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Scholar Van Den Bussche, R. A., and Hoofer, S. R. (2004). Phylogenetic relationships among recent chiropteran families and the importance of choosing appropriate out-group taxa. J. Mammal. 85: 321.2.0.CO;2" data-track-item_id="10.1644/1545-1542(2004)0852.0.CO;2" data-track-value="article reference" data-track-action="article reference" href=" aria-label="Article reference 103" data-doi="10.1644/1545-1542(2004)0852.0.CO;2">Article Google Scholar Van Den Bussche, R. A., Hoofer, S. R., and Hansen, E. W. (2002). Characterization and phylogenetic utility of the mammalian protamine P1 gene. Mol. Phylogenet. Evol. 22: 333.PubMed CAS Google Scholar Van Den Bussche, R. A., Reeder, S. A., Hansen, E. W., and Hoofer, S. R. (2003). Utility of the dentin matrix protein 1 (DMP1) gene for resolving mammalian intraordinal relationships. Mol. Phylogenet. Evol. 26: 89.PubMed CAS Google Scholar Wible, J. R., and Novacek, J. M. (1988). Cranial evidence for the monophyletic origin of bats. Am. Mus. Novit. 2911: 1. Google Scholar Yang, J. (1977). On some Salientia and Chiroptera from Shanwang, Linqu Shandong. Vert. PalAs. 15: 76 (in Chinese).Download references About EVOL Album. EVOL is a English album released on . This album is composed by Adnan Aziz. EVOL Album has 1 song sung by Mischief. Listen to EVOL song in high quality download EVOL song on Gaana.com. Related Tags - EVOL, EVOL Songs, EVOL Songs Download, Download EVOL Songs, Listen EVOL Songs, EVOL MP3 Songs And bloom samples from Jiaozhou Bay. China Harmful Algae 96:101821. CAS Google Scholar Zhang T, Fan X, Gao F et al (2019) Further analyses on the phylogeny of the subclass Scuticociliatia (Protozoa, Ciliophora) based on both nuclear and mitochondrial data. Mol Phylogenet Evol 139:106565. CAS Google Scholar Zhao Y, Yi Z, Gentekaki E et al (2016) Utility of combining morphological characters, nuclear and mitochondrial genes: An attempt to resolve the conflicts of species identification for ciliated protists. Mol Phylogenet Evol 94:718–729. Google Scholar Stern RF, Andersen RA, Jameson I et al (2012) Evaluating the ribosomal internal transcribed spacer (ITS) as a candidate dinoflagellate barcode marker. PLoS ONE 7:e42780. CAS Google Scholar Choi J, Park JS (2020) Comparative analyses of the V4 and V9 regions of 18S rDNA for the extant eukaryotic community using the Illumina platform. Sci Rep 10:6519. CAS Google Scholar Mordret S, Piredda R, Vaulot D et al (2018) dinoref: a curated dinoflagellate (Dinophyceae) reference database for the 18S rRNA gene. Mol Ecol Resour 18:974–987. CAS Google Scholar Zimmermann J, Jahn R, Gemeinholzer B (2011) Barcoding diatoms: evaluation of the V4 subregion on the 18S rRNA gene, including new primers and protocols. Org Divers Evol 11:173. Google Scholar Forster D, Filker S, Kochems R et al (2019) A comparison of different ciliate metabarcode genes as bioindicators for environmental impact assessments of salmon aquaculture. J Eukaryot Microbiol 66:294–308. CAS Google Scholar Hamsher SE, Evans KM, Mann DG et al (2011) Barcoding diatoms: exploring alternatives to COI-5P. Protist 162:405–422. CAS

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Scholar Van Den Bussche, R. A., and Hoofer, S. R. (2004). Phylogenetic relationships among recent chiropteran families and the importance of choosing appropriate out-group taxa. J. Mammal. 85: 321.2.0.CO;2" data-track-item_id="10.1644/1545-1542(2004)0852.0.CO;2" data-track-value="article reference" data-track-action="article reference" href=" aria-label="Article reference 103" data-doi="10.1644/1545-1542(2004)0852.0.CO;2">Article Google Scholar Van Den Bussche, R. A., Hoofer, S. R., and Hansen, E. W. (2002). Characterization and phylogenetic utility of the mammalian protamine P1 gene. Mol. Phylogenet. Evol. 22: 333.PubMed CAS Google Scholar Van Den Bussche, R. A., Reeder, S. A., Hansen, E. W., and Hoofer, S. R. (2003). Utility of the dentin matrix protein 1 (DMP1) gene for resolving mammalian intraordinal relationships. Mol. Phylogenet. Evol. 26: 89.PubMed CAS Google Scholar Wible, J. R., and Novacek, J. M. (1988). Cranial evidence for the monophyletic origin of bats. Am. Mus. Novit. 2911: 1. Google Scholar Yang, J. (1977). On some Salientia and Chiroptera from Shanwang, Linqu Shandong. Vert. PalAs. 15: 76 (in Chinese).Download references

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And bloom samples from Jiaozhou Bay. China Harmful Algae 96:101821. CAS Google Scholar Zhang T, Fan X, Gao F et al (2019) Further analyses on the phylogeny of the subclass Scuticociliatia (Protozoa, Ciliophora) based on both nuclear and mitochondrial data. Mol Phylogenet Evol 139:106565. CAS Google Scholar Zhao Y, Yi Z, Gentekaki E et al (2016) Utility of combining morphological characters, nuclear and mitochondrial genes: An attempt to resolve the conflicts of species identification for ciliated protists. Mol Phylogenet Evol 94:718–729. Google Scholar Stern RF, Andersen RA, Jameson I et al (2012) Evaluating the ribosomal internal transcribed spacer (ITS) as a candidate dinoflagellate barcode marker. PLoS ONE 7:e42780. CAS Google Scholar Choi J, Park JS (2020) Comparative analyses of the V4 and V9 regions of 18S rDNA for the extant eukaryotic community using the Illumina platform. Sci Rep 10:6519. CAS Google Scholar Mordret S, Piredda R, Vaulot D et al (2018) dinoref: a curated dinoflagellate (Dinophyceae) reference database for the 18S rRNA gene. Mol Ecol Resour 18:974–987. CAS Google Scholar Zimmermann J, Jahn R, Gemeinholzer B (2011) Barcoding diatoms: evaluation of the V4 subregion on the 18S rRNA gene, including new primers and protocols. Org Divers Evol 11:173. Google Scholar Forster D, Filker S, Kochems R et al (2019) A comparison of different ciliate metabarcode genes as bioindicators for environmental impact assessments of salmon aquaculture. J Eukaryot Microbiol 66:294–308. CAS Google Scholar Hamsher SE, Evans KM, Mann DG et al (2011) Barcoding diatoms: exploring alternatives to COI-5P. Protist 162:405–422. CAS

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Bioclimatic modelling. Glob. Ecol. Biogeogr. 2018, 27, 277–284. [Google Scholar] [CrossRef]Tozer, B.; Sandwell, D.T.; Smith, W.H.F.; Olson, C.; Beale, J.R.; Wessel, P. Global Bathymetry and Topography at 15 Arc Sec: SRTM15+. Earth Space Sci. 2019, 6, 1847–1864. [Google Scholar] [CrossRef]Davies, A.J.; Guinotte, J.M. Global Habitat Suitability for Framework-Forming Cold-Water Corals. PLoS ONE 2011, 6, e18483. [Google Scholar] [CrossRef] [PubMed]Steinacher, M.; Joos, F.; Frölicher, T.L.; Plattner, G.K.; Doney, S.C. Imminent ocean acidification in the Arctic projected with the NCAR global coupled carbon cycle-climate model. Biogeosciences 2009, 6, 515–533. [Google Scholar] [CrossRef]Cutler, D.R.; Jr, E.T.; Beard, K.H.; Cutler, A.; Hess, K.T.; Gibson, J.; Lawler, J.J. Random forests for classification in ecology. Ecol. A Publ. Ecol. Soc. Am. 2007, 88, 2783–2792. [Google Scholar] [CrossRef] [PubMed]Elith, J.; Leathwick, J.R. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annu. Rev. Ecol. Evol. Syst. 2009, 40, 677–697. [Google Scholar] [CrossRef]Vignali, S.; Barras, A.G.; Arlettaz, R.; Braunisch, V. SDMtune: An R package to tune and evaluate species distribution models. Ecol. Evol. 2020, 10, 11488–11506. [Google Scholar] [CrossRef]Dullo, W.C.; Flögel, S.; Rüggeberg, A. Cold-water coral growth in relation to the hydrography of the Celtic and Nordic European continental margin. Mar. Ecol. Prog. 2008, 371, 165–176. [Google Scholar] [CrossRef]Xia, Y.; Liu, C.; Li, Y.; Liu, N. A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring. Expert Syst. Appl. 2017, 78, 225–241. [Google Scholar] [CrossRef]Allouche, O.; Tsoar, A.; Kadmon, R. Assessing the accuracy of species distribution models: Prevalence, kappa and the true skill statistic

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(TSS). J. Appl. Ecol. 2006, 43, 1223–1232. [Google Scholar] [CrossRef]Thuiller, W.; Lafourcade, B.; Engler, R.; Araújo, M.B. BIOMOD—A platform for ensemble forecasting of species distributions. Ecography 2009, 32, 369–373. [Google Scholar] [CrossRef]Breiner, F.T.; Nobis, M.P.; Bergamini, A.; Guisan, A. Optimizing ensembles of small models for predicting the distribution of species with few occurrences. Methods Ecol. Evol. 2018, 9, 802–808. [Google Scholar] [CrossRef]Ingram, M.; Vukcevic, D.; Golding, N. Multi-output Gaussian processes for species distribution modelling. Methods Ecol. Evol. 2020, 11, 1587–1598. [Google Scholar] [CrossRef]Marchetto, E.; Da Re, D.; Tordoni, E.; Bazzichetto, M.; Zannini, P.; Celebrin, S.; Chieffallo, L.; Malavasi, M.; Rocchini, D. Testing the effect of sample prevalence and sampling methods on probability-and favourability-based SDMs. Ecol. Model. 2023, 477, 110248. [Google Scholar] [CrossRef]Marmion, M.; Luoto, M.; Heikkinen, R.K.; Thuiller, W. The performance of state-of-the-art modelling techniques depends on geographical distribution of species. Ecol. Model. 2009, 220, 3512–3520. [Google Scholar] [CrossRef]Godsoe, W.; Harmon, L.J. How do species interactions affect species distribution models? Ecography 2012, 35, 811–820. [Google Scholar] [CrossRef]Kinlan, B.P.; Poti, M.; Drohan, A.F.; Packer, D.B.; Dorfman, D.S.; Nizinski, M.S. Predictive modeling of suitable habitat for deep-sea corals offshore the Northeast United States. Deep Sea Res. Part I Oceanogr. Res. Pap. 2020, 158, 103229. [Google Scholar] [CrossRef]Doherty, B.; Cox, S.P.; Rooper, C.N.; Johnson, S.D.; Kronlund, A.R. Species distribution models for deep-water coral habitats that account for spatial uncertainty in trap-camera fishery data. Mar. Ecol. Prog. Ser. 2021, 660, 69–93. [Google Scholar] [CrossRef]Chu, J.W.; Nephin, J.; Georgian, S.; Knudby, A.; Rooper, C.; Gale,

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M.; Hocine, H.; Benammar, L.; Ayachi, A.; Bachir, A.S.; Monteoliva-Sánchez, M.; Dekak, A. Diversity and bioprospecting of extremely halophilic archaea isolated from Algerian arid and semi-arid wetland ecosystems for halophilic-active hydrolytic enzymes. Microbiol. Res. 2018, 207, 289–298. [Google Scholar] [CrossRef]Benhadj, M.; Gacemi-Kirane, D.; Toussaint, M.; Hotel, L.; Bontemps, C.; Duval, R.E.; Leblond, P.; Aigle, B. Diversity and antimicrobial activities of Streptomyces isolates from Fetzara Lake, north eastern Algeria. Ann. Biol. Clin. 2018, 76, 81–95. [Google Scholar] [CrossRef]Shirling, E.T.; Gottlieb, D. Methods for characterization of Streptomyces species. Int. J. Syst. Evol. 1966, 16, 313–340. [Google Scholar] [CrossRef]Gordon, R.E.; Barnett, D.A.; Handerhan, J.E.; Pang, C.H.N. Nocardia coeliaca, Nocardia autotrophica, and the nocardin strain. Int. J. Syst. Evol. Microbiol. 1974, 24, 54–63. [Google Scholar] [CrossRef]Cassagne, C.; Normand, A.C.; Bonzon, L.; L’Ollivier, C.; Gautier, M.; Jeddi, F.; Ranque, S.; Piarroux, R. Routine identification and mixed species detection in 6,192 clinical yeast isolates. Med. Mycol. 2016, 54, 256–265. [Google Scholar] [CrossRef]Kieser, T.B.M.J.; Bibb, M.J.; Buttner, M.J.; Chater, K.F.; Hopwood, D.A. Practical Streptomyces Genetics. A Laboratory Manual; The John Innes Foundation: Norwich, UK, 2000. [Google Scholar]Weisburg, W.G.; Barns, S.M.; Pelletier, D.A.; Lane, D.J. 16S ribosomal DNA amplification for phylogenetic study. J. Bacteriol. 1991, 173, 697–703. [Google Scholar] [CrossRef] [PubMed]Yoon, S.H.; Ha, S.M.; Lim, J.; Kwon, S.; Chun, J. A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek 2017, 110, 1281–1286. [Google Scholar] [CrossRef] [PubMed]Larkin, M.A.; Blackshields, G.; Brown, N.P.; Chenna, R.; McGettigan, P.A.; McWilliam, H.; Valentin, F.; Wallace, I.M.; Wilm, A.; Lopez,

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Feio MJ, Filipe AF, Garcia-Raventós A et al (2020) Advances in the use of molecular tools in ecological and biodiversity assessment of aquatic ecosystems. Avanços no uso de ferramentas moleculares na avaliação ecológica e biodiversidade dos ecossistemas aquáticos. Limnetica. Google Scholar Schweiger AK, Cavender-Bares J, Townsend PA et al (2018) Plant spectral diversity integrates functional and phylogenetic components of biodiversity and predicts ecosystem function. Nat Ecol Evol 2:976–982. Google Scholar Rico-Sánchez AE, Sundermann A, López-López E et al (2020) Biological diversity in protected areas: not yet known but already threatened. Glob Ecol Conserv 22:e01006. Google Scholar Chantangsi C, Lynn DH, Brandl MT et al (2007) Barcoding ciliates: a comprehensive study of 75 isolates of the genus Tetrahymena. Int J Syst Evol Microbiol 57:2412–2423. CAS Google Scholar Park M-H, Jung J-H, Jo E et al (2019) Utility of mitochondrial CO1 sequences for species discrimination of Spirotrichea ciliates (Protozoa, Ciliophora). Mitochondrial DNA Part A 30:148–155. CAS Google Scholar Xu J (2017) Fungal DNA barcoding. In: The 6th international barcode of life conference 01:913–932. T, Sandionigi A, Viard F, Casiraghi M (2015) DNA (meta)barcoding of biological invasions: a powerful tool to elucidate invasion processes and help managing aliens. Biol Invasions 17:905–922. Google Scholar Hebert PDN, Cywinska A, Ball SL, deWaard JR (2003) Biological identifications through DNA barcodes. Proc R Soc Lond B 270:313–321. CAS Google Scholar Yao H, Song J, Liu C et al (2010) Use of ITS2 region as the universal DNA barcode for plants and animals. PLoS ONE 5:e13102. CAS Google

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