubMed Central 

Google Scholar 
Almoneafy AA, Kakar KU, Nawaz Z, Li B, Saand MA, Chun-lan Y, et al. Tomato plant growth promotion and antibacterial related-mechanisms of four rhizobacterial Bacillus strains against Ralstonia solanacearum. Symbiosis 2014;63:59–70.CAS 

Google Scholar 
Kakar KU, Duan Y-P, Nawaz Z, Sun G, Almoneafy AA, Hassan MA, et al. A novel rhizobacterium Bk7 for biological control of brown sheath rot of rice caused by Pseudomonas fuscovaginae and its mode of action. Eur J Plant Pathol. 2014;138:819–34.
Google Scholar 
Raynaud X, Nunan N. Spatial ecology of bacteria at the microscale in soil. PLoS ONE. 2014;9:e87217.PubMed 
PubMed Central 

Google Scholar 
Girard L, Lood C, Höfte M, Vandamme P, Rokni-Zadeh H, van Noort V, et al. The ever-expanding Pseudomonas genus: description of 43 new species and partition of the Pseudomonas putida group. Microorganisms. 2021;9:1–24.
Google Scholar 
Hua GKH, Höfte M. The involvement of phenazines and cyclic lipopeptide sessilin in biocontrol of Rhizoctonia root rot on bean (Phaseolus vulgaris) by Pseudomonas sp. CMR12a is influenced by substrate composition. Plant Soil. 2015;388:243–53.CAS 

Google Scholar 
Ma Z, Hoang Hua GKH, Ongena M, Höfte M. Role of phenazines and cyclic lipopeptides produced by Pseudomonas sp. CMR12a in induced systemic resistance on rice and bean. Environ Microbiol Rep. 2016;8:896–904.PubMed 

Google Scholar 
Olorunleke FE, Hua GKH, Kieu NP, Ma Z, Höfte M. Interplay between orfamides, sessilins and phenazines in the control of Rhizoctonia diseases by Pseudomonas sp. CMR12a. Environ Microbiol Rep. 2015;7:774–81.CAS 
PubMed 

Google Scholar 
van Gestel J, Vlamakis H, Kolter R. From cell differentiation to cell collectives: Bacillus subtilis uses division of labor to migrate. PLoS Biol. 2015;13:1–29.
Google Scholar 
Nihorimbere V, Cawoy H, Seyer A, Brunelle A, Thonart P, Ongena M. Impact of rhizosphere factors on cyclic lipopeptide signature from the plant beneficial strain Bacillus amyloliquefaciens S499. FEMS Microbiol Ecol. 2012;79:176–91.CAS 
PubMed 

Google Scholar 
Hoff G, Arias AA, Boubsi F, Pršić J, Meyer T, Ibrahim HMM, et al. Surfactin stimulated by pectin molecular patterns and root exudates acts as a key driver of the Bacillus-plant mutualistic interaction. MBio 2021;12:e01774–21.CAS 
PubMed Central 

Google Scholar 
Andrić S, Meyer T, Rigolet A, Prigent-Combaret C, Höfte M, Balleux G, et al. Lipopeptide interplay mediates molecular interactions between soil bacilli and pseudomonads. Microbiol Spectr. 2021;9:e0203821.PubMed 

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 Bioinform. 2010;11:395.
Google Scholar 
Li W, Godzik A. Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006;22:1658–9.CAS 
PubMed 

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

Google Scholar 
Paradis E, Claude J, Strimmer K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 2004;20:289–90.CAS 
PubMed 

Google Scholar 
Ivica Letunic PB. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 2021;49:W293–W296.PubMed 
PubMed Central 

Google Scholar 
R Core Team (2020). R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2020.Steinke K, Mohite OS, Weber T, Kovács ÁT. Phylogenetic distribution of secondary metabolites in the Bacillus subtilis species complex. mSystems. 2021;6:2–10.
Google Scholar 
Molinatto G, Puopolo G, Sonego P, Moretto M, Engelen K, Viti C, et al. Complete genome sequence of Bacillus amyloliquefaciens subsp. plantarum S499, a rhizobacterium that triggers plant defences and inhibits fungal phytopathogens. J Biotechnol. 2016;238:56–59.CAS 
PubMed 

Google Scholar 
Fan B, Wang C, Song X, Ding X, Wu L, Wu H, et al. Bacillus velezensis FZB42 in 2018: The gram-positive model strain for plant growth promotion and biocontrol. Front Microbiol. 2018;9:3389.
Google Scholar 
Mansfield J, Genin S, Magori S, Citovsky V, Sriariyanum M, Ronald P, et al. Top 10 plant pathogenic bacteria in molecular plant pathology. Mol Plant Pathol. 2012;13:614–29.PubMed 
PubMed Central 

Google Scholar 
Scholz R, Vater J, Budiharjo A, Wang Z, He Y, Dietel K, et al. Amylocyclicin, a novel circular bacteriocin produced by Bacillus amyloliquefaciens FZB42. J Bacteriol. 2014;196:1842–52.PubMed 
PubMed Central 

Google Scholar 
Lembrechts JJ, van den Hoogen J, Aalto J, Ashcroft MB, De Frenne P, Kemppinen J, et al. Global maps of soil temperature. Glob Chang Biol. 2022;28:3110–44.CAS 
PubMed 
PubMed Central 

Google Scholar 
Blake C, Christensen MN, Kovacs AT. Molecular aspects of plant growth promotion and protection by Bacillus subtilis. Mol Plant-Microbe Interact. 2021;34:15–25.CAS 
PubMed 

Google Scholar 
Arnaouteli S, Bamford NC, Stanley-Wall NR, Kovács ÁT. Bacillus subtilis biofilm formation and social interactions. Nat Rev Microbiol. 2021;19:600–14.CAS 
PubMed 

Google Scholar 
D’aes J, Hua GKH, De Maeyer K, Pannecoucque J, Forrez I, Ongena M, et al. Biological control of Rhizoctonia root rot on bean by phenazine- and cyclic lipopeptide-producing Pseudomonas CMR12a. Phytopathology. 2011;101:996–1004.PubMed 

Google Scholar 
Grandchamp GM, Caro L, Shank EA. Pirated siderophores promote sporulation in Bacillus subtilis. Appl Environ Microbiol. 2017;83:e03293–16.CAS 
PubMed 
PubMed Central 

Google Scholar 
Miethke M, Klotz O, Linne U, May JJ, Beckering CL, Marahiel MA. Ferri-bacillibactin uptake and hydrolysis in Bacillus subtilis. Mol Microbiol. 2006;61:1413–27.CAS 
PubMed 

Google Scholar 
Pi H, Helmann JD. Genome-wide characterization of the fur regulatory network reveals a link between catechol degradation and bacillibactin metabolism in Bacillus subtilis. MBio. 2018;9:1–15.
Google Scholar 
Adler C, Corbalán NS, Seyedsayamdost MR, Pomares MF, de Cristóbal RE, Clardy J, et al. Catecholate siderophores protect bacteria from pyochelin toxicity. PLoS ONE. 2012;7:e46754.CAS 
PubMed 
PubMed Central 

Google Scholar 
Trottmann F, Franke J, Ishida K, García-Altares M, Hertweck C. A pair of bacterial siderophores releases and traps an intercellular signal molecule: an unusual case of natural nitrone bioconjugation. Angew Chem. 2019;58:200–4.CAS 

Google Scholar 
Mongkolsuk S, Helmann JD. Regulation of inducible peroxide stress responses. Mol Microbiol. 2002;45:9–15.CAS 
PubMed 

Google Scholar 
Cox CD, Rinehart KL, Moore ML, Cook JC. Pyochelin: novel structure of an iron-chelating growth promoter for Pseudomonas aeruginosa. Proc Natl Acad Sci USA. 1981;78:4256–60.CAS 
PubMed 
PubMed Central 

Google Scholar 
Youard ZA, Mislin GLA, Majcherczyk PA, Schalk IJ, Reimmann C. Pseudomonas fluorescens CHA0 produces enantio-pyochelin, the optical antipode of the Pseudomonas aeruginosa siderophore pyochelin. J Biol Chem. 2007;282:35546–53.CAS 
PubMed 

Google Scholar 
Ronnebaum TA, Lamb AL. Nonribosomal peptides for iron acquisition: pyochelin biosynthesis as a case study. Curr Opini Struct Biol. 2018;53:1–11.CAS 

Google Scholar 
Seipke RF, Song L, Bicz J, Laskaris P, Yaxley AM, Challis GL, et al. The plant pathogen Streptomyces scabies 87-22 has a functional pyochelin biosynthetic pathway that is regulated by TetR- and AfsR-family proteins. Microbiology. 2011;157:2681–93.CAS 
PubMed 

Google Scholar 
Gu S, Wei Z, Shao Z, Friman VP, Cao K, Yang T, et al. Competition for iron drives phytopathogen control by natural rhizosphere microbiomes. Nat Microbiol. 2020;5:1002–10.CAS 
PubMed 
PubMed Central 

Google Scholar 
Komaki H, Ichikawa N, Hosoyama A, Hamada M, Igarashi Y. In silico analysis of PKS and NRPS gene clusters in arisostatin-and kosinostatin-producers and description of Micromonospora okii sp. nov. Antibiotics. 2021;10:1447.CAS 
PubMed 
PubMed Central 

Google Scholar 
Engelbrecht A, Saad H, Gross H, Kaysser L. Natural products from Nocardia and their role in pathogenicity. Micro Physiol. 2021;31:217–32.
Google Scholar 
Inahashi Y, Zhou S, Bibb MJ, Song L, Al-Bassam MM, Bibb MJ, et al. Watasemycin biosynthesis in Streptomyces venezuelae: thiazoline C-methylation by a type B radical-SAM methylase homologue. Chem Sci. 2017;8:2823–31.CAS 
PubMed 
PubMed Central 

Google Scholar 
Song J, Qiu S, Zhao J, Han C, Wang Y, Sun X, et al. Pseudonocardia tritici sp. nov., a novel actinomycete isolated from rhizosphere soil of wheat (Triticum aestivum L.). Nat Microbiol. 2019;12:470–80.
Google Scholar 
Sayed AM, Abdel-Wahab NM, Hassan HM, Abdelmohsen UR. Saccharopolyspora: an underexplored source for bioactive natural products. J Appl Microbiol. 2020;128:314–29.CAS 
PubMed 

Google Scholar 
Nordstedt NP, Jones ML. Genomic analysis of Serratia plymuthica MBSA-MJ1: A plant growth promoting rhizobacteria that improves water stress tolerance in greenhouse ornamentals. Front Microbiol. 2021;12:653556.PubMed 
PubMed Central 

Google Scholar 
Zhalnina K, Louie KB, Hao Z, Mansoori N, Da Rocha UN, Shi S, et al. Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly. Nat Microbiol. 2018;3:470–80.CAS 
PubMed 

Google Scholar 
Takahashi Y, Malisorn K, Kanchanasin P, Phongsopitanun W, Tanasupawat S, Spain AM, et al. Actinomadura rhizosphaerae sp. nov., isolated from rhizosphere soil of the plant Azadirachta indica. ISME J 2018;68:3012–6.
Google Scholar 
Takahashi Y. Genus Kitasatospora, taxonomic features and diversity of secondary metabolites. J Antibiot. 2017;70:506–13.CAS 

Google Scholar 
Bennur T, Kumar AR, Zinjarde S, Javdekar V. Nocardiopsis species: Incidence, ecological roles and adaptations. Microbiol Res. 2015;174:33–47.PubMed 

Google Scholar 
Walterson AM, Stavrinides J. Pantoea: Insights into a highly versatile and diverse genus within the Enterobacteriaceae. J Basic Microbiol. 2015;39:33–47.
Google Scholar 
Sungthong R, Nakaew N. The genus Nonomuraea: a review of a rare actinomycete taxon for novel metabolites. J Basic Microbiol. 2015;55:554–65.PubMed 

Google Scholar 
Müller S, Strack SN, Ryan SE, Kearns DB, Kirby JR. Predation by Myxococcus xanthus induces Bacillus subtilis to form spore-filled megastructures. Appl Environ Microbiol. 2015;81:203–10.PubMed 

Google Scholar 
Straight PD, Fischbach MA, Walsh CT, Rudner DZ, Kolter R. A singular enzymatic megacomplex from Bacillus subtilis. Proc Natl Acad Sci USA. 2007;104:305–10.CAS 
PubMed 

Google Scholar 
Barger SR, Hoefler BC, Cubillos-Ruiz A, Russell WK, Russell DH, Straight PD. Imaging secondary metabolism of Streptomyces sp. Mg1 during cellular lysis and colony degradation of competing Bacillus subtilis. Antonie van Leeuwenhoek. 2012;102:435–45.CAS 
PubMed 

Google Scholar 
Ogran A, Yardeni EH, Keren-Paz A, Bucher T, Jain R, Gilhar O, et al. The plant host induces antibiotic production to select the most-beneficial colonizers. Appl Environ Microbiol. 2019;85:1–15.
Google Scholar 
Rosenberg G, Steinberg N, Oppenheimer-Shaanan Y, Olender T, Doron S, Ben-Ari J, et al. Not so simple, not so subtle: The interspecies competition between Bacillus simplex and Bacillus subtilis and its impact on the evolution of biofilms. npj Biofilms Microbiomes. 2016;2:15027.PubMed 
PubMed Central 

Google Scholar 
Straight PD, Willey JM, Kolter R. Interactions between Streptomyces coelicolor and Bacillus subtilis: Role of surfactants in raising aerial structures. J Bacteriol. 2006;188:4918–25.CAS 
PubMed 
PubMed Central 

Google Scholar 
Hoefler BC, Gorzelnik KV, Yang JY, Hendricks N, Dorrestein PC, Straight PD. Enzymatic resistance to the lipopeptide surfactin as identified through imaging mass spectrometry of bacterial competition. Proc Natl Acad Sci USA. 2012;109:13082–7.CAS 
PubMed 
PubMed Central 

Google Scholar 
Liu Y, Kyle S, Straight PD. Antibiotic stimulation of a Bacillus subtilis migratory response. mSphere 2018;3:e00586–17.CAS 
PubMed 
PubMed Central 

Google Scholar 
Qi G, Zhu F, Du P, Yang X, Qiu D, Yu Z, et al. Lipopeptide induces apoptosis in fungal cells by a mitochondria-dependent pathway. Peptides. 2010;31:1978–86.CAS 
PubMed 

Google Scholar 
McCully LM, Bitzer AS, Seaton SC, Smith LM, Silby MW. Interspecies social spreading: interaction between two sessile soil bacteria leads to emergence of surface motility. mSphere. 2019;4:e00696–18.CAS 
PubMed 
PubMed Central 

Google Scholar 
Flemming HC, Wingender J, Szewzyk U, Steinberg P, Rice SA, Kjelleberg S. Biofilms: an emergent form of bacterial life. Nat Rev Microbiol. 2016;14:563–75.CAS 
PubMed 

Google Scholar 
Townsley L, Shank EA. Natural-product antibiotics: cues for modulating bacterial biofilm formation. Trends Microbiol. 2017;25:1016–26.CAS 
PubMed 
PubMed Central 

Google Scholar 
Sun X, Xu Z, Xie J, Hesselberg-Thomsen V, Tan T, Zheng D, et al. Bacillus velezensis stimulates resident rhizosphere Pseudomonas stutzeri for plant health through metabolic interactions. ISME J. 2022;16:774–87.CAS 
PubMed 

Google Scholar 
Dumas Z, Ross-Gillespie A, Kümmerli R. Switching between apparently redundant iron-uptake mechanisms benefits bacteria in changeable environments. Proc R Soc B Biol Sci. 2013;280:20131055.
Google Scholar 
Lee N, Kim W, Chung J, Lee Y, Cho S, Jang KS, et al. Iron competition triggers antibiotic biosynthesis in Streptomyces coelicolor during coculture with Myxococcus xanthus. ISME J. 2020;14:1111–24.CAS 
PubMed 
PubMed Central 

Google Scholar 
Kramer J, Özkaya Ö, Kümmerli R. Bacterial siderophores in community and host interactions. Nat Rev Microbiol. 2020;18:152–63.CAS 
PubMed 

Google Scholar 
Niehus R, Picot A, Oliveira NM, Mitri S, Foster KR. The evolution of siderophore production as a competitive trait. Evolution. 2017;71:1443–55.CAS 
PubMed 

Google Scholar 
Ho YN, Lee HJ, Hsieh CT, Peng CC, Yang YL. Chemistry and biology of salicyl-capped siderophores. Stud Nat Prod Chem. 2018;59:431–90.Schalk IJ, Rigouin C, Godet J. An overview of siderophore biosynthesis among fluorescent Pseudomonads and new insights into their complex cellular organization. Environ Microbiol. 2020;22:1447–66.PubMed 

Google Scholar 
Deveau A, Gross H, Palin B, Mehnaz S, Schnepf M, Leblond P, et al. Role of secondary metabolites in the interaction between Pseudomonas fluorescens and soil microorganisms under iron-limited conditions. FEMS Microbiol Ecol. 2016;92:1–11.
Google Scholar 
Jenul C, Keim K, Jens J, Zeiler MJ, Schilcher K, Schurr M, et al. Pyochelin biotransformation shapes bacterial competition. bioRxiv. 2022. https://doi.org/10.1101/2022.04.18.486787.Ho YN, Hoo SY, Wang BW, Hsieh CT, Lin CC, Sun CH, et al. Specific inactivation of an antifungal bacterial siderophore by a fungal plant pathogen. ISME J. 2021;15:1858–61.CAS 
PubMed 
PubMed Central 

Google Scholar 
Lopez-Medina E, Fan D, Coughlin LA, Ho EX, Lamont IL, Reimmann C, et al. Candida albicans inhibits Pseudomonas aeruginosa virulence through suppression of pyochelin and pyoverdine biosynthesis. PLoS Pathog. 2015;11:1–34.
Google Scholar 
Meisel JD, Panda O, Mahanti P, Schroeder FC, Kim DH. Chemosensation of bacterial secondary metabolites modulates neuroendocrine signaling and behavior of C. elegans. Cell. 2014;159:267–80.CAS 
PubMed 
PubMed Central 

Google Scholar 
Finkel OM, Castrillo G, Herrera Paredes S, Salas González I, Dangl JL. Understanding and exploiting plant beneficial microbes. Curr Opin Plant Biol. 2017;38:155–63.PubMed 
PubMed Central 

Google Scholar 
Saad MM, Eida AA, Hirt H, Doerner P. Tailoring plant-associated microbial inoculants in agriculture: a roadmap for successful application. J Exp Bot. 2020;71:3878–901.CAS 
PubMed 
PubMed Central 

Google Scholar 
Ansari FA, Ahmad I. Fluorescent Pseudomonas -FAP2 and Bacillus licheniformis interact positively in biofilm mode enhancing plant growth and photosynthetic attributes. Sci Rep. 2019;9:4547.PubMed 
PubMed Central 

Google Scholar 
Domenech J, Reddy MS, Kloepper JW, Ramos B, Gutierrez-Mañero J. Combined application of the biological product LS213 with Bacillus, Pseudomonas or Chryseobacterium for growth promotion and biological control of soil-borne diseases in pepper and tomato. BioControl. 2006;51:245–58.CAS 

Google Scholar 
Powers MJ, Sanabria-Valentín E, Bowers AA, Shank EA. Inhibition of cell differentiation in Bacillus subtilis by Pseudomonas protegens. J Bacteriol. 2015;197:2129–38.CAS 
PubMed 
PubMed Central 

Google Scholar  More

Precht, W. F., Gintert, B. E., Robbart, M. L., Fura, R. & van Woesik, R. Unprecedented disease-related coral mortality in Southeastern Florida. Sci. Rep. 6, 31374 (2016).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
NOAA. Stony Coral Tissue Loss Disease Case Definition. NOAA, Silver Spring, MD 10 (2018).Aeby, G. S. et al. Pathogenesis of a tissue loss disease affecting multiple species of corals along the Florida Reef Tract. Front Mar. Sci. 6, 00678 (2019).
Google Scholar 
Landsberg, J. H. et al. Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology. Front Mar. Sci. 7, 576013 (2020).
Google Scholar 
Neely, K. L., Macaulay, K. A., Hower, E. K. & Dobler, M. A. Effectiveness of topical antibiotics in treating corals affected by Stony Coral Tissue Loss Disease. PeerJ 8, 9289 (2020).
Google Scholar 
Shilling, E. N., Combs, I. R. & Voss, J. D. Assessing the effectiveness of two intervention methods for stony coral tissue loss disease on Montastraea cavernosa. Sci. Rep. 11, 8566 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
Walker, B. K., Turner, N. R., Noren, H. K. G., Buckley, S. F. & Pitts, K. A. Optimizing stony coral tissue loss disease (SCTLD) intervention treatments on Montastraea cavernosa in an endemic zone. Front Mar. Sci. 8, 666224 (2021).
Google Scholar 
Work, T. M. et al. Viral-like particles are associated with endosymbiont pathology in Florida corals affected by stony coral tissue loss disease. Front Mar. Sci. 8, 750658 (2021).
Google Scholar 
Veglia, A. J. et al. Alphaflexivirus genomes in stony coral tissue loss disease-affected, disease-exposed, and disease-unexposed coral colonies in the U.S. Virgin Islands. Microbiol. Resource Announc. 11, e01199-e1221 (2022).CAS 

Google Scholar 
Rosales, S. M. et al. Bacterial metabolic potential and micro-eukaryotes enriched in stony coral tissue loss disease lesions. Front Mar. Sci. 8, 776859 (2022).
Google Scholar 
Rosales, S. M., Clark, A. S., Huebner, L. K., Ruzicka, R. R. & Muller, E. M. Rhodobacterales and Rhizobiales are associated with stony coral tissue loss disease and its suspected sources of transmission. Front. Microbiol. 11, 681 (2020).PubMed 
PubMed Central 

Google Scholar 
Studivan, M. S. et al. Reef sediments can act as a stony coral tissue loss disease vector. Front Mar. Sci. 8, 815698 (2022).
Google Scholar 
Meyer, J. L. et al. Microbial community shifts associated with the ongoing stony coral tissue loss disease outbreak on the Florida Reef Tract. Front. Microbiol. 10, 2244 (2019).PubMed 
PubMed Central 

Google Scholar 
Ushijima, B. et al. Disease diagnostics and potential coinfections by Vibrio coralliilyticus during an ongoing coral disease outbreak in Florida. Front. Microbiol. 11, 2682 (2020).
Google Scholar 
Meiling, S. S. et al. Variable species responses to experimental stony coral tissue loss disease (SCTLD) exposure. Front Mar. Sci. 8, 670829 (2021).
Google Scholar 
Becker, C. C., Brandt, M., Miller, C. A. & Apprill, A. Microbial bioindicators of stony coral tissue loss disease identified in corals and overlying waters using a rapid field-based sequencing approach. Environ. Microbiol. 24, 1166–1182 (2021).PubMed 

Google Scholar 
Dobbelaere, T., Muller, E. M., Gramer, L. J., Holstein, D. M. & Hanert, E. Coupled epidemio-hydrodynamic modeling to understand the spread of a deadly coral disease in Florida. Front Mar. Sci. 7, 591881 (2020).
Google Scholar 
Dobbelaere, T. et al. Connecting the dots: Transmission of stony coral tissue loss disease from the Marquesas to the Dry Tortugas. Front Mar. Sci. 9, 778938 (2022).
Google Scholar 
Muller, E. M., Sartor, C., Alcaraz, N. I. & van Woesik, R. Spatial epidemiology of the stony-coral-tissue-loss disease in Florida. Front Mar. Sci. 7, 00163 (2020).
Google Scholar 
Sharp, W. C., Shea, C. P., Maxwell, K. E., Muller, E. M. & Hunt, J. H. Evaluating the small-scale epidemiology of the stony-coral-tissue-loss-disease in the middle Florida Keys. PLoS ONE 15, e0241871 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Williamson, O. M., Dennison, C. E., O’Neil, K. L. & Baker, A. C. Susceptibility of Caribbean brain coral recruits to stony coral tissue loss disease (SCTLD). Front Mar. Sci. 9, 821165 (2022).
Google Scholar 
Noonan, K. R. & Childress, M. J. Association of butterflyfishes and stony coral tissue loss disease in the Florida Keys. Coral Reefs 39, 1581–1590 (2020).
Google Scholar 
Dahlgren, C., Pizarro, V., Sherman, K., Greene, W. & Oliver, J. Spatial and temporal patterns of stony coral tissue loss disease outbreaks in the Bahamas. Front Mar. Sci. 8, 682114 (2021).
Google Scholar 
Rosenau, N. A. et al. Considering commercial vessels as potential vectors of stony coral tissue loss disease. Front Mar. Sci. 8, 709764 (2021).
Google Scholar 
Roth, L., Kramer, P., Doyle, E. & O’Sullivan, C. Caribbean SCTLD Dashboard. Available www.agrra.org. Accessed 06 Mar 2021. (2020).Brandt, M. E. et al. The emergence and initial impact of stony coral tissue loss disease (SCTLD) in the United States Virgin Islands. Front Mar. Sci. 8, 715329 (2021).
Google Scholar 
Bailey, S. A. et al. Trends in the detection of aquatic non-indigenous species across global marine, estuarine and freshwater ecosystems: A 50-year perspective. Divers. Distrib. 26, 1780–1797 (2020).MathSciNet 

Google Scholar 
Hewitt, C. L., Gollasch, S. & Minchin, D. The vessel as a vector: Biofouling, ballast water and sediments. In Biological Invasions in Marine Ecosystems Vol. 204 (eds Rilov, G. & Crooks, J. A.) 117–131 (Springer, 2009).
Google Scholar 
Zabin, C. J. et al. Small boats provide connectivity for nonindigenous marine species between a highly invaded international port and nearby coastal harbors. Manag. Biol. Invas. 5, 97–112 (2014).
Google Scholar 
Ashton, G. V., Zabin, C. J., Davidson, I. C. & Ruiz, G. M. Recreational boats routinely transfer organisms and promote marine bioinvasions. Biol. Invas. 24, 1083–1096 (2022).
Google Scholar 
Drake, L. A., Doblin, M. A. & Dobbs, F. C. Potential microbial bioinvasions via ships’ ballast water, sediment, and biofilm. Mar. Pollut. Bull. 55, 333–341 (2007).CAS 
PubMed 

Google Scholar 
Pagenkopp Lohan, K. M., Fleischer, R. C., Carney, K. J., Holzer, K. K. & Ruiz, G. M. Amplicon-based pyrosequencing reveals high diversity of protistan parasites in ships’ ballast water: Implications for biogeography and infectious diseases. Microb. Ecol. 71, 530–542 (2015).PubMed 

Google Scholar 
Ruiz, G. M. et al. Global spread of microorganisms by ships. Nature 408, 49–50 (2000).ADS 
CAS 
PubMed 

Google Scholar 
Hwang, J., Park, S. Y., Lee, S. & Lee, T. K. High diversity and potential translocation of DNA viruses in ballast water. Mar. Pollut. Bull. 137, 449–455 (2018).CAS 
PubMed 

Google Scholar 
Shikuma, N. J. & Hadfield, M. G. Marine biofilms on submerged surfaces are a reservoir for Escherichia coli and Vibrio cholerae. Biofouling 26, 39–46 (2009).
Google Scholar 
Aguirre-Macedo, M. L. et al. Ballast water as a vector of coral pathogens in the Gulf of Mexico: The case of the Cayo Arcas coral reef. Mar. Pollut. Bull. 56, 1570–1577 (2008).CAS 
PubMed 

Google Scholar 
Bruno, J. F. The coral disease triangle. Nat. Clim. Chang. 5, 302–303 (2015).ADS 

Google Scholar 
Lakshmi, E., Priya, M. & Achari, V. S. An overview on the treatment of ballast water in ships. Ocean Coast. Manag. 199, 105296 (2021).
Google Scholar 
Petersen, N. B., Madsen, T., Glaring, M. A., Dobbs, F. C. & Jørgensen, N. O. G. Ballast water treatment and bacteria: Analysis of bacterial activity and diversity after treatment of simulated ballast water by electrochlorination and UV exposure. Sci. Total Environ. 648, 408–421 (2019).ADS 
CAS 
PubMed 

Google Scholar 
Romero-Martínez, L., Moreno-Andrés, J., Acevedo-Merino, A. & Nebot, E. Evaluation of ultraviolet disinfection of microalgae by growth modeling: Application to ballast water treatment. J. Appl. Phycol. 28, 2831–2842 (2016).
Google Scholar 
First, M. R. et al. Stratification of living organisms in ballast tanks: How do organism concentrations vary as ballast water is discharged?. Environ. Sci. Technol. 47, 4442–4448 (2013).ADS 
CAS 
PubMed 

Google Scholar 
Drake, L. A. et al. Microbial ecology of ballast water during a transoceanic voyage and the effects of open-ocean exchange. Mar. Ecol. Prog. Ser. 233, 13–20 (2002).ADS 

Google Scholar 
Khandeparker, L., Kuchi, N., Desai, D. V. & Anil, A. C. Changes in the ballast water tank bacterial community during a trans-sea voyage: Elucidation through next generation DNA sequencing. J. Environ. Manag. 273, 111018 (2020).
Google Scholar 
Ruiz, G. M., Lorda, J., Arnwine, A. & Lion, K. Shipping patterns associated with the Panama Canal: Effects on biotic exchange? In Bridging Divides Vol. 83 (eds Gollasch, S. et al.) 113–126 (Springer, 2006).
Google Scholar 
Pagano, A., Wang, G., Sánchez, O., Ungo, R. & Tapiero, E. The impact of the Panama Canal expansion on Panama’s maritime cluster. Marit. Policy Manag. 43, 164–178 (2016).
Google Scholar 
Muirhead, J. R., Minton, M. S., Miller, W. A. & Ruiz, G. M. Projected effects of the Panama Canal expansion on shipping traffic and biological invasions. Divers. Distrib. 21, 75–87 (2015).
Google Scholar 
Ros, M. et al. The Panama Canal and the transoceanic dispersal of marine invertebrates: Evaluation of the introduced amphipod Paracaprella pusilla Mayer, 1890 in the Pacific Ocean. Mar. Environ. Res. 99, 204–211 (2014).ADS 
CAS 
PubMed 

Google Scholar 
Stehouwer, P. P., Buma, A. & Peperzak, L. A comparison of six different ballast water treatment systems based on UV radiation, electrochlorination and chlorine dioxide. Environ. Technol. 36, 2094–2104 (2015).CAS 
PubMed 

Google Scholar 
Wu, Y., Li, Z., Du, W. & Gao, K. Physiological response of marine centric diatoms to ultraviolet radiation, with special reference to cell size. J. Photochem. Photobiol., B 153, 1–6 (2015).CAS 

Google Scholar 
Aguirre, L. E. et al. Diatom frustules protect DNA from ultraviolet light. Sci. Rep. 8, 5138 (2018).ADS 
PubMed 
PubMed Central 

Google Scholar 
First, M. R. & Drake, L. A. Life after treatment: Detecting living microorganisms following exposure to UV light and chlorine dioxide. J. Appl. Phycol. 26, 227–235 (2014).CAS 

Google Scholar 
Liebich, V., Stehouwer, P. P. & Veldhuis, M. Re-growth of potential invasive phytoplankton following UV-based ballast water treatment. Aquat. Invas. 7, 29–36 (2012).
Google Scholar 
Hess-Erga, O. K., Moreno-Andrés, J., Enger, Ø. & Vadstein, O. Microorganisms in ballast water: Disinfection, community dynamics, and implications for management. Sci. Total Environ. 657, 704–716 (2019).ADS 
CAS 
PubMed 

Google Scholar 
Endresen, Ø., Lee Behrens, H., Brynestad, S., Bjørn Andersen, A. & Skjong, R. Challenges in global ballast water management. Mar. Pollut. Bull. 48, 615–623 (2004).CAS 
PubMed 

Google Scholar 
Vorkapić, A., Radonja, R. & Zec, D. Cost efficiency of ballast water treatment systems based on ultraviolet irradiation and electrochlorination. Promet Traffic Transp. 30, 343–348 (2018).
Google Scholar 
King, D., Hagan, P., Riggio, M. & Wright, D. Preview of global ballast water treatment markets. J. Mar. Eng. Technol. 11, 3–15 (2012).
Google Scholar 
Wang, Z., Saebi, M., Corbett, J. J., Grey, E. K. & Curasi, S. R. Integrated biological risk and cost model analysis supports a geopolitical shift in ballast water management. Environ. Sci. Technol. 55, 12791–12800 (2021).CAS 
PubMed 

Google Scholar 
Moreno-Andrés, J. & Peperzak, L. Operational and environmental factors affecting disinfection byproducts formation in ballast water treatment systems. Chemosphere 232, 496–505 (2019).ADS 
PubMed 

Google Scholar 
David, M., Linders, J., Gollasch, S. & David, J. Is the aquatic environment sufficiently protected from chemicals discharged with treated ballast water from vessels worldwide? A decadal environmental perspective and risk assessment. Chemosphere 207, 590–600 (2018).ADS 
CAS 
PubMed 

Google Scholar 
U.S. Environmental Protection Agency. Generic protocol for the verification of ballast water treatment technology, version 5.1. Report number EPA/600/R-10/146. Washington, D.C. 157 (2010).Evans, J. S., Paul, V. J., Ushijima, B. & Kellogg, C. A. Combining tangential flow filtration and size fractionation of mesocosm water as a method for the investigation of waterborne coral diseases. Biol. Methods Protocols 7, bpac007 (2022).
Google Scholar 
Fujimoto, M. et al. Application of Ion Torrent sequencing to the assessment of the effect of alkali ballast water treatment on microbial community diversity. PLoS ONE 9, e107534 (2014).ADS 
PubMed 
PubMed Central 

Google Scholar 
United States Coast Guard. Ballast Water Best Management Practices to Reduce the Likelihood of Transporting Pathogens That May Spread Stony Coral Tissue Loss Disease. Marine Safety Information Bulletin 07–19. Washington, D.C. 2 (2019).Bolton, J. R. & Linden, K. G. Standardization of methods for fluence (UV dose) determination in bench-scale UV experiments. J. Environ. Eng. 129, 209–215 (2003).CAS 

Google Scholar 
Enochs, I. C. et al. The influence of diel carbonate chemistry fluctuations on the calcification rate of Acropora cervicornis under present day and future acidification conditions. J. Exp. Mar. Biol. Ecol. 506, 135–143 (2018).CAS 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Preprint at https://www.r-project.org/ (2019).Therneau, T. M. survival: A package for survival analysis in R. R package version 3.2–13. (2021).Kassambara, A., Kosinski, M. & Biecek, P. survminer: Drawing survival curves using “ggplot2”. R package version 0.4.9. (2021).Bakalar, G. Review of interdisciplinary devices for detecting the quality of ship ballast water. Springerplus 3, 468 (2014).PubMed 
PubMed Central 

Google Scholar 
Water Environmental Federation & American Public Health Association. Standard methods for the examination of water and wastewater. Washington, D.C. 21 (2005).Steinberg, M. K., Lemieux, E. J. & Drake, L. A. Determining the viability of marine protists using a combination of vital, fluorescent stains. Mar. Biol. 158, 1431–1437 (2011).
Google Scholar 
Oksanen, J. et al. vegan: Community ecology package. R package version 2.0–10. (2015).Martinez Arbizu, P. pairwiseAdonis: Pairwise multilevel comparison using adonis. R package version 0.4. (2020).Studivan, MS. Mstudiva/SCTLD-ballast-transmission: Stony coral tissue loss disease ballast transmission and treatment (Version 1.0), Zenodo, https://doi.org/10.5281/zenodo.6561517 (2022). More

Howe, B. M. et al. Observing the oceans acoustically. Front. Mar. Sci. 6, 426. https://doi.org/10.3389/fmars.2019.00426 (2019).Article 

Google Scholar 
Molenaar, M. M., Hill, D., Webster, P., Fidan, E. & Birch, B. First downhole application of distributed acoustic sensing for hydraulic-fracturing monitoring and diagnostics. SPE Drill. Complet. 27, 32–38. https://doi.org/10.2118/140561-PA (2012).Article 

Google Scholar 
Lindsey, N. J. et al. Fiber-optic network observations of earthquake wavefields. Geophys. Res. Lett. 44, 11792–11799. https://doi.org/10.1002/2017GLO75722 (2017).Article 
ADS 

Google Scholar 
Jousset, P. et al. Dynamic strain determination using fibre-optic cables allows imaging of seismological and structural features. Nat. Commun. 9, 1–11. https://doi.org/10.1038/s41467-018-04860-y (2018).Article 
CAS 

Google Scholar 
Ajo-Franklin, J. B. et al. Distributed acoustic sensing using dark fiber for near-surface characterization and broadband seismic event detection. Sci. Rep. 9, 1–14. https://doi.org/10.1038/s41598-018-36675-8 (2019).Article 
CAS 

Google Scholar 
Williams, E. F. et al. Distributed sensing of microseisms and teleseisms with submarine dark fibers. Nat. Commun. 10, 1–11. https://doi.org/10.1038/s41467-019-13262-7 (2019).Article 
CAS 

Google Scholar 
Lindsey, N. J., Dawe, T. C. & Ajo-Franklin, J. B. Illuminating seafloor faults and ocean dynamics with dark fiber distributed acoustic sensing. Science 366, 1103–1107. https://doi.org/10.1126/science.aay5881 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Sladen, A. et al. Distributed sensing of earthquakes and ocean-solid Earth interactions on seafloor telecom cables. Nat. Commun. 10, 5777. https://doi.org/10.1038/s41467-019-13793-z (2019).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Williams, E. F. et al. Surface gravity wave interferometry and ocean current monitoring with ocean-bottom DAS. J. Geophys. Res. Oceans 127, e2021JC018375. https://doi.org/10.1029/2021JC018375 (2022).Article 
ADS 

Google Scholar 
Zhan, Z. et al. Optical polarization-based seismic and water wave sensing on transoceanic cables. Science 371, 931–936. https://doi.org/10.1126/science.abe6648 (2021).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Waagaard, O. H. et al. Real-time low noise distributed acoustic sensing in 171 km low loss fiber. OSA Contin. 4, 688–701. https://doi.org/10.1364/OSAC.408761 (2021).Article 
CAS 

Google Scholar 
Rivet, D., de Cacqueray, B., Sladen, A., Roques, A. & Calbris, G. Preliminary assessment of ship detection and trajectory evaluation using distributed acoustic sensing on an optical fiber telecom cable. J. Acoust. Soc. Am. 149, 2615–2627. https://doi.org/10.1121/10.0004129 (2021).Article 
ADS 
PubMed 

Google Scholar 
Taweesintananon, K., Landrø, M., Brenne, J. K. & Haukanes, A. Distributed acoustic sensing for near-surface imaging using submarine telecommunication cable: a case study in the Trondheimsfjord, Norway. Geophysics 86, B303–B320. https://doi.org/10.1190/geo2020-0834.1 (2021).Article 

Google Scholar 
Matsumoto, H. et al. Detection of hydroacoustic signals on a fiber-optic submarine cable. Sci. Rep. 11, 2797. https://doi.org/10.1038/s41598-021-82093-8 (2021).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Bouffaut, L. et al. Eavesdropping at the speed of light: Distributed acoustic sensing of baleen whales in the Arctic. Front. Mar. Sci. 9, 901348. https://doi.org/10.3389/fmars.2022.901348 (2022).Article 

Google Scholar 
Jones, N. The quest for quieter seas. Nature 568, 158–161. https://doi.org/10.1038/d41586-019-01098-6 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Williams, R. et al. Chronic ocean noise and cetacean population models. J. Cetacean Res. Manag. 21, 85–94. https://doi.org/10.47536/jcrm.v21i1.202 (2020).Article 

Google Scholar 
Roman, J. et al. Whales as marine ecosystem engineers. Front. Ecol. Environ. 12, 377–385. https://doi.org/10.1890/130220 (2014).Article 

Google Scholar 
Pershing, A. J., Christensen, L. B., Record, N. R., Sherwood, G. D. & Stetson, P. B. The impact of whaling on the ocean carbon cycle: Why bigger was better. PLoS ONE 5, 1–9. https://doi.org/10.1371/journal.pone.0012444 (2010).Article 
CAS 

Google Scholar 
IUCN – SSC Cetacean Specialist Group. Status of the World’s cetaceans (2021). https://iucn-csg.org/status-of-the-worlds-cetaceans/.Bailey, H. et al. Behavioural estimation of blue whale movements in the Northeast Pacific from state-space model analysis of satellite tracks. Endanger. Species Res. 10, 93–106. https://doi.org/10.3354/esr00239 (2010).Article 

Google Scholar 
Thomas, P. O., Reeves, R. R. & Brownell, R. L. Jr. Status of the world’s baleen whales. Mar. Mamm. Sci. 32, 682–734. https://doi.org/10.1111/mms.12281 (2016).Article 

Google Scholar 
Grigoli, F. et al. Current challenges in monitoring, discrimination, and management of induced seismicity related to underground industrial activities: A European perspective. Rev. Geophys. 55, 310–340. https://doi.org/10.1002/2016RG000542 (2017).Article 
ADS 

Google Scholar 
Bigg, G. R. & Hanna, E. Impacts and effects of ocean warming on the weather. In: Laffoley, D. & Baxter, J. M. (eds.) Explaining ocean warming: Causes, scale, effects and consequences, 359–372, https://doi.org/10.2305/IUCN.CH.2016.08.en (International Union for Conservation of Nature and Natural Resources (IUCN), Gland, Switzerland, 2016).Hartog, A. H. An Introduction to Distributed Optical Fibre Sensors 1st edn. (CRC Press, 2017). https://doi.org/10.1201/9781315119014.Book 

Google Scholar 
Lin, J., Fang, S., Li, X., Wu, R. & Zheng, H. Seismological observations of ocean swells induced by Typhoon Megi using dispersive microseisms recorded in coastal areas. Remote Sens.https://doi.org/10.3390/rs10091437 (2018).Article 

Google Scholar 
Munk, W. H., Miller, G. R., Snodgrass, F. E., Barber, N. F. & Deacon, G. E. R. Directional recording of swell from distant storms. Philos. Trans. R. Soc. Lond. Ser. A Math. Phys. Sci. 255, 505–584. https://doi.org/10.1098/rsta.1963.0011 (1963).Article 
ADS 

Google Scholar 
Mellinger, D. K. & Clark, C. W. Blue whale (balaenoptera musculus) sounds from the North Atlantic. J. Acoust. Soc. Am. 114, 1108–1119. https://doi.org/10.1121/1.1593066 (2003).Article 
ADS 
PubMed 

Google Scholar 
Ou, H., Au, W. W., Van Parijs, S., Oleson, E. M. & Rankin, S. Discrimination of frequency-modulated baleen whale downsweep calls with overlapping frequencies. J. Acoust. Soc. Am. 137, 3024–3032. https://doi.org/10.1121/1.4919304 (2015).Article 
ADS 
PubMed 

Google Scholar 
Saito, T. & Tsushima, H. Synthesizing ocean bottom pressure records including seismic wave and tsunami contributions: Toward realistic tests of monitoring systems. J. Geophys. Res. Solid Earth 121, 8175–8195. https://doi.org/10.1002/2016JB013195 (2016).Article 
ADS 

Google Scholar 
Rørstadbotnen, R. A. et al. Analysis of a local earthquake in the Arctic using a 120 km long fibre-optic cable. In 83rd EAGE Annual Conference & Exhibition, vol. 2022 of Conference Proceedings, 1–5, https://doi.org/10.3997/2214-4609.202210404 (European Association of Geoscientists & Engineers, 2022).Bromirski, P. D. & Duennebier, F. K. The near-coastal microseism spectrum: Spatial and temporal wave climate relationships. J. Geophys. Res. Solid Earth 107, ESE 5-1-20. https://doi.org/10.1029/2001JB000265 (2002).Article 

Google Scholar 
Pasch, R. J. National hurricane center tropical cyclone report: Tropical storm Edouard (AL052020). Technical report, National Oceanic and Atmospheric Administration (2021). https://www.nhc.noaa.gov/data/tcr/AL052020_Edouard.pdf.Gobato, R. & Heidari, A. Cyclone Bomb hits Southern Brazil in 2020. J. Atmos. Sci. Res. 3, 8–12. https://doi.org/10.30564/jasr.v3i3.2163 (2020).Article 

Google Scholar 
Khalid, A., de Lima, Ad. S., Cassalho, F., Miesse, T. & Ferreira, C. Hydrodynamic and wave responses during storm surges on the Southern Brazilian Coast: A real-time forecast system. Water 12, 3397. https://doi.org/10.3390/w12123397 (2020).Article 

Google Scholar 
Ćirić, J. Weather warning for Central Highland, Northwest Iceland (2020). https://www.icelandreview.com/travel/weather-warning-for-central-highland-northwest-iceland/.Schoeman, R. P., Patterson-Abrolat, C. & Plön, S. A global review of vessel collisions with marine animals. Front. Mar. Sci. 7, 292. https://doi.org/10.3389/fmars.2020.00292 (2020).Article 

Google Scholar 
Ringrose, P. S. et al. Storage of carbon dioxide in saline aquifers: Physicochemical processes, key constraints, and scale-up potential. Annu. Rev. Chem. Biomol. Eng. 12, 471–494. https://doi.org/10.1146/annurev-chembioeng-093020-091447 (2021).Article 
CAS 
PubMed 

Google Scholar 
Nishimura, T. et al. Source location of volcanic earthquakes and subsurface characterization using fiber-optic cable and distributed acoustic sensing system. Sci. Rep. 11, 6319. https://doi.org/10.1038/s41598-021-85621-8 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ardhuin, F. & Herbers, T. H. C. Noise generation in the solid Earth, oceans and atmosphere, from nonlinear interacting surface gravity waves in finite depth. J. Fluid Mech. 716, 316–348. https://doi.org/10.1017/jfm.2012.548 (2013).Article 
ADS 
MATH 

Google Scholar 
Airy, G. B. Encyclopaedia Metropolitana (1817–1845), vol. 3 of Mixed Sciences, chap. Tides and waves (London, 1841).Craik, A. D. The origins of water wave theory. Annu. Rev. Fluid Mech. 36, 1–28. https://doi.org/10.1146/annurev.fluid.36.050802.122118 (2004).Article 
ADS 
MathSciNet 
MATH 

Google Scholar 
Matsumoto, H., Inoue, S. & Ohmachi, T. Dynamic response of bottom water pressure due to the 2011 Tohoku earthquake. J. Disaster Res. 7, 468–475. https://doi.org/10.20965/jdr.2012.p0468 (2012).Article 

Google Scholar 
Landrø, M. & Hatchell, P. Normal modes in seismic data: Revisited. Geophysics 77, W27–W40. https://doi.org/10.1190/geo2011-0094.1 (2012).Article 
ADS 

Google Scholar  More

Urbanization is fast progressing in the Global South, requiring new solutions for infrastructure, services, industrial development and land and energy use for these regions. In this context, fast-growing cities in Africa can take on a leadership role in driving climate change mitigation and adaptation, disaster risk reduction and sustainable development.
Credit: Stefan Rotter / Alamy Stock PhotoCities in Africa and elsewhere in the Global South continue to grapple with the challenge of delivering equitable services, infrastructure, housing and action to respond to climate change extremes and disasters. One well-known problem is a mismatch between the pace of urban growth and the slower development of basic services and critical infrastructure. This results in, for example, deficient sanitation, water supply systems and localized waste management for large parts of the population, which in turn contribute substantially to heightened poverty and inequality. For inclusive, equitable, prosperous and climate-resilient cities, urban management needs to integrate low-income communities into the urban economy by ensuring access to water, sanitation, energy transition, waste management, poverty reduction and by improving resilience through innovative solutions.
Credit: Patrick J. Endres/Corbis Documentary/GettySuch an equitable urban transition requires changes in the urban infrastructure, and land and energy use, as well as water and ecosystem management. The key research question in this field is to find ways to ensure city-wide access to infrastructure and services, while minimizing emissions and resource use, and building resilience to climate change impacts. In this regard, cities in the Global South and Africa in particular can serve as examples for other parts of the world as they have the potential to adopt disruptive, innovative yet practical solutions to low emissions, resource minimization and resilience building.
Credit: Nature Picture Library / Alamy Stock PhotoFor example, rapid urbanization creates the opportunity to develop economic structures in African cities that strongly integrate waste by promoting recovery, recycling, re-use and repair for lengthening lifecycles. Such a circular economy can create business opportunities, while also reducing resource use, thus creating a pathway for sustainable development. Another potential solution is hybrid systems for urban water management that are off-grid and utilize multiple water sources and treatment but that can also connect to centralized water systems. Business models for micro-to-medium enterprises have the potential to integrate some of the low-income groups through these kinds of technology and building social resilience.
Credit: Images of Africa Photobank / Alamy Stock PhotoThese examples are part of a broader assessment of urban infrastructure innovations, their disruption of centralized systems and rethinking of urban form for more compact, walkable, co-located land use for low carbon intensity towards net-zero cities. However, to translate research on these new solutions into action, a shift is necessary in the planning, governing and managing of cities so as to allow for opportunities for leapfrogging to emerge and expand the possibilities of urban development for inclusive and resilient African cities. More

Bascompte, J. & Jordano, P. Mutualistic Networks (Princeton Univ. Press, Princeton, NJ, 2013).Cordeiro, N. J. & Howe, H. F. Forest fragmentation severs mutualism between seed dispersers and an endemic African tree. Proc. Natl Acad. Sci. USA 100, 14052–14056 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
Wandrag, E. M., Dunham, A. E., Duncan, R. P. & Rogers, H. S. Seed dispersal increases local species richness and reduces spatial turnover of tropical tree seedlings. Proc. Natl Acad. Sci. USA 114, 10689–10694 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Fahrig, L. Effects of habitat fragmentation on biodiversity. Annu. Rev. Ecol. Evol. Syst. 34, 487–515 (2003).
Google Scholar 
Fahrig, L. Ecological responses to habitat fragmentation per se. Annu. Rev. Ecol. Evol. Syst. 48, 1–23 (2017).
Google Scholar 
Haddad, N. M. et al. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Sci. Adv. 1, e1500052 (2015).PubMed 
PubMed Central 

Google Scholar 
Fricke, E. C. & Svenning, J. C. Accelerating homogenization of the global plant-frugivore meta-network. Nature 585, 74–78 (2020).CAS 
PubMed 

Google Scholar 
Fontúrbel, F. E. et al. Meta-analysis of anthropogenic habitat disturbance effects on animal-mediated seed dispersal. Glob. Change Biol. 21, 3951–3960 (2015).
Google Scholar 
Poisot, T. et al. Global knowledge gaps in species interaction networks data. J. Biogeogr. 48, 1552–1563 (2021).
Google Scholar 
Hortal, J. et al. Seven shortfalls that beset large-scale knowledge of biodiversity. Annu. Rev. Ecol. Evol. Syst. 46, 523–549 (2015).
Google Scholar 
Magrach, A., Laurance, W. F., Larrinaga, A. R. & Santamaria, L. Meta-analysis of the effects of forest fragmentation on interspecific interactions. Conserv. Biol. 28, 1342–1348 (2014).PubMed 

Google Scholar 
Pocock, M. J. O., Evans, D. M. & Memmott, J. The robustness and restoration of a network of ecological networks. Science 335, 973–977 (2012).CAS 
PubMed 

Google Scholar 
Tylianakis, J. M., Didham, R. K., Bascompte, J. & Wardle, D. A. Global change and species interactions in terrestrial ecosystems. Ecol. Lett. 11, 1351–1363 (2008).PubMed 

Google Scholar 
de Assis Bomfim, J., Guimarães, P. R. Jr., Peres, C. A., Carvalho, G. & Cazetta, E. Local extinctions of obligate frugivores and patch size reduction disrupt the structure of seed dispersal networks. Ecography 41, 1899–1909 (2018).
Google Scholar 
Emer, C. et al. Seed dispersal networks in tropical forest fragments: Area effects, remnant species, and interaction diversity. Biotropica 52, 81–89 (2020).
Google Scholar 
Evans, D. M., Pocock, M. J. O. & Memmott, J. The robustness of a network of ecological networks to habitat loss. Ecol. Lett. 16, 844–852 (2013).PubMed 

Google Scholar 
Grass, I., Jauker, B., Steffan-Dewenter, I., Tscharntke, T. & Jauker, F. Past and potential future effects of habitat fragmentation on structure and stability of plant-pollinator and host-parasitoid networks. Nat. Ecol. Evol. 2, 1408–1417 (2018).PubMed 

Google Scholar 
Neff, F. M. et al. Changes in plant-herbivore network structure and robustness along land-use intensity gradients in grasslands and forests. Sci. Adv. 7, eabf3985 (2021).PubMed 
PubMed Central 

Google Scholar 
Dunne, J. A., Williams, R. J. & Martinez, N. D. Network structure and biodiversity loss in food webs: robustness increases with connectance. Ecol. Lett. 5, 558–567 (2002).
Google Scholar 
James, A., Pitchford, J. W. & Plank, M. J. Disentangling nestedness from models of ecological complexity. Nature 487, 227–230 (2012).CAS 
PubMed 

Google Scholar 
Jordano, P. Patterns of mutualistic interactions in pollination and seed dispersal: connectance, dependence asymmetries, and coevolution. Am. Nat. 129, 657–677 (1987).
Google Scholar 
Vieira, M. C. & Almeida-Neto, M. A simple stochastic model for complex coextinctions in mutualistic networks: robustness decreases with connectance. Ecol. Lett. 18, 144–152 (2015).PubMed 

Google Scholar 
Olesen, J. M., Bascompte, J., Dupont, Y. L. & Jordano, P. The modularity of pollination networks. Proc. Natl Acad. Sci. USA 104, 19891–19896 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
Gilarranz, L. J., Rayfield, B., Liñán-Cembrano, G., Bascompte, J. & Gonzalez, A. Effects of network modularity on the spread of perturbation impact in experimental metapopulations. Science 357, 199–201 (2017).CAS 
PubMed 

Google Scholar 
Liu, H. et al. Geographic variation in the robustness of pollination networks is mediated by modularity. Glob. Ecol. Biogeogr. 30, 1447–1460 (2021).
Google Scholar 
Bascompte, J., Jordano, P., Melián, C. J. & Olesen, J. M. The nested assembly of plant-animal mutualistic networks. Proc. Natl Acad. Sci. USA 100, 9383–9387 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
Bastolla, U. et al. The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature 458, 1018–1020 (2009).CAS 
PubMed 

Google Scholar 
Memmott, J., Waser, N. M. & Price, M. V. Tolerance of pollination networks to species extinctions. Proc. R. Soc. B. 271, 2605–2611 (2004).PubMed 
PubMed Central 

Google Scholar 
Delmas, E. et al. Analysing ecological networks of species interactions. Biol. Rev. 9, 16–36 (2019).
Google Scholar 
Fortuna, M. A. et al. Nestedness versus modularity in ecological networks: two sides of the same coin? J. Anim. Ecol. 79, 811–817 (2010).PubMed 

Google Scholar 
Song, C., Rohr, R. P. & Saavedra, S. Why are some plant-pollinator networks more nested than others? J. Anim. Ecol. 86, 1417–1424 (2017).PubMed 

Google Scholar 
Schleuning, M., Böhning-Gaese, K., Dehling, D. M. & Burns, K. C. At a loss for birds: insularity increases asymmetry in seed-dispersal networks. Glob. Ecol. Biogeogr. 23, 385–394 (2014).
Google Scholar 
Aizen, M. A., Sabatino, M. & Tylianakis, J. M. Specialization and rarity predict nonrandom loss of interactions from mutualist networks. Science 335, 1486–1489 (2012).CAS 
PubMed 

Google Scholar 
Fortuna, M. A. & Bascompte, J. Habitat loss and the structure of plant-animal mutualistic networks. Ecol. Lett. 9, 278–283 (2006).
Google Scholar 
Spiesman, B. J. & Inouye, B. D. Habitat loss alters the architecture of plant-pollinator interaction networks. Ecology 94, 2688–2696 (2013).PubMed 

Google Scholar 
Traveset, A. et al. Bird-flower visitation networks in the Galápagos unveil a widespread interaction release. Nat. Commun. 6, 6376 (2015).CAS 
PubMed 

Google Scholar 
Thébault, E. & Fontaine, C. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329, 853–856 (2010).PubMed 

Google Scholar 
Monteiro, E. C. S., Pizo, M. A., Vancine, M. H. & Ribeiro, M. C. Forest cover and connectivity have pervasive effects on the maintenance of evolutionary distinct interactions in seed dispersal networks. Oikos 2022, e08240 (2022).
Google Scholar 
Whittaker, R. J., Fernández-Palacios, J. M., Matthews, T. J., Borregaard, M. K. & Triantis, K. A. Island biogeography: taking the long view of nature’s laboratories. Science 357, eaam8326 (2017).PubMed 

Google Scholar 
Vizentin-Bugoni, J. et al. Structure, spatial dynamics, and stability of novel seed dispersal mutualistic networks in Hawai’i. Science 364, 78–82 (2019).CAS 
PubMed 

Google Scholar 
Diamond, J. Dammed experiments! Science 294, 1847–1848 (2001).CAS 
PubMed 

Google Scholar 
Jones, I. L., Bunnefeld, N., Jump, A. S., Peres, C. A. & Dent, D. H. Extinction debt on reservoir land-bridge islands. Biol. Conserv. 199, 75–83 (2016).
Google Scholar 
Wu, J., Huang, J., Han, X., Xie, Z. & Gao, X. Three-Gorges dam–experiment in habitat Fragmentation? Science 300, 1239–1240 (2003).CAS 
PubMed 

Google Scholar 
Wilson, M. C. et al. Habitat fragmentation and biodiversity conservation: key findings and future challenges. Landsc. Ecol. 31, 219–227 (2016).
Google Scholar 
Trøjelsgaard, K. et al. Island biogeography of mutualistic interaction networks. J. Biogeogr. 40, 2020–2031 (2013).
Google Scholar 
Emer, C., Venticinque, E. M. & Fonseca, C. R. Effects of dam-induced landscape fragmentation on amazonian ant-plant mutualistic networks. Conserv. Biol. 27, 763–773 (2013).PubMed 

Google Scholar 
Zhu, C. et al. Arboreal camera trapping: a reliable tool to monitor plant-frugivore interactions in the trees on large scales. Remote Sens. Ecol. Conserv. 8, 92–104 (2022).
Google Scholar 
Zhu, C., Li, W., Wang, D., Ding, P. & Si, X. Plant-frugivore interactions revealed by arboreal camera trapping. Front. Ecol. Environ. 19, 149–151 (2021).
Google Scholar 
Galiana, N. et al. The spatial scaling of species interaction networks. Nat. Ecol. Evol. 2, 782–790 (2018).PubMed 

Google Scholar 
Hanski, I., Zurita, G. A., Bellocq, M. I. & Rybicki, J. Species-fragmented area relationship. Proc. Natl Acad. Sci. USA 110, 12715–12720 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Sugiura, S. Species interactions-area relationships: biological invasions and network structure in relation to island area. Proc. R. Soc. B. 277, 1807–1815 (2010).PubMed 
PubMed Central 

Google Scholar 
Galiana, N. et al. Ecological network complexity scales with area. Nat. Ecol. Evol. 6, 307–314 (2022).PubMed 

Google Scholar 
Santos, M., Cagnolo, L., Roslin, T., Marrero, H. J. & Vázquez, D. P. Landscape connectivity explains interaction network patterns at multiple scales. Ecology 100, e02883 (2019).PubMed 

Google Scholar 
Si, X., Pimm, S. L., Russell, G. J. & Ding, P. Turnover of breeding bird communities on islands in an inundated lake. J. Biogeogr. 41, 2283–2292 (2014).
Google Scholar 
Si, X. et al. Functional and phylogenetic structure of island bird communities. J. Anim. Ecol. 86, 532–542 (2017).PubMed 

Google Scholar 
Rosenfeld, J. S. Functional redundancy in ecology and conservation. Oikos 98, 156–162 (2002).
Google Scholar 
Sebastián-González, E. Drivers of species’ role in avian seed-dispersal mutualistic networks. J. Anim. Ecol. 86, 878–887 (2017).PubMed 

Google Scholar 
Donoso, I. et al. Downsizing of animal communities triggers stronger functional than structural decay in seed-dispersal networks. Nat. Commun. 11, 1582 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Kaiser-Bunbury, C. N., Muff, S., Memmott, J., Müller, C. B. & Caflisch, A. The robustness of pollination networks to the loss of species and interactions: a quantitative approach incorporating pollinator behaviour. Ecol. Lett. 13, 442–452 (2010).PubMed 

Google Scholar 
Dalsgaard, B. et al. Opposed latitudinal patterns of network-derived and dietary specialization in avian plant-frugivore interaction systems. Ecography 40, 1395–1401 (2017).
Google Scholar 
Borrvall, C., Ebenman, B. & Jonsson, T. Biodiversity lessens the risk of cascading extinction in model food webs. Ecol. Lett. 3, 131–136 (2000).
Google Scholar 
Liao, J. et al. Robustness of metacommunities with omnivory to habitat destruction: disentangling patch fragmentation from patch loss. Ecology 98, 1631–1639 (2017).PubMed 

Google Scholar 
Rumeu, B. et al. Predicting the consequences of disperser extinction: richness matters the most when abundance is low. Funct. Ecol. 31, 1910–1920 (2017).
Google Scholar 
Wong, B. B. M. & Candolin, U. Behavioral responses to changing environments. Behav. Ecol. 26, 665–673 (2015).
Google Scholar 
Betts, M. G. et al. Extinction filters mediate the global effects of habitat fragmentation on animals. Science 366, 1236–1239 (2019).CAS 
PubMed 

Google Scholar 
Menke, S., Böhning-Gaese, K. & Schleuning, M. Plant-frugivore networks are less specialized and more robust at forest–farmland edges than in the interior of a tropical forest. Oikos 121, 1553–1566 (2012).
Google Scholar 
Redhead, J. W. et al. Potential landscape-scale pollinator networks across Great Britain: structure, stability and influence of agricultural land cover. Ecol. Lett. 21, 1821–1832 (2018).PubMed 

Google Scholar 
Si, X. et al. The importance of accounting for imperfect detection when estimating functional and phylogenetic community structure. Ecology 99, 2103–2112 (2018).PubMed 

Google Scholar 
Schoereder, J. H. et al. Should we use proportional sampling for species-area studies? J. Biogeogr. 31, 1219–1226 (2004).
Google Scholar 
Liu, J. et al. The distribution of plants and seed dispersers in response to habitat fragmentation in an artificial island archipelago. J. Biogeogr. 46, 1152–1162 (2019).
Google Scholar 
Olson, E. R. et al. Arboreal camera trapping for the Critically Endangered greater bamboo lemur Prolemur simus. Oryx 46, 593–597 (2012).
Google Scholar 
Li, H.-D. et al. The functional roles of species in metacommunities, as revealed by metanetwork analyses of bird-plant frugivory networks. Ecol. Lett. 23, 1252–1262 (2020).PubMed 

Google Scholar 
Snow, B. & Snow, D. Birds and berries: a study of an ecological interaction (T & AD Poyser, Calton, 1988).Si, X., Kays, R. & Ding, P. How long is enough to detect terrestrial animals? Estimating the minimum trapping effort on camera traps. PeerJ 2, e374 (2014).PubMed 
PubMed Central 

Google Scholar 
Vázquez, D. P. et al. Species abundance and asymmetric interaction strength in ecological networks. Oikos 116, 1120–1127 (2007).
Google Scholar 
Chao, A. & Jost, L. Coverage-based rarefaction and extrapolation: standardizing samples by completeness rather than size. Ecology 93, 2533–2547 (2012).PubMed 

Google Scholar 
Hsieh, T. C., Ma, K. H. & Chao, A. iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol. 7, 1451–1456 (2016).
Google Scholar 
Beckett, S. J. Improved community detection in weighted bipartite networks. R. Soc. Open. Sci. 3, 140536 (2016).PubMed 
PubMed Central 

Google Scholar 
Almeida-Neto, M. & Ulrich, W. A straightforward computational approach for measuring nestedness using quantitative matrices. Environ. Modell. Softw. 26, 173–178 (2011).
Google Scholar 
Scherber, C. et al. Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment. Nature 468, 553–556 (2010).CAS 
PubMed 

Google Scholar 
Schleuning, M. et al. Ecological networks are more sensitive to plant than to animal extinction under climate change. Nat. Commun. 7, 13965 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Humphreys, A. M., Govaerts, R., Ficinski, S. Z., Nic Lughadha, E. & Vorontsova, M. S. Global dataset shows geography and life form predict modern plant extinction and rediscovery. Nat. Ecol. Evol. 3, 1043–1047 (2019).PubMed 

Google Scholar 
Dirzo, R. et al. Defaunation in the Anthropocene. Science 345, 401–406 (2014).CAS 
PubMed 

Google Scholar 
Rogers, H. S., Donoso, I., Traveset, A. & Fricke, E. C. Cascading impacts of seed disperser loss on plant communities and ecosystems. Annu. Rev. Ecol. Evol. Syst. 52, 641–666 (2021).
Google Scholar 
Dormann, C. F., Gruber, B. & Fründ, J. Introducing the bipartite package: analysing ecological networks. R News 8, 8–11 (2008).
Google Scholar 
Patefield, W. M. Algorithm AS 159: An efficient method of generating random R × C tables with given row and column totals. Appl. Stat. 30, 91–97 (1981).
Google Scholar 
Lefcheck, J. S. piecewiseSEM: piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).
Google Scholar 
Kabacoff, R. R in Action: Data Analysis and Graphics with R (Manning Publications Co, 2015).R Core Team. R: A Language And Environment For Statistical Computing (R Foundation for Statistical Computing, 2021). More

Study areaSituated in western India’s southwestern part of the Gujarat state, the Saurashtra region typically represents the semi-arid Gujarat-Rajputana province 4B23, which covers 11 out of 33 districts of the state. The region forms a rocky tableland (altitude 300–600 m) fringed by coastal plains with an undulating central plain broken by hills and dissected by various rivers that flow in all directions24. With the longest coastline (~ 1600 km) in India, Gujarat is endowed with rich coastal biodiversity25,26. The Saurashtra coast in Gujarat is encircled by the open sea between two Gulfs (68° 58′–71° 30′ N and 22° 15′–20° 50′ E) and divided into two segments, viz. the southwestern coast from Dwarka to Diu (~ 300 km stretch) and south-eastern coast from Diu to Bhavnagar (~ 250 km stretch)26.The Asiatic Lion Landscape covers an area of ~ 30,000 km2 (permanent lion distribution range: ~ 16,000 km2; visitation record range: ~ 14,000 km2) of varied habitat types within Saurashtra. The landscape includes five protected areas (Gir National Park, Gir Wildlife Sanctuary, Paniya Wildlife Sanctuary, Mitiyala Wildlife Sanctuary, and Girnar Wildlife Sanctuary) and other forest classes (reserved forests, protected forests, and unclassed forests).The coastal habitats extend across the districts of Bhavnagar, Amreli, Gir-Somnath, and Junagadh (Fig. 1). Within these districts (Fig. 1), the tehsils (sub-divisions/taluka) of Mangrol, Malia, Patan-Veraval, Sutrapada, Kodinar and Una are categorized under the southwestern coast (hereafter western coastal habitat), Jafrabad, Rajula, form the south-eastern coast and Mahuva and Talaja constitute the Bhavnagar coast and represent distinct lion range units (Fig. 1). The total area covered in the study is 2843 km2 on the eastern coast and 1413 km2 on the western coast (Fig. 1).The Saurashtra region is bestowed with three distinct seasons, viz. dry and hot summer (March–June), monsoon (July–October), and primarily dry winter (November–February). It receives a mean annual rainfall of ~ 600 mm, with most rainfall during the southwest monsoon27. The mean maximum and minimum temperatures are 34 °C and 19 °C, respectively28. There is a 110 km2 stretch of forests along the coast. The rest of the areas are multi-use consisting of private, industrial, pastoral and wastelands of varied ownerships. The natural vegetation primarily consists of Prosopis juliflora and Casuarina equistsetifolia. On the beach and dune areas, vegetation such as Ipomea pescaprae, Sporobolus trinules, Fimrystylis sp., Crotalaria sp., and Euphorbia nivuleria29. The mudflats along the coast are restricted to Talaja, Mahuva, Pipavav Port, Jafrabad creek, and Porbandar, sparsely covered by the Avicennia marina29. Fisheries, agriculture, horticulture, livestock rearing, and some large- and small-scale industries are the leading economies in the coastal belt.Coastal segments are characterized by the variety of vegetation, sandy beaches, small cliffs, wave-cut platforms, open and submerged dunes, minor estuaries, embankments, and transition from the open sea to gulf environment with tidal mud26,29 and also support a diverse assemblage of biodiversity25. This biodiversity is further enriched by several perennial/ephemeral rivers originating from the Gir PA (Shetrunji, Machundari, Raval, Ardak, Bhuvatirth, Shinghoda, Hiran, Saraswati, etc.)12. These rivers meet the sea at different sections of the coast, forming prominent coastal ecosystems25. The riverine tracts act as important corridors for wildlife movement9,12,30. Dispersing through these corridors, lions have started inhabiting these coastal habitats30,31.MethodsAll the research activities involved in this study on Asiatic lions were carried out after taking due permission from the Ministry of Environment, Forests & Climate Change (MoEF&CC), Government of India (Letter No.: F. No. 1-50/2018 WL) and Principal Chief Conservator of Forests (Wildlife) & Chief Wildlife Warden, Gujarat State, Gandhinagar (Letter No.: WLP 26B 781-83/2019-20). Procedures and protocols were followed as per the Standard Operating Procedures of the Gujarat Forest Department, Government of Gujarat, concerning the handling of wild animals. Qualified and experienced veterinarians and their team carried out all procedures related to radio-collaring. Moreover, the study is reported in accordance with ‘Animal Research: Reporting of In Vivo Experiments’ (ARRIVE) guidelines as applicable.A long-term lion monitoring project was initiated in 2019 by the Gujarat Forest Department to understand the movement patterns and ecology of lions in the Asiatic Lion Landscape. Looking at the heterogeneity and vastness of the coastal areas, ten individuals were carefully selected for satellite radio-collaring based on their frequent movement in different coastal habitats and monitored from 2019 to 2021.The lions were deployed with Vertex Plus GPS Collars (Vectronics Aerospace GmbH, Berlin, Germany) that weighed less than three per cent of the individual’s body weight, irrespective of age and sex. The lions were immobilized using a combination of Ketamine hydrochloride (2.2 mg per kg body weight; Ketamine, Biowet, Pulawy) and Xylazine hydrochloride (1.1 mg per kg body weight; Xylaxil, Brilliant Bio Pharma Pvt. Ltd., Telangana)32 administered intramuscularly using a gas-powered Telinject™ G.U.T 50 (Telinject Inc., Dudenhofen, Germany) dart delivery system. A blindfold was placed to protect the eyes and decrease visual stimuli33,34. Each sedated individual was sexed, aged, and measured as per the standard operating procedure (SOP) of the Gujarat Forest Department, Government of Gujarat, and recorded the data in the trapping datasheet. The radio-collars were deployed considering the neck girth of the individual, ensuring free movement of it so as not to hamper the individual’s routine activities. After deploying the radio-collar, we used the specific antidote for Xylazine, i.e., Yohimbine hydrochloride (0.1–0.15 mg per kg body weight; Yohimbe, Equimed, USA) intravenously, resulting in the total recovery of immobilized individuals32 within 5–10 min. The individuals were intensively monitored for 72 h and, after that, regularly monitored throughout the functional period of the radio-collars. The entire radio-collaring exercise was carried out by trained and experienced veterinary officers and their teams that constituted wildlife health care personnel and field staff.Each collar had a unique VHF and UHF frequency. The radio-collars were equipped with a programmable GPS schedule and configured to record the location fixes at every hour and provided the data through the constellation of low-earth-orbit Iridium satellite data service (Iridium Communications Inc., Virginia, USA) at four-hour intervals after getting activated. The data logs included location fixes in degree decimal format (latitude/longitude), speed (km/hour), altitude (meters above mean sea level), UTC timestamp (dd-mm-yyyy h:m:s), direction (degrees), and temperature (Celsius). Radio-collars were equipped with mortality sensors and a programmable drop-off activation system. Gir Hi-Tech Monitoring Unit, Sasan-Gir, Gujarat, monitored and coordinated these activities. The location data from each radio-collar was downloaded using the GPS Plus X software (Vectronics Aerospace GmbH, Berlin, Germany) in the Gir Hi-Tech Monitoring Unit (a technology-driven scientific monitoring initiative in the landscape established in 2019 at Sasan-Gir, Gujarat).Data analysisIn this study, we calculated the home range of lions resident in the coastal region using the Fixed Kernel method. We expressed them as 90% and 50% Fixed Kernel (FK) to summarize the overall home range and core area, respectively35,36,37. Additionally, the home range of lions categorized as “link lions” and lions of the protected area was summarized for comparison (Table 1).MaxEnt (version 3.4.1) stand-alone software38 was applied for fine-scaled lion distribution modelling39,40. The logistic output format was set for the MaxEnt output. 30% random lion occurrence points were used as test data to evaluate model performance. The area under the receiver operating characteristic curve (AUC) was used to evaluate the discriminative ability of the model based on the values of sensitivity (correct discrimination of true positive location points) and specificity (correct discrimination of true negative absence points)41. The Jackknife regularised training gain for the species was used to understand the effect of each variable in model building. The logical output by the MaxEnt was presented in a table format as “percent contribution” and “permutation importance” values (from 0 to 100%). Spatial inputs were prepared on the GIS platform using ArcMap (version 10.8.1, ESRI, Redlands, USA)42. Input data for MaxEnt were categorized as (i) lion occurrence data, (ii) model variables were prepared as described below:

i.

Occurrence data
At the first level, inconsistent location fixes (records with missing coordinates, time stamps, and elevation) and outliers were filtered out. Next, each lion’s hourly GPS location fixes obtained from remotely monitored radio-telemetry data were randomized to overcome spatial and temporal biases. The data was reduced by taking every three-hour location fix43,44. The data was further categorized season-wise, viz. summer, monsoon and winter. This consolidated data was then subject to spatial thinning of one kilometre using SDMtoolbox (version 2.0)45,46.

ii.

Model variables

The variables used for distribution modelling broadly included different categories of land use, including both natural habitats and anthropogenic factors, namely, roads and human settlement areas. All variables were rasterized at 10 m spatial resolution.Land Use Land Cover (LULC) data of Saurashtra was obtained from Bhaskaracharya National Institute for Space Applications and Geo-informatics (BISAG-N), Gandhinagar, Gujarat. The data was then further classified into 18 sub-classes—Forest, Sandy areas, Salt-affected, Saltpan, open scrub, dense scrub (Wastelands), Waterlogged, River/Stream/Drain, Lakes and Ponds, Mining/Industrial areas, Reservoir/Tanks, Mangrove/Swamp Area, Crop Land, Agriculture Plantation (horticulture and agro-forestry), Core urban, Mixed settlement, Peri-urban, Village (Fig. 2).Roads and highways were also analyzed as separate variables in the model. Roads were classified as village roads, major district roads, and state and national highways and digitized individually to estimate Euclidean distance further (Table 2). Euclidean distance from the human settlement (Core-urban, Peri-urban, villages and mixed settlement) was analyzed and taken as a separate input variable for the model. More

Gardner TA, Cote IM, Gill JA, Grant A, Watkinson AR. Long-term region-wide declines in Caribbean corals. Science. 2003;301:958–60.CAS 
PubMed 

Google Scholar 
Knowlton N. The future of coral reefs. Proc Natl Acad Sci USA. 2001;98:5419–25.CAS 
PubMed 
PubMed Central 

Google Scholar 
Worm B, Barbier EB, Beaumont N, Duffy JE, Folke C, Halpern BS, et al. Impacts of biodiversity loss on ocean ecosystem services. Science. 2006;314:787–90.CAS 
PubMed 

Google Scholar 
Dudgeon SR, Aronson RB, Bruno JF, Precht WF. Phase shifts and stable states on coral reefs. Mar Ecol Prog Ser. 2010;413:201–16.
Google Scholar 
Bell JJ, Davy SK, Jones T, Taylor MW, Webster NS. Could some coral reefs become sponge reefs as our climate changes? Glob Climate Change. 2013;19:2613–24.
Google Scholar 
McMurray SE, Henkel TP, Pawlik JR. Demographics of increasing populations of the giant barrel sponge Xestospongia muta in the Florida Keys. Ecology. 2010;91:560–70.PubMed 

Google Scholar 
Bell JJ. The functional roles of marine sponges. Est Coast Shelf Sci. 2008;79:341–53.
Google Scholar 
Lesser MP, Slattery M. Will coral reef sponges be winners in the Anthropocene? Glob Change Biol. 2020;26:3202–11.
Google Scholar 
Pankey MS, Plachetzki DC, Macartney KJ, Gastaldi M, Slattery M, Gochfeld DJ, et al. Co-phylogeny and convergence shape holobiont evolution in sponge-microbe symbioses. Nat Ecol Evol. 2022;6:750–62.
Google Scholar 
Lesser MP, Slattery M, Mobley CD. Biodiversity and functional ecology of mesophotic coral reefs. Ann Rev Ecol Syst. 2018;49:49–71.
Google Scholar 
Diaz MC, Rützler K. Sponges: an essential component of Caribbean coral reefs. Bull Mar Sci. 2001;69:535–46.
Google Scholar 
Wulff JL. Ecological interactions and the distribution, abundance, and diversity of sponges. Adv Mar Biol. 2012;61:273–344.PubMed 

Google Scholar 
Lesser MP. Benthic-pelagic coupling on coral reefs: feeding and growth of Caribbean sponges. J Exp Mar Biol Ecol. 2006;328:277–88.
Google Scholar 
Perea-Blazquez A, Davy SK, Bell JJ. Estimates of particulate organic carbon flowing from the pelagic environment to the benthos through sponge assemblages. PLoS One. 2012;7:e29569.CAS 
PubMed 
PubMed Central 

Google Scholar 
Lesser MP, Slattery M. Ecology of Caribbean sponges: are top-down or bottom-up processes more important? PLoS One. 2013;8:e79799.CAS 
PubMed 
PubMed Central 

Google Scholar 
Pawlik JR. The chemical ecology of sponges on Caribbean reefs: natural products shape natural systems. BioScience. 2011;61:888–98.
Google Scholar 
Slattery M, Gochfeld DJ. Chemical interactions among marine competitors, and host-pathogens. In: Fattorusso, E, Gerwick, WH, Taglialatela-Scafati, O (eds). Handbook of Marine Natural Products. Springer, 2012. pp. 824–59.Thacker RW, Freeman CJ. Sponge-microbe symbioses: recent advances and new directions. Adv Mar Biol. 2012;62:57–112.PubMed 

Google Scholar 
Taylor MW, Radax R, Steger D, Wagner M. Sponge-associated microorganisms: evolution, ecology, and biotechnological potential. Microbiol Biol Rev. 2007;71:295–347.CAS 

Google Scholar 
Schmitt S, Tsai P, Bell J, Fromont J, Ilan M, Lindquist N, et al. Assessing the complex sponge microbiota: core, variable and species-specific bacterial communities in marine sponges. ISME J. 2012;6:564–76.CAS 
PubMed 

Google Scholar 
Gloeckner V, Wehrl M, Moitinho-Silva L, Gernert C, Schupp P, Pawlik JR, et al. The HMA-LMA dichotomy revisited: an electron microscopical survey of 56 sponge species. Biol Bull. 2014;227:78–88.PubMed 

Google Scholar 
Hentschel U, Fieseler L, Wehrl M, Gernert C, Steinert M, Hacker J, et al. Microbial diversity of marine sponges. Prog Mol Subcell Biol. 2003;37:59–88.CAS 
PubMed 

Google Scholar 
Fiore CL, Jarett JK, Olson ND, Lesser MP. Nitrogen fixation and nitrogen transformation in marine symbioses. Trends Microbiol. 2010;18:455–63.CAS 
PubMed 

Google Scholar 
Zhang F, Jonas L, Lin H, Hill RT. Microbially mediated nutrient cycles in marine sponges. FEMS Microbiol Ecol. 2019;95:115.
Google Scholar 
Schläppy M-L, Schöttner SI, Lavik G, Kuypers MMM, de Beer D, Hoffmann F. Evidence of nitrification and denitrification in high and low microbial abundance sponges. Mar Biol. 2010;157:593–602.PubMed 

Google Scholar 
Giles EC, Kamke J, Moitinho-Silva L, Taylor MW, Hentschel U, Ravasi T, et al. Bacterial community profiles in low microbial abundance sponges. FEMS Microbiol Ecol. 2013;83:232–41.CAS 
PubMed 

Google Scholar 
Weisz JB, Lindquist N, Martens CS. Do associated microbial abundances impact marine demosponge pumping rates and tissue densities. Oecologia. 2008;155:367–76.PubMed 

Google Scholar 
de Goeij JM, van Oevelen D, Vermiej MJA, Osinga R, Middelburg JJ, de Goeij AFPM, et al. Surviving in a marine desert: the sponge loop retains resources within coral reefs. Science. 2013;342:108–10.PubMed 

Google Scholar 
de Goeij JM, Lesser MP, Pawlik JR. Nutrient fluxes and ecological functions of coral reef sponges in a changing ocean. In: Carballo, J, Bell, J eds. Climate Change, Ocean Acidification and Sponges. Springer, 2017. pp 373–410.Tanaka Y, Miyajima T, Wtanabe A, Nadaoka K, Yamamoto T, Ogawa H. Distribution of dissolved organic carbon and nitrogen in a coral reef. Coral Reefs. 2011;30:533–41.
Google Scholar 
Lesser MP, Slattery M, Laverick JH, Macartney KJ, Bridge TC. Global community breaks at 61 m on mesophotic coral reefs. Global Ecol Biogeogr. 2019;28:1403–16.
Google Scholar 
Lønborg C, Álvarez-Salgado XA, Duggan S, Carreira C. Organic matter bioavailability in tropical coastal waters: The Great Barrier Reef. Limnol Oceanogr. 2018;63:1015–35.
Google Scholar 
Macartney KJ, Abraham AC, Slattery M, Lesser MP. Growth and feeding in the sponge Agelas tubulata from shallow to mesophotic depths on Grand Cayman Island. Ecosphere. 2021;12:e03764.
Google Scholar 
Ribes M, Coma R, Atkinson MJ, Kinzie RA. Particle removal by coral reef communities: picoplankton is a major source of nitrogen. Mar Ecol Prog Ser. 2003;257:13–23.
Google Scholar 
Ribes M, Coma R, Atkinson MJ, Kinzie RA. Sponges and ascidians control removal of particulate organic nitrogen from coral reef water. Limnol Oceanogr. 2005;50:1480–9.CAS 

Google Scholar 
Maldonado M, Ribes M, van Duyl FC. Nutrient fluxes through sponges: biology, budgets, and ecological implications. Adv Mar Biol. 2012;62:113–82.PubMed 

Google Scholar 
Seutin G, White BN, Boag PT. Preservation of avian blood and tissue samples for DNA analyses. Can J Zool. 1991;69:82–90.CAS 

Google Scholar 
Abraham AC, Gochfeld DJ, Macartney K, Mellow A, Lesser MP, Slattery M. Biochemical variability in sponges across the Caribbean basin. Invertebr Biol. 2021;140:e12341.
Google Scholar 
Sunagawa S, Woodley CM, Medina M. Threatened corals provide underexplored microbial habitats. PLoS One. 2010;5:e9554.PubMed 
PubMed Central 

Google Scholar 
Parada AE, Needham DM, Fuhrman JA. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ Microbiol. 2016;18:1403–14.CAS 
PubMed 

Google Scholar 
Apprill A, McNally S, Parsons R, Weber L. Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat Microb Ecol. 2015;75:129–37.
Google Scholar 
Simion P, Phillippe H, Baurain D, Jager M, Richter RJ, Di Franco A, et al. A Large and consistent phylogenomic dataset supports sponges as the sister group to all other animals. Curr Biol. 2017;27:958–67.CAS 
PubMed 

Google Scholar 
Katoh K, Misawa K, Kuma KI, Miyata T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 2002;30:3059–66.CAS 
PubMed 
PubMed Central 

Google Scholar 
Oksanen J, Simpson GL, Blanchet FG, Kindt R, Legendre P, Minchin PR, et al. vegan: Community Ecology Package. R package version 2.5-5. https://CRAN.R-project.org/package=vegan. Released May, 2019.Pinheiro J, Bates D, DebRoy S, Sarkar D, EISPACK Authors, Heisterkamp S, et al. nlme: Linear and Nonlinear Mixed Effects Models. R package version 3.1-155. https://svn.r-project.org/R-packages/trunk/nlme/. Released Jan, 2022.Kindt R, Coe R. Tree diversity analysis. A manual and software for common statistical methods for ecological and biodiversity studies. World Agroforestry Centre, ICRAF, 2005. https://www.worldagroforestry.org/publication/tree-diversity-analysis-manual-and-software-common-statistical-methods-ecological-and.Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.PubMed 
PubMed Central 

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 

Google Scholar 
Westbrook A, Ramsdell J, Schuelke T, Normington L, Bergeron RD, Thomas WK, et al. PALADIN: protein alignment for functional profiling whole metagenome shotgun data. Bioinformatics. 2017;33:1473–8.CAS 
PubMed 
PubMed Central 

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

Google Scholar 
Li D, Luo R, Liu C-M, Leung C-M, Ting H-F, 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 

Google Scholar 
Li H, Durbin R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics. 2009;25:1754–60.CAS 
PubMed 
PubMed Central 

Google Scholar 
Blin K, Shaw S, Kautsar SA, Medema MH, Weber T. The antiSMASH database version 3: increased taxonomic coverage and new query features for modular enzymes. Nucleic Acids Res. 2009;49:D639–43.
Google Scholar 
Conte-Jerpe IE, Thompson PD, Wong CWM, Oliveira NL, Duprey NN, Moynihan MA, et al. Trophic strategy and bleaching resistance in reef-building corals. Sci Adv. 2020;6:eaaz5443.
Google Scholar 
Jackson AL, Inger R, Parnell AC, Bearhop S. Comparing isotopic niche widths among and within communities: SIBER-Stable Isotope Bayesian Ellipses. Anim Ecol. 2011;80:595–602.
Google Scholar 
Thomas T, Moitinho-Silva L, Lurgi M, Björk JR, Easson C, Astudillo-Garcia C, et al. Diversity, structure and convergent evolution of the global sponge microbiome. Nat Comm. 2016;7:11870.CAS 

Google Scholar 
Erwin PM, Coma R, López-Sendino P, Serrano E, Ribes M. Stable symbionts across the HMA-LMA dichotomy: low seasonal and inter-annual variation in sponge-associated bacteria from taxonomically diverse hosts. FEMS Microbiol Ecol. 2015;91:fiv115.PubMed 

Google Scholar 
Moitinho-Silva L, Steinert G, Nielsen S, Hardoim CCP, Wu Y-C, McCormack GP. Predicting the HMA-LMA status in marine sponges by machine learning. Front Microbiol. 2017;8:752.PubMed 
PubMed Central 

Google Scholar 
Campana S, Demey C, Busch K, Hentschel U, Muyzer G, de Goeij J. Marine sponges maintain stable bacterial communities between reef sites with different coral to algae cover ratios. FEMS Microbiol Ecol. 2021;97:fiab115.CAS 
PubMed 
PubMed Central 

Google Scholar 
Freeman CJ, Thacker RW. Complex interactions between marine sponges and their symbiotic microbial communities. Limnol Oceanogr. 2011;56:1577–86.
Google Scholar 
Siegel A, Kamke J, Hochmuth T, Piel J, Richter M, Liang C, et al. Single-cell genomic reveals the lifestyle of Poribacteria, a candidate phylum symbiotically associated with marine sponges. ISME J. 2011;5:61–70.
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:e00150–18.CAS 
PubMed 
PubMed Central 

Google Scholar 
Fan L, Reynolds D, Liu M, Thomas T. Functional equivalence and evolutionary convergence in complex communities of microbial sponge symbionts. Proc Natl Acad Sci USA. 2012;109:1878–87.
Google Scholar 
Ribes M, Jiménez E, Yahel G, López-Sendino P, Diez B, Massana R, et al. Functional convergence of microbes associated with temperate marine sponges. Environ Microbiol. 2012;14:1224–39.CAS 
PubMed 

Google Scholar 
Thomas T, Rusch D, DeMaere MZ, Yung PY, Lewis M, Halpern A, et al. Functional genomic signatures of sponge bacteria reveal unique and shared features of symbiosis. ISME J. 2010;4:1557–67.CAS 
PubMed 

Google Scholar 
Fiore CL, Labrie M, Jarett JK, Lesser MP. Transcriptional activity of the giant barrel sponge, Xestospongia muta holobiont: molecular evidence for metabolic interchange. Front Microbiol. 2015;6:364.PubMed 
PubMed Central 

Google Scholar 
Engel S, Pawlik JR. Allelopathic activities of sponge extracts. Mar Ecol Prog Ser. 2000;207:273–82.
Google Scholar 
Gochfeld DJ, Kamel HN, Olson JB, Thacker RW. Trade-offs in defensive metabolite production but not ecological function in healthy and diseased sponges. J Chem Ecol. 2012;38:451–62.CAS 
PubMed 

Google Scholar 
van Duyl FC, Mueller B, Meesters EH. Spatio-temporal variation in stable isotopic signatures (δ13C and δ15N) of sponges on the Saba Bank. PeerJ. 2018;6:e5460.PubMed 
PubMed Central 

Google Scholar 
Fiore CL, Baker DM, Lesser MP. Nitrogen biogeochemistry in the Caribbean sponge, Xestospongia muta: a source or sink of dissolved inorganic nitrogen? PLoS One. 2013;8:e72961.CAS 
PubMed 
PubMed Central 

Google Scholar 
Hudspith M, de Goeij JM, Streekstra M, Kornder NA, Bougoure J, Guagliardo P, et al. Harnessing solar power: photoautotrophy supplements the diet of a low-light dwelling sponge. ISME J. 2022; https://doi.org/10.1038/s41396-022-01254-3.Shih JL, Selph KE, Wall CB, Wallsgrove NJ, Lesser MP, Popp BN. Trophic ecology of the tropical Pacific sponge Mycale gradis inferred from amino acid compound-specific isotopic analyses. Microb Ecol. 2020;79:495–510.CAS 
PubMed 

Google Scholar 
Macartney KJ, Slattery M, Lesser MP. Trophic ecology of Caribbean sponges in the mesophotic zone. Limnol Oceanogr. 2021;66:1113–24.CAS 

Google Scholar 
Southwell MW, Popp BN, Martens CS. Nitrification controls on fluxes and isotopic composition of nitrate from Florida Keys sponges. Mar Chem. 2008;108:96–108.CAS 

Google Scholar 
Lamb K, Swart PK. The carbon and nitrogen isotopic values of particulate organic material from the Florida Keys: a temporal and spatial study. Coral Reefs. 2008;27:351–62.
Google Scholar 
Ferrier-Pagès C, Leal MG. Stable isotopes as tracers of trophic interactions in marine mutualistic symbioses. Ecol Evol. 2019;9:723–40.PubMed 

Google Scholar 
McMurray SE, Stubler AD, Erwin PM, Finelli CM, Pawlik JR. A test of the sponge-loop hypothesis for emergent Caribbean reef sponges. Mar Ecol Prog Ser. 2018;588:1–14.CAS 

Google Scholar 
Freeman CJ, Easson CG, Baker DM. Metabolic diversity and niche structure in sponges from the Miskito Cays, Honduras. PeerJ. 2014;2:e695.PubMed 
PubMed Central 

Google Scholar 
Freeman CJ, Easson CG, Matterson KO, Thacker RW, Baker DM, Paul VJ. Microbial symbionts and ecological divergence of Caribbean sponges: a new perspective on an ancient association. ISME J. 2020;14:1571–83.PubMed 
PubMed Central 

Google Scholar 
Poppell E, Weisz J, Spicer L, Massaro A, Hill A, Hill M. Sponge heterotrophic capacity and bacterial community structure in high‐and low‐microbial abundance sponges. Mar Ecol. 2014;35:414–24.
Google Scholar 
Morganti TM, Ribes M, Yahel G, Coma R. Size is the major determinant of pumping rates in marine sponges. Front Physiol. 2019;10:1474.PubMed 
PubMed Central 

Google Scholar 
Rix L, Ribes M, Coma R, Jahn MT, de Goeij JM, van Oevelen D, et al. Heterotrophy in the earliest gut: a single-cell view of heterotrophic carbon and nitrogen assimilation in sponge-microbe symbioses. ISME J. 2020;14:2554–67.CAS 
PubMed 
PubMed Central 

Google Scholar 
O’Brien PA, Tan S, Yang C, Frade PR, Andreakis N, Smith HA, et al. Diverse coral reef invertebrates exhibit patterns of phylosymbiosis. ISME J. 2020;14:2211–22.PubMed 
PubMed Central 

Google Scholar 
Erwin PM, Thacker RW. Incidence and identity of photosynthetic symbionts in Caribbean coral reef sponge assemblages. J Mar Biol Assoc UK. 2007;87:1683–92.CAS 

Google Scholar 
Palumbi SR. Tactics of acclimation: morphological changes of sponges in an unpredictable environment. Science. 1984;225:1478–80.CAS 
PubMed 

Google Scholar 
Slattery M, Gochfeld DJ, Diaz MC, Thacker RW, Lesser MP. Variability in chemical defense across a shallow to mesophotic depth gradient in the Caribbean sponge Plakortis angulospiculatus. Coral Reefs. 2016;35:11–22.
Google Scholar 
Morganti T, Coma R, Yahel G, Ribes M. Trophic niche separation that facilitates co‐existence of high and low microbial abundance sponges is revealed by in situ study of carbon and nitrogen fluxes. Limnol Oceanogr. 2017;62:1963–83.CAS 

Google Scholar 
Maldonado M. Sponge waste that fuels marine oligotrophic food webs: a re-assessment of its origin and nature. Mar Ecol. 2016;37:477–91.
Google Scholar  More

Williams, R. et al. Prioritizing global marine mammal habitats using density maps in place of range maps. Ecography 37, 212–220 (2014).
Google Scholar 
Tyack, P. L. & Clark, C. W. Communication and acoustic behavior of dolphins and whales in Hearing by whales and dolphins 156–224 (Springer, 2000).Davis, G. E. et al. Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data. Glob. Change Biol. 26, 4812 (2020).ADS 

Google Scholar 
Lomac-MacNair, K. S. et al. Marine mammal visual and acoustic surveys near the Alaskan Colville River Delta. Polar Biol. 42, 441–448 (2018).
Google Scholar 
Keen, E., Hendricks, B., Wray, J., Alidina, H. & Picard, C. Integrating passive acoustic and visual surveys for marine mammals in coastal habitats in 176th Meeting of Acoustical Society of America. 1 edn.Gregr, E. J., Baumgartner, M. F., Laidre, K. L. & Palacios, D. M. Marine mammal habitat models come of age: The emergence of ecological and management relevance. Endang. Species Res. 22, 205–212 (2013).
Google Scholar 
Hastie, G. D., Wilson, B., Wilson, L., Parsons, K. M. & Thompson, P. M. Functional mechanisms underlying cetacean distribution patterns: Hotspots for bottlenose dolphins are linked to foraging. Mar. Biol. 144, 397–403 (2004).
Google Scholar 
Lambert, C., Mannocci, L., Lehodey, P. & Ridoux, V. Predicting cetacean habitats from their energetic needs and the distribution of their prey in two contrasted tropical regions. PLoS ONE 9, e105958 (2014).ADS 
PubMed 
PubMed Central 

Google Scholar 
Huot, Y. et al. Does chlorophyll a provide the best index of phytoplankton biomass for primary productivity studies?. Biogeosci. Discuss. 4, 707–745 (2007).ADS 

Google Scholar 
Etnoyer, P. et al. Sea-surface temperature gradients across blue whale and sea turtle foraging trajectories off the Baja California Peninsula, Mexico. Deep Sea Res. II 53, 340–358 (2006).ADS 

Google Scholar 
Shabangu, F. W. et al. Seasonal occurrence and diel calling behaviour of Antarctic blue whales and fin whales in relation to environmental conditions off the west coast of South Africa. J. Mar. Syst. 190, 25–39 (2019).
Google Scholar 
Haida Nation & Parks Canada Agency. Gwaii Haanas Gina ’Waadluxan Kilguhlga. Land-Sea-People Management Plan. 33 (© Council of the Haida Nation and Her Majesty the Queen in Right of Canada, represented by the Chief Executive Officer of Parks Canada, 2018).Ford, J. K. B. Marine Mammals of British Columbia. (Royal BC Museum, 2014).Allen, A. S., Yurk, H., Vagle, S., Pilkington, J. & Canessa, R. The underwater acoustic environment at SGaan Kinghlas-Bowie Seamount Marine Protected Area: Characterizing vessel traffic and associated noise using satellite AIS and acoustic datasets. Mar. Pollut. Bull. 128, 82–88 (2018).CAS 
PubMed 

Google Scholar 
Ainslie, M. A. Principles of Sonar Performance Modeling. (Springer, 2010).Collins, M. D. A split-step Padé solution for the parabolic equation method. J. Acoust. Soc. Am. 93, 1736–1742 (1993).ADS 

Google Scholar 
Porter, M. B. & Bucker, H. P. Gaussian beam tracing for computing ocean acoustic fields. J. Acoust. Soc. Am. 82, 1349–1359 (1987).ADS 

Google Scholar 
Mouy, X., MacGillivray, A. O., Vallarta, J. H., Martin, B. & Delarue, J. J.-Y. Ambient Noise and Killer Whale Monitoring near Port Metro Vancouver’s Proposed Terminal 2 Expansion Site: July–September 2012. (Technical report by JASCO Applied Sciences for Hemmera, 2012).Ford, J. et al. Distribution and relative abundance of cetaceans in western Canadian waters from ship surveys, 2002–2008. Can. Tech. Rep. Fish. Aquat. Sci. 2913, 51 (2010).
Google Scholar 
Wright, B. M., Nichol, L. M. & Doniol-Valcroze, T. Spatial density models of cetaceans in the Canadian Pacific estimated from 2018 ship-based surveys. DFO Can. Sci. Advis. Sec. Res. Doc. 2021, 49 (2021).
Google Scholar 
Devred, E., Hardy, M. & Hannah, C. Satellite observations of the Northeast Pacific Ocean. Can. Tech. Rep. Hydrogr. Ocean Sci. 335, 46 (2021).
Google Scholar 
Saha, K. et al. NOAA National centers for environmental information. Dataset https://doi.org/10.7289/v52j68xx (2018).Article 

Google Scholar 
NASA Goddard Space Flight Center, Ocean Ecology Laboratory & Ocean Biology Processing Group. (NASA OB.DAAC, Greenbelt, MD, USA. https://doi.org/10.5067/AQUA/MODIS/L3B/CHL/2018. Accessed 3 Feb 2021.Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. B Stat. Methodol. 73, 3–36 (2011).MathSciNet 
MATH 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. R foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ (2021).Ogle, D. H., Wheeler, P. & Dinno, A. FSA: Fisheries Stock Analysis. R package version 0.8.32. https://github.com/droglenc/FSA (2021).Payne, R. S. & McVay, S. Songs of humpback whales. Science 173, 585–597 (1971).ADS 
CAS 
PubMed 

Google Scholar 
Rekdahl, M. L. et al. Non-song social call bouts of migrating humpback whales. J. Acoust. Soc. Am. 137, 3042–3053 (2015).ADS 
PubMed 
PubMed Central 

Google Scholar 
Oswald, J. N., Rankin, S. & Barlow, J. To whistle or not to whistle? Geographic variation in the whistling behavior of small odontocetes. Aquat. Mamm. 34, 288–302 (2008).
Google Scholar 
Rankin, S., Oswald, J., Barlow, J. P. & Lammers, M. Patterned burst-pulse vocalizations of the northern right whale dolphin, Lissodelphis borealis. J. Acoust. Soc. Am. 121, 1213–1218. https://doi.org/10.1121/1.2404919 (2007).Article 
ADS 
PubMed 

Google Scholar 
Arranz, P. et al. Discrimination of fast click-series produced by tagged Risso’s dolphins (Grampus griseus) for echolocation or communication. J. Exp. Biol. 219, 2898–2907. https://doi.org/10.1242/jeb.144295 (2016).Article 
CAS 
PubMed 

Google Scholar 
Halpin, L. R., Towers, J. R. & Ford, J. K. First record of common bottlenose dolphin (Tursiops truncatus) in Canadian Pacific waters. Mar. Biodivers. Rec. 11, 1–5 (2018).
Google Scholar 
Nikolich, K. & Towers, J. R. Vocalizations of common minke whales (Balaenoptera acutorostrata) in an eastern North Pacific feeding ground. Bioacoustics 29, 97–108 (2020).
Google Scholar 
Money, J. H. & Trites, A. W. A preliminary assessment of the status of marine mammal populations and associated research needs for the west coast of Canada. Report No. Final Report, 80 (Fisheries and Oceans Canada, 1998).Gregr, E. J. & Trites, A. W. Predictions of critical habitat for five whale species in the waters of coastal British Columbia. Can. J. Fish. Aquat. Sci. 58, 1265–1285 (2001).
Google Scholar 
Ou, H., Au, W. W. L., Van Parijs, S., Oleson, E. M. & Rankin, S. Discrimination of frequency-modulated Baleen whale downsweep calls with overlapping frequencies. J. Acoust. Soc. Am. 137, 3024–3032. https://doi.org/10.1121/1.4919304 (2015).Article 
ADS 
PubMed 

Google Scholar 
Mellinger, D. K., Stafford, K. M., Moore, S. E., Dziak, R. P. & Matsumoto, H. An overview of fixed passive acoustic observation methods for cetaceans. Oceanography 20, 36–45 (2007).
Google Scholar 
Stafford, K. M., Citta, J. J., Moore, S. E., Daher, M. A. & George, J. E. Environmental correlates of blue and fin whale call detections in the North Pacific Ocean from 1997 to 2002. Mar. Ecol. Prog. Ser. 395, 37–53 (2009).ADS 

Google Scholar 
Burnham, R., Duffus, D. & Mouy, X. The presence of large whale species in Clayoquot Sound and its offshore waters. Cont. Shelf Res. 177, 15–23 (2019).ADS 

Google Scholar 
Burtenshaw, J. C. et al. Acoustic and satellite remote sensing of blue whale seasonality and habitat in the Northeast Pacific. Deep Sea Res. II 51, 967–986 (2004).ADS 

Google Scholar 
Calambokidis, J., Barlow, J., Ford, J. K. B., Chandler, T. E. & Douglas, A. B. Insights into the population structure of blue whales in the Eastern North Pacific from recent sightings and photographic identification. Mar. Mamm. Sci. 25, 816–832 (2009).
Google Scholar 
Jackson, J. M., Thomson, R. E., Brown, L. N., Willis, P. G. & Borstad, G. A. Satellite chlorophyll off the British Columbia Coast, 1997–2010. J. Geophys. Res. Oceans 120, 4709–4728 (2015).ADS 

Google Scholar 
Evans, R., English, P. A., Anderson, S. C., Gauthier, S. & Robinson, C. L. Factors affecting the seasonal distribution and biomass of E. pacifica and T. spinifera along the Pacific coast of Canada: A spatiotemporal modelling approach. PLoS ONE 16, e0249818 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
Moore, S. E., Watkins, W. A., Daher, M. A., Davies, J. R. & Dahlheim, M. E. Blue whale habitat associations in the Northwest Pacific: Analysis of remotely-sensed data using a Geographic Information System. Oceanography 15, 1–10 (2002).
Google Scholar 
Lockyer, C. Review of Baleen Whale (Mysticeti) reproduction and implications for management. Rep. Int. Whal. Commn Spec. Issue 6, 27–50 (1984).
Google Scholar 
Ohsumi, S. M. N. Growth of fin whale in the Northern Pacific Ocean. Sci. Rep. Whale Res. Inst. 13, 97–133 (1958).
Google Scholar 
Watkins, W. A. et al. Seasonality and distribution of whale calls in the North Pacific. Oceanography 13, 62–67 (2000).
Google Scholar 
Watkins, W. A., Tyack, P., Moore, K. E. & Bird, J. E. The 20-Hz signals of finback whales (Balaenoptera physalus). J. Acoust. Soc. Am. 82, 1901–1912 (1987).ADS 
CAS 
PubMed 

Google Scholar 
Stafford, K. M., Mellinger, D. K., Moore, S. E. & Fox, C. G. Seasonal variability and detection range modeling of baleen whale calls in the Gulf of Alaska, 1999–2002. J. Acoust. Soc. Am. 122, 3378–3390 (2007).ADS 
PubMed 

Google Scholar 
Koot, B. Winter Behaviour and Population Structure of Fin Whales (Balaenoptera physalus) in British Columbia inferred from passive acoustic data (University of British Columbia, 2015).
Google Scholar 
Pilkington, J. F., Stredulinsky, E. H., Abernethy, R. M. & Ford, J. K. B. Patterns of Fin whale (Balaenoptera physalus) Seasonality and Relative Distribution in Canadian Pacific Waters Inferred from Passive Acoustic Monitoring. DFO Can. Sci. Advis. Sec. Res. Doc. (2018).Best, B. D., Fox, C. H., Williams, R., Halpin, P. H. & Paquet, P. C. Updated Marine Mammal Distribution and Abundance Estimates in British Columbia (Springer, 2015).
Google Scholar 
Clarke, C. & Jamieson, G. Identification of ecologically and biologically significant areas in the Pacific North Coast integrated management area: Phase II: Final report. Can. Tech. Rep. Fish. Aquat. Sci. 2678, 59 (2006).
Google Scholar 
Nichol, L. M. et al. Distribution, movements and habitat fidelity patterns of Fin Whales (Balaenoptera physalus) in Canadian Pacific Waters. DFO Can. Sci. Advis. Sec. Res. Doc. (2018).Nichol, L. M. & Ford, J. K. B. Information in Support of the Identification of Habitat of Special Importance to Fin Whales (Balaenoptera physalus) in Canadian Pacific Waters. DFO Can. Sci. Advis. Sec. Res. Doc. (2018).Mizroch, S. A., Rice, D. W., Zwiefelhofer, D., Waite, J. & Perryman, W. L. Distribution and movements of fin whales in the North Pacific Ocean. Mammal Rev. 39, 193–227 (2009).
Google Scholar 
Širović, A., Williams, L. N., Kerosky, S. M., Wiggins, S. M. & Hildebrand, J. A. Temporal separation of two fin whale call types across the eastern North Pacific. Mar. Biol. 160, 47–57 (2013).PubMed 

Google Scholar 
Flinn, R. D., Trites, A. W., Gregr, E. J. & Perry, R. I. Diets of fin, sei, and sperm whales in British Columbia: an analysis of commercial whaling records, 1963–1967. Mar. Mamm. Sci. 18, 663–679 (2002).
Google Scholar 
Barnes, R. S. K. & Hughes, R. N. An Introduction to Marine Ecology (Wiley, 1999).
Google Scholar 
Romagosa, M. et al. Food talks: 40-hz fin whale calls are associated with prey biomass. Proc. R. Soc. B 288, 20211156 (2021).PubMed 
PubMed Central 

Google Scholar 
Gregr, E. J., Nichol, L., Ford, J. K., Ellis, G. & Trites, A. W. Migration and population structure of northeastern Pacific whales off coastal British Columbia: An analysis of commercial whaling records from 1908–1967. Mar. Mamm. Sci. 16, 699–727 (2000).
Google Scholar 
Williams, R. & Thomas, L. Distribution and abundance of marine mammals in the coastal waters of British Columbia, Canada. J. Cetac. Res. Manage. 9, 15 (2007).
Google Scholar 
Dalla Rosa, L., Ford, J. K. & Trites, A. W. Distribution and relative abundance of humpback whales in relation to environmental variables in coastal British Columbia and adjacent waters. Contin. Shelf Res. 36, 89–104 (2012).ADS 

Google Scholar 
Winn, H. E. & Winn, L. K. The song of the humpback whale Megaptera novaeangliae in the West Indies. Mar. Biol. 47, 97–114. https://doi.org/10.1007/BF00395631 (1978).Article 

Google Scholar 
Baker, C. S. et al. Population characteristics and migration of summer and late-season humpback whales (Megaptera novaeangliae) in southeastern Alaska. Mar. Mamm. Sci. 1, 304–323 (1985).ADS 

Google Scholar 
McSweeney, D., Chu, K., Dolphin, W. & Guinee, L. North Pacific humpback whale songs: A comparison of southeast Alaskan feeding ground songs with Hawaiian wintering ground songs. Mar. Mamm. Sci. 5, 139–148 (1989).
Google Scholar 
Norris, T. F., McDonald, M. & Barlow, J. Acoustic detections of singing humpback whales (Megaptera novaeangliae) in the eastern North Pacific during their northbound migration. J. Acoust. Soc. Am. 106, 506–514 (1999).ADS 
CAS 
PubMed 

Google Scholar 
Clark, C. W. & Clapham, P. J. Acoustic monitoring on a humpback whale (Megaptera novaeangliae) feeding ground shows continual singing into late spring. Proc. R. Soc. Lond. B 271, 1051–1057 (2004).
Google Scholar 
Stimpert, A. K., Peavey, L. E., Friedlaender, A. S. & Nowacek, D. P. Humpback whale song and foraging behavior on an Antarctic feeding ground. PLoS ONE 7, e51214 (2012).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Kowarski, K., Evers, C., Moors-Murphy, H., Martin, B. & Denes, S. L. Singing through winter nights: Seasonal and diel occurrence of humpback whale (Megaptera novaeangliae) calls in and around the Gully MPA, offshore eastern Canada. Mar. Mamm. Sci. 34, 169–189 (2018).
Google Scholar 
Nichol, L. M., Abernethy, R., Flostrand, L., Lee, T. S. & Ford, J. K. B. Information relevant for the identification of critical habitats of north pacific humpback whales (Megaptera novaeangliae) in British Columbia. DFO Can. Sci. Advis. Sec. Res. Doc. (2010).Williams, R., Erbe, C., Ashe, E. & Clark, C. W. Quiet (er) marine protected areas. Mar. Pollut. Bull. 100, 154–161 (2015).CAS 
PubMed 

Google Scholar 
Gaston, A. J., Pilgrim, N. G. & Pattison, V. Humpback Whale (Megaptera novaeangliae) observations in Laskeek Bay, western Hecate Strait, in spring and early summer, 1990–2018. Can. Field Nat. 133, 263–269 (2019).
Google Scholar 
Robinson, C. L., Gower, J. F. & Borstad, G. Twenty years of satellite observations describing phytoplankton blooms in seas adjacent to Gwaii Haanas National Park Reserve, Canada. Can. J. Remote Sens. 30, 36–43 (2004).ADS 

Google Scholar 
Swartz, S. L., Taylor, B. L. & Rugh, D. J. Gray whale Eschrichtius robustus population and stock identity. Mamm. Rev. 36, 66–84 (2006).
Google Scholar 
Gaston, A. J. & Heise, K. Results of cetacean observations in Laskeek Bay, 1990–2003. Laskeek Bay Res. 55, 1–10 (2004).
Google Scholar 
Ford, J. K. et al. New insights into the northward migration route of gray whales between Vancouver Island, British Columbia, and southeastern Alaska. Mar. Mamm. Sci. 29, 325–337 (2013).
Google Scholar 
Burnham, R. E. & Duffus, D. A. The use of passive acoustic monitoring as a census tool of gray whale (Eschrichtius robustus) migration. Ocean Coast. Manag. 188, 105070 (2020).
Google Scholar 
Best, P. B. Social organization in sperm whales. In Physeter macrocephalus in Behavior of Marine Animals (eds Winn, H. E. & Olla, B. L.) 227–289 (Springer, 1979).
Google Scholar 
Jaquet, N. & Gendron, D. Distribution and relative abundance of sperm whales in relation to key environmental features, squid landings and the distribution of other cetacean species in the Gulf of California, Mexico. Mar. Biol. 141, 591–601 (2002).
Google Scholar 
Rice, D. W. Sperm whale Physeter macrocephalus Linnaeus, 1758. Handb. Mar. Mamm. 4, 177–233 (1989).
Google Scholar 
Whitehead, H. & Arnbom, T. Social organization of sperm whales off the Galapagos Islands, February–April 1985. Can. J. Zool. 65, 913–919 (1987).
Google Scholar 
Whitehead, H. Sperm whale: Physeter macrocephalus. In Encyclopedia of Marine Mammals 3rd edn (eds Würsig, B. et al.) 919–925 (Academic Press, 2018).
Google Scholar 
Mizroch, S. A. & Rice, D. W. Ocean nomads: Distribution and movements of sperm whales in the North Pacific shown by whaling data and Discovery marks. Mar. Mamm. Sci. 29, E136–E165 (2013).
Google Scholar 
Diogou, N. et al. Sperm whale (Physeter macrocephalus) acoustic ecology at Ocean Station PAPA in the Gulf of Alaska-Part 2: Oceanographic drivers of interannual variability. Deep Sea Res. I 150, 103044 (2019).
Google Scholar 
Ford, J. K. & Ellis, G. M. You are what you eat: Foraging specializations and their influence on the social organization and behavior of killer whales. in Primates and Cetaceans 75–98 (Springer, 2014).Ford, J. K. B. et al. Habitats of special importance to resident killer whales (Orcinus orca) off the West Coast of Canada. DFO Can. Sci. Advis. Sec. Res. Doc. (2017).Ford, J. K. B., Stredulinsky, E. H., Ellis, G. M., Durban, J. W. & Pilkington, J. F. Offshore Killer whales in Canadian pacific waters: Distribution, seasonality, foraging ecology, population status and potential for recovery. DFO Can. Sci. Advis. Sec. Res. Doc. (2014).Nichol, L. M. & Shackleton, D. M. Seasonal movements and foraging behaviour of northern resident killer whales (Orcinus orca) in relation to the inshore distribution of salmon (Oncorhynchus spp.) in British Columbia. Can. J. Zool. 74, 983–991 (1996).
Google Scholar 
Olesiuk, P. F., Ellis, G. M. & Ford, J. K. Life History and Population Dynamics of Northern Resident Killer Whales (Orcinus orca) in British Columbia (Canadian Science Advisory Secretariat Ottawa, 2005).
Google Scholar 
Newman, K. & Springer, A. Nocturnal activity by mammal-eating killer whales at a predation hot spot in the Bering Sea. Mar. Mamm. Sci. 24, 990 (2008).
Google Scholar 
Ford, J. K. B. et al. Dietary specialization in two sympatric populations of killer whales (Orcinus orca) in coastal British Columbia and adjacent waters. Can. J. Zool. 76, 1456–1471 (1998).
Google Scholar 
Barrett-Lennard, L. G., Ford, J. K. B. & Heise, K. A. The mixed blessing of echolocation: Differences in sonar use by fish-eating and mammal-eating killer whales. Anim. Behav. 51, 553–565 (1996).
Google Scholar 
Deecke, V. B., Ford, J. K. B. & Slater, P. J. B. The vocal behaviour of mammal-eating killer whales: Communicating with costly calls. Anim. Behav. 69, 395–405 (2005).
Google Scholar 
Ford, J. K. B. Call traditions and vocal dialects of killer whales (Orcinus orca) in British Columbia Ph.D. thesis, University of British Columbia (1984).Baird, R. W. Status of killer whales, Orcinus orca, Canada. Can. Field. Nat. 115, 676–701 (2001).
Google Scholar 
Ford, J. K. B., Stredulinsky, E. H., Towers, J. R. & Ellis, G. M. Information in Support of the Identification of Critical Habitat for Transient Killer Whales (Orcinus orca) off the West Coast of Canada. DFO Can. Sci. Advis. Sec. Res. Doc. (2013).Tyack, P. L., Johnson, M., Soto, N. A., Sturlese, A. & Madsen, P. T. Extreme diving of beaked whales. J. Exp. Biol. 209, 4238–4253 (2006).PubMed 

Google Scholar 
Baumann-Pickering, S. et al. Species-specific beaked whale echolocation signals. J. Acoust. Soc. Am. 134, 2293–2301 (2013).ADS 
PubMed 

Google Scholar 
Pike, G. C. Two records of Berardius bairdi from the coast of British Columbia. J. Mammal. 34, 98–104 (1953).
Google Scholar 
Pike, G. C. & MacAskie, I. Marine mammals of British Columbia. Fish. Res. Board Can. Bull. 171, 1–10 (1969).
Google Scholar 
Willis, P. M. & Baird, R. W. Sightings and strandings of beaked whales on the west coast of. Aquat. Mamm. 24, 21–25 (1998).
Google Scholar 
Jefferson, T. A. Phocoenoides dalli. Mamm. Spec. https://doi.org/10.2307/3504170 (1988).Article 

Google Scholar 
Boyd, C. et al. Estimation of population size and trends for highly mobile species with dynamic spatial distributions. Divers. Distrib. 24, 1–12 (2018).
Google Scholar 
Carretta, J. V., Taylor, B. L. & Chivers, S. J. Abundance and depth distribution of harbor porpoise (Phocoena phocoena) in northern California determined from a 1995 ship survey. Fish. Bull. 99, 29–29 (2001).
Google Scholar 
Willis, P. M. & Baird, R. W. Status of the dwarf sperm whale, Kogia simus, with special reference to Canada. Can. Field Nat. 112, 114–125 (1998).
Google Scholar 
Kyhn, L. A. et al. Clicking in a killer whale habitat: Narrow-band, high-frequency biosonar cliks of harbour porpoise (Phocoena phocoena) and Dall’s porpoise (Phocoenoides dalli). PLoS ONE 8, e63763 (2013).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Madsen, P., Carder, D., Bedholm, K. & Ridgway, S. Porpoise clicks from a sperm whale nose—Convergent evolution of 130 kHz pulses in toothed whale sonars?. Bioacoustics 15, 195–206 (2005).
Google Scholar 
Merkens, K. et al. Clicks of dwarf sperm whales (Kogia sima). Mar. Mamm. Sci. 34, 963–978 (2018).
Google Scholar 
Griffiths, E. T. et al. Detection and classification of narrow-band high frequency echolocation clicks from drifting recorders. J. Acoust. Soc. Am. 147, 3511–3522 (2020).ADS 
PubMed 

Google Scholar 
Baird, R. W. & Stacey, P. J. Status of Risso’s Dolphin, Grampus griseus, in Canada. Naturalist 5, 233142 (1991).
Google Scholar 
Benoit-Bird, K. J. & Au, W. W. Prey dynamics affect foraging by a pelagic predator (Stenella longirostris) over a range of spatial and temporal scales. Behav. Ecol. Sociobiol. 53, 364–373 (2003).
Google Scholar 
Benoit-Bird, K. J., Würsig, B. & Mfadden, C. J. Dusky dolphin (Lagenorhynchus obscurus) foraging in two different habitats: active acoustic detection of dolphins and their prey. Mar. Mamm. Sci. 20, 215–231 (2004).
Google Scholar 
Soldevilla, M. S., Wiggins, S. M. & Hildebrand, J. A. Spatial and temporal patterns of Risso’s dolphin echolocation in the Southern California Bight. J. Acoust. Soc. Am. 127, 124–132 (2010).ADS 
PubMed 

Google Scholar 
Soldevilla, M. S., Wiggins, S. M. & Hildebrand, J. A. Spatio-temporal comparison of Pacific white-sided dolphin echolocation click types. Aquat. Biol. 9, 49–62 (2010).
Google Scholar 
Taylor, F. The relationship of midwater trawl catches to sound scattering layers off the coast of northern British Columbia. J. Fish. Board Can. 25, 457–472 (1968).
Google Scholar 
Curtis, K. R., Howe, B. M. & Mercer, J. A. Low-frequency ambient sound in the North Pacific: Long time series observations. J. Acoust. Soc. Am. 106, 3189–3200 (1999).ADS 

Google Scholar 
Aroyan, J. L. et al. Acoustic models of sound production and propagation in Hearing by whales and dolphins 409–469 (Springer, 2000).
Google Scholar 
Cummings, W. C. & Thompson, P. O. Underwater sounds from the blue whale, Balaenoptera musculus. J. Acoust. Soc. Am. 50, 1193–1198 (1971).ADS 

Google Scholar 
McDonald, M. A., Calambokidis, J., Teranishi, A. M. & Hildebrand, J. A. The acoustic calls of blue whales off California with gender data. J. Acoust. Soc. Am. 109, 1728–1735 (2001).ADS 
CAS 
PubMed 

Google Scholar 
Weirathmueller, M. J., Wilcock, W. S. D. & Soule, D. C. Source levels of fin whale 20 Hz pulses measured in the Northeast Pacific Ocean. J. Acoust. Soc. Am. 133, 741–749 (2013).ADS 
PubMed 

Google Scholar 
Vihtakari, M. ggOceanMaps: Plot Data on Oceanographic Maps using ‘ggplot2’. R package version 1.2.14. https://mikkovihtakari.github.io/ggOceanMaps/ (2022). More