Ecology

Laxminarayan R, Duse A, Wattal C, Zaidi AKM, Wertheim HFL, Sumpradit N, et al. Antibiotic resistance—the need for global solutions. Lancet Infect Dis. 2013;13:1057–98.PubMed 
Article 

Google Scholar 
Murray CJ, Ikuta KS, Sharara F, Swetschinski L, Robles Aguilar G, Gray A, et al. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022;399:629–55.CAS 
Article 

Google Scholar 
O’Neil J. Antimicrobial resistance: tackling a crisis for the health and wealth of nations. The review on antimicrobial resistance. 2014. https://amr-review.org/sites/default/files/AMRReviewPaper-Tacklingacrisisforthehealthandwealthofnations_1.pdf.Pang Z, Raudonis R, Glick BR, Lin T-J, Cheng Z. Antibiotic resistance in Pseudomonas aeruginosa: mechanisms and alternative therapeutic strategies. Biotechnol Adv. 2019;37:177–92.CAS 
PubMed 
Article 

Google Scholar 
Vandeplassche E, Tavernier S, Coenye T, Crabbé A. Influence of the lung microbiome on antibiotic susceptibility of cystic fibrosis pathogens. Eur Respir Rev. 2019;28:190041.PubMed 
Article 

Google Scholar 
Wheatley R, Diaz Caballero J, Kapel N, de Winter FHR, Jangir P, Quinn A, et al. Rapid evolution and host immunity drive the rise and fall of carbapenem resistance during an acute Pseudomonas aeruginosa infection. Nat Commun. 2021;12:2460.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Adamowicz EM, Flynn J, Hunter RC, Harcombe WR. Cross-feeding modulates antibiotic tolerance in bacterial communities. ISME J. 2018;12:2723–35.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Allison DG, Matthews MJ. Effect of polysaccharide interactions on antibiotic susceptibility of Pseudomonas aeruginosa. J Appl Bacteriol. 1992;73:484–8.CAS 
PubMed 
Article 

Google Scholar 
Beaudoin T, Yau YCW, Stapleton PJ, Gong Y, Wang PW, Guttman DS, et al. Staphylococcus aureus with Pseudomonas aeruginosa biofilm enhances tobramycin resistance. Npj Biofilms Microbiomes. 2017;3:25.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bottery MJ, Matthews JL, Wood AJ, Johansen HK, Pitchford JW, Friman V-P. Inter-species interactions alter antibiotic efficacy in bacterial communities. ISME J. 2022;16:812–21.CAS 
PubMed 
Article 

Google Scholar 
Elias S, Banin E. Multi-species biofilms: living with friendly neighbors. FEMS Microbiol Rev. 2012;36:990–1004.CAS 
PubMed 
Article 

Google Scholar 
Hoffman LR, Deziel E, D’Argenio DA, Lepine F, Emerson J, McNamara S, et al. Selection for Staphylococcus aureus small-colony variants due to growth in the presence of Pseudomonas aeruginosa. Proc Natl Acad Sci USA. 2006;103:19890–5.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Molina-Santiago C, Daddaoua A, Fillet S, Duque E, Ramos J-L. Interspecies signalling: Pseudomonas putida efflux pump TtgGHI is activated by indole to increase antibiotic resistance: Antibiotic resistance. Environ Microbiol. 2014;16:1267–81.CAS 
PubMed 
Article 

Google Scholar 
Orazi G, O’Toole GA. Pseudomonas aeruginosa alters Staphylococcus aureus sensitivity to vancomycin in a biofilm model of cystic fibrosis infection. mBio. 2017;8:e00873–17. https://doi.org/10.1128/mBio.00873-17.Article 
PubMed 
PubMed Central 

Google Scholar 
Perlin MH, Clark DR, McKenzie C, Patel H, Jackson N, Kormanik C, et al. Protection of Salmonella by ampicillin-resistant Escherichia coli in the presence of otherwise lethal drug concentrations. Proc R Soc B Biol Sci. 2009;276:3759–68.CAS 
Article 

Google Scholar 
Ryan RP, Fouhy Y, Garcia BF, Watt SA, Niehaus K, Yang L, et al. Interspecies signalling via the Stenotrophomonas maltophilia diffusible signal factor influences biofilm formation and polymyxin tolerance in Pseudomonas aeruginosa. Mol Microbiol. 2008;68:75–86.CAS 
PubMed 
Article 

Google Scholar 
Sherrard LJ, McGrath SJ, McIlreavey L, Hatch J, Wolfgang MC, Muhlebach MS, et al. Production of extended-spectrum β -lactamases and the potential indirect pathogenic role of Prevotella isolates from the cystic fibrosis respiratory microbiota. Int J Antimicrob Agents. 2016;47:140–5.CAS 
PubMed 
Article 

Google Scholar 
Tognon M, Köhler T, Gdaniec BG, Hao Y, Lam JS, Beaume M, et al. Co-evolution with Staphylococcus aureus leads to lipopolysaccharide alterations in Pseudomonas aeruginosa. ISME J. 2017;11:2233–43.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Adamowicz EM, Muza M, Chacón JM, Harcombe WR. Cross-feeding modulates the rate and mechanism of antibiotic resistance evolution in a model microbial community of Escherichia coli and Salmonella enterica. PLOS Pathog. 2020;16:e1008700.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bottery MJ, Pitchford JW, Friman V-P. Ecology and evolution of antimicrobial resistance in bacterial communities. ISME J. 2021;15:939–48.PubMed 
Article 

Google Scholar 
Estrela S, Brown SP. Community interactions and spatial structure shape selection on antibiotic resistant lineages. PLOS Comput Biol. 2018;14:e1006179.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Klümper U, Recker M, Zhang L, Yin X, Zhang T, Buckling A, et al. Selection for antimicrobial resistance is reduced when embedded in a natural microbial community. ISME J. 2019;13:2927–37.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Scheuerl T, Hopkins M, Nowell RW, Rivett DW, Barraclough TG, Bell T. Bacterial adaptation is constrained in complex communities. Nat Commun. 2020;11:754.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Sorg RA, Lin L, van Doorn GS, Sorg M, Olson J, Nizet V, et al. Collective resistance in microbial communities by intracellular antibiotic deactivation. PLOS Biol. 2016;14:e2000631.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Kulczycki LL, Kostuch M, Bellanti JA. A clinical perspective of cystic fibrosis and new genetic findings: relationship of CFTR mutations to genotype-phenotype manifestations. Am J Med Genet. 2003;116A:262–7.PubMed 
Article 

Google Scholar 
Flume PA, Mogayzel PJ, Robinson KA, Rosenblatt RL, Quittell L, Marshall BC. Cystic fibrosis pulmonary guidelines: pulmonary complications: hemoptysis and pneumothorax. Am J Respir Crit Care Med. 2010;182:298–306.PubMed 
Article 

Google Scholar 
Belkin RA, Henig NR, Singer LG, Chaparro C, Rubenstein RC, Xie SX, et al. Risk factors for death of patients with cystic fibrosis awaiting lung transplantation. Am J Respir Crit Care Med. 2006;173:659–66.PubMed 
Article 

Google Scholar 
Martin C, Hamard C, Kanaan R, Boussaud V, Grenet D, Abély M, et al. Causes of death in French cystic fibrosis patients: the need for improvement in transplantation referral strategies! J Cyst Fibros. 2016;15:204–12.PubMed 
Article 

Google Scholar 
Döring G, Conway SP, Heijerman HGM, Hodson ME, Høiby N, Smyth A, et al. Antibiotic therapy against Pseudomonas aeruginosa in cystic fibrosis: a European consensus. Eur Respir J. 2000;16:749.PubMed 
Article 

Google Scholar 
Marshall B, Faro A, Brown W, Elbert A, Fink A, Cromwell E, et al. Patient registry, annual data report. Bethesda, Maryland: Cystic Fibrosis Foundation; 2020. https://www.cff.org/sites/default/files/2021-11/Patient-Registry-Annual-Data-Report.pdf.Vongthilath R, Richaud Thiriez B, Dehillotte C, Lemonnier L, Guillien A, Degano B, et al. Clinical and microbiological characteristics of cystic fibrosis adults never colonized by Pseudomonas aeruginosa: analysis of the French CF registry. PLOS ONE. 2019;14:e0210201.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zolin A, Orenti A, Jung A, van Rens J. ECFSPR annual report 2019. Denmark: European Cystic Fibrosis Society Patient Registry; 2021. https://www.ecfs.eu/sites/default/files/general-content-files/working-groups/ecfs-patient-registry/ECFSPR_Report_2019_v1_16Feb2022.pdf.Conrad D, Haynes M, Salamon P, Rainey PB, Youle M, Rohwer F. Cystic fibrosis therapy: a community ecology perspective. Am J Respir Cell Mol Biol. 2013;48:150–6.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Filkins LM, Graber JA, Olson DG, Dolben EL, Lynd LR, Bhuju S, et al. Coculture of Staphylococcus aureus with Pseudomonas aeruginosa drives S. aureus towards fermentative metabolism and reduced viability in a cystic fibrosis model. J Bacteriol. 2015;197:2252–64.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zhao J, Schloss PD, Kalikin LM, Carmody LA, Foster BK, Petrosino JF, et al. Decade-long bacterial community dynamics in cystic fibrosis airways. Proc Natl Acad Sci USA. 2012;109:5809–14.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ballestero S, Vírseda I, Escobar H, Suárez L, Baquero F. Stenotrophomonas maltophilia in cystic fibrosis patients. Eur J Clin Microbiol Infect Dis. 1995;14:728–9.CAS 
PubMed 
Article 

Google Scholar 
Gladman G, Connor PJ, Williams RF, David TJ. Controlled study of Pseudomonas cepacia and Pseudomonas maltophilia in cystic fibrosis. Arch Dis Child. 1992;67:192–5.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Goss CH. Association between Stenotrophomonas maltophilia and lung function in cystic fibrosis. Thorax. 2004;59:955–9.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Parkins MD, Floto RA. Emerging bacterial pathogens and changing concepts of bacterial pathogenesis in cystic fibrosis. J Cyst Fibros. 2015;14:293–304.CAS 
PubMed 
Article 

Google Scholar 
Goss CH, Otto K, Aitken ML, Rubenfeld GD. Detecting Stenotrophomonas maltophilia does not reduce survival of patients with cystic fibrosis. Am J Respir Crit Care Med. 2002;166:356–61.PubMed 
Article 

Google Scholar 
Alonso A, Martínez JL. Multiple antibiotic resistance in Stenotrophomonas maltophilia. Antimicrob Agents Chemother. 1997;41:1140–2.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zhang L, Li XZ, Poole K. Multiple antibiotic resistance in Stenotrophomonas maltophilia: involvement of a multidrug efflux system. Antimicrob Agents Chemother. 2000;44:287–93.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Abda EM, Krysciak D, Krohn-Molt I, Mamat U, Schmeisser C, Förstner KU, et al. Phenotypic heterogeneity affects Stenotrophomonas maltophilia K279a colony morphotypes and β-lactamase expression. Front Microbiol. 2015;6:1373.Okazaki A, Avison MB. Induction of L1 and L2 β-lactamase production in Stenotrophomonas maltophilia is dependent on an AmpR-type regulator. Antimicrob Agents Chemother. 2008;52:1525–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Walsh TR, Hall L, Assinder SJ, Nichols WW, Cartwright SJ, MacGowan AP, et al. Sequence analysis of the L1 metallo-β-lactamase from Xanthomonas maltophilia. Biochim Biophys Acta. 1994;1218:199–201.CAS 
PubMed 
Article 

Google Scholar 
Yang Z, Liu W, Cui Q, Niu W, Li H, Zhao X, et al. Prevalence and detection of Stenotrophomonas maltophilia carrying metallo-I2-lactamase blaL1 in Beijing, China. Front Microbiol. 2014;5:692.Kataoka D, Fujiwara H, Kawakami T, Tanaka Y, Tanimoto A, Ikawa S, et al. The indirect pathogenicity of Stenotrophomonas maltophilia. Int J Antimicrob Agents. 2003;22:601–6.CAS 
PubMed 
Article 

Google Scholar 
Winstanley C, O’Brien S, Brockhurst MA. Pseudomonas aeruginosa evolutionary adaptation and diversification in cystic fibrosis chronic lung infections. Trends Microbiol. 2016;24:327–37.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
McGuigan L, Callaghan M. The evolving dynamics of the microbial community in the cystic fibrosis lung. Environ Microbiol. 2015;17:16–28.PubMed 
Article 

Google Scholar 
Wistrand-Yuen E, Knopp M, Hjort K, Koskiniemi S, Berg OG, Andersson DI. Evolution of high-level resistance during low-level antibiotic exposure. Nat Commun. 2018;9:1599.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Mahrt N, Tietze A, Künzel S, Franzenburg S, Barbosa C, Jansen G, et al. Bottleneck size and selection level reproducibly impact evolution of antibiotic resistance. Nat Ecol Evol. 2021;5:1233–1242.Govaert L, Altermatt F, De Meester L, Leibold MA, McPeek MA, Pantel JH, et al. Integrating fundamental processes to understand eco‐evolutionary community dynamics and patterns. Funct Ecol. 2021;35:2138–55.Article 

Google Scholar 
Palmer KL, Aye LM, Whiteley M. Nutritional cues control Pseudomonas aeruginosa multicellular behavior in cystic fibrosis sputum. J Bacteriol. 2007;189:8079–87.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Souza Barbosa F, Capra Pezzi L, Tsao M, Oliveira TF, Manoela Dias Macedo S, Schapoval EES, et al. Stability and degradation products of imipenem applying High‐Resolution Mass Spectrometry: an analytical study focused on solutions for infusion. Biomed Chromatogr. 2018;33:4471.Verpooten G, Verbist L, Buntinx A, Entwistle L, Jones K, Broe M. The pharmacokinetics of imipenem (thienamycin-formamidine) and the renal dehydropeptidase inhibitor cilastatin sodium in normal subjects and patients with renal failure. Br J Clin Pharmacol. 1984;18:183–93.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Li H, Luo Y-F, Williams BJ, Blackwell TS, Xie C-M. Structure and function of OprD protein in Pseudomonas aeruginosa: from antibiotic resistance to novel therapies. Int J Med Microbiol. 2012;302:63–8.CAS 
PubMed 
Article 

Google Scholar 
Kousser C, Clark C, Sherrington S, Voelz K, Hall RA. Pseudomonas aeruginosa inhibits Rhizopus microsporus germination through sequestration of free environmental iron. Sci Rep. 2019;9:5714.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Schalk IJ, Guillon L. Pyoverdine biosynthesis and secretion in Pseudomonas aeruginosa: implications for metal homeostasis: pyoverdine biosynthesis. Environ Microbiol. 2013;15:1661–73.CAS 
PubMed 
Article 

Google Scholar 
Duan X, Pan Y, Cai Z, Liu Y, Zhang Y, Liu M, et al. rpoS-mutation variants are selected in Pseudomonas aeruginosa biofilms under imipenem pressure. Cell Biosci. 2021;11:138.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zhu K, Chen S, Sysoeva TA, You L. Universal antibiotic tolerance arising from antibiotic-triggered accumulation of pyocyanin in Pseudomonas aeruginosa. PLOS Biol. 2019;17:e3000573.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
El-Fouly MZ, Sharaf AM, Shahin AAM, El-Bialy HA, Omara AMA. Biosynthesis of pyocyanin pigment by Pseudomonas aeruginosa. J Radiat Res Appl Sci. 2015;8:36–48.CAS 
Article 

Google Scholar 
Baron SS, Rowe JJ. Antibiotic action of pyocyanin. Antimicrob Agents Chemother. 1981;20:814–20.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kimura M, Ohta T. The average number of generations until fixation of a mutant gene in a finite population. Genetics. 1969;61:763–71.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Meirelles LA, Perry EK, Bergkessel M, Newman DK. Bacterial defenses against a natural antibiotic promote collateral resilience to clinical antibiotics. PLOS Biol. 2021;19:e3001093.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hall JPJ, Harrison E, Brockhurst MA. Competitive species interactions constrain abiotic adaptation in a bacterial soil community. Evol Lett. 2018;2:580–9.PubMed 
PubMed Central 
Article 

Google Scholar 
Scanlan PD, Hall AR, Blackshields G, Friman V-P, Davis MR, Goldberg JB, et al. Coevolution with bacteriophages drives genome-wide host evolution and constrains the acquisition of abiotic-beneficial mutations. Mol Biol Evol. 2015;32:1425–35.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Finkel SE. Long-term survival during stationary phase: evolution and the GASP phenotype. Nat Rev Microbiol. 2006;4:113–20.CAS 
PubMed 
Article 

Google Scholar 
Gefen O, Fridman O, Ronin I, Balaban NQ. Direct observation of single stationary-phase bacteria reveals a surprisingly long period of constant protein production activity. Proc Natl Acad Sci. 2014;111:556–61.CAS 
PubMed 
Article 

Google Scholar 
Fang Z, Zhang L, Huang Y, Qing Y, Cao K, Tian G, et al. OprD mutations and inactivation in imipenem-resistant Pseudomonas aeruginosa isolates from China. Infect Genet Evol. 2014;21:124–8.CAS 
PubMed 
Article 

Google Scholar 
Hirabayashi A, Kato D, Tomita Y, Iguchi M, Yamada K, Kouyama Y, et al. Risk factors for and role of OprD protein in increasing minimal inhibitory concentrations of carbapenems in clinical isolates of Pseudomonas aeruginosa. J Med Microbiol. 2017;66:1562–72.CAS 
PubMed 
Article 

Google Scholar 
Huang H, Jeanteur D, Pattus F, Hancock REW. Membrane topology and site-specific mutagenesis of Pseudomonas aeruginosa porin OprD. Mol Microbiol. 1995;16:931–41.CAS 
PubMed 
Article 

Google Scholar 
Fournier D, Richardot C, Müller E, Robert-Nicoud M, Llanes C, Plésiat P, et al. Complexity of resistance mechanisms to imipenem in intensive care unit strains of Pseudomonas aeruginosa. J Antimicrob Chemother. 2013;68:1772–80.CAS 
PubMed 
Article 

Google Scholar 
Kao C-Y, Chen S-S, Hung K-H, Wu H-M, Hsueh P-R, Yan J-J, et al. Overproduction of active efflux pump and variations of OprD dominate in imipenem-resistant Pseudomonas aeruginosa isolated from patients with bloodstream infections in Taiwan. BMC Microbiol. 2016;16:107.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Ocampo-Sosa AA, Cabot G, Rodríguez C, Roman E, Tubau F, Macia MD, et al. Alterations of OprD in carbapenem-intermediate and -susceptible strains of Pseudomonas aeruginosa isolated from patients with bacteremia in a Spanish multicenter study. Antimicrob Agents Chemother. 2012;56:1703–13.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Shu J-C, Kuo A-J, Su L-H, Liu T-P, Lee M-H, Su I-N, et al. Development of carbapenem resistance in Pseudomonas aeruginosa is associated with OprD polymorphisms, particularly the amino acid substitution at codon 170. J Antimicrob Chemother. 2017;72:2489–95.CAS 
PubMed 
Article 

Google Scholar 
Pernet E, Guillemot L, Burgel P-R, Martin C, Lambeau G, Sermet-Gaudelus I, et al. Pseudomonas aeruginosa eradicates Staphylococcus aureus by manipulating the host immunity. Nat Commun. 2014;5:5105.CAS 
PubMed 
Article 

Google Scholar 
Briaud P, Camus L, Bastien S, Doléans-Jordheim A, Vandenesch F, Moreau K. Coexistence with Pseudomonas aeruginosa alters Staphylococcus aureus transcriptome, antibiotic resistance and internalization into epithelial cells. Sci Rep. 2019;9:16564.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Khare A, Tavazoie S. Multifactorial competition and resistance in a two-species bacterial system. PLOS Genet. 2015;11:e1005715.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Mashburn LM, Jett AM, Akins DR, Whiteley M. Staphylococcus aureus serves as an iron source for Pseudomonas aeruginosa during in vivo coculture. J Bacteriol. 2005;187:554–66.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Cirz RT, O’Neill BM, Hammond JA, Head SR, Romesberg FE. Defining the Pseudomonas aeruginosa SOS response and its role in the global response to the antibiotic ciprofloxacin. J Bacteriol. 2006;188:7101–10.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
García-Contreras R, Nuñez-López L, Jasso-Chávez R, Kwan BW, Belmont JA, Rangel-Vega A, et al. Quorum sensing enhancement of the stress response promotes resistance to quorum quenching and prevents social cheating. ISME J. 2015;9:115–25.PubMed 
Article 
CAS 

Google Scholar 
Moradali MF, Ghods S, Rehm BHA. Pseudomonas aeruginosa lifestyle: a paradigm for adaptation, survival, and persistence. Front Cell Infect Microbiol 2017;7:39.Vogt SL, Green C, Stevens KM, Day B, Erickson DL, Woods DE, et al. The stringent response is essential for Pseudomonas aeruginosa virulence in the rat lung agar bead and Drosophila melanogaster feeding models of infection. Infect Immun. 2011;79:4094–104.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Baron SS, Terranova G, Rowe JJ. Molecular mechanism of the antimicrobial action of pyocyanin. Curr Microbiol. 1989;18:223–30.CAS 
Article 

Google Scholar 
Castañeda-Tamez P, Ramírez-Peris J, Pérez-Velázquez J, Kuttler C, Jalalimanesh A, Saucedo-Mora MÁ, et al. Pyocyanin restricts social cheating in Pseudomonas aeruginosa. Front Microbiol. 2018;9:1348.PubMed 
PubMed Central 
Article 

Google Scholar 
Fontoura R, Spada JC, Silveira ST, Tsai SM, Brandelli A. Purification and characterization of an antimicrobial peptide produced by Pseudomonas sp. strain 4B. World J Microbiol Biotechnol. 2009;25:205–13.CAS 
Article 

Google Scholar 
Hassan HM, Fridovich I. Mechanism of the antibiotic action pyocyanine. J Bacteriol. 1980;141:156–63.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Machan ZA, Pitt TL, White W, Watson D, Taylor GW, Cole PJ, et al. Interaction between Pseudomonas aeruginosa and Staphylococcus aureus: description of an antistaphylococcal substance. J Med Microbiol. 1991;34:213–7.CAS 
PubMed 
Article 

Google Scholar 
Raji El Feghali PA, Nawas T. Pyocyanin: a powerful inhibitor of bacterial growth and biofilm formation. Madridge J Case Rep Stud. 2018;3:101–7.Article 

Google Scholar 
Saha S, Thavasi R, Jayalakshmi S. Phenazine pigments from Pseudomonas aeruginosa and their application as antibacterial agent and food colourants. Res J Microbiol. 2008;3:122–8.CAS 
Article 

Google Scholar 
Schiessl KT, Hu F, Jo J, Nazia SZ, Wang B, Price-Whelan A, et al. Phenazine production promotes antibiotic tolerance and metabolic heterogeneity in Pseudomonas aeruginosa biofilms. Nat Commun. 2019;10:762.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Jagmann N, Brachvogel H-P, Philipp B. Parasitic growth of Pseudomonas aeruginosa in co-culture with the chitinolytic bacterium Aeromonas hydrophila: parasitic growth of Pseudomonas aeruginosa. Environ Microbiol. 2010;12:1787–802.CAS 
PubMed 
Article 

Google Scholar 
Noto MJ, Burns WJ, Beavers WN, Skaar EP. Mechanisms of pyocyanin toxicity and genetic determinants of resistance in Staphylococcus aureus. J Bacteriol. 2017;199:00221–17.Venkataraman A, Rosenbaum MA, Perkins SD, Werner JJ, Angenent LT. Metabolite-based mutualism between Pseudomonas aeruginosa PA14 and Enterobacter aerogenes enhances current generation in bioelectrochemical systems. Energy Environ Sci. 2011;4:4550.CAS 
Article 

Google Scholar 
Waite RD, Qureshi MR, Whiley RA. Modulation of behaviour and virulence of a high alginate expressing Pseudomonas aeruginosa strain from cystic fibrosis by oral commensal bacterium Streptococcus anginosus. PLOS ONE. 2017;12:e0173741.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Whooley MA, McLoughlin AJ. The regulation of pyocyanin production in Pseudomonas aeruginosa. Eur J Appl Microbiol Biotechnol. 1982;15:161–6.CAS 
Article 

Google Scholar 
Elbargisy RM. Optimization of nutritional and environmental conditions for pyocyanin production by urine isolates of Pseudomonas aeruginosa. Saudi J Biol Sci. 2021;28:993–1000.CAS 
PubMed 
Article 

Google Scholar 
Gupta S, Laskar N, Kadouri DE. Evaluating the effect of oxygen concentrations on antibiotic sensitivity, growth, and biofilm formation of human pathogens. Microbiol Insights. 2016;9. https://doi.org/10.4137/MBI.S40767.Article 
PubMed 
PubMed Central 

Google Scholar 
Worlitzsch D, Tarran R, Ulrich M, Schwab U, Cekici A, Meyer KC, et al. Effects of reduced mucus oxygen concentration in airway Pseudomonas infections of cystic fibrosis patients. J Clin Investig. 2002;109:317–25.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Skurnik D, Roux D, Cattoir V, Danilchanka O, Lu X, Yoder-Himes DR, et al. Enhanced in vivo fitness of carbapenem-resistant oprD mutants of Pseudomonas aeruginosa revealed through high-throughput sequencing. Proc Natl Acad Sci USA. 2013;110:20747–52.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Higgins S, Heeb S, Rampioni G, Fletcher MP, Williams P, Cámara M. Differential regulation of the phenazine biosynthetic operons by quorum sensing in Pseudomonas aeruginosa PAO1-N. Front Cell Infect Microbiol. 2018;8:252.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Dragoš A, Martin M, Falcón García C, Kricks L, Pausch P, Heimerl T, et al. Collapse of genetic division of labour and evolution of autonomy in pellicle biofilms. Nat Microbiol. 2018;3:1451–60.PubMed 
Article 
CAS 

Google Scholar 
Cuthbertson L, Walker AW, Oliver AE, Rogers GB, Rivett DW, Hampton TH, et al. Lung function and microbiota diversity in cystic fibrosis. Microbiome. 2020;8:45.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rogers GB, Carroll MP, Serisier DJ, Hockey PM, Jones G, Bruce KD. Characterization of bacterial community diversity in cystic fibrosis lung infections by use of 16S ribosomal DNA terminal restriction fragment length polymorphism profiling. J Clin Microbiol. 2004;42:5176–83.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Workentine ML, Sibley CD, Glezerson B, Purighalla S, Norgaard-Gron JC, Parkins MD, et al. Phenotypic heterogeneity of Pseudomonas aeruginosa populations in a cystic fibrosis patient. PLoS ONE. 2013;8:e60225.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Valdezate S. Persistence and variability of Stenotrophomonas maltophilia in cystic fibrosis patients, Madrid, 1991-8. Emerg Infect Dis. 2001;7:113–22.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Dalbøge CS, Hansen CR, Pressler T, Høiby N, Johansen HK. Chronic pulmonary infection with Stenotrophomonas maltophilia and lung function in patients with cystic fibrosis. J Cyst Fibros. 2011;10:318–25.PubMed 
Article 

Google Scholar 
Jeon YD, Jeong WY, Kim MH, Jung IY, Ahn MY, Ann HW, et al. Risk factors for mortality in patients with Stenotrophomonas maltophilia bacteremia. Medicine. 2016;95:e4375.PubMed 
PubMed Central 
Article 

Google Scholar 
Sherrard LJ, Tunney MM, Elborn JS. Antimicrobial resistance in the respiratory microbiota of people with cystic fibrosis. Lancet Lond Engl. 2014;384:703–13.CAS 
Article 

Google Scholar 
Choi K-H, Schweizer HP. Mini-Tn7 insertion in bacteria with single attTn7 sites: example Pseudomonas aeruginosa. Nat Protoc. 2006;1:153–61.CAS 
PubMed 
Article 

Google Scholar 
Jelsbak L, Johansen HK, Frost A-L, Thøgersen R, Thomsen LE, Ciofu O, et al. Molecular epidemiology and dynamics of Pseudomonas aeruginosa populations in lungs of cystic fibrosis patients. Infect Immun. 2007;75:2214–24.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Yeung ATY, Parayno A, Hancock REW. Mucin promotes rapid surface motility in Pseudomonas aeruginosa. mBio. 2012;3:300073–12.Kirchner S, Fothergill JL, Wright EA, James CE, Mowat E, Winstanley C. Use of artificial sputum medium to test antibiotic efficacy against Pseudomonas aeruginosa in conditions more relevant to the cystic fibrosis lung. J Vis Exp. 2012;64:3857.Hill DB, Long RF, Kissner WJ, Atieh E, Garbarine IC, Markovetz MR, et al. Pathological mucus and impaired mucus clearance in cystic fibrosis patients result from increased concentration, not altered pH. Eur Respir J. 2018;52:1801297.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Benoni G, Cuzzolin L, Bertrand C, Puchetti V, Velo G. Imipenem kinetics in serum, lung tissue and pericardial fluid in patients undergoing thoracotomy. J Antimicrob Chemother. 1987;20:725–8.CAS 
PubMed 
Article 

Google Scholar 
Radhakrishnan M, Jaganath A, Rao GSU, Kumari HBV. Nebulized imipenem to control nosocomial pneumonia caused by Pseudomonas aeruginosa. J Crit Care. 2008;23:148–50.CAS 
PubMed 
Article 

Google Scholar 
Wenzler E, Fraidenburg DR, Scardina T, Danziger LH. Inhaled antibiotics for gram-negative respiratory infections. Clin Microbiol Rev. 2016;29:581–632.PubMed 
PubMed Central 
Article 

Google Scholar 
The European Committee on Antimicrobial Susceptibility Testing. Breakpoint tables for interpretation of MICs and zone diameters.Version 12.0, 2022. http://www.eucast.org.Kang D, Revtovich AV, Chen Q, Shah KN, Cannon CL, Kirienko NV. Pyoverdine-dependent virulence of Pseudomonas aeruginosa isolates from cystic fibrosis patients. Front Microbiol. 2019;10:2048.PubMed 
PubMed Central 
Article 

Google Scholar 
Martin LW, Reid DW, Sharples KJ, Lamont IL. Pseudomonas siderophores in the sputum of patients with cystic fibrosis. BioMetals. 2011;24:1059–67.CAS 
PubMed 
Article 

Google Scholar 
Caldwell CC, Chen Y, Goetzmann HS, Hao Y, Borchers MT, Hassett DJ, et al. Pseudomonas aeruginosa exotoxin pyocyanin causes cystic fibrosis airway pathogenesis. Am J Pathol. 2009;175:2473–88.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
O’Loughlin CT, Miller LC, Siryaporn A, Drescher K, Semmelhack MF, Bassler BL. A quorum-sensing inhibitor blocks Pseudomonas aeruginosa virulence and biofilm formation. Proc Natl Acad Sci USA. 2013;110:17981–6.PubMed 
PubMed Central 
Article 

Google Scholar 
Sass G, Nazik H, Penner J, Shah H, Ansari SR, Clemons KV, et al. Studies of Pseudomonas aeruginosa mutants indicate pyoverdine as the central factor in inhibition of Aspergillus fumigatus biofilm. J Bacteriol. 2018;200:00345–17.Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19:455–77.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–9.CAS 
PubMed 
Article 

Google Scholar 
Deatherage DE, Barrick JE. Identification of mutations in laboratory-evolved microbes from next-generation sequencing data using breseq. In: Sun L, Shou W, editors. Engineering and Analyzing Multicellular Systems. New York, NY: Springer New York; 2014. p. 165–88.Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, et al. Integrative genomics viewer. Nat Biotechnol. 2011;29:24–6.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Thorvaldsdottir H, Robinson JT, Mesirov JP. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform. 2013;14:178–92.CAS 
PubMed 
Article 

Google Scholar  More

Xie, Y., Fang, M. & Shauman, K. STEM education. Annu. Rev. Sociol. 41, 331–357 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
Chen, X. STEM attrition: College students’ paths into and out of STEM fields. National Center for Education Statistics. Retrieved from http://ies.ed.gov/pubsearch/pubsinfo.asp?pubid=2014001rev. Accessed 22 September 2021.Huang G, Taddese N, Walter E (2000) Entry and persistence of women and minorities in college science and engineering education. National Center for Education Statistics. Retrieved from https://eric.ed.gov/?id=ED566411. Accessed 22 September 2021.Hurtado, S., Eagan, K., & Chang, M. Degrees of Success: Bachelor’s Degree Completion Rates among Initial STEM Majors (Higher Education Research Institute, Los Angeles, CA) (2010).National Science Foundation, Broadening Participation Working Group (2014) Pathways to broadening participation in response to the CEOSE 2011–2012 recommendation. National Science Foundation. Retrieved from https://www.nsf.gov/pubs/2015/nsf15037/nsf15037.pdf. Accessed 22 Sep 2021.James, S. M. & Singer, S. R. From the NSF: The National Science Foundation’s investments in broadening participation in science, technology, engineering, and mathematics education through research and capacity building. CBE Life Sci. Educ. 15(3), 1–8 (2016).Article 

Google Scholar 
Smith, B. L., MacGregor, J., Matthews, R. & Gabelnick, F. Learning communities: Reforming undergraduate education (Jossey-Bass, 2004).
Google Scholar 
Andrade, M. S. Learning communities: Examining positive outcomes. J. Coll. Stud. Ret. 9(1), 1–20 (2007).Article 

Google Scholar 
Maton, K. I., Pollard, S. A., McDougall Weise, T. V. & Hrabowski, F. A. Meyerhoff Scholars Program: A strengths-based, institution-wide approach to increasing diversity in science, technology, engineering, and mathematics. Mt Sinai J. Med. 79(5), 610–623 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
Dagley, M., Georgiopoulos, M., Reece, A. & Young, C. Increasing retention and graduation rates through a STEM learning community. J. Coll. Stud. Ret. 18(2), 167–182 (2016).Article 

Google Scholar 
National Survey of Student Engagement (2015) Engagement Insights: Survey Findings on the Quality of Undergraduate Education—Annual Results 2015 (Bloomington, IN).Tinto, V. Leaving college: Rethinking the causes and cures of student attrition (University of Chicago Press, 1987).
Google Scholar 
Tinto, V. Learning better together: The impact of learning communities on student success. Higher Educ. Monogr. Ser. 1(8), 1–8 (2003).
Google Scholar 
Otto, S., Evins, M. A., Boyer-Pennington, M. & Brinthaupt, T. M. Learning communities in higher education: Best practices. Journal of Student Success and Retention 2(1), 1–20 (2015).
Google Scholar 
Boda, Z., Elmer, T., Vörös, A. & Stadtfeld, C. Short-term and long-term effects of a social network intervention on friendships among university students. Sci. Rep. 10(1), 1–2 (2020).Article 
CAS 

Google Scholar 
Hotchkiss, J. L., Moore, R. E. & Pitts, M. M. Freshman learning communities, college performance, and retention. Educ. Econ. 14(2), 197–210 (2006).Article 

Google Scholar 
Whalen, D. F. & Shelley, M. C. Academic success for STEM and non-STEM majors. J. STEM Educ. 11(1), 45–60 (2010).
Google Scholar 
Xu, D., Solanki, S., McPartlan, P. & Sato, B. EASEing students into college: The impact of multidimensional support for underprepared students. Educ. Res. 47(7), 435–450 (2018).Article 

Google Scholar 
Jaffee, D., Carle, A., Phillips, R. & Paltoo, L. Intended and unintended consequences of first-year learning communities: An initial investigation. J. First-Year Exp. Stud. Trans. 20(1), 53–70 (2008).
Google Scholar 
Tinto, V. & Goodsell, A. Freshman interest groups and the first-year experience: Constructing student communities in a large university. J. First Year Exp. Stud. Trans. 6(1), 7–28 (1994).
Google Scholar 
Domizi, D. Student perceptions about their informal learning experiences in a first-year residential learning community. J. First Year Exp. Stud. Transit. 20(1), 97–110 (2008).
Google Scholar 
Lee, D. S. & Lemieux, T. Regression discontinuity designs in economics. J. Econ. Lit. 2, 281–355 (2010).Article 

Google Scholar 
Jacob, R., Zhu, P., Somers, M.A., & Bloom, H. A Practical Guide to Regression Discontinuity (MDRC, New York, NY, 2012).Hays, R. B. & Oxley, D. Social network development and functioning during a life transition. J. Pers. Soc. Psychol. 50(2), 305–313 (1986).CAS 
PubMed 
Article 

Google Scholar 
Freeman, T. M., Anderman, L. H. & Jensen, J. M. Sense of belonging in college freshmen at the classroom and campus levels. J. Exp. Educ. 75(3), 203–220 (2007).Article 

Google Scholar 
Zumbrunn, S., McKim, C., Buhs, E. & Hawley, L. R. Support, belonging, motivation, and engagement in the college classroom: A mixed method study. Instr. Sci. 42(5), 661–684 (2014).Article 

Google Scholar 
Hasan, S. & Bagde, S. The mechanics of social capital and academic performance in an Indian college. Am. Sociol. Rev. 78(6), 1009–1032 (2013).Article 

Google Scholar 
Stadtfeld, C., Vörös, A., Elmer, T., Boda, Z. & Raabe, I. J. Integration in emerging social networks explains academic failure and success. Proc. Natl. Acad. Sci. USA 116(3), 792–797 (2019).CAS 
PubMed 
Article 

Google Scholar 
Kraemer, B. A. The academic and social integration of Hispanic students into college. Rev. High Educ. 20(2), 163–179 (1997).Article 

Google Scholar 
Nora, A. Two-year colleges and minority students’ educational aspirations: Help or hindrance. Higher Educ. Handb. Theory Res. 9(3), 212–247 (1993).
Google Scholar 
McCabe, J.M. Connecting in College: How Friendship Networks Matter for Academic and Social Success (University of Chicago Press, Chicago, IL, 2016).Felten, P., & Lambert, L. M. Relationship-rich Education: How Human Connections Drive Success in College (Johns Hopkins University Press, Baltimore, MD, 2020).Hallinan, M. T. The peer influence process. Stud. Educ. Eval. 7(3), 285–306 (1981).Article 

Google Scholar 
Thomas, S. L. Ties that bind: A social network approach to understanding student integration and persistence. J. Higher Educ. 71(5), 591–615 (2000).
Google Scholar 
Turetsky, K. M., Purdie-Greenaway, V., Cook, J. E., Curley, J. P. & Cohen, G. L. A psychological intervention strengthens students’ peer social networks and promotes persistence in STEM. Sci. Adv. 6(45), 1–10 (2020).Article 

Google Scholar 
Dokuka, S., Valeeva, D. & Yudkevich, M. How academic achievement spreads: The role of distinct social networks in academic performance diffusion. PLoS ONE 15(7), 1–16 (2020).Article 
CAS 

Google Scholar 
Epstein, J. L. & Karweit, N. (eds) Friends in school: Patterns of selection and influence in secondary schools (Academic Press, 1983).
Google Scholar 
Feld, S. L. The focused organization of social ties. AJS 86(5), 1015–1035 (1981).
Google Scholar 
Rivera, M. T., Soderstrom, S. B. & Uzzi, B. Dynamics of dyads in social networks: Assortative, relational, and proximity mechanisms. Annu. Rev. Sociol. 36, 91–115 (2010).Article 

Google Scholar 
Mollenhorst, G., Volker, B. & Flap, H. Changes in personal relationships: How social contexts affect the emergence and discontinuation of relationships. Soc. Netw. 37, 65–80 (2014).Article 

Google Scholar 
Thomas, R. J. Sources of friendship and structurally induced homophily across the life course. Sociol Perspect 62(6), 822–843 (2019).Article 

Google Scholar 
Kubitschek, W. N. & Hallinan, M. T. Tracking and students’ friendships. Soc. Psychol. Q 46, 1–5 (1998).Article 

Google Scholar 
Frank, K. A., Muller, C. & Mueller, A. S. The embeddedness of adolescent friendship nominations: The formation of social capital in emergent network structures. AJS 119(1), 216–253 (2013).PubMed 
PubMed Central 

Google Scholar 
Kossinets, G. & Watts, D. J. Origins of homophily in an evolving social network. AJS 115(2), 405–450 (2009).
Google Scholar 
Wimmer, A. & Lewis, K. Beyond and below racial homophily: ERG models of a friendship network documented on Facebook. AJS 116(2), 583–642 (2010).PubMed 

Google Scholar 
Hallinan, M. T. & Sørensen, A. B. Ability grouping and student friendships. Am. Educ. Res. J. 51, 485–499 (1985).Article 

Google Scholar 
Leszczensky, L. & Pink, S. Ethnic segregation of friendship networks in school: Testing a rational-choice argument of differences in ethnic homophily between classroom-and grade-level networks. Soc. Netw. 42, 18–26 (2015).Article 

Google Scholar 
DiMaggio, P. & Garip, F. Network effects and social inequality. Annu. Rev. Sociol. 54, 93–118 (2012).Article 

Google Scholar 
Johnson, A. M. ‘“I can turn it on when i need to”’: Pre-college Integration, culture, and peer academic engagement among black and Latino/a engineering Students. Sociol. Educ. 56, 1–20 (2019).Article 

Google Scholar 
Perry, B. L., Pescosolido, B. A. & Borgatti, S. P. Egocentric network analysis: Foundations, methods, and models (Cambridge University Press, 2018).Book 

Google Scholar 
Wasserman, S. & Faust, K. Social network analysis: Methods and applications (Cambridge University Press, 1994).MATH 
Book 

Google Scholar 
Hartup, W. W. & Stevens, N. Friendships and adaptation in the life course. Psychol. Bull. 121(3), 355 (1997).Article 

Google Scholar 
Vaquera, E. & Kao, G. Do you like me as much as I like you? Friendship reciprocity and its effects on school outcomes among adolescents. Soc. Sci. Res. 37(1), 55–72 (2008).PubMed 
PubMed Central 
Article 

Google Scholar 
Imbens, G. W. & Lemieux, T. Regression discontinuity designs: A guide to practice. J. Econom. 142(2), 615–635 (2008).MathSciNet 
MATH 
Article 

Google Scholar 
Imbens, G. W. & Angrist, J. D. Identification and estimation of local average treatment effects. Econometrica 62(2), 467–475 (1994).MATH 
Article 

Google Scholar 
Robins, G., Pattison, P., Kalish, Y. & Lusher, D. An introduction to exponential random graph (p*) models for social networks. Soc. Netw. 29(2), 173–191 (2007).Article 

Google Scholar 
Handcock, M. S., Hunter, D. R., Butts, C. T., Goodreau, S. M. & Morris, M. Statnet: Software tools for the representation, visualization, analysis and simulation of network data. J. Stat. Softw. 24(1), 1548–7660 (2008).PubMed 
PubMed Central 
Article 

Google Scholar 
Calonico, S., Cattaneo, M. D. & Titiunik, R. Optimal data-driven regression discontinuity plots. J. Am. Stat. Assoc. 110(512), 1753–1769 (2015).MathSciNet 
CAS 
MATH 
Article 

Google Scholar 
Duxbury, S. W. The problem of scaling in exponential random graph models. Sociol. Methods Res. https://doi.org/10.1177/0049124120986178:1-39 (2021).MathSciNet 
Article 

Google Scholar 
McPherson, M., Smith-Lovin, L. & Cook, J. M. Birds of a feather: Homophily in social networks. Annu. Rev. Sociol. 27(1), 415–444 (2001).Article 

Google Scholar 
Kadushin, C. Understanding social networks: Theories, concepts, and findings (Oxford University Press, 2012).
Google Scholar 
Flashman, J. Academic achievement and its impact on friend dynamics. Sociol. Educ. 85(1), 61–80 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
Carrell, S. E., Sacerdote, B. I. & West, J. E. From natural variation to optimal policy? The importance of endogenous peer group formation. Econometrica 81(3), 855–882 (2013).MathSciNet 
MATH 
Article 

Google Scholar 
Cox, A. B. Cohorts, ‘“siblings”,’ and mentors: Organizational structures and the creation of social capital. Sociol. Educ. 90(1), 47–63 (2017).Article 

Google Scholar 
Valente, T. W. Network interventions. Science 337(6090), 49–53 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Nunn, L. M. College belonging: How first-year and first-generation students navigate campus life (Rutgers University Press, 2021).Book 

Google Scholar 
Garlick, R. Academic peer effects with different group assignment policies: Residential tracking versus random assignment. Am. Econ. J. Appl. Econ. 10(3), 345–369 (2018).Article 

Google Scholar 
Carrell, S. E., Fullerton, R. L. & West, J. E. Does your cohort matter? Measuring peer effects in college achievement. J. Labor. Econ. 27(3), 439–464 (2009).Article 

Google Scholar 
Lomi, A., Snijders, T. A., Steglich, C. E. & Torló, V. J. Why are some more peer than others? Evidence from a longitudinal study of social networks and individual academic performance. Soc. Sci. Res. 40(6), 1506–1520 (2011).PubMed 
PubMed Central 
Article 

Google Scholar 
Poldin, O., Valeeva, D. & Yudkevich, M. Which peers matter: How social ties affect peer-group effects. Res. High Educ. 57(4), 448–468 (2016).Article 

Google Scholar 
Raabe, I. J., Boda, Z. & Stadtfeld, C. The social pipeline: How friend influence and peer exposure widen the STEM gender gap. Sociol. Educ. 92(2), 105–123 (2019).Article 

Google Scholar 
Burt, R. S. Structural holes and good ideas. AJS 110(2), 349–399 (2004).
Google Scholar 
Oakes, J. Keeping track: How schools structure inequality (Yale University Press, 2005).
Google Scholar 
Park JJ et al. (2021) Who are you studying with? The role of diverse friendships in STEM and corresponding inequality. Res. High Educ. https://doi.org/10.1007/s11162-021-09638-8.Marsden, P. V. & Campbell, K. E. Measuring tie strength. Soc. Forces 63(2), 482–501 (1984).Article 

Google Scholar 
Mattie, H., Engø-Monsen, K., Ling, R. & Onnela, J. P. Understanding tie strength in social networks using a local “bow tie” framework. Sci. Rep. 8(1), 1–9 (2018).CAS 
Article 

Google Scholar 
Sørensen, A. B. Organizational differentiation of students and educational opportunity. Sociol. Educ. 43(4), 355–376 (1970).Article 

Google Scholar  More

Massive drift of pumice along the northeastern coast of Okinawa IslandA large amount of pumice stones reached and was deposited along the northeastern coast of Okinawa Island, that were brought by strong seasonal northeasterly winds (Supplementary Video 1). The pumice was thought to be brought by the Kuroshio countercurrent from sites near the Ogasawara Archipelago 1300 km away. Because the Kuroshio countercurrent is composed of various medium-sized eddies in the ocean, the current does not always flow in one direction and as a continuous flow27,28. The pumice drift was more strongly controlled by the seasonal northwesterly winds to be transported to Okinawa across the Philippine Sea (Fig. 1a). The pumice raft reached the northern part of Okinawa approximately 2 months after the eruption (Figs. 2, 3 and 4). According to a very recent report, the pumice clasts were drifting ashore in Thailand (traveling 4000 km-long distance) across the South China Sea within half a year of this eruption29. Most pumice stones were gray, but some pumice was banded, and others were black reflecting some compositional variation25,29 (Fig. 2d,e). The Kuroshio Current is faster than the Kuroshio countercurrent27, so some pumice clasts have already reached the main island of Japan25. Tracking the dispersal of the pumice will allow a better forecasting model based on observed raft trajectories by considering exact wind effects in the Philippine Sea30.Figure 2An example of a natural beach on Okinawa Island where pumice has washed ashore. (a) Appearance of natural sandy beaches on the northern part of Okinawa Island (Ibu beach, Kunigami Village, 26°75′57.88″ N, 128°32′23.32″ E). Photo was taken on 24 October 2021. Pumice drifted onto the sandy beach and formed a striped pattern. The white-capped waves indicate on the place where the reef edge exist. The white arrow points to the mangrove river estuary corresponding to Fig. 9. (b) Estimation of the pumice sedimentation depth on the original sand beach surface. (c) The high tide zone of the natural sandy beach is covered with pumice pebbles and stones. Yellow arrows indicate black pumice stones. Scale bar: 10 cm. (d, e) Front and back of examples of relatively large pumice stones from the same beach. The left image is mostly light brown, whereas the right image is almost black. Scale bars: 5 cm.Full size imageFigure 3Short-term migration of pumice from beaches as revealed by stationary observations. These four photos were taken at two sites on northern Okinawa Island on two consecutive days, 23 and 24 October 2021. (a, b) A sandy beach along the Sate Coast (26°78′84.56″ N, 128°22′30.57″ E). It was windy on the first day, and pumice stones were washed up with the waves. Almost all the pumice stones were removed from the beach and transported offshore on the following day. The black arrow in photo (a) indicates Cape Hedo, the northernmost tip of Okinawa Island. (c, d) At this gravelly beach (26°80′83.25″ N, 128°23′38.56″ E), pumice fully covers the seawall on the first day, but all of the pumice stones washed away, leaving the original gravels, on the following day. The white arrow in each photo indicates an identical marker stone placed on the beach. Weather data of northern Okinawa (https://www.data.jma.go.jp/obd/stats/etrn/view/daily_a1.php?prec_no=91&block_no=0901&year=2021&month=10&day=23&view=g_wsp) and tidal data (Naha: 26°13′ N, 127°40′ E) (https://www.data.jma.go.jp/gmd/kaiyou/db/tide/genbo/genbo.php) are provided by Japan Meteorological Agency.Full size imageFigure 4Pumice stones settled by marine organisms. (a) Pumice collected from Ibu beach on 31 October 2021. Two marine benthos coexist close together on a pumice stone. Scale bar: 1 cm. (b) Enlarged image of the Lepas barnacle. Scale bar: 3 mm. (c) Enlarged image of the bryozoan. Scale bar: 3 mm. (d) Stereo microscopic image of pumice pebbles of a few millimeters in diameter collected from Ibu beach on 15 January 2022. The light brown coloration indicates some algal/cyanobacterial growth on the pumice. Scale bar 1 mm. (e) Red autofluorescence was detected from pumice pebbles. Image corresponds to (d). Autofluorescence from microalgae was confirmed by Supplementary Fig. 2. Scale bar 1 mm. (f) Enlarged image of the center of the figure of (e) shows red autofluorescent signals with a diameter of 10–30 µm. Scale bar: 200 µm.Full size imageChanges in the coastal landscape: natural beaches and estuariesMarine calcifiers, including corals, calcareous algae, and foraminifers, produce white sandy beaches on Okinawa Island. However, the gray pumice drifting ashore changed the white sand beach, especially along the northeastern coastline. We observed several lines of pumice aggregations, suggesting that pumice was brought ashore by wavefronts several times produced by a strong north wind at the tide lines (Supplementary Video 1; Fig. 2a). At the same sampling site, the thickest depth of beached pumice was more than 30 cm (Fig. 2b; Supplementary Video 2). Most of the pumice stones were from 0.5 cm to 3 cm in diameter, with a few black pumice stones included (Fig. 2c: yellow arrow). Pumice stones arrived at the estuaries of some brackish rivers (Fig. 8, Supplementary Fig. 1a) and mangrove forests in northwest Okinawa (Fig. 9).Pumice stones and pumice rafts show dynamic behavior in a short period. We captured photographs 24 h apart at two positions on the shore of Okinawa, which allowed us to compare the pumice dynamics during this period (Fig. 3). Within that time frame, there were two high tides, and the tide level changed by up to 170 cm. As seen in Fig. 3a, on the first day, the coast was covered with pumice, and floating pumice could be seen on the seafront. The north wind was strong that day, as shown by the relatively high waves near the shore as well as white‐crested waves near the reef edge. By the following day, most of the pumice had been moved offshore by tides and winds (Fig. 3b), indicating that newly beached pumice raft deposits were removed quickly from open beach areas. At another site on a gravelly beach, pumice fully covered the seawall on the first day, but almost all of the pumice stones were washed away, leaving the original gravels, on the following day (Fig. 3c,d). Japan Meteorological Agency (Oku station: 232 m above sea level, latitude 26°50.1, longitude 128°16.3′) reported that northerly winds were blowing (mean wind speed: 3.4 m/s) on 23rd October in northern Okinawa. The following day, the wind direction changed to the east-southeast; blowing offshore (mean wind speed: 2.9 m/s), resulting in the dramatic removal of pumice form the coast (Fig. 3). These observations indicate that surface winds rather than ocean currents had a strong influence on the raft trajectory and residence time on beaches, and are consistent with past research5. These observations lead us to expect that the pumice rafts will disappear from the coast of Okinawa fairly quickly, but in fact, there have been many cases where they have come back again in a few days. Although the overall amount of pumice drifting has been decreasing, a small amount of pumice has been drifting in coastal area of Okinawa in May, 202231. It is unlikely that large amounts of pumice will drift repeatedly throughout Okinawa Prefecture as reported in this report, but it should be noted that detached pumice material remains in beach and river runoff.Biofouling of sessile organisms on pumice arriving to OkinawaIt is noteworthy that the pumice rafts traveled over the deep Philippine Sea for over 2 months, and on arrival in Okinawa there was little to no biofouling of the pumice (Fig. 2). Some stranded pumices observed on Okinawa beaches had become habitats for sessile organisms (Fig. 4), as reported in previous studies1,2,3,4,5,6,29. Goose barnacles (Lepas sp.) without external damage to the shell were the most abundant species observed on the pumice (Fig. 4b). Lepas is a common biofouling taxon distributed globally and plays a role in biofouling as a foundation organism. The shell growth rate is more than 1 mm/day in some Lepas species32 suggesting that the Lepas had been growing on the pumice for about two weeks. Measurements of the shell size of Lepas attached to the pumice collections conducted in the same area (Supplementary Video 2) showed a bias toward larger sizes in the second collection (5.92 ± 3.86 mm (average ± S.D.), n = 75, 13 November 2021) than in the first one (3.43 ± 1.08 mm, n = 21, 31 October 2021), and significant differences were detected between the measurement periods (Mann–Whitney U test, p  More

Harun, N., Chaudhry, A. S., Shaheen, S., Ullah, K. & Khan, F. Ethnobotanical studies of fodder grass resources for ruminant animals, based on the traditional knowledge of indigenous communities in Central Punjab Pakistan. J. Ethnobiol. Ethnomed. 13(1), 56. https://doi.org/10.1186/s13002-017-0184-5 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Shaheen, H., Qureshi, R., Qaseem, M. F. & Bruschi, P. The fodder grass resources for ruminants: A indigenous treasure of local communities of Thal desert Punjab, Pakistan. PLoS One 15(3), e0224061. https://doi.org/10.1371/journal.pone.0224061 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Huston, J. E. Forage utilization and nutrient requirements of the goat1. J. Dairy Sci. 61(7), 988–993. https://doi.org/10.3168/jds.S0022-0302(78)83679-0 (1978).Article 

Google Scholar 
Wilson, A. D., Leigh, J. H., Hindley, N. L. & Mulham, W. E. Comparison of the diets of goats and sheep on a Casuarina cristata–Heterodendrum oleifolium woodland community in western New South Wales. Aust. J. Exp. Agric. 15(72), 45–53. https://doi.org/10.1071/EA9750045 (1975).CAS 
Article 

Google Scholar 
Grünwaldt, E. G., Pedrani, A. R. & Vich, A. I. Goat grazing in the arid piedmont of Argentina. Small Ruminants Res. 13(3), 211–216. https://doi.org/10.1016/0921-4488(94)90066-3 (1994).Article 

Google Scholar 
Aganga, A. A., Omphile, U. J., Thema, T. & Baitshotlhi, J. C. Chemical composition of napier grass (Pennisetum purpureum) at different stages of growth and napier grass silages with additives. J. Biosci. 5(4), 493–496. https://doi.org/10.3923/jbs.2005.493.496 (2005).Article 

Google Scholar 
Ganskopp, D. & Bohnert, D. Nutritional dynamics of 7 Northern Great Basin grasses. J. Range Manage. 54, 640–647. https://doi.org/10.2307/4003664 (2001).Article 

Google Scholar 
Capstaff, N. M. & Miller, A. J. Improving the yield and nutritional quality of forage crops. Front. Plant Sci. 9, 535. https://doi.org/10.3389/fpls.2018.00535 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Arzani, H., Basiri, M., Khatibi, F. & Ghorbani, G. Nutritive value of some Zagros Mountain rangeland species. Small Ruminants Res. 65(1–2), 128–135. https://doi.org/10.1016/j.smallrumres.2005.05.033 (2006).Article 

Google Scholar 
Keba, H. T., Madakadze, I. C., Angassa, A. & Hassen, A. Nutritive value of grasses in semi-arid rangelands of Ethiopia, Local experience based herbage preference evaluation versus laboratory analysis. Asian-Aust. J. Anim. Sci. 26(3), 366. https://doi.org/10.5713/ajas.2012.12551 (2013).Article 

Google Scholar 
Dhungana, S., Tripathee, H. P., Puri, L., Timilsina, Y. P. & Devkota, K. P. Nutritional analysis of locally preferred fodder trees of Middle Hills of Nepal, a case study from Hemja VDC, Kaski District, Nepal. J. Sci. Technol. 13(2), 39–44. https://doi.org/10.3126/njst.v13i2.7712 (2012).Article 

Google Scholar 
Talore, D. G. Evaluation of major feed resources in crop-livestock mixed farming systems, southern Ethiopia, Indigenous knowledge versus laboratory analysis results. J. Agric. Rural Dev. 116(2), 157–166 (2015). http://nbn-resolving.de/urn:nbn:de:hebis:34-2015061048507.Geng, Y. et al. Nutrient value of wild fodder species and the implications for improving the diet of mithun (Bos frontalis) in Dulongjiang area, Yunnan Province, China. Plant Diversity 42(6), 455–463. https://doi.org/10.1016/j.pld.2020.09.007 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Sayed, M. A. I., Kulkarni, S., Kulkarni, D., Pande, A. & Kauthale, V. Nutritional study of local fodder species in Ahmednagar district of western Maharashtra. Agric. Sci. Digest A Res. J. 37(2), 154–156. https://doi.org/10.18805/asd.v37i2.7979 (2017).Article 

Google Scholar 
Evitayani, L. W., Fariani, A., Ichinohe, T. & Fujihara, T. Study on nutritive value of tropical forages in North Sumatra, Indonesia. Asian-Aust. J. Anim. Sci. 17(11), 1518–1523. https://doi.org/10.5713/ajas.2004.1518 (2004).Article 

Google Scholar 
Kanak, A. R., Khan, M. J., Debi, M. R., Pikar, M. K. & Aktar, M. Nutritive value of three fodder species at different stages of maturity, Bangladesh. J. Anim. Sci. 41(2), 90–95. https://doi.org/10.3329/bjas.v41i2.14123 (2012).Article 

Google Scholar 
Rahim, I., Maselli, D., Rueff, H. & Wiesmann, U. Indigenous fodder trees can increase grazing accessibility for landless and mobile pastoralists in northern Pakistan. Pastoral. Res. Policy Pract. 1(2), 1–2. https://doi.org/10.1186/2041-7136-1-2 (2011).Article 

Google Scholar 
Sultan, J., Inam-ur-rahim, I., Nawaz, H., Yaqoob, M. & Javed, I. Mineral composition, palatability and digestibility of free rangeland grasses of northern grasslands of Pakistan. Pak. J. Bot. 40(5), 2059–2070 (2008).CAS 

Google Scholar 
Bano, G., Islam, M., Ahmad, S., Aslam, S. & Koukab, S. Seasonal variation in nutritive value of Chrysopogon aucheri (boiss) stapf., and Cymbopogon jwarancusa (jones) schult., in highland Balochistan, Pakistan. Pak. J. Bot. 41(2), 511–517 (2009).CAS 

Google Scholar 
Rafay, M., Khan, R. A., Yaqoob, S. & Ahmad, M. Nutritional evaluation of major range grasses from Cholistan Desert. Pak. J. Nutr. 12(1), 23–29. https://doi.org/10.3923/pjn.2013.23.29 (2013).CAS 
Article 

Google Scholar 
Sultan, J. I., Manzoor, M. N., Shahzad, M. A. & Nisa M. Nutritional profile and in situ digestion kinetics of some irrigated grasses at pre-bloom stage. In International Conference on Biology, Environment and Chemistry 455–463 (2011). https://doi.org/10.3923/pjn.2013.23.29.Ahmed, K. et al. Proximate analysis, Relative feed values of various forage plants for ruminants investigated in a semi-arid region of Punjab, Pakistan. J. Agric. Sci. 27(6), 302. https://doi.org/10.4236/as.2013.46043 (2013).Article 

Google Scholar 
Manzoor, M. N., Sultan, J. I., Nisa, M. U. & Bilal, M. Q. Nutritive evaluation and in-situ digestibility of irrigated grasses. J. Anim. Plant Sci. 23, 1223–1227 (2013).CAS 

Google Scholar 
Sultan, J. I., Rahim, I. U., Nawaz, H. & Yaqoob, M. Nutritive value of marginal land grasses of northern grasslands of Pakistan. Pak. J. Bot. 39(4), 1071–1082 (2007).
Google Scholar 
Khan, R. I., Alam, M. R. & Amin, M. R. Effect of season and fertilizer on species composition and nutritive value of native grasses. Asian-Aust. J. Anim. Sci. 12(8), 1222–1227. https://doi.org/10.5713/ajas.1999.1222 (1999).Article 

Google Scholar 
Grant, K., Kreyling, J., Dienstbach, L. F. H., Beierkuhnlein, C. & Jentsch, A. Water stress due to increased intra-annual precipitation variability reduced forage yield but raised forage quality of a temperate grassland. Agric. Ecosyst. Environ. 186, 11–22. https://doi.org/10.1016/j.agee.2014.01.013 (2014).Article 

Google Scholar 
Ray, D. K., Gerber, J. S., MacDonald, G. K. & West, P. C. Climate variation explains a third of global crop yield variability. Nat. Commun. 6(1), 1–9. https://doi.org/10.1038/ncomms6989 (2015).CAS 
Article 

Google Scholar 
Egeru, A. et al. Land cover and soil properties influence on forage quantity in a semiarid region in East Africa. Appl. Environ. Soil Sci. https://doi.org/10.1155/2019/6874268 (2019).Article 

Google Scholar 
Mertens, D. R. Interpretation of forage analysis reports. In 30th National Alfalfa symposium. Las vegas, NV. (2000).Hussain, F. & Durrani, M. J. Nutritional evaluation of some forage plants from Harboi Rangeland, Kalat, Pakistan. Pak. J. Bot. 41(3), 1137–1154 (2009).CAS 

Google Scholar 
Ammar, H., López, S., Bochi-Brum, O., García, R. & Ranilla, M. J. Composition and in vitro digestibility of leaves and stems of grasses and legumes harvested from permanent mountain meadows at different stages of maturity. J. Anim. Feed Sci. 8(4), 599–610. https://doi.org/10.22358/jafs/69184/1999 (1999).Article 

Google Scholar 
Faichney, G. J., Gordon, G. L. R., Welch, R. J. & Rintoul, A. J. Effect of dietary free lipid on anaerobic fungi and digestion in the rumen of sheep. Aust. J. Agric. Res. 53(5), 519–527. https://doi.org/10.1071/AR01143 (2002).CAS 
Article 

Google Scholar 
Khan, S., Anwar, K., Kalim, K., Saeed, A. & Shah, S. Z. Nutritional evaluation of some top fodder tree leaves and shrubs of District Dir (Lower), Pakistan as a quality livestock feed. Int. J. Curr. Microbiol. Appl. Sci. 3(5), 941–947 (2014).
Google Scholar 
Tudsri, S. & Kaewkunya, C. Effect of leucaena row spacing and cutting intensity on the growth of leucaena and three associated grasses in Thailand. Asian Aust. J. Anim. Sci. 15(7), 986–991 (2002).
Google Scholar 
Nasrullah, M., Niimi, R., Akashi, X. & Kawamura, O. Nutritive evaluation of forage plants grown in South Sulawesi, Indonesia. Asian Aust. J. Anim. Sci. 16(5), 693–701. https://doi.org/10.5713/ajas.2004.63 (2003).CAS 
Article 

Google Scholar 
Yahaya, M. S., Kawai, M., Takahashi, J. & Matsuoka, S. The effects of different moisture content and ensiling time on silo degradation of structural carbohydrate of orchard grass. Asian Aust. J. Anim. Sci. 15(2), 213–217. https://doi.org/10.5713/ajas.2002.213 (2002).Article 

Google Scholar 
Norton, B. W. Differences between species in forage quality. In Nutritional Limits to Animal Production from Pastures, proceedings of an international symposium held at St. Lucia, Queensland, Australia, UK. Commonwealth Agricultural Bureaux, (1982).National Research council. Nutrient Requirements of Dairy Cattle 7th edn. (National Academy Press, 2001).
Google Scholar 
Nogueira Filho, J. C. M., Fondevila, M., Urdaneta, A. B. & Ronquillo, M. G. In vitro microbial fermentation of tropical grasses at an advanced maturity stage. Anim. Feed Sci. Technol. 83(2), 145–157. https://doi.org/10.1016/S0377-8401(99)00123-6 (2000).CAS 
Article 

Google Scholar 
National Research Council. Nutrient Requirements of Sheep, Vol ***5 (National Academies Press, 1985).
Google Scholar 
Erickson, P. S. & Kalscheur, K. F. Nutrition and feeding of dairy cattle. In Animal Agriculture pp 157–180 (2020).Holechek, J. L., Pieper, R. D. & Herbel, C. H. Range Management Principles and Practices 5th edn. (Prentice-Hall, 2004).
Google Scholar 
Saro, C. et al. Effect of dietary crude protein on animal performance, blood biochemistry profile, ruminal fermentation parameters and carcass and meat quality of heavy fattening Assaf lambs. Animals 10(11), 2177 (2020).PubMed Central 

Google Scholar 
Buckmaster, D. R. Forage Looses, Equal Economic Looses Agricultural Engineer Fact Shell PM-107 (The Pennsylvania State University, 1990).
Google Scholar 
Paulson, J., Jung, H., Raeth-Knight, M. & Linn, J. Grass vs. legume forages for dairy cattle (2008). https://conservancy.umn.edu/bitstream/handle/11299/204154/SF95_M658a-69-2008_magr56173.pdf?sequence=1.Lüscher, A., Mueller-Harvey, I., Soussana, J. F., Rees, R. M. & Peyraud, J. L. Potential of legume-based grassland–livestock systems in Europe: A review. Grass Forage Sci. 69(2), 206–228. https://doi.org/10.1111/gfs.12124 (2014).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Van Soest, P. J. Nutritional Ecology of the Ruminant 2nd edn. (Cornell University Press, 1994).
Google Scholar 
Tucak, M., Ravlic, M., Horvat, D. & Cupic, T. Improvement of forage nutritive quality of alfalfa and red clover through plant breeding. Agronomy 11(11), 2176. https://doi.org/10.3390/agronomy11112176 (2021).CAS 
Article 

Google Scholar 
Harper, K. & McNeill, D. The role iNDF in the regulation of feed intake and the importance of its assessment in subtropical ruminant systems (the role of iNDF in the regulation of forage intake). Agriculture 5(3), 778–790. https://doi.org/10.3390/agriculture5030778 (2015).CAS 
Article 

Google Scholar 
Singh, G. P. & Oosting, S. J. A model for describing the energy value of straws. Indian Dairyman XLI 322–327 (1992). https://agris.fao.org/agris-search/search.do?recordID=NL2012083374.Reed, J. A. & Goe, M. R. Estimating the Nutritive Value of Cereal Crop Residues, Implications for developing feeding standards for draught animals. ILCA Bulletin (1989). https://hdl.handle.net/10568/4610.Kumar, K. & Soni, A. Nutrient evaluation of common vegetation of Rajasthan, Pennisetum typholdenum, Cenchrus ciliaris, Cenchrus setigerus and Lasiurus sindicus. Int. J. Plant Anim. Environ. Sci. 4(1), 177–183 (2014).CAS 

Google Scholar 
Kramberger, B. & Klemenčič, S. Effect of harvest date on the chemical composition and nutritive value of Cerastium holosteoides. Grass Forage Sci. 58(1), 12–16. https://doi.org/10.1046/j.1365-2494.2003.00346.x (2003).CAS 
Article 

Google Scholar 
Raffrenato, E. et al. Effect of lignin linkages with other plant cell wall components on in vitro and in vivo neutral detergent fiber digestibility and rate of digestion of grass forages. J. Dairy Sci. 100(10), 8119–8131. https://doi.org/10.3168/jds.2016-12364 (2017).CAS 
Article 
PubMed 

Google Scholar 
McDonald, P. et al. Animal nutrition. Pearson UK https://doi.org/10.1088/1755-1315/951/1/012013 (2022).Article 

Google Scholar 
Brown, P. H., Graham, R. D. & Nicholas, D. G. D. The effect of manganese and nitrate supply on the level of phenolics and lignin in young wheat plant. Plant Soil 81, 437–440 (1984).CAS 

Google Scholar 
Mbwile, R. P. & Uden, P. Effects of age and season on growth and nutritive value of Rhodes grass (Chloris gayana cv. Kunthi). Anim. Feed Sci. Technol. 65, 87–98 (1997).
Google Scholar 
Hameed, M., Naz, N., Ahmad, M. S. A. & Islam-ud-Din, R. A. Morphological adaptations of some grasses from the salt range, Pakistan. Pak. J. Bot. 40(4), 1571–1578 (2008).
Google Scholar 
Makkar, H. P. S. Effects and fate of tannins in ruminant animals, adaptation to tannins, and strategies to overcome detrimental effects of feeding tannin-rich feeds. Small Rumin. Res. 49(3), 241–256. https://doi.org/10.1016/S0921-4488(03)00142-1 (2003).ADS 
Article 

Google Scholar 
Patra, A. K. Nutritional management in organic livestock farming for improved ruminant health and production—an overview. Livestock Res. Rural Dev. 19(3), 41 (2007).
Google Scholar 
Akande, K. E., Doma, U. D., Agu, H. O. & Adamu, H. M. Major antinutrients found in plant protein sources: Their effect on nutrition. Pak. J. Nutr. 9(8), 827–832 (2010).CAS 

Google Scholar 
Tadele, Y. Important anti-nutritional substances and inherent toxicants of feeds. Food Sci. Qual. Manage. 36, 40–47 (2015).
Google Scholar 
D’Mello, J.F. Farm animal metabolism and nutrition. Cabi Publishing. UK. (2000). https://www.researchgate.net/profile/Adegbola-Adesogan/publication/242151831_What_are_feeds_worth_A_critical_evaluation_of_selected_nutritive_value_methods/links/5852780c08aef7d030a4e95b/What-are-feeds-worth-A-critical-evaluation-of-selected-nutritive-value-methods.pdf.Panhwar, F. Anti-nutritional Factors in Oil Seeds as Aflatoxin in Ground Nut (Digitalverlag GmbH, 2005).
Google Scholar 
Huang, J. et al. Tree defence and bark beetles in a drying world: Carbon partitioning, functioning and modelling. New Phytol. 225(1), 26–36. https://doi.org/10.1111/nph.16173 (2020).Article 
PubMed 

Google Scholar 
Min, B. R., Barry, T. N., Attwood, G. T. & McNabb, W. C. The effect of condensed tannins on the nutrition and health of ruminants fed fresh temperate forages, a review. Anim. Feed Sci. Technol. 106(1–4), 3–19 (2003).CAS 

Google Scholar 
Muetzel, S., Hoffmann, E. M. & Becker, K. Supplementation of barley straw with Sesbania pachycarpa leaves in vitro: Effects on fermentation variables and rumen microbial population structure quantified by ribosomal RNA targeted probes. Br. J. Nutr. 89(4), 445–453 (2003).CAS 
PubMed 

Google Scholar 
Yao, L. H. et al. Flavonoids in food and their health benefits. Plant Foods Hum. Nutr. 59(3), 113–122 (2004).CAS 
PubMed 

Google Scholar 
Tracy, B. F. et al. Resilience in forage and grazinglands. Crop Sci. 58(1), 31–42 (2018).
Google Scholar 
Ehsen, S. et al. Secondary metabolites as anti-nutritional factors in locally used halophytic forage/fodder. Pak. J. Bot. 48(2), 629–636 (2016).CAS 

Google Scholar 
Mudzwiri, M. Evaluation of traditional South African leafy plants for their safety in human consumption. Doctoral Dissertation (2007).Francis, G., Kerem, Z., Makkar, H. P. & Becker, K. The biological action of saponins in animal systems, A review. Brit. J. Nutr. 88(6), 587–605 (2002).CAS 
PubMed 

Google Scholar 
Duke, J. Phytochemical and ethnobotanical databases (2000).Terrill, T. H., Rowan, A. M., Douglas, G. B. & Barry, T. N. Determination of extractable and bound condensed tannin concentrations in forage plants, protein concentrate meals and cereal grains. J. Sci. Food Agric. 58(3), 321–329. https://doi.org/10.1002/jsfa.2740580306 (1992).CAS 
Article 

Google Scholar 
Barry, T. N. & McNabb, W. C. The implications of condensed tannins on the nutritive value of temperate forages fed to ruminants. Br. J. Nutr. 81(4), 263–272 (1999).CAS 
PubMed 

Google Scholar 
Kallah, S. K., Bale, J. D., Abdullahi, U. S., Mohammed, I. R. & Lawai, R. Nutrient composition of native forms of semi-arid and dry-humid savannahs of Nigeria. Anim. Feed Sci. Technol. 84, 137–145 (2000).CAS 

Google Scholar 
Megersa, E., Mengistu, A. & Asebe, G. Nutritional characterization of selected fodder species in Abol and Lare Districts of Gambella Region, Ethiopia. J. Nutr. Food Sci. 7(2), 2–6 (2017).
Google Scholar 
Van Soest, P. J. & Robertson, J. B. Analysis of Forages and Fibrous Foods (Cornell University, 1985).
Google Scholar 
Moore, K. J. & Jung, H. G. Lignin and fiber digestion. J. Range Manag. 54(4), 420–430 (2001).
Google Scholar 
Ramirez, R. G., Haenlein, G. F. W., Garcia-Castillo, C. G. & Nunez-Gonzalez, M. A. Protein, lignin and mineral contents and In-Situ dry matter digestibility of native Mexican grasses consumed by range goats. Small Ruminant Resour. 52(3), 261–269 (2004).
Google Scholar 
Ronquillo, M. G., Fondevila, M., Urdaneta, A. B. & Newman, Y. In vitro gas production from buffel grass Cenchrus ciliaris L. fermentation in relation to the cutting interval, the level of nitrogen fertilisation and the season of growth. Anim. Feed Sci. Technol. 72(1–2), 19–32 (1998).
Google Scholar 
Mlay, P. S. et al. Feed value of selected tropical grasses, legumes and concentrates. Vet. Arch. 76(1), 53–63 (2006).
Google Scholar 
Arif, M. et al. In vitro digestibility of selected forages in Sargodha district, Pakistan. In Vitro 6(3), 62–72 (2016).CAS 

Google Scholar 
Revell, D. K., Baker, S. K. & Purser, B. B. Estimates of the intake and digestion of nitrogen by sheep grazing a Mediterranean pasture as it matures senesces. Aust. Soc. Anim. Prod. 20, 217–220 (1994).
Google Scholar 
Cherney, D. J. R., Mertens, D. R. & Moore, J. E. Intake and digestibility by withers as influenced by forage morphology at three levels of forage offering. J. Anim. Sci. 68(12), 4387–4399. https://doi.org/10.2527/1990.68124387x (1990).CAS 
Article 
PubMed 

Google Scholar 
Lichtenberg, V. L. & Hemken, R. W. Hay quality. In: Grazing Management: An Ecological Perspective. Timber Press, Portland, Oregon USA (1985). https://www.pakbs.org/pjbot/PDFs/40(1)/PJB40(1)249.pdf.de Oliveira, C. V. et al. Urea supplementation in rumen and post-rumen for cattle fed a low-quality tropical forage. Brit. J. Nutr. 124(11), 1166–1178. https://doi.org/10.1017/S0007114520002251 (2020).CAS 
Article 
PubMed 

Google Scholar 
Rufino, L. M. et al. Effects of the amount and frequency of nitrogen supplementation on intake, digestion, and metabolism in cattle fed low-quality tropical grass. Anim. Feed Sci. Technol. 260, 114367 (2020).CAS 

Google Scholar 
Njidda, A. A. Determining dry matter degradability of some semi-arid browse species of north-eastern Nigeria using the in vitro technique. Nigerian J. Basic Appl. Sci. 18(2), 160–167. https://doi.org/10.4314/njbas.v18i2.64306 (2014).Article 

Google Scholar 
Rakib-Uz-Zaman, S. M. et al. Ethnobotanical study and phytochemical profiling of Heptapleurum hypoleucum leaf extract and evaluation of its antimicrobial activities against diarrhea-causing bacteria. J. Genet. Engl. Biotechnol. https://doi.org/10.1186/s43141-020-00030-0 (2020).Article 

Google Scholar 
Rodrigues, E. & de Oliveira, D. R. Ethnopharmacology: A laboratory science?. Rodriguésia 71, 25 (2020).
Google Scholar 
Kellogg, E. A. Poaceae. In The Families and Genera of Vascular Plants (ed. Kubtizki, K.) (Springer, 2014).
Google Scholar 
Horwitz W. & Latimer G. W. Official methods of analysis of AOAC International. 18th Ed. Gaithersburg, Md. AOAC International (2005). https://doi.org/10.1071/EA9750045.Makkar, H. P., Siddhuraju, P. & Becker, K. Plant Secondary Metabolites (Humana Press, 2007).
Google Scholar 
Tilley, J. M. & Terry, R. A. A two stage technique for the in vitro digestion of forage crops. Grass Forage Sci. 18(2), 104–111. https://doi.org/10.1111/j.1365-2494.1963.tb00335.x (1963).CAS 
Article 

Google Scholar  More

Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).ADS 
Article 

Google Scholar 
Céréghino, R. et al. Constraints on the functional trait space of aquatic invertebrates in bromeliads. Funct. Ecol. 32, 2435–2447 (2018).Article 

Google Scholar 
Winemiller, K. O., Fitzgerald, D. B., Bowler, L. & Pianka, E. R. Functional traits, convergent evolution, and periodic tables of niches. Ecol. Lett. 18, 737–751 (2015).Article 

Google Scholar 
Díaz, S. et al. Functional traits, the phylogeny of function, and ecosystem service vulnerability. Ecol. Evol. 3, 2958–2975 (2013).Article 

Google Scholar 
Leimar, O. Evolutionary change and Darwinian demons. Selection 2, 65–72 (2001).Article 

Google Scholar 
Cummins, K. W. & Klug, M. J. Feeding ecology of stream invertebrates. Annu. Rev. Ecol. Syst. 10, 147–172 (1979).Article 

Google Scholar 
Pianka, E. R., Vitt, L. J., Pelegrin, N., Fitzgerald, D. B. & Winemiller, K. O. Toward a periodic table of niches, or exploring the lizard niche hypervolume. Am. Nat. 190, 601–616 (2017).Article 

Google Scholar 
Rosenberg, D. M. & Resh, V. H. Freshwater Biomonitoring and Benthic Macroinvertebrates (Chapman and Hall, 1993).
Google Scholar 
Allan, J. D. & Castillo, M. M. Stream Ecology. Structure and Function of Running Waters 2nd edn. (Springer, 2007).
Google Scholar 
Wallace, J. B. & Webster, J. R. The role of macroinvertebrates in stream ecosystem function. Annu. Rev. Entomol. 41, 115–139 (1996).CAS 
Article 

Google Scholar 
Southwood, T. R. E. Habitat, the templet for ecological strategies?. J. Anim. Ecol. 46, 336–365 (1977).Article 

Google Scholar 
Townsend, C. R. & Hildrew, A. G. Species traits in relation to a habitat templet for river systems. Freshw. Biol. 31, 265–275 (1994).Article 

Google Scholar 
Violle, C. et al. Let the concept of trait be functional!. Oikos 116, 882–892 (2007).Article 

Google Scholar 
Schmera, D., Heino, J., Podani, J., Erős, T. & Dolédec, S. Functional diversity: A review of methodology and current knowledge in freshwater macroinvertebrate research. Hydrobiologia 787, 27–44 (2017).Article 

Google Scholar 
Diehl, S. Fish predation and benthic community structure: The role of omnivory and habitat complexity. Ecology 73, 1646–1661 (1992).Article 

Google Scholar 
Brucet, S. et al. Effects of temperature, salinity and fish in structuring the macroinvertebrate community in shallow lakes: Implications for the effects of climate change. PLoS ONE 7, e30877 (2012).ADS 
CAS 
Article 

Google Scholar 
Usseglio-Polatera, P., Bournaud, M., Richoux, P. & Tachet, H. Biological and ecological traits of benthic freshwater macroinvertebrates: Relationships and definition of groups with similar traits. Freshw. Biol. 43, 175–205 (2000).Article 

Google Scholar 
Poff, N. L. et al. Functional trait nichees of North American lotic insects: Trait-based ecological applications in light of phylogenetic relationships. J. North Am. Soc. 25, 730–755 (2006).Article 

Google Scholar 
Bonada, N., Dolédec, S. & Statzner, B. Taxonomic and biological trait differences of stream macroinvertebrate communities between Mediterranean and temperate regions: Implications for future climatic scenarios. Glob. Change Biol. 13, 1658–1671 (2007).ADS 
Article 

Google Scholar 
Stazner, B., Bonada, N. & Dolédec, S. Biological attributes discriminating invasive from native European stream macroinvertebrates. Biol. Invasions 10, 517–530 (2008).Article 

Google Scholar 
Schmidt-Kloiber, A. & Hering, D. www.freshwaterecology.info—An online tool that unifies, standardises and codifies more than 20,000 European freshwater organisms and their ecological preferences. Ecol. Indic. 53, 271–282 (2015).Article 

Google Scholar 
Verberk, W. C. E. P., Siepel, H. & Esselink, H. Life-history strategies in freshwater macroinvertebrates. Freshw. Biol. 53, 1722–1738 (2008).Article 

Google Scholar 
Dolédec, S., Statzner, B. & Frainay, V. Accurate description of functional community structure: Identifying stream invertebrates to species-level?. Bull. North Am. Benthol. Soc. 15, 154–155 (1998).
Google Scholar 
Podani, J., Kalapos, T., Barta, B. & Schmera, D. Principal component analysis of incomplete data—A simple solution to an old problem. Ecol. Inform. 61, 101235 (2021).Article 

Google Scholar 
Podani, J. Introduction to the Exploration of Multivariate Biological Data (Backhuys Publishers, 2000).MATH 

Google Scholar 
Tachet, H., Richoux, P., Bournaud, M. & Usseglio-Polatera, P. Invertébrés d’eau douce—systématique, biologie, écologie 600 (CNRS Editions, 2010).
Google Scholar 
Chevenet, F., Dolédec, S. & Chessel, D. A fuzzy coding approach for the analysis of long-term ecological data. Freshw. Biol. 31, 295–309 (1994).Article 

Google Scholar 
Schmidt-Kloiber A. & Hering, D. www.freshwaterecology.info—The Taxa and Autecology Database for Freshwater Organisms, Version 7.0. (Accessed on 12.09.2019) (2019).Schmera, D., Podani, J., Heino, J., Erős, T. & Poff, N. L. A proposed unified terminology of species traits in stream ecology. Freshw. Sci. 34, 823–830 (2015).Article 

Google Scholar 
Schmera, D., Podani, J., Erős, T. & Heino, J. Combining taxon-by-trait and taxon-by-site matrices for analysing trait patterns of macroinvertebrate communities: A rejoinder to Monaghan & Soares (2014). Freshw. Biol. 59, 1551–1557 (2014).Article 

Google Scholar 
Bonada, N. et al. Do Mediterranean genera not included in Tachet et al. 2002 have Mediterranean characteristics?. Limnetica 30, 129–142 (2011).Article 

Google Scholar 
de Jong, Y. et al. Fauna Europaea—All European animal species on the web. Biodivers. Data J. 2, e4034 (2014).Article 

Google Scholar 
de Bello, F., Botta-Dukát, Z., Leps, J. & Fibich, P. Towards a more balanced combination of multiple traits when computing functional differences between species. Methods Ecol. Evol. 12, 443–448 (2021).Article 

Google Scholar 
Legendre, P. & Legendre, L. Numerical Ecology 2 English. (Elsevier, 1998).MATH 

Google Scholar 
Cornwell, W. K., Schwilk, D. W. & Ackerly, D. A trait-based test for habitat filtering: Convex hull volume. Ecology 87, 1465–1471 (2006).Article 

Google Scholar 
Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral. Ecol. 26, 32–46 (2001).
Google Scholar 
Anderson, M. J. Distance-based tests for homogeneity of multivariate dispersions. Biometrics 62, 245–253 (2006).MathSciNet 
Article 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).
Google Scholar 
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).
Google Scholar 
Habel, K., Grasman, R., Gramacy, R. G., Mozharovskyi, P. & Sterratt, D. C. Geometry: Mesh Generation and Surface Tessellation. R package version 0.4.5. https://CRAN.R-project.org/package=geometry (2019).Oksanen, J., Blanchet, F. G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P. R., O’Hara, R. G., Simpson, G. L., Solymos, P., Stevens, M. H. H., Szoecs, E. & Wagner, H. vegan: Community Ecology Package. R package version 2.5-6. https://CRAN.R-project.org/package=vegan (2019). More

After the successful protection of Himalayan areas on the border of China and Nepal, we propose that the two nations should create the world’s highest international peace park by combining the Qomolangma and Sagarmatha national parks. This would align with United Nations Sustainable Development Goal 17, to achieve sustainable development through international cooperation (see go.nature.com/3ixmini).
Competing Interests
The authors declare no competing interests. More

Climate change drove evolution, biogeography, and demographyPhylogenetic results (Fig. 1 and Supplementary Fig. 2) confirm previous findings, recovering Aptenodytes (king and emperor penguins) as the sister clade to all other crown penguins, with brush-tailed (Pygoscelis) penguins in turn sister to two clades uniting the banded (Spheniscus) and little (Eudyptula) penguins and the yellow-eyed (Megadyptes) and crested (Eudyptes) penguins6,7,9. Biogeographical reconstructions (Fig. 1, Supplementary Figs. 3–4 and Supplementary Data 1) support a Zealandian origin for penguins6,7. Stem penguins radiated extensively in Zealandia before dispersing to South America and Antarctica multiple times, following the eastward-flowing direction of the Antarctic Circumpolar Current (ACC) (Fig. 1). Crown penguins most likely arose from descendant lineages in South America, before dispersing back to Zealandia at least three times. Interestingly, at least two such dispersals occurred before the inferred onset of the ACC system, suggesting that early stem penguins were not dependent on currents to disperse over long distances. A second pulse of speciation coincides with the onset of the ACC, though understanding whether this pattern is real or an artifact of fossil sampling requires more collecting from early Eocene localities. We infer an age of ~14 Ma for the origin of crown penguins, which is more recent than the ~24 Ma age recovered in genomic analyses, not including fossil taxa7 (Supplementary Fig. 2b) and coincides with the onset of global cooling during the middle Miocene climate transition4,10 (Supplementary Fig. 3a). This young age suggests that expansion of Antarctic ice sheets and the onset of dispersal vectors such as the Benguela Current11 during the middle to late Miocene facilitated crown penguin dispersal and speciation, as hinted at by fossil evidence12.Incongruences between species trees and gene trees were identified, e.g., alternate topologies occurred at high frequencies ( >10%) for several internal branches (Fig. 1c; Supplementary Fig. 5). These patterns indicate that gene tree discordance may be caused by incomplete lineage sorting (ILS) or introgression events. By quantifying ILS and introgression via branch lengths from over 10,000 gene trees, we found that the rapid speciation within crown penguins was accompanied by >5% ILS content within the ancestors of Spheniscus, Eudyptula, Eudyptes, and several subgroups within Eudyptes (Fig. 2a). Our dated tree provides a temporal framework for this rapid radiation: the four extant Spheniscus taxa are all inferred to have split from one another within the last ~3 Ma, and likewise the nine extant Eudyptes taxa likely split from one another in that same time (Fig. 1b). Many closely related penguin species/lineages are known to hybridize in the wild (see supplementary methods). Consistent with this, multiple analyses suggest that introgression also contributes to species tree—gene tree incongruence (Supplementary Figs. 6–9 and Supplementary Data 2; also see Supplementary Methods for further details). This could explain the most notable conflict in previous phylogenetic results, which showed inconsistency over whether Aptenodytes alone7 or Aptenodytes and Pygoscelis together4,5 represent the sister clade to all other extant penguins. Introgression was detected between the ancestor of Aptenodytes and the ancestor of other extant penguins, and is inferred to have occurred when the range of these ancestors overlapped in South America (Fig. 2a and Supplementary Data 2). Introgression ( >9%) was also detected between Eudyptula novaehollandiae and Eudyptula minor, and several introgression events were especially pervasive in Eudyptes (Fig. 2a and Supplementary Fig. 6).Fig. 2: Incomplete lineage sorting, introgression events, and demographic history among penguins.a Model of incomplete lineage sorting (ILS) and introgression events estimated from QuIBL and hybrid pairwise sequentially Markovian coalescent (hPSMC) results. hPSMC was only run for 20 species pairs (see b). Numbers on branches represent the proportion (%) of ILS (orange branches) or introgression (blue lines, blue dashed lines, and blue dotted lines) detected by QuIBL. Proportions 50 km; see Supplementary Data 117), while taxa that decreased towards the end of the LGP (e.g., S. humboldti, S. demersus, M. a. antipodes and likely M. a. richdalei) tend to be residential, and forage inshore; see Supplementary Data 1. Taxa that disperse farther may have overcome local impacts of global climate cooling during the LGP (e.g., changes in sea-ice extent, prey abundance and terrestrial glaciation, however see18) largely by relocating to lower latitudes (e.g.,14), whereas locally-restricted taxa may have been more prone to sudden population collapses.Penguins have the slowest evolutionary rates among birdsThe integrated evolutionary speed hypothesis (IESH) proposes that temperature, water availability, population size, and spatial heterogeneity influence evolutionary rate19. Life history traits also impact the evolutionary rate, but such relationships remain incompletely understood in birds20. Penguins are long-lived, large-bodied, and produce few offspring, thus providing an ideal case study in how life history may impact evolutionary rate. We tested the IESH using three proxies for evolutionary rate: substitution rate, P and K2P distances between lineages and their ancestors (Supplementary Fig. 12 and Supplementary Data 3). We found that penguins and their sister group (Procellariiformes) had the lowest evolutionary rates of the 17 avian orders sampled by21 (Fig. 3a, Supplementary Fig. 13, and Supplementary Data 3). Because other aquatic orders also show slow rates (e.g., the aquatic Anseriformes show a significantly slower rate than their terrestrial sister group Galliformes), we hypothesize that the rate in penguins represents the culmination of a gradual slowdown associated with increasingly aquatic ecology. Intriguingly, we detected a trend toward decreasing rate over the first ~10 Ma of crown penguin evolution, followed by a marked uptick ~2 Ma, which suggests the onset of glacial-interglacial cycles contributed to a recent increase in evolutionary rates in penguins (Fig. 3b).Fig. 3: Evolutionary rates in birds.a Evolutionary rate in avian orders based on a ~19 Mbp alignment of highly conserved genome regions. Sphenisciformes and Procellariiformes have the lowest evolutionary rate among modern bird orders (One-sided Wilcoxon Rank sum test, P values  0.1)). Numbers at the tips represent the sample size in each group. Numbers at nodes represent the divergence times (Ma) between each order and its sister taxon and red dots within the boxplots indicate average values. We did not attempt to estimate the evolutionary rates for orders containing less than three sampled species (gray font; Musophagiformes, Mesitornithiformes, and Struthioniformes). Boxplots show the median with hinges at the 25th and 75th percentile and whiskers extending 1.5 times the interquartile range. Some bird images were downloaded from phylopic.org and were licensed under the Creative Commons (CC0) 1.0 Universal Public Domain Dedication. b Evolutionary rates inferred for extant penguin lineages at internal nodes from the maximum clade credibility tree, calculated using a 500 Mbp genome alignment. Gray shadows represent the 95% credible intervals. c–e Correlations between c, body mass and generation time (P value  More

Fisher, M. C. et al. Emerging fungal threats to animal, plant and ecosystem health. Nature 484, 186–194 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Fisher, M. C., Gow, N. A. & Gurr, S. J. Tackling emerging fungal threats to animal health, food security and ecosystem resilience. Philos. Trans. R. Soc. B 371, 20160332. https://doi.org/10.1098/rstb.2016.0332 (2016).Article 

Google Scholar 
Lips, K. R. Overview of chytrid emergence and impacts on amphibians. Philos. Trans. R. Soc. B 371, 20150465. https://doi.org/10.1098/rstb.2015.0465 (2016).Article 

Google Scholar 
Lips, K. R., Diffendorfer, J., Mendelson, J. R. III. & Sears, M. W. Riding the wave: Reconciling the roles of disease and climate change in amphibian declines. PLoS Biol. 6, e72 (2008).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Caruso, N. M. & Lips, K. R. Truly enigmatic declines in terrestrial salamander populations in great smoky mountains national park. Divers. Distrib. 19, 38–48 (2013).Article 

Google Scholar 
Martel, A. et al. Recent introduction of a chytrid fungus endangers western palearctic salamanders. Science 346, 630–631 (2014).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
van der Spitzen Sluijs, A. et al. Rapid enigmatic decline drives the fire salamander (Salamandra salamandra) to the edge of extinction in the Netherlands. Amphib.-Reptil. 34, 233–239 (2013).Article 

Google Scholar 
Blehert, D. S. et al. Bat white-nose syndrome: An emerging fungal pathogen?. Science 323, 227–227 (2009).CAS 
PubMed 
Article 

Google Scholar 
Thogmartin, W. E., King, R. A., McKann, P. C., Szymanski, J. A. & Pruitt, L. Population-level impact of white-nose syndrome on the endangered Indiana bat. J. Mammal. 93, 1086–1098 (2012).Article 

Google Scholar 
Fisher, M. C., Garner, T. W. & Walker, S. F. Global emergence of Batrachochytrium dendrobatidis and amphibian chytridiomycosis in space, time, and host. Annu. Rev. Microbiol. 63, 291–310 (2009).CAS 
PubMed 
Article 

Google Scholar 
Martel, A. et al. Batrachochytrium salamandrivorans sp. Nov. causes lethal chytridiomycosis in amphibians. Proc. Natl. Acad. Sci. 110, 15325–15329 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Allender, M. C., Raudabaugh, D. B., Gleason, F. H. & Miller, A. N. The natural history, ecology, and epidemiology of Ophidiomyces ophiodiicola and its potential impact on free-ranging snake populations. Fungal Ecol. 17, 187–196. https://doi.org/10.1016/j.funeco.2015.05.003 (2015).Article 

Google Scholar 
Grioni, A. et al. Detection of Ophidiomyces ophidiicola in a wild Burmese python (Python bivittatus) in Hong Kong SAR, China. J. Herpetol. Med. Surg. 31, 283–291 (2021).Article 

Google Scholar 
Allender, M. C. et al. Chrysosporium sp. infection in eastern massasauga rattlesnakes. Emerg. Infect. Dis. 17, 2383–2384. https://doi.org/10.1136/vr.b4816 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Franklinos, L. H. V. et al. Emerging fungal pathogen Ophidiomyces ophiodiicola in wild European snakes. Sci. Rep. 7, 1–7. https://doi.org/10.1038/s41598-017-03352-1 (2017).CAS 
Article 

Google Scholar 
Lorch, J. M. et al. Experimental infection of snakes with Ophidiomyces ophiodiicola causes pathological changes that typify snake fungal disease. mBio 6, 1–9. https://doi.org/10.1128/mBio.01534-15 (2015).CAS 
Article 

Google Scholar 
Clark, R. W., Marchand, M. N., Clifford, B. J., Stechert, R. & Stephens, S. Decline of an isolated timber rattlesnake (Crotalus horridus) population: Interactions between climate change, disease, and loss of genetic diversity. Biol. Cons. 144, 886–891. https://doi.org/10.1016/j.biocon.2010.12.001 (2011).Article 

Google Scholar 
Chandler, H. C. et al. Ophidiomycosis prevalence in Georgia’s eastern indigo snake (Drymarchon couperi) populations. PLoS ONE 14, e0218351 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Guthrie, A. L., Knowles, S., Ballmann, A. E. & Lorch, J. M. Detection of snake fungal disease due to Ophidiomyces ophiodiicola in Virginia, USA. J. Wildl. Dis. 52, 143–149. https://doi.org/10.7589/2015-01-007 (2016).CAS 
Article 
PubMed 

Google Scholar 
Last, L. A., Fenton, H., Gonyor-McGuire, J., Moore, M. & Yabsley, M. J. Snake fungal disease caused by Ophidiomyces ophiodiicola in a free-ranging mud snake (Farancia abacura). J. Vet. Diagn. Invest. 28, 709–713. https://doi.org/10.1177/1040638716663250 (2016).CAS 
Article 
PubMed 

Google Scholar 
Lorch, J. M. et al. Snake fungal disease: An emerging threat to wild snakes. Philos. Trans. R. Soc. B 371, 20150457. https://doi.org/10.1098/rstb.2015.0457 (2016).Article 

Google Scholar 
Haynes, E. et al. First report of ophidiomycosis in a free-ranging California Kingsnake (Lampropeltis californiae) in California, USA. J. Wildl. Dis. 57, 246–249 (2021).CAS 
PubMed 
Article 

Google Scholar 
Burbrink, F. T., Lorch, J. M. & Lips, K. R. Host susceptibility to snake fungal disease is highly dispersed across phylogenetic and functional trait space. Sci. Adv. 3, 1–10. https://doi.org/10.1126/sciadv.1701387 (2017).Article 

Google Scholar 
Dixon, J. R. Amphibians and Reptiles of Texas: With Keys, Taxonomic synopses, Bibliography, and Distribution Maps 3rd edn. (Texas A&M University Press, 2000).
Google Scholar 
McKeown, S. A Field Guide to Reptiles and Amphibians in the Hawaiian Islands (Diamond Head Publishing, 1996).
Google Scholar 
Powell, R., Conant, R. & Collins, J. T. Peterson Field Guide to Reptiles and Amphibians of Eastern and Central NORTH AMERICA (Houghton Mifflin Harcourt, 2016).
Google Scholar 
Stebbins, R. C. & McGinnis, S. M. Peterson Field Guide to Western Reptiles and Amphibians (Houghton Mifflin Harcourt, 2018).
Google Scholar 
Texas Administrative Code. State‐listed threatened species in Texas. 31 TAC §65.175. (2020).Dixon, J. R., Werler, J. E. & Forstner, M. R. J. Texas Snakes: A Field Guide Revised. (University of Texas Press, 2020).Book 

Google Scholar 
Rodriguez, D., Forstner, M. R. J., McBride, D. L., Densmore, L. D. III. & Dixon, J. R. Low genetic diversity and evidence of population structure among subspecies of Nerodia harteri, a threatened water snake endemic to Texas. Conserv. Genet. 13, 977–986 (2012).Article 

Google Scholar 
Scott, N. J., Maxwell, T. C., Thornton, O. W., Fitzgerald, L. A. & Flury, J. W. Distribution, habitat, and future of Harter’s water snake, Nerodia harteri Texas. J. Herpetol. 23, 373–389 (1989).Article 

Google Scholar 
Whiting, M. J., Dixon, J. R. & Greene, B. D. Spatial ecology of the Concho water snake (Nerodia harteri paucimaculata) in a large lake system. J. Herpetol. 31, 327–335 (1997).Article 

Google Scholar 
McBride, D. L. Distribution and status of the Brazos water snake (Nerodia harteri harteri) Master of Science thesis, Tarleton State University (2009).United States Office of the Federal Register. Endangered and threatened wildlife and plants; determination of Nerodia harteri paucimaculata (Concho water snake) to be a threatened species Final rule. Fed. Regist. 51, 31412–31422 (1986).
Google Scholar 
United States Office of the Federal Register. Endangered and threatened wildlife and plants; removal of the Concho water snake from the federallist of endangered and threatened wildlife and removal of designated critical habitat. Fed. Reg. 76, 66779–66804 (2011).
Google Scholar 
United States Office of the Federal Register. Endangered and threatened wildlife and plants; findings on petitions and initiation of status review. Fed. Reg. 50, 29238–29239 (1985).
Google Scholar 
United States Office of the Federal Register. Endangered and threatened wildlife and plants; animal candidate review for listing as endangered or threatened species. Fed. Reg. 59, 58982–59028 (1994).
Google Scholar 
Gibbons, J. W. & Dorcas, M. E. North American Watersnakes: A Natural History (University of Oklahoma Press, 2004).
Google Scholar 
Werler, J. E. & Dixon, J. R. Texas Snakes: Identification, Distribution, and Natural History (University of Texas Press, 2000).
Google Scholar 
Lind, C. M., McCoy, C. M. & Farrell, T. M. Tracking outcomes of snake fungal disease in free-ranging pigmy rattlesnakes (Sistrurus miliarius). J. Wildl. Dis. 54, 352–356. https://doi.org/10.7589/2017-05-109 (2018).Article 
PubMed 

Google Scholar 
McBride, M. P. et al. Ophidiomyces ophiodiicola dermatitis in eight free-ranging timber rattlesnakes (Crotalus horridus) from Massachusetts. J. Zoo Wildl. Med. 46, 86–94. https://doi.org/10.1638/2012-0248R2.1 (2015).Article 
PubMed 

Google Scholar 
McCoy, C. M., Lind, C. M. & Farrell, T. M. Environmental and physiological correlates of the severity of clinical signs of snake fungal disease in a population of pigmy rattlesnakes Sistrurus miliarius. Conserv. Physiol. 5, cow077. https://doi.org/10.1093/conphys/cow077 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Haynes, E. et al. Ophidiomycosis surveillance of snakes in Georgia, USA reveals new host species and taxonomic associations with disease. Sci. Rep. 10, 1–15 (2020).Article 
CAS 

Google Scholar 
Stengle, A. G. et al. Evidence of vertical transmission of the snake fungal pathogen Ophidiomyces ophiodiicola. J. Wildl. Dis. 55, 961–964 (2019).PubMed 
Article 

Google Scholar 
Britton, M., Allender, M. C., Hsiao, S.-H. & Baker, S. J. Postnatal mortality in neonate rattlesnakes associated with Ophidiomyces ophiodiicola. J. Zoo Wildl. Med. 50, 672–677 (2019).PubMed 
Article 

Google Scholar 
Allender, M. C., Hileman, E., Moore, J. & Tetzlaff, S. Detection of Ophidiomyces, the caustive agent of snake fungal disease, in the eastern massasauga (Sistrurus catenatus) in Michigan, USA, 2014. J. Wildl. Dis. 52, 694–698. https://doi.org/10.7589/2015-12-333 (2016).CAS 
Article 
PubMed 

Google Scholar 
Hileman, E. T. et al. Estimation of Ophidiomyces prevalence to evaluate snake fungal disease risk. J. Wildl. Manag. 82, 173–181. https://doi.org/10.1002/jwmg.21345 (2018).Article 

Google Scholar 
McKenzie, J. M. et al. Field diagnostics and seasonality of Ophidiomyces ophiodiicola in wild snake populations. EcoHealth 16, 141–150 (2019).PubMed 
Article 

Google Scholar 
Snyder, S. D., Sutton, W. B. & Walker, D. M. Prevalence of Ophidiomyces ophiodiicola, the causative agent of Snake Fungal Disease, in the Interior Plateau Ecoregion of Tennessee, USA. J. Wildl. Dis. 56, 907–911 (2020).PubMed 
Article 

Google Scholar 
Tetzlaff, S. J. et al. Snake fungal disease affects behavior of free-ranging massasauga rattlesnakes (Sistrurus catenatus). Herpetol. Conserv. Biol. 12, 624–634 (2017).
Google Scholar 
Aldridge, R. D., Flanagan, W. P. & Swarthout, J. T. Reproductive biology of the water snake Nerodia rhombifer from Veracruz, Mexico, with comparisons of tropical and temperate snakes. Herpetologica 51, 182–192 (1995).
Google Scholar 
Greene, B. D., Dixon, J. R., Whiting, M. J. & Mueller, J. M. Reproductive ecology of the Concho water snake Nerodia harteri paucimaculata. Copeia 1999, 701–709 (1999).Article 

Google Scholar 
Kofron, C. P. Reproduction of aquatic snakes in south-central Louisiana. Herpetologica 35, 44–50 (1979).
Google Scholar 
Green, B. D. Life History and Ecology of the Concho Water Snake, Nerodia harteri paucimaculata. Dissertation (Texas A&M University, 1993).
Google Scholar 
McKenzie, C. M. et al. Ophidiomycosis in red cornsnakes (Pantherophis guttatus): potential roles of brumation and temperature on pathogenesis and transmission. Vet. Pathol. 57, 825–837 (2020).CAS 
PubMed 
Article 

Google Scholar 
Gregoire, D. R. Nerodia rhombifer (Hallowell, 1852): U.S. geological survey, nonindigenous aquatic species database, Gainesville, FL, Retrieved from 27 Oct 2009 https://nas.er.usgs.gov/queries/FactSheet.aspx?SpeciesID=2577.Janecka, M. J., Janecka, J. E., Haines, A. M., Michaels, A. & Criscione, C. D. Post-delisting genetic monitoring reveals population subdivision along river and reservoir localities of the endemic Concho water snake (Nerodia harteri paucimaculata). Conserv. Genet. 22, 1005–1021 (2021).CAS 
Article 

Google Scholar 
Madsen, T., Stille, B. & Shine, R. Inbreeding depression in an isolated population of adders Vipera berus. Biol. Cons. 75, 113–118 (1996).Article 

Google Scholar 
Carter, J. et al. Variation in pathogenicity associated with the genetic diversity of Fusarium graminearum. Eur. J. Plant Pathol. 18, 573–583 (2002).Article 

Google Scholar 
Charlesworth, D. & Willis, J. H. The genetics of inbreeding depression. Nat. Rev. Genet. 10, 783 (2009).CAS 
PubMed 
Article 

Google Scholar 
Keller, L. F. & Waller, D. M. Inbreeding effects in wild populations. Trends Ecol. Evol. 17, 230–241 (2002).Article 

Google Scholar 
Nieminen, M., Singer, M. C., Fortelius, W., Schöps, K. & Hanski, I. Experimental confirmation that inbreeding depression increases extinction risk in butterfly populations. Am. Nat. 157, 237–244 (2001).CAS 
PubMed 
Article 

Google Scholar 
Roelke, M. E., Martenson, J. S. & O’Brien, S. J. The consequences of demographic reduction and genetic depletion in the endangered Florida panther. Curr. Biol. 3, 340–350. https://doi.org/10.1016/0960-9822(93)90197-v (1993).CAS 
Article 
PubMed 

Google Scholar 
United States Office of the Federal Register. Endangered and threatened wildlife and plants: findings on petitions involving the Yacare Caiman and Harter’s water snake. Fed. Reg. 49, 21089–21090 (1984).
Google Scholar 
NatureServe. NatureServe Explorer: An Online Encyclopedia of Life [web application]. Version 7.0. NatureServe, Arlington, Virginia., http://www.natureserve.org/explorer (2020).Hammerson, G. A. Nerodia harteri (Trapido, 1941). The IUCN red list of threatened species 2007. https://doi.org/10.2305/IUCN.UK.2007.RLTS.T62238A12583490.en (2007).Allender, M. C. et al. Hematology in an eastern massasauga (Sistrurus catenatus) population and the emergence of Ophidiomyces in Illinois, USA. J. Wildl. Dis. 52, 258–269 (2016).CAS 
PubMed 
Article 

Google Scholar 
Becker, C. G., Rodriguez, D., Lambertini, C., Toledo, L. F. & Haddad, C. F. Historical dynamics of Batrachochytrium dendrobatidis in Amazonia. Ecography 39, 954–960 (2016).Article 

Google Scholar 
Rodriguez, D., Becker, C. G., Pupin, N. C., Haddad, C. F. B. & Zamudio, K. R. Long-term endemism of two highly divergent lineages of the amphibian-killing fungus in the Atlantic forest of Brazil. Mol. Ecol. 23, 774–787. https://doi.org/10.1111/mec.12615 (2014).CAS 
Article 
PubMed 

Google Scholar 
Fitch, H. S. Collecting and Life-History Techniques. In Snakes: Ecology and Evolutionary Biology (eds Seigel, Richard A. et al.) 143–164 (Macmillan, 1987).
Google Scholar 
Winne, C. T., Willson, J. D., Andrews, K. M. & Reed, R. N. Efficacy of marking snakes with disposable medical cautery units. Herpetol. Rev. 37, 52–54 (2006).
Google Scholar 
Greene, B. D., Dixon, J. R., Mueller, J. M., Whiting, M. J. & Thornton, O. W. Jr. Feeding ecology of the Concho water snake, Nerodia harteri paucimaculata. J. Herpetol. 28, 165–172 (1994).Article 

Google Scholar 
Lacki, M. J., Hummer, J. W. & Fitzgerald, J. L. Population patterns of copperbelly water snakes (Nerodia erythrogaster neglecta) in a riparian corridor impacted by mining and reclamation. Am. Midl. Nat. 153, 357–369 (2005).Article 

Google Scholar 
Hyatt, A. D. et al. Diagnostic assays and sampling protocols for the detection of Batrachochytrium dendrobatidis. Dis. Aquat. Org. 73, 175–192 (2007).CAS 
Article 

Google Scholar 
Allender, M. C., Bunick, D., Dzhaman, E., Burrus, L. & Maddox, C. Development and use of a real-time polymerase chain reaction assay for the detection of Ophidiomyces ophiodiicola in snakes. J. Vet. Diagn. Invest. 27, 217–220. https://doi.org/10.1177/1040638715573983 (2015).CAS 
Article 
PubMed 

Google Scholar 
Bohuski, E., Lorch, J. M., Griffin, K. M. & Blehert, D. S. TaqMan real-time polymerase chain reaction for detection of Ophidiomyces ophiodiicola, the fungus associated with snake fungal disease. BMC Vet. Res. 11, 1–10. https://doi.org/10.1186/s12917-015-0407-8 (2015).CAS 
Article 

Google Scholar 
Longo, A. V. et al. ITS1 copy number varies among Batrachochytrium dendrobatidis strains: Implications for qPCR estimates of infection intensity from field-collected amphibian skin swabs. PLoS ONE 8, e59499 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ohkura, M. et al. Genome sequence of Ophidiomyces ophiodiicola, an emerging fungal pathogen of snakes. Genome Announc. 5, 1–2 (2017).Article 

Google Scholar 
Falk, B. G., Snow, R. W. & Reed, R. N. A validation of 11 body-condition indices in a giant snake species that exhibits positive allometry. PLoS ONE 12, e0180791 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Garrow, J. S. & Webster, J. Quetelet’s index (W/H2) as a measure of fatness. Int. J. Obes. 9, 147–153 (1985).CAS 
PubMed 

Google Scholar 
Dorai-Raj, S. binom: Binomial confidence intervals for several parameterizations. https://CRAN.R-project.org/package=binom (2014).Thiele, C. & Hirschfeld, G. cutpointr: Improved estimation and validation of optimal cutpoints in R. J. Stat. Softw. 98, 1–27 (2021).Article 

Google Scholar 
Diggle, P. J. Estimating prevalence using an imperfect test. Epidemiol. Res. Int. 2011, 1–5 (2011).Article 

Google Scholar 
Bender, R. & Lange, S. Adjusting for multiple testing: When and how?. J. Clin. Epidemiol. 54, 343–349 (2001).CAS 
PubMed 
Article 

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

Google Scholar 
Barton, K. MuMIn: Multi-model inference. R package version 1.43.6 (2019).Lenth, R., Singmann, H., Love, J., Buerkner, P. & Herve, M. emmeans: Estimated marginal means, aka least-squares means, R package version 1.4.8. https://CRAN.R-project.org/package=emmeans (2020). More