Philippa Kaur

1.Stark, R., Grzelak, M. & Hadfield, J. RNA sequencing: The teenage years. Nat. Rev. Genet. https://doi.org/10.1038/s41576-019-0150-2 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
2.Gutzwiller, F. et al. Dynamics of Wolbachia pipientis gene expression across the Drosophila melanogaster life cycle. G3 Genes Genomes Genet. 5, 2843–2856 (2015).CAS 

Google Scholar 
3.Bennuru, S. et al. Stage-specific transcriptome and proteome analyses of the filarial parasite Onchocerca volvulus and its Wolbachia endosymbiont. MBio 7, e02028-e2116 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
4.Baião, G. C., Schneider, D. I., Miller, W. J. & Klasson, L. The effect of Wolbachia on gene expression in Drosophila paulistorum and its implications for symbiont-induced host speciation. BMC Genom. 20, 465 (2019).Article 
CAS 

Google Scholar 
5.Werren, J. H., Baldo, L. & Clark, M. E. Wolbachia: Master manipulators of invertebrate biology. Nat. Rev. Microbiol. 6, 741–751 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
6.Zug, R. & Hammerstein, P. Still a host of hosts for Wolbachia: Analysis of recent data suggests that 40% of terrestrial arthropod species are infected. PLoS One 7, e38544 (2012).CAS 
PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
7.Sazama, E. J., Bosch, M. J., Shouldis, C. S., Ouellette, S. P. & Wesner, J. S. Incidence of Wolbachia in aquatic insects. Ecol. Evol. 7, 1165–1169 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
8.Detcharoen, M., Arthofer, W., Schlick-Steiner, B. C. & Steiner, F. M. Wolbachia megadiversity: 99% of these microorganismic manipulators unknown. FEMS Microbiol. Ecol. 95, fiz151 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
9.Hosokawa, T., Koga, R., Kikuchi, Y., Meng, X. Y. & Fukatsu, T. Wolbachia as a bacteriocyte-associated nutritional mutualist. Proc. Natl. Acad. Sci. U. S. A. 107, 769–774 (2010).CAS 
PubMed 
Article 
ADS 
PubMed Central 

Google Scholar 
10.Teixeira, L., Ferreira, Á. & Ashburner, M. The bacterial symbiont Wolbachia induces resistance to RNA viral infections in Drosophila melanogaster. PLoS Biol. 6, 2753–2763 (2008).CAS 
Article 

Google Scholar 
11.Hedges, L. M., Brownlie, J. C., O’Neill, S. L. & Johnson, K. N. Wolbachia and virus protection in insects. Science (80-). 322, 702–702 (2008).CAS 
Article 
ADS 

Google Scholar 
12.Osborne, S. E., Leong, Y. S., O’Neill, S. L. & Johnson, K. N. Variation in antiviral protection mediated by different Wolbachia strains in Drosophila simulans. PLoS Pathog. 5, e1000656 (2009).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
13.Cattel, J., Martinez, J., Jiggins, F., Mouton, L. & Gibert, P. Wolbachia-mediated protection against viruses in the invasive pest Drosophila suzukii. Insect Mol. Biol. 25, 595–603 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
14.Ranz, J. M., Castillo-Davis, C. I., Meiklejohn, C. D. & Hartl, D. L. Sex-dependent gene expression and evolution of the Drosophila transcriptome. Science (80-). 300, 1742–1745 (2003).CAS 
Article 
ADS 

Google Scholar 
15.Herbert, R. I. & McGraw, E. A. The nature of the immune response in novel Wolbachia-host associations. Symbiosis 74, 225–236 (2018).Article 

Google Scholar 
16.Woodford, L. et al. Vector species-specific association between natural Wolbachia infections and avian malaria in black fly populations. Sci. Rep. 8, 4188 (2018).PubMed 
PubMed Central 
Article 
ADS 
CAS 

Google Scholar 
17.Huigens, M. E., De Almeida, R. P., Boons, P. A. H., Luck, R. F. & Stouthamer, R. Natural interspecific and intraspecific horizontal transfer of parthenogenesis-inducing Wolbachia in Trichogramma wasps. Proc. R. Soc. B Biol. Sci. 271, 509–515 (2004).CAS 
Article 

Google Scholar 
18.Detcharoen, M., Arthofer, W., Jiggins, F. M., Steiner, F. M. & Schlick-Steiner, B. C. Wolbachia affect behavior and possibly reproductive compatibility but not thermoresistance, fecundity, and morphology in a novel transinfected host, Drosophila nigrosparsa. Ecol. Evol. 10, 4457–4470 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
19.Woolfit, M. et al. Genomic evolution of the pathogenic Wolbachia strain, wMelPop. Genome Biol. Evol. 5, 2189–2204 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
20.Suh, E., Mercer, D. R., Fu, Y. & Dobson, S. L. Pathogenicity of life-shortening Wolbachia in Aedes albopictus after transfer from Drosophila melanogaster. Appl. Environ. Microbiol. 75, 7783–7788 (2009).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
21.McGraw, E. A., Merritt, D. J., Droller, J. N. & O’Neill, S. L. Wolbachia-mediated sperm modification is dependent on the host genotype in Drosophila. Proc. R. Soc. B Biol. Sci. 268, 2565–2570 (2001).CAS 
Article 

Google Scholar 
22.Xie, J., Vilchez, I. & Mateos, M. Spiroplasma bacteria enhance survival of Drosophila hydei attacked by the parasitic wasp Leptopilina heterotoma. PLoS One 5, e12149 (2010).PubMed 
PubMed Central 
Article 
ADS 
CAS 

Google Scholar 
23.Hutchence, K. J., Fischer, B., Paterson, S. & Hurst, G. D. D. How do insects react to novel inherited symbionts? A microarray analysis of Drosophila melanogaster response to the presence of natural and introduced Spiroplasma. Mol. Ecol. 20, 950–958 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
24.O’Grady, P. M. & DeSalle, R. Phylogeny of the genus Drosophila. Genetics 209, 1–25 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
25.Kellermann, V., Van Heerwaarden, B., Sgrò, C. M. & Hoffmann, A. A. Fundamental evolutionary limits in ecological traits drive Drosophila species distributions. Science (80-). 325, 1244–1246 (2009).CAS 
Article 
ADS 

Google Scholar 
26.Bächli, G., Viljoen, F., Escher, S. A. & Saura, A. The Drosophilidae (Diptera) of Fennoscandia and Denmark (Brill, 2005).27.Kinzner, M.-C. et al. Life-history traits and physiological limits of the alpine fly Drosophila nigrosparsa (Diptera: Drosophilidae): A comparative study. Ecol. Evol. 8, 2006–2020 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
28.Kinzner, M.-C. et al. Major range loss predicted from lack of heat adaptability in an alpine Drosophila species. Sci. Total Environ. 695, 133753 (2019).CAS 
PubMed 
Article 
ADS 
PubMed Central 

Google Scholar 
29.Kinzner, M.-C. et al. Oviposition substrate of the mountain fly Drosophila nigrosparsa (Diptera: Drosophilidae). PLoS One 11, e0165743 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
30.Cicconardi, F. et al. Chemosensory adaptations of the mountain fly Drosophila nigrosparsa (Insecta: Diptera) through genomics’ and structural biology’s lenses. Sci. Rep. 7, 43770 (2017).PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
31.Tratter Kinzner, M. et al. Is temperature preference in the laboratory ecologically relevant for the field? The case of Drosophila nigrosparsa. Glob. Ecol. Conserv. 18, e00638 (2019).Article 

Google Scholar 
32.Arthofer, W. et al. Genomic resources notes accepted 1 August 2014–30 September 2014. Mol. Ecol. Resour. 15, 228–229 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
33.Cicconardi, F., Marcatili, P., Arthofer, W., Schlick-Steiner, B. C. & Steiner, F. M. Positive diversifying selection is a pervasive adaptive force throughout the Drosophila radiation. Mol. Phylogenet. Evol. 112, 230–243 (2017).PubMed 
Article 
PubMed Central 

Google Scholar 
34.Verspoor, R. L. & Haddrill, P. R. Genetic diversity, population structure and Wolbachia infection status in a worldwide sample of Drosophila melanogaster and D. simulans populations. PLoS One 6, e26318 (2011).CAS 
PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
35.Lints, F. A. Size in relation to development-time and egg-density in Drosophila melanogaster. Nature 197, 1128–1130 (1963).Article 
ADS 

Google Scholar 
36.Clemson, A. S., Sgrò, C. M. & Telonis-Scott, M. Thermal plasticity in Drosophila melanogaster populations from eastern Australia: Quantitative traits to transcripts. J. Evol. Biol. 29, 2447–2463 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
37.Morozova, T. V., Anholt, R. H. & Mackay, T. F. Transcriptional response to alcohol exposure in Drosophila melanogaster. Genome Biol. 7, R95 (2006).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
38.Elya, C., Zhang, V., Ludington, W. B. & Eisen, M. B. Stable host gene expression in the gut of adult Drosophila melanogaster with different bacterial mono-associations. PLoS One 11, e0167357 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
39.Chrostek, E. et al. Wolbachia variants induce differential protection to viruses in Drosophila melanogaster: A phenotypic and phylogenomic analysis. PLoS Genet. 9, e1003896 (2013).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
40.Zhang, B. et al. Comparative transcriptome analysis of chemosensory genes in two sister leaf beetles provides insights into chemosensory speciation. Insect Biochem. Mol. Biol. 79, 108–118 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
41.Gazara, R. K. et al. De novo transcriptome sequencing and comparative analysis of midgut tissues of four non-model insects pertaining to Hemiptera, Coleoptera, Diptera and Lepidoptera. Gene 627, 85–93 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
42.Braig, H. R., Zhou, W., Dobson, S. L. & O’Neill, S. L. Cloning and characterization of a gene encoding the major surface protein of the bacterial endosymbiont Wolbachia pipientis. J. Bacteriol. 180, 2373–2378 (1998).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
43.Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
44.Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
45.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020), https://www.R-project.org.46.Soneson, C., Love, M. I. & Robinson, M. D. Differential analyses for RNA-seq: Transcript-level estimates improve gene-level inferences. F1000Research 4, 1521 (2016).PubMed Central 
Article 

Google Scholar 
47.Thurmond, J. et al. FlyBase 2.0: The next generation. Nucleic Acids Res. 47, D759–D765 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
48.Hardcastle, T. J. & Kelly, K. A. BaySeq: Empirical Bayesian methods for identifying differential expression in sequence count data. BMC Bioinform. 11, 422 (2010).Article 

Google Scholar 
49.Huang, D. W., Sherman, B. T. & Lempicki, R. A. Bioinformatics enrichment tools: Paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37, 1–13 (2009).Article 
CAS 

Google Scholar 
50.Gaujoux, R. & Seoighe, C. A flexible R package for nonnegative matrix factorization. BMC Bioinform. 11, 367 (2010).Article 
CAS 

Google Scholar 
51.Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5-6. (2019) https://cran.r-project.org/web/packages/vegan/.52.Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
53.Wickham, H. ggplot2. Wiley Interdiscip. Rev. Comput. Stat. 3, 180–185 (2011).54.Wittkopp, P. J. Variable gene expression in eukaryotes: A network perspective. J. Exp. Biol. 210, 1567–1575 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
55.Lin, Y., Chen, Z.-X., Oliver, B. & Harbison, S. T. Microenvironmental gene expression plasticity among individual Drosophila melanogaster. G3 Genes Genomes Genet. 6, 4197–4210 (2016).CAS 

Google Scholar 
56.Kristensen, T. N., Sørensen, P., Pedersen, K. S., Kruhøffer, M. & Loeschcke, V. Inbreeding by environmental interactions affect gene expression in Drosophila melanogaster. Genetics 173, 1329–1336 (2006).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
57.Dunning, L. T., Dennis, A. B., Sinclair, B. J., Newcomb, R. D. & Buckley, T. R. Divergent transcriptional responses to low temperature among populations of alpine and lowland species of New Zealand stick insects (Micrarchus). Mol. Ecol. 23, 2712–2726 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
58.Lambert, A. J. & Brand, M. D. Reactive oxygen species production by mitochondria. In Mitochondrial DNA. Methods in Molecular Biology (ed. Stuart, J. A.) vol. 554 165–181 (Humana Press, 2009).
Google Scholar 
59.Kurz, M. et al. Structural and functional characterization of the oxidoreductase α-DsbA1 from Wolbachia pipientis. Antioxidants Redox Signal. 11, 1485–1500 (2009).CAS 
Article 

Google Scholar 
60.Zug, R. & Hammerstein, P. Wolbachia and the insect immune system: What reactive oxygen species can tell us about the mechanisms of Wolbachia-host interactions. Front. Microbiol. 6, 1201 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
61.Ratzka, C., Gross, R. & Feldhaar, H. Endosymbiont tolerance and control within insect hosts. Insects 3, 553–572 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
62.Pan, X. et al. Wolbachia induces reactive oxygen species (ROS)-dependent activation of the Toll pathway to control dengue virus in the mosquito Aedes aegypti. Proc. Natl. Acad. Sci. U. S. A. 109, E23-31 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
63.Brennan, L. J., Haukedal, J. A., Earle, J. C., Keddie, B. & Harris, H. L. Disruption of redox homeostasis leads to oxidative DNA damage in spermatocytes of Wolbachia-infected Drosophila simulans. Insect Mol. Biol. 21, 510–520 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
64.Blagrove, M. S. C., Arias-Goeta, C., Failloux, A.-B. & Sinkins, S. P. Wolbachia strain wMel induces cytoplasmic incompatibility and blocks dengue transmission in Aedes albopictus. Proc. Natl. Acad. Sci. 109, 255–260 (2012).CAS 
PubMed 
Article 
ADS 
PubMed Central 

Google Scholar 
65.Andrews, E. S., Crain, P. R., Fu, Y., Howe, D. K. & Dobson, S. L. Reactive oxygen species production and Brugia pahangi survivorship in Aedes polynesiensis with artificial Wolbachia infection types. PLoS Pathog. 8, e1003075 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
66.Oliveira, M. F. et al. Haem detoxification by an insect. Nature 400, 517–518 (1999).CAS 
PubMed 
Article 
ADS 
PubMed Central 

Google Scholar 
67.Paiva-Silva, G. O. et al. A heme-degradation pathway in a blood-sucking insect. Proc. Natl. Acad. Sci. U. S. A. 103, 8030–8035 (2006).CAS 
PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
68.Levi, S. & Rovida, E. The role of iron in mitochondrial function. Biochim. Biophys. Acta Gen. Subj. 1790, 629–636 (2009).CAS 
Article 

Google Scholar 
69.Kremer, N. et al. Wolbachia interferes with ferritin expression and iron metabolism in insects. PLoS Pathog. 5, e1000630 (2009).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
70.Kremer, N. et al. Influence of Wolbachia on host gene expression in an obligatory symbiosis. BMC Microbiol. 12, S7 (2012).CAS 
PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
71.Peng, Y., Nielsen, J. E., Cunningham, J. P. & McGraw, E. A. Wolbachia infection alters olfactory-cued locomotion in Drosophila spp. Appl. Environ. Microbiol. 74, 3943–3948 (2008).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
72.Peng, Y. & Wang, Y. Infection of Wolbachia may improve the olfactory response of Drosophila. Chin. Sci. Bull. 54, 1369–1375 (2009).
Google Scholar 
73.Fattouh, N., Cazevieille, C. & Landmann, F. Wolbachia endosymbionts subvert the endoplasmic reticulum to acquire host membranes without triggering ER stress. PLoS Negl. Trop. Dis. 13, e0007218 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
74.Chagas-Moutinho, V. A., Silva, R., de Souza, W. & Motta, M. C. Identification and ultrastructural characterization of the Wolbachia symbiont in Litomosoides chagasfilhoi. Parasit. Vectors 8, 74 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
75.Serbus, L. R., Casper-Lindley, C., Landmann, F. & Sullivan, W. The genetics and cell biology of Wolbachia-host interactions. Annu. Rev. Genet. 42, 683–707 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
76.Ping, Y. et al. Linking Aβ42-induced hyperexcitability to neurodegeneration, learning and motor deficits, and a shorter lifespan in an Alzheimer’s model. PLoS Genet. 11, e1005025 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
77.Ping, Y. et al. Shal/Kv4 channels are required for maintaining excitability during repetitive firing and normal locomotion in Drosophila. PLoS One 6, e16043 (2011).CAS 
PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
78.Ping, Y. & Tsunoda, S. Inactivity-induced increase in nAChRs upregulates Shal K+ channels to stabilize synaptic potentials. Nat. Neurosci. 15, 90–97 (2012).CAS 
Article 

Google Scholar 
79.Kim, W. J., Jan, L. Y. & Jan, Y. N. A PDF/NPF neuropeptide signaling circuitry of male Drosophila melanogaster controls rival-induced prolonged mating. Neuron 80, 1190–1205 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
80.King, A. N. et al. A peptidergic circuit links the circadian clock to locomotor activity. Curr. Biol. 27, 1915-1927.e5 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
81.Kim, Y. J., Žitňan, D., Galizia, C. G., Cho, K. H. & Adams, M. E. A command chemical triggers an innate behavior by sequential activation of multiple peptidergic ensembles. Curr. Biol. 16, 1395–1407 (2006).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
82.Rapaport, F. et al. Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data. Genome Biol. 14, 3158 (2013).Article 
CAS 

Google Scholar 
83.Kvam, V. M., Liu, P. & Si, Y. A comparison of statistical methods for detecting differentially expressed genes from RNA-seq data. Am. J. Bot. 99, 248–256 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
84.Guo, Y., Li, C. I., Ye, F. & Shyr, Y. Evaluation of read count based RNAseq analysis methods. BMC Genom. 14, S2 (2013).Article 

Google Scholar  More

1.Krumhansl, K. A. et al. Global patterns of kelp forest change over the past half-century. Proc. Natl. Acad. Sci. USA 113, 13785–13790 (2016).CAS 
PubMed 
Article 

Google Scholar 
2.Filbee-Dexter, K. & Scheibling, R. E. Sea urchin barrens as alternative stable states of collapsed kelp ecosystems. Mar. Ecol. Prog. Ser. 495, 1–25 (2014).ADS 
Article 

Google Scholar 
3.Steneck, R. S. et al. Kelp forest ecosystems: biodiversity, stability, resilience and future. Environ. Conserv. 29, 436–459 (2002).Article 

Google Scholar 
4.Steneck, R. S. Regular sea urchins as drivers of shallow benthic marine community structure. Dev. Aquacult. Fish. Sci. 43, 255–279 (2020).
Google Scholar 
5.Rogers-Bennett, L. & Catton, C. A. Marine heat wave and multiple stressors tip bull kelp forest to sea urchin barrens. Sci. Rep. 9, 1–9 (2019).CAS 
Article 

Google Scholar 
6.Pearse, J. S. Ecological role of purple sea urchins. Science 31, 940–941 (2006).ADS 
Article 
CAS 

Google Scholar 
7.Harrold, C. & Reed, D. C. Food availability, sea urchin grazing, and kelp forest community structure. Ecology 66, 1160–1169 (1985).Article 

Google Scholar 
8.Kriegisch, N., Reeves, S. E., Flukes, E. B., Johnson, C. R. & Ling, S. D. Drift-kelp suppresses foraging movement of overgrazing sea urchins. Oecologia 190, 665–677 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
9.Pearse, J. S. & Hines, A. H. Long-term population dynamics of sea urchins in a central California kelp forest: rare recruitment and rapid decline. Mar. Ecol. Prog. Ser. 39, 275–283 (1987).ADS 
Article 

Google Scholar 
10.Watanabe, J. M. & Harrold, C. Destructive grazing by sea urchins Strongylocentrotus spp. in a central California kelp forest: potential roles of recruitment, depth, and predation. Mar. Ecol. Prog. Ser. 71, 125–141 (1991).ADS 
Article 

Google Scholar 
11.Reid, J. et al. The economic value of the recreational red abalone fishery in northern California. Calif. Fish Game 102, 119–130 (2016).
Google Scholar 
12.Menge, B. A. & Menge, D. N. Dynamics of coastal meta-ecosystems: the intermittent upwelling hypothesis and a test in rocky intertidal regions. Ecol. Monogr. 83, 283–310 (2013).Article 

Google Scholar 
13.Breitburg, D. L., Loher, T., Pacey, C. A. & Gerstein, A. Varying effects of low dissolved oxygen on trophic interactions in an estuarine food web. Ecol. Monogr. 67, 489–507 (1997).Article 

Google Scholar 
14.Hauri, C. et al. (2009) Ocean acidification in the California current system. Oceanography 22, 60–71 (2009).Article 

Google Scholar 
15.Connell, S. D. & Russell, B. D. The direct effects of increasing CO2 and temperature on non-calcifying organisms: increasing the potential for phase shifts in kelp forests. Proc. R. Soc. B 277, 1409–1415 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
16.Sellers, A. J. et al. Seasonal upwelling reduces herbivore control of tropical rocky intertidal algal communities. Ecology e03335 https://doi.org/10.1002/ecy.3335(2021).17.Moulin, L., Grosjean, P., Leblud, J., Batigny, A. & Dubois, P. Impact of elevated pCO2 on acid-base regulation of the sea urchin Echinometra mathaei and its relation to resistance to ocean acidification: a study in mesocosms. J. Exp. Mar. Biol. Ecol. 457, 97–104 (2014).CAS 
Article 

Google Scholar 
18.Siikavuopio, S. I., Dale, T., Mortensen, A. & Foss, A. Effects of hypoxia on feed intake and gonad growth in the green sea urchin, Strongylocentrotus droebachiensis. Aquaculture 266, 112–116 (2007).Article 

Google Scholar 
19.Low, H. N. N. The Effects of Upwelling-driven Hypoxia on Sea Urchins in California Current Kelp Forests. PhD dissertation, Stanford University, Stanford, CA (2018).20.Low, N. H. & Micheli, F. Lethal and functional thresholds of hypoxia in two key benthic grazers. Mar. Ecol. Prog. Ser. 594, 165–173 (2018).ADS 
CAS 
Article 

Google Scholar 
21.Low, N. H. & Micheli, F. Short-and long-term impacts of variable hypoxia exposures on kelp forest sea urchins. Sci. Rep. 10, 1–9 (2020).CAS 
Article 

Google Scholar 
22.Huyer, A. Coastal upwelling in the California current system. Prog. Oceanogr. 12, 259–284 (1983).ADS 
Article 

Google Scholar 
23.Frieder, C. A., Nam, S. H., Martz, T. R. & Levin, L. A. High temporal and spatial variability of dissolved oxygen and pH in a nearshore California kelp forest. Biogeosciences 9, 3917–3930 (2012).24.Feely, R. A. et al. The combined effects of acidification and hypoxia on pH and aragonite saturation in the coastal waters of the California current ecosystem and the northern Gulf of Mexico. Cont. Shelf Res. 152, 50–60 (2018).ADS 
Article 

Google Scholar 
25.Chan, F. et al. Persistent spatial structuring of coastal ocean acidification in the California Current System. Sci. Rep. 7, 1–7 (2017).Article 
CAS 

Google Scholar 
26.Orr, J. C. et al. Anthropogenic ocean acidification over the twenty-first century and its impact on calcifying organisms. Nature 437, 681–686 (2005).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
27.Feely, R. A. et al. Chemical and biological impacts of ocean acidification along the west coast of North America. Estuar. Coast. Shelf Sci. 183, 260–270 (2016).ADS 
CAS 
Article 

Google Scholar 
28.Iles, A. C. et al. Climate-driven trends and ecological implications of event-scale upwelling in the California Current System. Glob. Change Biol. 18, 783–796 (2012).ADS 
Article 

Google Scholar 
29.CeNCOOS. Real-Time Sensor Feeds of Oceanographic and Atmospheric Models’ Online Tool to Extract Temperature, pH, and Dissolved Oxygen. https://data.cencoos.org (2020).30.Bakun, A. Global climate change and intensification of coastal ocean upwelling. Science 247, 198–201 (1990).ADS 
CAS 
PubMed 
Article 

Google Scholar 
31.McGregor, H. V., Dima, M., Fischer, H. W. & Mulitza, S. Rapid 20th-century increase in coastal upwelling off northwest Africa. Science 315, 637–639 (2007).ADS 
CAS 
PubMed 
Article 

Google Scholar 
32.Narayan, N., Paul, A., Mulitza, S. & Schulz, M. Trends in coastal upwelling intensity during the late 20th century. Ocean Sci. 6, 815–823 (2010).ADS 
Article 

Google Scholar 
33.Barton, E. D. D., Field, D. B. B. & Roy, C. Canary current upwelling: more or less?. Prog. Oceanogr. 116, 167–178 (2013).ADS 
Article 

Google Scholar 
34.Mote, P. W. & Mantua, N. J. Coastal upwelling in a warmer future. Geophys. Res. Lett. 29, 2138 (2002).ADS 
Article 

Google Scholar 
35.Bakun, A. et al. Anticipated effects of climate change on coastal upwelling ecosystems. Curr. Clim. Change Rep. 1, 85–93 (2015).Article 

Google Scholar 
36.Wang, D., Gouhier, T. C., Menge, B. A. & Ganguly, A. R. Intensification and spatial homogenization of coastal upwelling under climate change. Nature 518, 390–394 (2015).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
37.Snyder, M. A., Sloan, L. C., Diffenbaugh, N. S. & Bell, J. L. Future climate change and upwelling in the California Current. Geophys. Res. Lett. 30, 1823 (2003).38.García‐Reyes, M. & Largier, J. Observations of increased wind‐driven coastal upwelling off central California. J. Geophys. Res. Oceans 115, 1–8 (2010).39.Varela, R., Álvarez, I., Santos, F., DeCastro, M. & Gómez-Gesteira, M. Has upwelling strengthened along worldwide coasts over 1982–2010?. Sci. Rep. 5, 1–15 (2015).40.Varela, R., Lima, F. P., Seabra, R., Meneghesso, C. & Gómez-Gesteira, M. Coastal warming and wind-driven upwelling: a global analysis. Sci. Total Environ. 639, 1501–1511 (2018).41.Abrahams, A., Schlegel, R. W. & Smit, A. J. Variation and change of upwelling dynamics detected in the world’s eastern boundary upwelling systems. Front. Mar. Sci. 8, 626411 (2021).Article 

Google Scholar 
42.IPCC Climate change 2014: Synthesis report. In Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Vol. 151 (eds Core Writing Team et al.) (IPCC, Geneva, 2014).
Google Scholar 
43.Rykaczewski, R. R. & Dunne, J. P. Enhanced nutrient supply to the California Current Ecosystem with global warming and increased stratification in an earth system model. Geophys. Res. Lett. 37, 1-5 (2010).44.Somero, G. N. et al. What changes in the carbonate system, oxygen, and temperature portend for the northeastern Pacific Ocean: a physiological perspective. Bioscience 66, 14–26 (2016).Article 

Google Scholar 
45.Frölicher, T. L., Fischer, E. M. & Gruber, N. Marine heatwaves under global warming. Nature 560, 360–364 (2018).ADS 
PubMed 
Article 
CAS 

Google Scholar 
46.Filbee-Dexter, K. et al. Marine heatwaves and the collapse of marginal North Atlantic kelp forests. Sci. Rep. 10, 13388 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
47.Sokolova, I. M., Frederich, M., Bagwe, R., Lannig, G. & Sukhotin, A. A. Energy homeostasis as an integrative tool for assessing limits of environmental stress tolerance in aquatic invertebrates. Mar. Environ. Res. 79, 1–15 (2012).CAS 
PubMed 
Article 

Google Scholar 
48.Sokolova, I. M. Energy-limited tolerance to stress as a conceptual framework to integrate the effects of multiple stressors. Integr. Comp. Biol. 53, 597–608 (2013).PubMed 
Article 

Google Scholar 
49.Fitzgerald-Dehoog, L., Browning, J. & Allen, B. J. Food and heat stress in the California mussel: evidence for an energetic trade-off between survival and growth. Biol. Bull. 223, 205–216 (2012).PubMed 
Article 

Google Scholar 
50.Ramajo, L. et al. Food supply confers calcifiers resistance to ocean acidification. Sci. Rep. 6, 19374 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
51.Brown, N. E., Bernhardt, J. R., Anderson, K. M. & Harley, C. D. Increased food supply mitigates ocean acidification effects on calcification but exacerbates effects on growth. Sci. Rep. 8, 1–9 (2018).
Google Scholar 
52.Wahle, R. A. & Peckham, S. H. Density-related reproductive trade-offs in the green sea urchin, Strongylocentrotus droebachiensis. Mar. Biol. 134, 127–137 (1999).Article 

Google Scholar 
53.Rogers-Bennett, L., Allen, B. L. & Rothaus, D. P. Status and habitat associations of the threatened northern abalone: importance of kelp and coralline algae. Aquat. Conserv. Mar. Freshw. Ecosyst. 21, 573–581 (2011).Article 

Google Scholar 
54.Brown, M. B., Edwards, M. S. & Kim, K. Y. Effects of climate change on the physiology of giant kelp, Macrocystis pyrifera, and grazing by purple urchin, Strongylocentrotus purpuratus. Algae 29, 203–215 (2014).CAS 
Article 

Google Scholar 
55.Klinger, T. S. & Lawrence, J. M. Distance perception of food and the effect of food quantity on feeding behavior of Lytechinus variegatus (Lamarck) (Echinodermata: Echinoidea). Mar. Freshw. Behav. Physiol. 11, 327–344 (1985).Article 

Google Scholar 
56.Trowbridge, C. D. Establishment of the green alga Codium fragile ssp. tomentosoides on New Zealand rocky shores: current distribution and invertebrate grazers. J. Ecol. 83, 949–965 (1995).Article 

Google Scholar 
57.Meidel, S. K. & Scheibling, R. E. Effects of food type and ration on reproductive maturation and growth of the sea urchin Strongylocentrotus droebachiensis. Mar. Biol. 134, 155–166 (1999).Article 

Google Scholar 
58.Harianto, J., Nguyen, H. D., Holmes, S. P. & Byrne, M. The effect of warming on mortality, metabolic rate, heat-shock protein response and gonad growth in thermally acclimated sea urchins (Heliocidaris erythrogramma). Mar. Biol. 165, 1–12 (2018).CAS 
Article 

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

Google Scholar 
60.Hobday, A. J. et al. A hierarchical approach to defining marine heatwaves. Prog. Oceanogr. 141, 227–238 (2016).ADS 
Article 

Google Scholar 
61.Spicer, J. I., Widdicombe, S., Needham, H. R. & Berge, J. A. Impact of CO2-acidified seawater on the extracellular acid-base balance of the northern sea urchin Strongylocentrotus dröebachiensis. J. Exp. Mar. Biol. Ecol. 407, 19–25 (2011).CAS 
Article 

Google Scholar 
62.Catarino, A. I., Bauwens, M. & Dubois, P. Acid–base balance and metabolic response of the sea urchin Paracentrotus lividus to different seawater pH and temperatures. Environ. Sci. Pollut. Res. 19, 2344–2353 (2012).CAS 
Article 

Google Scholar 
63.Rogers-Bennett, L., Bennett, W. A., Fastenau, H. C. & Dewees, C. M. Spatial variation in red sea urchin reproduction and morphology: implications for harvest refugia. Ecol. Appl. 5, 1171–1180 (1995).Article 

Google Scholar 
64.Quinn, J. F., Wing, S. R. & Botsford, L. W. Harvest refugia in marine invertebrate fisheries: models and applications to the red sea urchin, Strongylocentrotus franciscanus. Am. Zool. 33, 537–550 (1993).Article 

Google Scholar 
65.Eurich, J. G., Selden, R. L. & Warner, R. R. California spiny lobster preference for urchins from kelp forests: implications for urchin barren persistence. Mar. Ecol. Prog. Ser. 498, 217–225 (2014).ADS 
Article 

Google Scholar 
66.Steneck, R. S., Leland, A., McNaught, D. C. & Vavrinec, J. Ecosystem flips, locks, and feedbacks: the lasting effects of fisheries on Maine’s kelp forest ecosystem. Bull. Mar. Sci. 89, 31–55 (2013).Article 

Google Scholar 
67.Gerard, V. A. Growth and utilization of internal nitrogen reserves by the giant kelp Macrocystis pyrifera in a low-nitrogen environment. Mar. Biol. 66(1), 27–35 (1982).CAS 
Article 

Google Scholar 
68.Simonson, E. J., Scheibling, R. E. & Metaxas, A. Kelp in hot water: I. Warming seawater temperature induces weakening and loss of kelp tissue. Mar. Ecol. Prog. Ser. 537, 89–104 (2015).ADS 
CAS 
Article 

Google Scholar 
69.Thomsen, M. S. et al. Local extinction of bull kelp (Durvillaea spp.) due to a marine heatwave. Front. Mar. Sci. 6, 84 (2019).Article 

Google Scholar 
70.O’Donnell, M. J., Hammond, L. M. & Hofmann, G. E. Predicted impact of ocean acidification on a marine invertebrate: elevated CO2 alters response to thermal stress in sea urchin larvae. Mar. Biol. 156, 439–446 (2009).Article 
CAS 

Google Scholar 
71.Dupont, S., Dorey, N., Stumpp, M., Melzner, F. & Thorndyke, M. Long-term and trans-life-cycle effects of exposure to ocean acidification in the green sea urchin Strongylocentrotus droebachiensis. Mar. Biol. 160, 1835–1843 (2013).CAS 
Article 

Google Scholar 
72.Marcel, E. V. et al. Variable responses to large-scale climate change in European Parus populations. Proc. R. Soc. B 270, 367–372 (2003).Article 

Google Scholar 
73.Parker, L. M., Ross, P. M. & O’Connor, W. A. Populations of the Sydney rock oyster, Saccostrea glomerata, vary in response to ocean acidification. Mar. Biol. 158, 689–697 (2011).Article 

Google Scholar 
74.Kroeker, K. J., Kordas, R. L. & Harley, C. D. Embracing interactions in ocean acidification research: confronting multiple stressor scenarios and context dependence. Biol. Lett. 13, 20160802 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
75.Conor, J. J. Gonad growth in the sea urchin, Strongylocentrotus purpuratus (Stimpson) (Echinodermata: Echinoidea) and the assumptions of gonad index methods. J. Exp. Mar. Biol. Ecol. 10, 89–103 (1972).Article 

Google Scholar 
76.Bandstra, L., Hales, B. & Takahashi, T. High-frequency measurements of total CO2: method development and first oceanographic observations. Mar. Chem. 100, 24–38 (2006).CAS 
Article 

Google Scholar 
77.Hales, B., Chipman, D. & Takahashi, T. High-frequency measurement of partial pressure and total concentration of carbon dioxide in seawater using microporous hydrophobic membrane contactors. Limnol. Oceanogr. Methods 2, 356–364 (2004).Article 

Google Scholar 
78.Lavigne, H., Epitalon, J. M. & Gattuso, J. P. Seacarb: Seawater Carbonate Chemistry with R. R package version 3.0 http://CRAN.R-project.org/package=seacarb (2011).79.Gattuso, J. P., Epitalon, J. M., Lavigne, H. & Orr, J. Seacarb: seawater carbonate chemistry. R package version 3.2.10. http://CRAN.R-project.org/package=seacarb (2018).80.Murie, K. A. & Bourdeau, P. E. Fragmented kelp forest canopies retain their ability to alter local seawater chemistry. Sci. Rep. 10, 1–13 (2020).Article 
CAS 

Google Scholar 
81.R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/ (2013). More

1.Jones, B. A. et al. Proc. Natl Acad. Sci. USA 110, 8399–8404 (2013).ADS 
CAS 
Article 

Google Scholar 
2.Chand, A. Nat. Food 1, 528 (2020).Article 

Google Scholar 
3.Messmer, T. A. Hum.-Wildl. Interact. 14, 137–140 (2020).
Google Scholar 
4.Malik, Y. S. et al. Vet. Quart. 40, 68–76 (2020).CAS 
Article 

Google Scholar 
5.Konda, M., Dodda, B., Konala, V., Naramala, S. & Adapa, S. Cureus 12, e8932 (2020).PubMed 
PubMed Central 

Google Scholar 
6.Lu, R. et al. Lancet 395, 565–574 (2020).CAS 
Article 

Google Scholar 
7.Lam, T. T. et al. Nature 583, 282–285 (2020).ADS 
CAS 
Article 

Google Scholar 
8.Hassell, J. M., Begon, M., Ward, M. J. & Fèvre, E. M. Trends. Ecol. Evol. 32, 55–67 (2017).Article 

Google Scholar 
9.Rulli, M. C., D’Odorico, P., Galli, N. & Hayman, D. T. S. Nat. Food https://doi.org/10.1038/s43016-021-00285-x (2021).10.Ancillotto, L., Santini, L., Ranc, N., Maiorano, L. & Russo, D. Sci. Nat. 103, 15 (2016).CAS 
Article 

Google Scholar 
11.Laurance, W. F. & Williamson, G. B. Conserv. Biol. 15, 1529–1535 (2001).Article 

Google Scholar 
12.Chand, A. Nat. Food 2, 137 (2021).Article 

Google Scholar 
13.Manning, L. Nat. Food 2, 10 (2021).Article 

Google Scholar 
14.Frutos, R., Serra-Cobo, J., Pinault, L., Lopez Roig, M. & Devaux, C. A. Front. Microbiol. 12, 591535 (2021).Article 

Google Scholar 
15.Schmiege, D. et al. One Health 10, 100170 (2020).Article 

Google Scholar 
16.Afelt, A., Frutos, R. & Devaux, C. Front. Microbiol. 9, 702 (2018).Article 

Google Scholar  More

Study site and speciesThe sub-tropical forest analysed in this study is located in China, Yunnan, Xishuangbanna, Mengla county, Village Quingyanzhai (#94) N 21.802068, E 101.380214, geodetic datum WGS84 (Fig. 6). The site is characterized by a rocky outcrop rising 30–50 m over surrounding rubber plantations, harbouring about 20 ha of relict dry tropical forest. The outcrop sides are steep and mainly covered with bamboo. The top area is colonized by shrubs and 10–15 m high trees (a few trees on the slopes are much higher). The most conspicuous species is Quercus yiwuensis Y.C. Hsu & H.W. Jen. In March 2017 we selected four individual trees of Q. yiwuensis, and an equal number of Pistacia weinmannifolia Franch, and Beilschmiedia percoriacea C.K. Allen that were also numerous on the site. Plants were identified by the authors in the field and labelled. Botanical specimens were deposited in the School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China.Figure 6Map of the study site with approximate position of analysed trees (aerial perspective from Google Maps 2018). GPS positions were obtained less than 1 m from the tree trunks. The distance from N3 to B1 is approximately 60 m.Full size imageQ. yiwuensis was designated P-tree (P1, P2, P3, P4) because we consistently found the orchid Panisea uniflora Lindl. growing on this phorophyte species. P. weinmannifolia was designated B-tree (B1, B2, B3, B4) because it harboured the orchid species Bulbophyllum odoratissimum (Sw) Lindl. (Supplementary Fig. S2 a-d). On P. weinmannifolia trees no P. uniflora was observed, while B. odoratissimum was never found on Q. yiwuensis trees. Both tree species were richly colonized by several other orchid species. Beilschmiedia percoriacea trees were designated neutral tree, N-tree (N1, N2, N3, N4), because neither of the two target orchid species grew on them. The latter tree species carried several lichens and a single fern species (Lepisorus sp.), but only in one instance was observed to carry an orchid epiphyte (Coelogyne sp.).GPS positions of investigated trees were obtained less than 1 m from the trunk (Fig. 6). Accuracy is about 3 m. Accuracy in altitude readings is about 100 m. Distance between degrees of latitude is 111 km. At N 21.78978 the distance between degrees of longitude is 103 km, which means that the last digit in the 5-digit decimal degrees corresponds to 1.11 m in latitude and 1.03 m in longitude.The trees were labelled with different colours as follows:

P-trees (carrying P. uniflora and other epiphytes, but not B. odoratissimum), identified as Q. yiwuensis, with red labels (P1 N 21.79880, E 101.37909, 1073; P2 N 21.79882, E 101.37923, 1072; P3 N 21.79878, E 101.37947, 1074; P4 N 21.79878, E 101.37904, 1073).

B-trees (carrying B. odoratissimum and other epiphytes, but not P. uniflora), identified as P. weinmannifolia, with blue labels (B1 N 21.79878, E 101.37950, 1074; B2 N 21.79880, E 101.37938, 1078; B3 N 21.79881, E 101.37931, 1083; B4 N 21.79884, E 101.37923, 1076).

N-trees (carrying epiphytes, but neither B. odoratissimum nor P. uniflora), identified as B. percoriacea, with yellow labels (N1 N 21.79873, E 101.37905, 1064; N2 N 21.79868, E 101.37908, 1072; N3 N 21.79883, E 101.37893, 1071; N4 N 21.79879, E 101.37895, 1071).

The point of access to the outcrop top area was located at the Western edge (N 21.79880, E 101.37827, 1058, Fig. 6).

SamplingFor each of the twelve selected trees, breast height circumference (BH = 130 cm above ground) was measured. Approximate total height was determined by Nikon Laser Forestry Pro or estimated if sighting lines were interfered by other vegetation.The lowermost individual of the target orchid species was recorded in relation to BH. Bark samples were collected, and bark features recorded at BH, by target orchid, and 50 cm above target orchid or BH, whichever was highest point. In N-trees, where there were no target orchids, sampling was thus at BH, BH + 50 cm, and BH + 100 cm.Sampling on each tree involved approximately 12 cm2 bark cut out with a sterile knife and rubber gloves to prevent cross-contamination, for pH-analysis, metabarcoding, fungal isolation and chemical analysis. Besides, 3 bark cores were taken by trephor sampler (16 mm, 2 mm diam., Costruzioni Meccaniche Carabin Carlo) for water holding measurement.Roots of target orchids were sampled, from three adult individual plants on each P- and B-tree. No permissions were necessary to collect plant samples, using a protocol that avoided plant damages. All plants were left in the exact location where they were found in the sampling site, after collecting the small portions of bark and root material for the study. All experiments including the collection of plant material in this study are in compliance with relevant institutional, national, and international guidelines and legislation.All fresh material collected from the sampling site was first kept in cool boxes, brought to the laboratory, and processed within three days.Fungal isolation from barkFor each sample, half of the bark material and orchid roots were kept at − 80 °C for subsequent metabarcoding analysis. The rest of bark (about 2 g for each sample) was immediately processed for fungal isolation. The large bark portions were ground into powder using a sterile mortar and pestle; 5 ml were reserved for pH measurement, while the rest was suspended in a final volume 50 ml sterile water solution in a sterile centrifuge tube. The tube was shaken with Vortex vibration meter thoroughly and solution aliquots were spread homogenously onto isolation medium plates. For each bark sample, aliquots of 500, 300, 200, and 100 μl, were spread per triplicate to one plate each of PDA (Potato Dextrose Agar) medium, containing ampicillin (50 μg/mL) and streptomycin (50 μg/ml) to inhibit bacterial growth49,50. A diluted solution was also made by mixing 1 ml of the original solution with 9 ml sterile water and plated. Petri dishes were incubated at room temperature (23–25 °C) in the dark for up to 2 months to allow the development of slow-growing mycelia. Fast growing fungal strains started to grow after about two days. Colonies showing different morphology and appearance were transferred to fresh plates to obtain pure cultures. In the following days, other slower growing mycelia were available in the Petri dishes and were also regularly picked up and isolated onto new PDA plates every 2 days. All isolated fungal strains were stored at 4 °C for further analysis. All strains were deposited in the LP Culture Collection (personal culture collection held in the laboratory of Prof. Lorenzo Pecoraro), at the School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China.Molecular and morphological analysis of bark culturable fungiThe identification of isolated fungal colonies was performed using DNA sequencing combined with microscopy. Total genomic DNA from isolated fungi was extracted following the cetyltrimethyl ammonium bromide (CTAB) method modified from Doyle and Doyle51. Fungal ITS regions were PCR-amplified using the primer pair ITS1F/ITS452 following the procedure described in Pecoraro et al.37 for PCR reaction, thermal cycling, and purification of PCR products. Controls with no DNA were included in every amplification experiment in order to test for the presence of laboratory contamination from reagents and reaction buffers. Purified DNA amplicons were sequenced with the same primer pair used for amplification. DNA sequencing was performed at the GENEWIZ Company, Tianjin, China.Sequences were edited to remove vector sequences and to ensure correct orientation and assembled using Sequencher 4.1 for MacOsX (Genes Codes, Ann Arbor, MI). Sequence analysis was conducted with BLAST searches against the National Center for Biotechnology Information (NCBI) sequence database (GenBank; http://www.ncbi.nlm.nih. gov/BLAST/index.html) to determine the closest sequence matches that enabled taxonomic identification. DNA sequences were deposited in GenBank (Accession Nos. MW603206 – MW603451). Fungal morphological characters (hyphae, pseudohyphae, conidiophores, conidia, poroconidia, arthroconidia, etc.) were examined using a Nikon ECLIPSE Ci microscope for the identification of isolates following the standard taxonomic keys53,54,55,56,57.Assessment of bark and orchid associated fungal community using Illumina sequencingBark and orchid root samples were pulverized in a sterile mortar, and genomic DNA was extracted using the FastDNA® Spin Kit as described by the manufacturer (MP Biomedicals, Solon, OH, USA)58,59. In total, this resulted in 60 DNA samples, including 36 from bark (3 sampling points for each tree × 12 trees) and 24 from orchid roots (3 orchid individuals sampled on each P- and B-tree × 8 trees; the 4 individual N-trees were not used for orchid sampling because they did not carry the study orchid species). Subsequently, amplicon libraries were created using two primer combinations targeting the internal transcribed spacer 2 (ITS-2): ITS7F and ITS4R60 was used as universal fungal primer pair to target nearly all fungal species, while ITS361 and ITS4OF62 was used to more specifically target orchid mycorrhizal fungi. Previous research has shown that most universal fungal primers have multiple mismatches to many species of the orchid-associating basidiomycetes, in particular in Tulasnellaceae family46,58,63. Since the goal of the present work was to analyse the total fungal community in the orchid-phorophyte environment (bark and orchid roots), as well as more specifically detect the orchid mycorrhizal fungi in the studied samples, it was necessary to combine two different primer pairs to characterise the whole investigated fungal diversity47,64,65,66. Polymerase chain reaction (PCR) amplification was performed in 50 μl reaction volume, containing 38 μl steril distilled water, 5 μl 10 × buffer (100 mM Tris–HCl pH 8.3, 500 mM KCl, 11 mM MgCl2, 0.1% gelatin), 1 μl of dNTP mixture of 10 mM concentration, 0.25 μM of each primer, 1.5 U of RED TaqTM DNA polymerase (Sigma) and approximately 10 μg of extracted genomic DNA. PCR conditions were as follows: 1 cycle of 95 °C for 5 min initial denaturation before thermocycling, 30 cycles of 94 °C for 40 s denaturation, 45 s annealing at various temperatures following Taylor and McCormick62, 72 °C for 40 s elongation, followed by 1 cycle of 72 °C for 7 min extension. To minimize PCR bias, three PCRs were pooled for each sample. The resulting PCR products were electrophoresed in 1% agarose gel with ethidium bromide and purified with the QIAEX II Gel Extraction Kit (QIAGEN). Amplicon libraries were generated using the NEB Next Ultra DNA Library Prep Kit for Illumina (New England Biolabs, USA) following the manufacturer’s instructions to add index codes. Samples were sequenced using the Illumina MiSeq PE 250 sequencing platform (Illumina Inc., San Diego, CA) at Shanghai Majorbio Bio‐Pharm Technology Co., Ltd. (Shanghai, China).Bioinformatics of fungal sequencesSequences originated from the total (ITS7F and ITS4R primers) and orchid-associated (ITS3 and ITS4OF primers) fungi datasets were processed separately. Raw reads were merged with a minimum overlap of 30 nucleotides, and the primer sequences were trimmed off. Subsequently, reads were filtered by discarding all sequences with expected error  > 1. The quality-filtered reads were denoised using the UNOISE3 algorithm67 to create zero-radius operational taxonomic units (zOTUs), with chimera removal. All the steps were performed using USEARCH v.1168. Raw sequences have been deposited in the Sequences Read Archive (SRA) of NCBI as BioProject ID PRJNA702612. The fungal zOTUs were assigned to taxonomic groups using the Blast algorithm by querying against the UNITE + INSD fungal ITS database (version 7.2, released on 10 October 2017)69 using the sintax algorithm with 0.8 cutoff70. The zOTUs originated with the orchid-associated fungal primers were manually screened for possible orchid-associated mycorrhizal families based on the information provided in Table 12.1 in Dearnaley et al.71, and only these were retained for further analysis in this dataset.To attempt removing spurious counts due to cross-talk (assignment of reads to a wrong sample) we removed all the zOTUs represented by less than 0.02% of reads in each sample, which is more conservative than previous error estimates72. The datasets were rarefied to the minimum sequencing depth (23,419 for total fungi and 13,074 for orchid-associated fungi), zOTUs present in less than three samples and low abundant zOTUs (with relative abundance  More

1.Falkowski PG, Fenchel T, Delong EF. The microbial engines that drive Earth’s biogeochemical cycles. Science. 2008;320:1034–9.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
2.Arnosti C. Microbial extracellular enzymes and the marine carbon cycle. Ann Rev Mar Sci. 2011;3:401–25.PubMed 
Article 
PubMed Central 

Google Scholar 
3.Arnosti C, Bell C, Moorhead DL, Sinsabaugh RL, Steen AD, Stromberger M, et al. Extracellular enzymes in terrestrial, freshwater, and marine environments: perspectives on system variability and common research needs. Biogeochemistry. 2013;117:5–21.Article 
CAS 

Google Scholar 
4.Moorhead DL, Rinkes ZL, Sinsabaugh RL, Weintraub MN. Dynamic relationships between microbial biomass, respiration, inorganic nutrients and enzyme activities: informing enzyme-based decomposition models. Front Microbiol. 2013;4:223.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
5.Li M, Gao Y, Qian W-J, Shi L, Liu Y, Nelson WC, et al. Targeted quantification of functional enzyme dynamics in environmental samples for microbially mediated biogeochemical processes. Environ Microbiol Rep. 2017;9:512–21.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
6.Song H-S, Thomas DG, Stegen JC, Li M, Liu C, Song X, et al. Regulation-structured dynamic metabolic model provides a potential mechanism for delayed enzyme response in denitrification process. Front Microbiol. 2017;8:1866.PubMed 
PubMed Central 
Article 

Google Scholar 
7.Khersonsky O, Tawfik DS. Enzyme promiscuity: a mechanistic and evolutionary perspective. Annu Rev Biochem. 2010;79:471–505.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
8.Baier F, Copp JN, Tokuriki N. Evolution of enzyme superfamilies: comprehensive exploration of sequence-function relationships. Biochemistry. 2016;55:6375–88.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
9.Sebastián M, Niell FX. Alkaline phosphatase activity in marine oligotrophic environments: implications of single-substrate addition assays for potential activity estimations. Mar Ecol Prog Ser. 2004;277:285–90.Article 

Google Scholar 
10.Catrina I, O’Brien PJ, Purcell J, Nikolic-Hughes I, Zalatan JG, et al. Probing the origin of the compromised catalysis of E. coli alkaline phosphatase in its promiscuous sulfatase reaction. J Am Chem Soc. 2007;129:5760–5.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
11.Sunden F, AlSadhan I, Lyubimov AY, Ressl S, Wiersma-Koch H, Borland J, et al. Mechanistic and evolutionary insights from comparative enzymology of phosphomonoesterases and phosphodiesterases across the alkaline phosphatase superfamily. J Am Chem Soc. 2016;138:14273–87.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
12.Yang K, Metcalf WW. A new activity for an old enzyme: Escherichia coli bacterial alkaline phosphatase is a phosphite-dependent hydrogenase. Proc Natl Acad Sci USA. 2004;101:7919–24.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
13.Copley SD. Shining a light on enzyme promiscuity. Curr Opin Struct Biol. 2017;47:167–75.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
14.Steen AD, Vazin JP, Hagen SM, Mulligan KH, Wilhelm SW. Substrate specificity of aquatic extracellular peptidases assessed by competitive inhibition assays using synthetic substrates. Aquat Micro Ecol. 2015;75:271–81.Article 

Google Scholar 
15.Ivars-Martínez E, D’Auria G, RodrÍGuez-Valera F, SÁNchez-Porro C, Ventosa A, et al. Biogeography of the ubiquitous marine bacterium Alteromonas macleodii determined by multilocus sequence analysis. Mol Ecol. 2008;17:4092–106.PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
16.Tada Y, Taniguchi A, Nagao I, Miki T, Uematsu M, Tsuda A, et al. Differing growth responses of major phylogenetic groups of marine bacteria to natural phytoplankton blooms in the western North Pacific Ocean. Appl Environ Microbiol. 2011;77:4055–65.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
17.Schubert M, Lindgreen S, Orlando L. AdapterRemoval v2: rapid adapter trimming, identification, and read merging. BMC Res Notes. 2016;9:88.PubMed 
PubMed Central 
Article 

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

Google Scholar 
19.Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinforma. 2010;11:119.Article 
CAS 

Google Scholar 
20.Bushnell B. “BBMap: a fast, accurate, splice-aware aligner,” in Proceedings of the 9th Annual Genomics of Energy & Environment Meeting. Walnut Creek, CA, USA; 2014.21.Scholz J, Besir H, Strasser C, Suppmann S. A new method to customize protein expression vectors for fast, efficient and background free parallel cloning. BMC Biotechnol. 2013;13:12.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
22.McLoughlin SY, Jackson C, Liu JW, Ollis DL. Growth of Escherichia coli coexpressing phosphotriesterase and glycerophosphodiester phosphodiesterase, using paraoxon as the sole phosphorus source. Appl Environ Microbiol. 2004;70:404–12.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
23.Britton J, Dyer RP, Majumdar S, Raston CL, Weiss GA. Ten-minute protein purification and surface tethering for continuous-flow biocatalysis. Angew Chem Int Ed Engl. 2017;56:2296–301.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
24.Ortiz-Tena JG, Rühmann B, Sieber V. Colorimetric determination of sulfate via an enzyme cascade for high-throughput detection of sulfatase activity. Anal Chem. 2018;90:2526–33.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
25.Huitema C, Horsman G. Analyzing enzyme kinetic data using the powerful statistical capabilities of R. 2018. http://biorxiv.org/content/10.1101/316588v1.26.Rainer SF. Soft-bottom benthic communities in Otago Harbour and Blueskin Bay, New Zealand. New Zealand Oceanographic Institute Memoir 80; 1981.27.Grove SL, Probert PK. Sediment macrobenthos of upper Otago Harbour, New Zealand. New Zeal J Mar Fresh. 1999;33:469–80.28.Hoppe HG. Significance of exoenzymatic activities in the ecology of brackish water: measurements by means of methylumbelliferyl-substrates. Mar Ecol Prog Ser. 1983;11:299–308.CAS 
Article 

Google Scholar 
29.Yamaguchi T, Sato M, Hashihama F, Ehama M, Shiozaki T, Takahashi K, et al. Basin‐scale variations in labile dissolved phosphoric monoesters and diesters in the central North Pacific Ocean. J Geophys Res Oceans. 2019;124:3058–72.CAS 
Article 

Google Scholar 
30.Baltar F, Lundin D, Palovaara J, Lekunberri I, Reinthaler T, Herndl GJ, et al. Prokaryotic responses to ammonium and organic carbon reveal alternative CO2 fixation pathways and importance of alkaline phosphatase in the mesopelagic North Atlantic. Front Microbiol. 2016;7:1670.PubMed 
PubMed Central 
Article 

Google Scholar 
31.Yamaguchi H, Arisaka H, Seki M, Adachi M, Kimura K, Tomaru Y. Phosphotriesterase activity in marine bacteria of the genera Phaeobacter, Ruegeria, and Thalassospira. Int Biodeter Biodegr. 2016;115:186–91.CAS 
Article 

Google Scholar 
32.Davidi D, Noor E, Liebermeister W, Bar-Even A, Flamholz A, Tummler K, et al. Global characterization of in vivo enzyme catalytic rates and their correspondence to in vitro kcat measurements. Proc Natl Acad Sci USA. 2016;113:3401–6.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
33.Paytan A, Cade-Menum BJ, McLaughlin K, Faul KL. Selective phosphorus regeneration of sinking marine particles: evidence from 31P-NMR. Mar Chem. 2003;82:55–70.CAS 
Article 

Google Scholar 
34.Wu J, Wang P, Wang Y. Cytotoxic and mutagenic properties of alkyl phosphotriester lesions in Escherichia coli cells. Nucleic Acids Res. 2018;46:4013–21.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
35.McCarthy JG, Edington BV, Schendel PF. Inducible repair of phosphotriesters in Escherichia coli. Proc Natl Acad Sci USA. 1983;80:7380–4.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
36.Helbert W. Marine polysaccharide sulfatases. Front Mar Sci. 2017;4:6.Article 

Google Scholar 
37.Wegner CE, Richter-Heitmann T, Klindworth A, Klockow C, Richter M, Achstetter T, et al. Expression of sulfatases in Rhodopirellula baltica and the diversity of sulfatases in the genus Rhodopirellula. Mar Genomics. 2013;9:51–61.PubMed 
Article 
PubMed Central 

Google Scholar 
38.Canfield DE, Farquhar J. Animal evolution, bioturbation, and the sulfate concentration of the oceans. Proc Natl Acad Sci USA. 2009;106:8123–7.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
39.Luo HW, Benner R, Long RA, Hu JJ. Subcellular localization of marine bacterial alkaline phosphatases. Proc Nat Acad Sci USA. 2009;106:21219–23.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
40.Wu J-R, Shien J-H, Shieh HK, Hu C-C, Gong S-R, Chen L-Y, et al. Cloning of the gene and characterization of the enzymatic properties of the monomeric alkaline phosphatase (PhoX) from Pasteurella multocida strain X-73. FEMS Microbiol Lett. 2007;267:113–20.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
41.Kageyama H, Tripathi K, Rai AK, Cha-um S, Waditee-Sirisattha R, Takabe T. An alkaline phosphatase/phosphodiesterase, PhoD, induced by salt stress and secreted out of the cells of Aphanothece halophytica, a halotolerant cyanobacterium. Appl Environ Micro. 2011;77:5178–83.CAS 
Article 

Google Scholar 
42.Rodriguez F, Lillington J, Johnson S, Timmel CR, Lea SM, Berks BC. Crystal structure of the Bacillus subtilis phosphodiesterase PhoD reveals an iron and calcium-containing active site. J Biol Chem. 2014;289:30889–99.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
43.Noskova Y, Likhatskaya G, Terentieva N, Son O, Tekutyeva L, Balabanova L. A novel alkaline phosphatase/phosphodiesterase, CamPhoD, from marine bacterium Cobetia amphilecti KMM 296. Mar Drugs. 2019;17:657.CAS 
PubMed Central 
Article 

Google Scholar 
44.Dyhrman ST, Ammerman JW, Van, Mooy BAS. Microbes and the marine phosphorus cycle. Oceanography. 2007;20:110–6.Article 

Google Scholar 
45.Larson TJ, Ehrmann M, Boos W. Periplasmic glycerophosphodiester phosphodiesterase of Escherichia coli, a new enzyme of the glp regulon. J Biol Chem. 1983;258:5428–32.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
46.van Veen HW. Phosphate transport in prokaryotes: molecules, mediators and mechanisms. Antonie Van Leeuwenhoek. 1997;72:299–315.PubMed 
Article 
PubMed Central 

Google Scholar 
47.Parthasarathy S, Parapatla H, Nandavaram A, Palmer T, Siddavattam D. Organophosphate hydrolase is a lipoprotein and interacts with Pi-specific transport system to facilitate growth of Brevundimonas diminuta using op insecticide as source of phosphate. J Biol Chem. 2016;291:7774–85.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
48.Hong T, Kong A, Lam J, Young L. Periplasmic alkaline phosphatase activity and abundance in Escherichia coli B23 and C29 during exponential and stationary phase. J Exp Microbiol Immunol. 2007;11:8–13.
Google Scholar 
49.Baltar F, Arístegui J, Gasol J, Yokokawa T, Herndl GJ. Bacterial versus archaeal origin of extracellular enzymatic activity in the Northeast Atlantic deep waters. Micro Ecol. 2013;65:277–88.CAS 
Article 

Google Scholar 
50.Thomson B, Wenley J, Currie K, Hepburn C, Herndl GJ, Baltar F. Resolving the paradox: continuous cell-free alkaline phosphatase activity despite high phosphate concentrations. Mar Chem. 2019;214:103671.CAS 
Article 

Google Scholar 
51.Lei L, Cherukuri KP, Alcolombri U, Meltzer D, Tawfik DS. The dimethylsulfoniopropionate (DMSP) lyase and lyase-like cupin family consists of bona fide DMSP lyases as well as other enzymes with unknown function. Biochemistry. 2018;57:3364–77.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
52.Ferla MP, Brewster JL, Hall KR, Evans GB, Patrick WM. Primordial‐like enzymes from bacteria with reduced genomes. Primordial-like enzymes from bacteria with reduced genomes. Mol Microbiol. 2017;105:508–24.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar  More

Study siteThis study was conducted at La Selva Biological Station, located in the lowland Atlantic forest of Costa Rica (10°26′ N, 83°59′ W). The mean annual temperature is 26 °C; mean annual precipitation is 4 m and all months have mean precipitation  > 100 mm39. La Selva has undulating topography, with elevation varying between 10 and 140 m above sea level. La Selva Biological Station includes multiple land uses; our analysis includes 103.5 hectares of forest, comprising 33.0 ha of old-growth forest and 70.5 ha of forests with past human disturbance (secondary forests, abandoned agroforestry, abandoned plantation, selectively-logged forests); here, we refer to all areas with past human disturbance as “secondary forests”. This study area does not include the full extent of old-growth or secondary forests at La Selva—we focused our drone data collection on this area because it contained the most severe apparent disturbance from the blowdown. Forests with past human disturbance have been naturally regenerating for a range of time (since 1955–1988); we excluded secondary forests with regeneration starting after 1988.Lidar dataWe use two airborne lidar datasets to quantify dynamics in canopy structure and ACD. Data were collected in 2009 and 2019 (Supplementary Table 2). Data from 2009 were collected by a fixed-wing aircraft over the entire reserve; data from 2019 were collected using the Brown Platform for Autonomous Remote Sensing40. We focused on an area 1.4 km2 in size that includes the region of most severe damage from the blowdown (Supplementary Fig. 1). Both lidar sensors were discrete-return systems. To minimize variation in lidar height estimates from variable laser beam divergence and detector characteristics, we only used data from first returns for all analyses. For the 2019 drone-based lidar with higher native point density and a wider scan angle range40, we limited our analysis to lidar returns with scan angle ± 15 degrees and randomly subsampled data to a homogenous resolution of 10 pts m−2. Previous research demonstrates that lidar data collected above densities of 1 pts m−2 have similar predictive power for determining many forest properties (including tree height, tree density, and basal area)41; both lidar datasets in this study are above this density threshold. All lidar data were projected using EPSG 32,616.For all lidar data, we calculated height above ground using a digital terrain model (DTM) created from lidar data collected in 2006 and validated using 4184 independent measurements within the old-growth forest (intercept =  − 0.406, slope = 0.999, r2 = 0.994, RMSE = 1.85 m; Supplementary Table 2)42. We verified that the horizontal geolocation accuracy with  More

Examining the serum metabolome profiles of bighorn sheep captured by the three primary techniques used to capture wild ungulates revealed significant changes in polar metabolite levels between the different animal groups, and trends that persisted throughout the analyses when directly comparing, in a pairwise fashion, specific capture techniques. Results from PLS-DA modeling and analysis of the top 15 metabolites that contribute most (VIP  > 1.2) to the separation of the three capture groups revealed that amino acid levels of tryptophan, valine, isoleucine, phenylalanine, and proline were highest in animals captured by dart, with intermediate levels in animals capture using dropnets, and lowest in animals captured using the helicopter method (Fig. 3A). One-way ANOVA analyses identified additional amino acids that displayed similar decreasing level trends from dart to dropnet to helicopter capture (dart  > drop net  > helicopter) methods, and included arginine, asparagine, aspartate, cysteine, glutamate, and glutamine, glycine, histidine, leucine, lysine, serine, and tyrosine (Fig. 4). These metabolite level changes suggest a shift in amino acid metabolism, and a potentially higher catabolism of these compounds as a function of increasingly more energetically intense and possibly more stressful capture methods such as helicopter capture.Of these amino acids, aspartate, glycine, and glutamate function as precursors for neurotransmitter synthesis, and may therefore be valuable indicators of the capture techniques’ impacts on animal health and changes to their physiological state. Glutamate is a fundamental component of nitrogen excretion in the urea cycle, and its lower serum levels in animals captured by helicopter support the idea of altered metabolite flow through the urea cycle. In addition to these patterns, decreasing levels of aspartate were observed in samples of dropnet and helicopter captured animals compared to the levels found in the dart-captured animals. The change regarding urea cycle alterations also manifested itself in differential serum urea levels, with fold changes (FC) between the groups decreasing significantly with capture techniques, with a mean FC difference of 1.4 for the dart-captured group, 0.26 for the dropnet-captured group, and − 0.3 for the helicopter-captured animals (Supplementary Table S2). As urea recycling is a prominent feature of ruminant metabolism and urea flux can rapidly change, the urea concentration changes observed between the three capture techniques support an impact on urea cycle intermediates29. While the trend of an overall decrease in urea cycle intermediates parallels a similar trend in amino acid concentrations, the extent to which amino acid metabolism is linked to changes in urea cycle activity is difficult to evaluate due to the nature of nitrogen recycling in the rumen of these ruminants.Other metabolites found in significantly higher concentrations in the serum samples of dart-captured animals compared to the two other techniques included: formate, glucose, 3-hydroxybutyrate, dimethylamine, carnitine (Fig. 3A). Propionate, which was observed to be higher in the dart and dropnet captured animals than that of helicopter captured animals (Fig. 4) is of interest, as it is the main precursor for glucose synthesis in the liver of ruminants30, and potentially reflect a higher dependence of ruminants on gluconeogenesis due to the almost complete conversion of available dietary carbohydrates to volatile fatty acids in the rumen31. As animal capture via nets increases physical activity as the animals struggle to free themselves from entanglement, generally resulting in longer times animals are under physical restraint, as well as the increased physical exertion and stress as they attempt to flee the pursuing helicopter, the observed decrease in serum propionate levels may reflect increased needs to generate glucose de novo via gluconeogenesis.This interpretation of the metabolite data is reinforced by the observation of significantly elevated levels of O-acetylcarnitine in the drop net and helicopter net gun animal capture groups compared to the darted animals (Fig. 4). As an important element of the carnitine/acyl-carnitine shuttle and import of fatty acids into the mitochondria for β-oxidation, acyl-carnitine is a major contributor to the flow of acyl groups into the TCA cycle, and a robust indicator of cardiac output and, by extension, TCA cycle activity levels in mammals32. Additional metabolites that displayed distinctly increasing trends based on capture method (dart  More

1.George, J. E., Pound, J. M. & Davey, R. B. Chemical control of ticks on cattle and the resistance of these parasites to acaricides. Parasitology 129(S1), 5353–5366 (2004).Article 
CAS 

Google Scholar 
2.Abbas, R. Z. et al. Acaricide resistance in cattle ticks and approaches to its management: The state of play. Vet. Parasitol. 203, 6–20 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
3.Yessinou, R. E. et al. Resistance of tick Rhipicephalus microplus to acaricides and control strategies. J. Ent. Zool. Stud. 4, 408–414 (2016).
Google Scholar 
4.Bradberry, S. M. et al. Poisoning due to pyrethroids. Toxicol. Rev. 24, 93–106 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
5.Klainbart, S. et al. Tremor salivation syndrome in canine following pyrethroid/permethrin intoxication. Pharm. Anal. Acta 5, 320 (2014).
Google Scholar 
6.Antwi, F. B. & Reddy, G. V. P. Toxicological effects of pyrethroids on non-target aquatic insects. Environ. Toxicol. Pharmacol. 40, 915–923 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
7.Glorennec, P. et al. Determinants of children’s exposure to pyrethroid insecticides in western France. Environ. Int. 104, 76–82 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
8.Alfeev, N. I. The utilization of Hunterellus hookeri How. for the control of the ticks, Ixodes ricinus L. and Ixodes persulcatus P. Sch. with reference to peculiarities of their metamorphosis under conditions of the Province of Lenningrad. Rev. Appl. Ent. B. 34, 108–109 (1946).
Google Scholar 
9.Hu, R., Hyland, K. E. & Oliver, J. H. A review on the use of Ixodiphagus wasps (Hymenoptera: Encyrtidae) as natural enemies for the control of ticks (Acari: Ixodidae). Syst. Appl. Acarol. 3, 19–28 (1988).
Google Scholar 
10.Mwangi, E. N. et al. The impact of Ixodiphagus hookeri, a tick parasitoid, on Amblyomma variegatum (Acari: Ixodidae) in a field trial in Kenya. Exp. Appl. Acarol. 21, 117–126 (1997).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
11.Takasu, K. & Nakamura, S. Life history of the tick parasitoid Ixodiphagus hookeri (Hymenoptera: Encyrtidae) in Kenya. Biol. Control 46, 114–121 (2008).Article 

Google Scholar 
12.Rehacek, J. & Kocianova, E. Attempt to infect Hunterellus hookeri Howard (Hymenoptera, Encyrtidae), an endoparasite of ticks, with Coxiella burnetti. Acta Virol. 36, 492 (1992).CAS 
PubMed 
PubMed Central 

Google Scholar 
13.Plantard, O. et al. Detection of Wolbachia in the tick Ixodes ricinus is due to the presence of the hymenoptera endoparasitoid Ixodiphagus hookeri. PLoS ONE 7, e30692 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
14.Bohacsova, M. et al. Arsenophonus nasoniae and Rickettsiae infection of Ixodes ricinus due to parasitic wasp Ixodiphagus hookeri. PLoS ONE 11, e0149950 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
15.Mather, T. N., Piesman, J. & Spielman, A. Absence of spirochete (Borrelia burgdorferi) and piroplasms (Babesia microti) in deer tick (Ixodes dammini) parasitized by Chalcid wasps (Hunterellus hookeri). Med. Vet. Entomol. 1, 3–8 (1987).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
16.Noda, H., Munderloh, U. & Kurtti, T. Endosymbionts of ticks relationship to Wolbachia spp. and tick-borne pathogens of humans and animals. Appl. Environ. Microbiol. 63, 3926–3932 (1997).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
17.Ahantarig, A. et al. Hard ticks and their bacterial endosymbionts (or would be pathogens). Folia Microbiol. 58, 419–428 (2013).CAS 
Article 

Google Scholar 
18.Duron, O. et al. Evolutionary changes in symbiont community structure in ticks. Mol. Ecol. 26, 2905–2921 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
19.Vila, A. et al. Endosymbionts carried by ticks feeding on dogs in Spain. Ticks Tick Borne Dis. 10, 848–852 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
20.Cooley, R. A. & Kohls, G. M. A summary of tick parasites. In Proceedings of the 5th Pacific Science Congress, Vol. 5, 3375–3381 (1934).21.Bowman, J. L., Logan, T. M. & Hair, J. A. Host suitability of Ixodiphagus texanus Howard on five species of hard ticks. J. Agric. Entomol. 3, 1–9 (1986).
Google Scholar 
22.Mather, T. N., Piesman, J. & Spielman, A. Absence of spirochete (Borrelia burgdorferi ) and piroplasms (Babesia microti) in deer tick (Ixodes dammini) parasitized by Chalcid wasps (Hunterellus hookeri). Med. Vet. Entomol. 1, 3–8 (1987).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
23.Hu, R., Hyland, K. E. & Mather, T. N. Occurrence and distribution in Rhode Island of Hunterellus hookeri (Hymenoptera: Encyrtidae), a wasp parasitoid of Ixodes dammini. J. Med. Entomol. 30, 277–280 (1993).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
24.Stafford, K. C. 3rd., Denicola, A. J. & Kilpatrick, H. J. Reduced abundance of Ixodes scapularis (Acari: Ixodidae) and the tick parasitoid Ixodiphagus hookeri (Hymenoptera: Encyrtidae) with reduction of white-tailed deer. J. Med. Entomol. 40, 642–652 (2003).PubMed 
Article 
PubMed Central 

Google Scholar 
25.Hu, R. & Hyland, K. E. Prevalence and seasonal activity of the wasp parasitoid, Ixodiphagus hookeri (Hymenoptera: Encyrtidae) in its tick host, Ixodes scapularis (Acari: Ixodidae). Syst. Appl. Acarol. 2, 95–100 (1997).
Google Scholar 
26.Lopes, A. J. O. et al. Parasitism by Ixodiphagus Wasps (Hymenoptera: Encyrtidae) in Rhipicephalus sanguineus and Amblyomma Ticks (Acari: Ixodidae) in Three Regions of Brazil. J. Econ. Entomol. 5, 1979–1981 (2012).Article 

Google Scholar 
27.Fiedler, O. G. H. A new African tick parasite, Hunterellus theilerae sp. n. Onderstepoort. J. Vet. Res. 26, 61–63 (1953).
Google Scholar 
28.Hoogstraal, H. & Kaiser, M. N. Records of Hunterellus theileri Fielder (Encyrtidae: Chalcidoidea) parasitizing Hyalomma ticks on birds migrating through Egypt. Ann. Ent. Soc. Am. 54, 616–617 (1961).Article 

Google Scholar 
29.Mwangi, E. N., Newson, R. M. & Kaaya, G. P. A hymenopteran parasitoid of the Bont tick Amblyomma variegatum Fabricius (Acarina: Ixodidae) in Kenya. Discov. Innov. 5, 331–335 (1993).
Google Scholar 
30.Shastri, U. V. Some observations on Hunterellus hookeri Howard, a parasitoid of Hyalomma-anatolicum anatolicum Koch, 1844 in Marathwada region Maharashtra State. Cheiron 13, 67–71 (1984).
Google Scholar 
31.Gaye, M. et al. Hymenopteran parasitoids of hard ticks in western Africa and the Russian Far East. Microorganisms 8, 1992 (2020).CAS 
PubMed Central 
Article 
PubMed 

Google Scholar 
32.Oliver, J. H. A wasp parasite of the possum tick, Ixodes tasmani, Australia. Pan-Pac. Entomol. 40, 227–230 (1964).
Google Scholar 
33.Doube, B. M. & Heath, A. C. G. Observations on the biology and seasonal abundance of an encyrtid wasp, a parasite of ticks in Queensland. J. Med. Entomol. 12, 433–447 (1975).CAS 
PubMed 

Google Scholar 
34.Heath, A. C. G. & Cane, R. P. A new species of Ixodiphagus (Hymenoptera: Chalcidoidea: Encyrtidae) parasitizing seabird ticks in New Zealand. N. Z. J. Zool. 37, 147–155 (2010).Article 

Google Scholar 
35.Costa Lima, A. The chalcid Hunterellus hookeri Howard, a parasite of the tick Rhipicephalus sanguineus Latreille, observed in Rio de Janeiro. Rev. Vet. Zoot. 5, 201–203 (1915).
Google Scholar 
36.Philip, C. B. Occurrence of a colony of the tick parasite Hunterellus hookeri Howard in West Africa. US Public Health Serv. Rpts. 46, 2168–2172 (1931).Article 

Google Scholar 
37.Bishopp, F. C. Record of hymenopterous parasites of ticks in the United States. Proc. Entomol. Soc. Wash. 36, 87–88 (1934).
Google Scholar 
38.Gahan, A. B. On the identities of chalcidoid tick parasites (Hymenoptera). Proc. Entomol. Soc. Wash. 36, 89–97 (1934).
Google Scholar 
39.Munaf, H. B. The first record of Hunterellus hookeri parasitizing Rhipicephalus sanguineus in Indonesia. South Asian J. Tropic. Med. Public Health 7, 492 (1976).CAS 

Google Scholar 
40.Cheong, W. H., Rajamanikam, C. & Mahadevan, S. A case of Hunterellus hookeri parasitization of ticks in Pentaling Jaya, Peninsula Malaysia. South Asian J. Tropic. Med. Publ. Health 9, 456–458 (1978).CAS 

Google Scholar 
41.Coronado, A. Ixodiphagus hookeri Howard, 1907 (Hymenoptera: Encyrtidae) in the brown dog tick Rhipicephalus sanguineus Latreille, 1806 (Acari: Ixodidae) in Venezuela. Entomotropica 21, 61–64 (2006).
Google Scholar 
42.Bezerra Santos, M. et al. Larvae of Ixodiphagus wasps (Hymenoptera: Encyrtidae) in Rhipicephalus sanguineus sensu lato ticks (Acari: Ixodidae) from Brazil. Ticks Tick Borne Dis. https://doi.org/10.1016/j.ttbdis.2017.03.004 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
43.Řehaček, J. Uzitočný cudzopasnik. Enviromagazin 3, 19 (1998).
Google Scholar 
44.Collatz, J. et al. A hidden beneficial: Biology of the tick-wasp Ixodiphagus hookeri in Germany. J. Appl. Entomol. 135, 351–358 (2011).Article 

Google Scholar 
45.Tijsse-Klasen, E. et al. Parasites of vectors—Ixodiphagus hookeri and its Wolbachia symbionts in ticks in the Netherlands. Parasit. Vectors 4, 228 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
46.Ramos, R. A. et al. Occurrence of Ixodiphagus hookeri (Hymenoptera: Encyrtidae) in Ixodes ricinus (Acari: Ixodidae) in southern Italy. Ticks Tick Borne Dis. 6, 234–236 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
47.Sormunen, J. J. et al. First evidence of Ixodiphagus hookeri (Hymenoptera: Encyrtidae) parasitization in Finnish castor bean ticks (Ixodes ricinus). Exp. Appl. Acarol. 79, 395–404 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
48.Krawczyk, A. I. et al. Tripartite interactions among Ixodiphagus hookeri, Ixodes ricinus and deer: Differential interference with transmission cycles of tick-borne pathogens. Pathogens 9, 339 (2020).PubMed Central 
Article 

Google Scholar 
49.Pervomaisky, G. S. On the infestation of Ixodes persulcatus by Hunterellus hookeri How. (Hymenoptera). Zool. Zh. 22, 211–213 (1943).
Google Scholar 
50.Alfeev, N. I. & Klimas, Y. V. Experience in cultivating ichneumon flies, Hunterellus hookeri, obtained from United States, which destroy ixodid ticks of Soviet fauna. Priroda 2, 98–101 (1938).
Google Scholar 
51.Brumpt, E. Utilisation des insectes auxiliares entomophages dans la lutte contre les insectes pathogenes. Presse Med. Paris 36, 359–361 (1913).
Google Scholar 
52.Klyushkina, E. A. A parasite of the ixodid ticks, Hunterellus hookeri How. in the Crimea. Zool. Zh. 37, 1561–1563 (1958).
Google Scholar 
53.Slovak, M. Finding of the endoparasitoid Ixodiphagus hookeri (Hymenoptera, Encyrtidae) in Haemaphysalis concinna ticks in Slovakia. Biologia 58, 890 (2003).
Google Scholar 
54.Brumpt, E. Parasitisme latent de l’Ixodiphagus caucurtei chez les larves gorgées et les nymphes á jeun de divers ixodines (Ixodes ricinus et Rhipicephalus sanguineus). Comptes Rendus de l’Académie des Sciences de Paris 191, 1085–1087 (1930).
Google Scholar 
55.Boucek, Z. & Černy, V. A parasite of ticks, the chalcid Hunterellus hookeri in Czechoslovakia. Zool. Listy 3, 109–111 (1954).
Google Scholar 
56.Heglasová, I. et al. Ticks, fleas and rodent-hosts analyzed for the presence of Borrelia miyamotoi in Slovakia: The first record of Borrelia miyamotoi in a Haemaphysalis inermis tick. Ticks Tick Borne Dis. 11, 101456 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
57.Nosek, J. The ecology, bionomics and behavior of Haemaphysalis (Haemaphysalis) concinna tick. Z. Parasitenkd. 36, 233–241 (1971).CAS 
PubMed 
PubMed Central 

Google Scholar 
58.Nosek, J. The ecology and public health importance of Dermacentor marginatus and D. reticulatus ticks in central Europe. Folia Parasitol. 19, 93–102 (1972).CAS 

Google Scholar 
59.Széll, Z. et al. Temporal distribution of Ixodes ricinus, Dermacentor reticulatus and Haemaphysalis concinna in Hungary. Vet. Parasitol. 141, 377–379 (2006).PubMed 
Article 
PubMed Central 

Google Scholar 
60.Harnok, S. & Farkas, R. Influence of biotope on the distribution and peak activity of questing ixodid ticks in Hungary. Med. Vet. Entomol. 23, 41–46 (2009).Article 

Google Scholar 
61.Bartosik, K., Wiśniowski, L. & Buczek, A. Abundance and seasonal activity of adult Dermacentor reticulatus (Acari: Amblyommidae) in eastern Poland in relation to meteorological conditions and the photoperiod. Ann. Agric. Environ. Med. 18, 340–344 (2011).PubMed 
PubMed Central 

Google Scholar 
62.Egyed, L. et al. Seasonal activity and tick-borne pathogen infection rates of Ixodes ricinus ticks in Hungary. Ticks Tick Borne Dis. 3, 90–94 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
63.Hornok, S. et al. Ixodid ticks on ruminants, with on-host initiated moulting (apolysis) of Ixodes, Haemaphysalis and Dermacentor larvae. Vet. Parasitol. 187, 350–353 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
64.Buczek, A. et al. Threat of attacks of Ixodes ricinus ticks (Ixodida: Ixodidae) and Lyme borreliosis within urban heat islands in south-western Poland. Parasit. Vectors 7, 562 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
65.Chitimia-Dobler, L. Spatial distribution of Dermacentor reticulatus in Romania. Vet. Parasitol. 214, 219–223 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
66.Pfäffle, M., Littwin, N. & Petney, T. Host preferences of immature Dermacentor reticulatus (Acari: Ixodidae) in a forest habitat in Germany. Ticks Tick Borne Dis. 6, 508–515 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
67.Collatz, J. et al. Being a parasitoid of parasites: Host finding in the tick wasp Ixodiphagus hookeri by odours from mammals. Ent. Exp. Appl. 134, 131–137 (2010).Article 

Google Scholar 
68.Takasu, K. et al. Host recognition by the tick parasitoid Ixodiphagus hookeri (Hymenoptera: Encyrtidae). Environ. Entomol. 32, 614–617 (2003).Article 

Google Scholar 
69.Demas, F. A. et al. Cattle and Amblyomma variegatum odors used in host habitat and host finding by the tick parasitoid, Ixodiphagus hookeri. J. Chem. Ecol. 26, 1079–1093 (2000).CAS 
Article 

Google Scholar 
70.Alfeev, N. I. & Klimas, Y. V. On the possibility of developing ichneumon flies, Hunterellus hookeri in climatic conditions of the USSR. Sovet. Vet. 15, 55 (1938).
Google Scholar 
71.Logan, T. M., Bowman, J. L. & Hair, J. A. Parthenogenesis and overwintering behavior in Ixodiphagus texanus Howard. J. Agric. Entomol. 2, 272–276 (1985).
Google Scholar 
72.Wood, H. P. Notes on the life history of the tick parasite Hunterellus hookeri Howard. J. Econ. Entomol. 4, 425–431 (1911).Article 

Google Scholar 
73.Cooley, R. A. & Kohls, G. M. Egg laying of Ixodiphagus caucurtei du Buysson in larval ticks. Science 67, 656 (1928).ADS 
CAS 
PubMed 
Article 

Google Scholar 
74.Hu, R. Identification of the wasp parasitoid of the deer tick, Ixodes dammini, in Rhode Island and its implication in the control of Lyme disease. M.S. thesis, University of Rhode Island, USA (1990).75.Mwangi, E. N. et al. Parasitism of Amblyomma variegatum by a hymenopteran parasitoid in the laboratory, and some aspects of its basic biology. Biol. Control 4, 101–104 (1994).Article 

Google Scholar 
76.Hu, R. & Hyland, K. E. Effects of the feeding proces of Ixodes scapularis (Acari: Ixodidae) on embryonic development of its parasitoid, Ixodiphagus hookeri (Hymenoptera: Encyrtidae). J. Med. Entomol. 35, 1050–1053 (1998).CAS 
PubMed 
Article 

Google Scholar 
77.Knipling, E. F. & Steelman, C. D. Feasibility of controlling Ixodes scapularis ticks (Acari: Ixodidae), the vector of Lyme disease, by parasitoid augmentation. J. Med. Entomol. 37, 647–652 (2000).Article 

Google Scholar 
78.Stafford, K. C. 3rd., Denicola, A. J. & Magnarelli, L. A. Presence of Ixodiphagus hookeri (Hymenoptera: Encyrtidae) in two Connecticut populations of Ixodes scapularis (Acari: Ixodidae). J. Med. Entomol. 33, 183–188 (1996).PubMed 
Article 

Google Scholar 
79.Cole, M. M. Biological control of ticks by the use of hymenopterous insects. A review. World Health Organization (WHO/EBL/43.66) 43, 1–12 (1965).
Google Scholar 
80.Hoogstraal, H., Santana, F. J. & van Peenen, P. F. D. Ticks (Ixodoidea) of Mt. Sontra, Danang, Republic of Vietnam. Ann. Ent. Soc. Am. 61, 722–729 (1968).CAS 
Article 

Google Scholar 
81.Zchori-Fein, E. et al. A newly discovered bacterium associated with parthenogenesis and a change in host selection behawior in parasitoid wasps. PNAS 98, 12555–12560 (2001).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
82.Giorgini, M. et al. Rickettsia symbionts cause parthenogenic reproduction in the parasitoid wasp Pnigalio soemius (Hymenoptera: Eulophidae). Appl. Environ. 8, 2589–2599 (2010).Article 
CAS 

Google Scholar  More