以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：33

、訪客IP：18.224.55.31

姓名	鄭琬萱(Wan-Hsuan Cheng)  查詢紙本館藏	畢業系所	國際研究生博士學位學程
論文名稱	探究環境變化對原核生物群落生態系統功能的影響 (Deciphering Ecosystem Functioning of Prokaryotic Community in Response to Environmental Change)
檔案	[Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 (2026-7-1以後開放)
摘要(中)	隨著人類對環境變化影響的加劇，研究環境變化如何影響生態系統功能變 得越來越重要，該領域的研究始於研究單個生態系統功能如何受到生物多樣性 降低的影響，儘管研究表明生物多樣性的降低對生態系統功能產生負面影響， 但為何不同系統功能會對生物多樣性降低有著不同反應、以及如何預測生物多 樣性降低的影響仍不清楚。此外，生態系統因其能同時執行多個生態系統功能 的能力而受到重視，而生態多系統功能也可能被除了生物多樣性之外的因素影 響，但我們對驅動生態多系統功能性的機制尤其是在隨時間尺度上如何變化的 了解有限。另外，環境變化可能以非隨機方式調節物種喪失，然，我們對非隨 機喪失對生態系統功能的影響的理解仍不清楚。因此，本論文欲通過研究臺灣 翡翠水庫的原核生物群落相關之生態系統功能來探討生態系統功能如何對環境 變化作出反應。具體而言，我發現以促進功能的物種數量和運用基質之複雜度 的兩個特異性指標有助於預測生物多樣性損失對生態系統功能的影響(第 2 章)。我展示了生物因素(多樣性)、外源因素(氣候)和內源因素(營養 鹽)分別對有機碳原利用相關之生態多系統功能性在短期動態、季節和年際尺 度上的影響最為顯著(第 3 章)。我藉由提出環境變化會驅動不同有機碳源利 用之生態位寬度及功能潛力之關係的全新的假說，揭示了功能潛力實際上可能 會增加以緩解面對惡劣養分條件的影響(第 4 章)。總結而言，本論文從不同 的方面探討了翡翠水庫原核生物群落在環境變化下的生態系統功能反應並提供 了不同層面的理解。這對於制定有效的管理策略，以維護地球生物多樣性及其 對人類的服務至關重要。
摘要(英)	Due to human impacts on Earth′s biological system, the study of how environmental change affects ecosystem functioning has become increasingly important. Research in this area began with examining how individual ecosystem functioning is affected by biodiversity loss. While research has shown that the loss of biodiversity negatively impacts ecosystem functions, the reasons for the different responses of functions to biodiversity loss and how to predict them are not yet fully understood. Moreover, the ecosystem is appreciated for its ability to perform multiple ecosystem functions simultaneously (i.e., ecosystem multifunctionality, EMF); moreover, factors other than diversity could impact ecosystem functioning. However, our current understanding of the underlying mechanisms that explain EMF, especially in terms of temporal variabilities, remains limited. In addition, environmental change could mediate the species loss in a non-random way. Yet, the understanding of the consequence of non-random loss on ecosystem functioning remains unclear. Therefore, the aim of this thesis is to comprehend how ecosystem functioning responds to environmental change, specifically through the prokaryotic community in Feitsui Reservoir, Taiwan. In particular, I demonstrated that the consequences of biodiversity loss on ecosystem functioning could be predicted by two specificity indices based on the number of species that promotes the functions and substrate complexity (Chapter 2). I identified primary factors influencing substrate-utilization based EMF at different temporal scales: biotic factor (diversity) for short-term dynamics, exogenous factor (temperature) for seasonal variations, and endogenous factor (dissolved organic carbon) for inter-annual patterns (Chapter 3). Additionally, I evaluated the potential influence of environmental change on ecosystem functioning by considering the non-random loss of species, which is influenced by their niche breadth in relation to resource utilization. By proposing a link to anticipate the relationship between niche breadth and functional potential under environmental change, I revealed that the functional potential could actually increase, thereby buffering the impact of harsh nutrient conditions (Chapter 4). In conclusion, this thesis provides a comprehensive understanding of how ecosystem functioning of prokaryotic community in Feitsui Reservoir responds to environmental change through different aspects, which is essential for developing effective management strategies to preserve the planet′s biodiversity and its services to humanity.
關鍵字(中)	★ 生物多樣性與生態系功能 ★ 冗餘 ★ 生態位寬度 ★ 生態多系統功能 ★ 時間序列 ★ 原核生物群落	關鍵字(英)	★ Biodiversity and ecosystem functioning ★ redundancy ★ niche breadth ★ ecosystem multifunctionality ★ time series ★ prokaryotic community
論文目次	摘要 i Abstract iii 誌謝 iv Table of Content vi List of Figures viii List of Tables x Chapter 1: Introduction 1 Chapter 2: New index of functional specificity to predict the redundancy of ecosystem functions in microbial communities 4 Abstract 4 Introduction 5 Materials and Methods 7 Results 13 Discussion 14 Supplementary Information 23 Chapter 3: Empirical dynamics of ecosystem multifunctionality in aquatic community 42 Abstract 42 Introduction 43 Materials and Methods 44 Results 49 Discussion 50 Supplementary Information 58 Chapter 4: Impacts of resource fluctuation and availability on niche breadth and their consequence on functional potential: a perspective from species to community levels 64 Abstract 64 Introduction 65 Materials and Methods 67 Results 74 Discussion 75 Supplementary information 85 Chapter 5: Conclusion 89 References: 92
參考文獻	References: 1. Amon, R.M.W. & Benner, R. (1994). Rapid-cycling of high-molecular-weight dissolved organic-matter in the ocean. Nature, 369, 549-552. 2. Antiqueira, P.A.P., Petchey, O.L. & Romero, G.Q. (2018). Warming and top predator loss drive ecosystem multifunctionality. Ecol. Lett., 21, 72-82. 3. Apprill, A., McNally, S., Parsons, R. & Weber, L. (2015). Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat. Microb. Ecol., 75, 129-137. 4. Becker, J., Eisenhauer, N., Scheu, S. & Jousset, A. (2012). Increasing antagonistic interactions cause bacterial communities to collapse at high diversity. Ecol. Lett., 15, 468-474. 5. Beier, S., Shen, D., Schott, T. & Jurgens, K. (2017). Metatranscriptomic data reveal the effect of different community properties on multifunctional redundancy. Mol. Ecol., 26, 6813-6826. 6. Bell, T., Newman, J.A., Silverman, B.W., Turner, S.L. & Lilley, A.K. (2005). The contribution of species richness and composition to bacterial services. Nature, 436, 1157-1160. 7. Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W. & Courchamp, F. (2012). Impacts of climate change on the future of biodiversity. Ecol. Lett., 15, 365-377. 8. Benner, R. & Amon, R.M.W. (2015). The size-reactivity continuum of major bioelements in the ocean. Ann. Rev. Mar. Sci., 7, 185-205. 9. Bernhardt, J.R., O′Connor, M.I., Sunday, J.M. & Gonzalez, A. (2020). Life in fluctuating environments. Philos. T. R. Soc. B, 375. 10. Berry, D., Mahfoudh, K.B., Wagner, M. & Loy, A. (2011). Barcoded primers used in multiplex amplicon pyrosequencing bias amplification. Appl. Environ. Microbiol., 77, 7846-7849. 11. Bertilsson, S., Eiler, A., Nordqvist, A. & Jorgensen, N.O.G. (2007). Links between bacterial production, amino-acid utilization and community composition in productive lakes. ISME J., 1, 532-544. 12. Bertz, S.H. (1981). The first general index of molecular complexity. J. Am, Chem. Soc., 103, 3599-3601. 13. Bohannan, B.J.M., Kerr, B., Jessup, C.M., Hughes, J.B. & Sandvik, G. (2002). Trade-offs and coexistence in microbial microcosms. Anton. Leeuw. Int. J. G., 81, 107-115. 14. Caffrey, J.M., Murrell, M.C., Amacker, K.S., Harper, J.W., Phipps, S. & Woodrey, M.S. (2014). Seasonal and Inter-annual Patterns in Primary Production, Respiration, and Net Ecosystem Metabolism in Three Estuaries in the Northeast Gulf of Mexico (vol 37, pg S222, 2014). Estuar. Coast., 37, 1312-1312. 15. Callahan, B.J., McMurdie, P.J., Rosen, M.J., Han, A.W., Johnson, A.J.A. & Holmes, S.P. (2016). DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods., 13, 581. 16. Careau, V., Thomas, D., Humphries, M.M. & Réale, D. (2008). Energy metabolism and animal personality. Oikos, 117, 641-653. 17. Carscadden, K.A., Emery, N.C., Arnillas, C.A., Cadotte, M.W., Afkhami, M.E., Gravel, D. et al. (2020). Niche Breadth: Causes and Consequences for Ecology, Evolution, and Conservation. Q. Rev. Biol., 95, 179-214. 18. Chang, C.W., Miki, T., Ye, H., Souissi, S., Adrian, R., Anneville, O. et al. (2022). Causal networks of phytoplankton diversity and biomass are modulated by environmental context. Nat. Commun., 13, 1140. 19. Chao, A.N., Chiu, C.H. & Jost, L. (2014). Unifying species diversity, phylogenetic diversity, functional diversity, and related similarity and differentiation measures through Hill numbers. Annu. Rev. Ecol. Evol. S., 45, 297-324. 20. Chen, J. (2018). GUniFrac: Generalized UniFrac Distances. 21. Cheng, W.H., Hsieh, C.H., Chang, C.W., Shiah, F.K. & Miki, T. (2022). New index of functional specificity to predict the redundancy of ecosystem functions in microbial communities. FEMS Microbiol Ecol., 98. 22. Cheng, W.H., Lu, H.P., Chen, C.C., Jan, S. & Hsieh, C.H. (2020). Vertical Beta-Diversity of Bacterial Communities Depending on Water Stratification. Front. Microbiol., 11. 23. Clavel, J., Julliard, R. & Devictor, V. (2011). Worldwide decline of specialist species: toward a global functional homogenization? Front. Ecol. Environ., 9, 222-228. 24. Daniel, R.M., Danson, M.J., Eisenthal, R., Lee, C.K. & Peterson, M.E. (2008). The effect of temperature on enzyme activity: new insights and their implications. Extremophiles, 12, 51-59. 25. Davidson, E.A. & Janssens, I.A. (2006). Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature, 440, 165-173. 26. Delgado-Baquerizo, M., Maestre, F.T., Reich, P.B., Jeffries, T.C., Gaitan, J.J., Encinar, D. et al. (2016). Microbial diversity drives multifunctionality in terrestrial ecosystems. Nat. Commun., 7. 27. Delgado‐Baquerizo, M., Giaramida, L., Reich, P.B., Khachane, A.N., Hamonts, K., Edwards, C. et al. (2016). Lack of functional redundancy in the relationship between microbial diversity and ecosystem functioning. J. Ecol., 104, 936-946. 28. Dell, A.I., Pawar, S. & Savage, V.M. (2011). Systematic variation in the temperature dependence of physiological and ecological traits. P. Natl. Acad. Sci. USA, 108, 10591-10596. 29. Donhauser, J., Niklaus, P.A., Rousk, J., Larose, C. & Frey, B. (2020). Temperatures beyond the community optimum promote the dominance of heat-adapted, fast growing and stress resistant bacteria in alpine soils. Soil Biology and Biochemistry, 148, 107873. 30. Egli, T. (2010). How to live at very low substrate concentration. Water Res., 44, 4826-4837. 31. Ehrlich, E., Kath, N.J. & Gaedke, U. (2020). The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton. ISME J., 14, 1451-1462. 32. Elena, S.F., Agudelo-Romero, P. & Lalić, J. (2009). The evolution of viruses in multi-host fitness landscapes. Open Virol. J., 3, 1-6. 33. Elton, C.S. (1927). Animal ecology. Sidgwick & Jackson, ltd., London,. 34. Fetzer, I., Johst, K., Schawe, R., Banitz, T., Harms, H. & Chatzinotas, A. (2015). The extent of functional redundancy changes as species′ roles shift in different environments. P. Natl. Acad. Sci. USA, 112, 14888-14893. 35. Fuhrman, J.A. & Azam, F. (1982). Thymidine Incorporation as a Measure of Heterotrophic Bacterioplankton Production in Marine Surface Waters - Evaluation and Field Results. Mar. Biol., 66, 109-120. 36. Fuhrman, J.A., Cram, J.A. & Needham, D.M. (2015). Marine microbial community dynamics and their ecological interpretation. Nat. Rev. Microbiol., 13, 133-146. 37. Futuyma, D.J. & Moreno, G. (1988). The Evolution of Ecological Specialization. Annu. Rev. Ecol. Syst., 19, 207-233. 38. Futuyma, D.J. & Philippi, T.E. (1987). Genetic Variation and Covariation in Responses to Host Plants by Alsophila Pometaria (Lepidoptera: Geometridae). Evolution, 41, 269-279. 39. Gamfeldt, L., Hillebrand, H. & Jonsson, P.R. (2008). Multiple functions increase the importance of biodiversity for overall ecosystem functioning. Ecology, 89, 1223-1231. 40. Garland, G., Banerjee, S., Edlinger, A., Oliveira, E.M., Herzog, C., Wittwer, R. et al. (2021). A closer look at the functions behind ecosystem multifunctionality: A review. J. Ecol., 109, 600-613. 41. Garland, J.L. & Mills, A.L. (1991). Classification and Characterization of Heterotrophic Microbial Communities on the Basis of Patterns of Community-Level Sole-Carbon-Source Utilization. Appl. Environ. Microbiol., 57, 2351-2359. 42. Giling, D.P., Beaumelle, L., Phillips, H.R.P., Cesarz, S., Eisenhauer, N., Ferlian, O. et al. (2019). A niche for ecosystem multifunctionality in global change research. Global Change Biol., 25, 763-774. 43. Girvan, M.S., Campbell, C.D., Killham, K., Prosser, J.I. & Glover, L.A. (2005). Bacterial diversity promotes community stability and functional resilience after perturbation. Environ. Microbiol., 7, 301-313. 44. Graeme Blair, J.C., Alexander Coppock, Macartan Humphreys and Luke Sonnet (2022). estimatr: Fast Estimators for Design-Based Inference. R package. 45. Griffiths, B., Ritz, K., Bardgett, R.D., Cook, R., Christensen, S., Ekelund, F. et al. (2000). Ecosystem response of pasture soil communities to fumigation‐induced microbial diversity reductions: an examination of the biodiversity–ecosystem function relationship. Oikos, 90, 279-294. 46. Grinnell, J. (1917). The Niche-Relationships of the California Thrasher. The Auk, 34, 427-433. 47. Grossart, H.-P., Van den Wyngaert, S., Kagami, M., Wurzbacher, C., Cunliffe, M. & Rojas-Jimenez, K. (2019). Fungi in aquatic ecosystems. Nat. Rev. Microbiol., 17, 339-354. 48. Grover, J.P. (2009). Is storage an adaptation to spatial variation in resource availability? Am. Nat., 173, E44-E61. 49. He, J.Z., Ge, Y., Xu, Z.H. & Chen, C.R. (2009). Linking soil bacterial diversity to ecosystem multifunctionality using backward-elimination boosted trees analysis. J. Soil Sediment, 9, 547-554. 50. Hector, A. & Bagchi, R. (2007). Biodiversity and ecosystem multifunctionality. Nature, 448, 188-U186. 51. Hoch, M.P. & Kirchman, D.L. (1993). Seasonal and inter-annual variability in bacterial production and biomass in a temperate estuary. Mar. Ecol. Prog. Ser., 98, 283-295. 52. Hou, J., Feng, H.B. & Wu, M.H. (2022). Incorporating Effect Factors into the Relationship between Biodiversity and Ecosystem Functioning (BEF). Diversity-Basel, 14. 53. Hsieh, T.C., Ma, K.H. & Chao, A. (2016). iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol, 7, 1451-1456. 54. Hui, D., Luo, Y. & Katul, G. (2003). Partitioning interannual variability in net ecosystem exchange between climatic variability and functional change. Tree Physiol., 23, 433-442. 55. Hutchinson, G.E. (1957). Concluding Remarks Cold Spring Harbor Symposia on Quantitative Biology, 22, 415-427. 56. Isbell, F., Calcagno, V., Hector, A., Connolly, J., Harpole, W.S., Reich, P.B. et al. (2011). High plant diversity is needed to maintain ecosystem services. Nature, 477, 199-U196. 57. Ives, A.R., Cardinale, B.J. & Snyder, W.E. (2005). A synthesis of subdisciplines: predator-prey interactions, and biodiversity and ecosystem functioning. Ecol. Lett., 8, 102-116. 58. Jessup, C.M. & Bohannan, B.J.M. (2008). The shape of an ecological trade-off varies with environment. Ecol. Lett., 11, 947-959. 59. Jiang, L. (2007). Negative selection effects suppress relationships between bacterial diversity and ecosystem functioning. Ecology, 88, 1075-1085. 60. Jiang, L., Pu, Z. & Nemergut, D.R. (2008). On the importance of the negative selection effect for the relationship between biodiversity and ecosystem functioning. Oikos, 117, 488-493. 61. Jurasinski, G., Koebsch, F., Guenther, A., Beetz, S. & Jurasinski, M.G. (2014). Package ‘flux’. Flux rate calculation from dynamic closed chamber measurement: R. 62. Ketola, T., Mikonranta, L., Zhang, J., Saarinen, K., Ormala, A.M., Friman, V.P. et al. (2013). Fluctuating Temperature Leads to Evolution of Thermal Generalism and Preadaptation to Novel Environments. Evolution, 67, 2936-2944. 63. Kirchman, D.L. (2013). Processes in microbial ecology. Oxford Scholarship Online. 64. Kitayama, K., Ushio, M. & Aiba, S.-I. (2021). Temperature is a dominant driver of distinct annual seasonality of leaf litter production of equatorial tropical rain forests. J. Ecol., 109, 727-736. 65. Koricheva, J. (2002). Meta-analysis of sources of variation in fitness costs of plant antiherbivore defenses. Ecology, 83, 176-190. 66. Krebs, C. (1998). Niche measures and resource preferences. Ecol. Methodol., 455-495. 67. Kritzberg, E.S., Langenheder, S. & Lindström, E.S. (2006). Influence of dissolved organic matter source on lake bacterioplankton structure and function – implications for seasonal dynamics of community composition. FEMS Microbiol Ecol., 56, 406-417. 68. Kutner, M.H. (2005). Applied linear statistical models. McGraw-Hill Irwin. 69. Lai, C.-C., Ko, C.-Y., Austria, E. & Shiah, F.-K. (2021). Extreme Weather Events Enhance DOC Consumption in a Subtropical Freshwater Ecosystem: A Multiple-Typhoon Analysis. Microorganisms, 9, 1199. 70. Langenheder, S., Lindstrom, E.S. & Tranvik, L.J. (2006). Structure and function of bacterial communities emerging from different sources under identical conditions. Appl. Environ. Microbiol., 72, 212-220. 71. Le Quere, C., Moriarty, R., Andrew, R.M., Canadell, J.G., Sitch, S., Korsbakken, J.I. et al. (2015). Global Carbon Budget. Earth Syst Sci Data, 7, 349-396. 72. Leflaive, J., Danger, M., Lacroix, G., Lyautey, E., Oumarou, C. & Ten-Hage, L. (2008). Nutrient effects on the genetic and functional diversity of aquatic bacterial communities. FEMS Microbiol Ecol., 66, 379-390. 73. Legendre, P. & Borcard, D. (2018). Box-Cox-chord transformations for community composition data prior to beta diversity analysis. Ecography, 41, 1820-1824. 74. Lennon, J.T., Aanderud, Z.T., Lehmkuhl, B.K. & Schoolmaster Jr., D.R. (2012). Mapping the niche space of soil microorganisms using taxonomy and traits. Ecology, 93, 1867-1879. 75. Levins, R. (1962). Theory of Fitness in a Heterogeneous Environment. I. The fitness set and adaptive function. Am. Nat., 96, 361-373. 76. Levins, R. (1965). Theory of Fitness in a Heterogeneous Environment. V. Optimal Genetic Systems. Genetics, 52, 891-904. 77. Levins, R. (1968). Evolution in changing environments; some theoretical explorations. Princeton University Press, Princeton, N.J.,. 78. Lindstrom, E.S., Feng, X.M., Graneli, W. & Kritzberg, E.S. (2010). The interplay between bacterial community composition and the environment determining function of inland water bacteria. Limnol. Oceanogr., 55, 2052-2060. 79. Lindstrom, E.S. & Ostman, O. (2011). The Importance of Dispersal for Bacterial Community Composition and Functioning. PLoS One, 6. 80. Logue, J.B., Stedmon, C.A., Kellerman, A.M., Nielsen, N.J., Andersson, A.F., Laudon, H. et al. (2016). Experimental insights into the importance of aquatic bacterial community composition to the degradation of dissolved organic matter. ISME J., 10, 533-545. 81. Loreau, M. (2000). Biodiversity and ecosystem functioning: recent theoretical advances. Oikos, 91, 3-17. 82. Loreau, M., Naeem, S., Inchausti, P., Bengtsson, J., Grime, J.P., Hector, A. et al. (2001). Ecology - Biodiversity and ecosystem functioning: Current knowledge and future challenges. Science, 294, 804-808. 83. Lu, H.P., Yeh, Y.C., Sastri, A.R., Shiah, F.K., Gong, G.C. & Hsieh, C.H. (2016). Evaluating community-environment relationships along fine to broad taxonomic resolutions reveals evolutionary forces underlying community assembly. ISME J., 10, 2867-2878. 84. Lynch, M. & Gabriel, W. (1987). Environmental Tolerance. Am. Nat., 129, 283-303. 85. Lyons, M.M. & Dobbs, F.C. (2012). Differential utilization of carbon substrates by aggregate-associated and water-associated heterotrophic bacterial communities. Hydrobiologia, 686, 181-193. 86. Ma, S.Y., Baldocchi, D.D., Mambelli, S. & Dawson, T.E. (2011). Are temporal variations of leaf traits responsible for seasonal and inter-annual variability in ecosystem CO2 exchange? Funct. Ecol., 25, 258-270. 87. Macarthur, R. & Levins, R. (1967). The Limiting Similarity, Convergence, and Divergence of Coexisting Species. Am. Nat., 101, 377-385. 88. MacArthur, R.H. (1972). Geographical ecology; patterns in the distribution of species. Harper & Row, New York,. 89. Maestre, F.T., Quero, J.L., Gotelli, N.J., Escudero, A., Ochoa, V., Delgado-Baquerizo, M. et al. (2012). Plant Species Richness and Ecosystem Multifunctionality in Global Drylands. Science, 335, 214-218. 90. Manning, P., van der Plas, F., Soliveres, S., Allan, E., Maestre, F.T., Mace, G. et al. (2018). Redefining ecosystem multifunctionality. Nat. Ecol. Evol., 2, 427-436. 91. Martiny, J.B.H., Jones, S.E., Lennon, J.T. & Martiny, A.C. (2015). Microbiomes in light of traits: A phylogenetic perspective. Science, 350. 92. Meyer, S.T., Ptacnik, R., Hillebrand, H., Bessler, H., Buchmann, N., Ebeling, A. et al. (2018). Biodiversity-multifunctionality relationships depend on identity and number of measured functions. Nat. Ecol. Evol., 2, 44-49. 93. Miki, T., Yokokawa, T., Ke, P.J., Hsieh, I.F., Hsieh, C.H., Kume, T. et al. (2018). Statistical recipe for quantifying microbial functional diversity from EcoPlate metabolic profiling. Ecol. Res., 33, 249-260. 94. Miki, T., Yokokawa, T. & Matsui, K. (2014). Biodiversity and multifunctionality in a microbial community: a novel theoretical approach to quantify functional redundancy. Proc. R. Soc. B: Biol. Sci., 281, 20132498. 95. Nielsen, U., Ayres, E., Wall, D. & Bardgett, R. (2011). Soil biodiversity and carbon cycling: a review and synthesis of studies examining diversity–function relationships. Eur. J. Soil Sci., 62, 105-116. 96. Novella, I.S., Hershey, C.L., Escarmis, C., Domingo, E. & Holland, J.J. (1999). Lack of evolutionary stasis during alternating replication of an arbovirus in insect and mammalian cells. J. Mol. Biol., 287, 459-465. 97. Osterholz, H., Niggemann, J., Giebel, H.-A., Simon, M. & Dittmar, T. (2015). Inefficient microbial production of refractory dissolved organic matter in the ocean. Nat. Commun., 6, 7422. 98. Parada, A.E., Needham, D.M. & Fuhrman, J.A. (2016). Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol., 18, 1403-1414. 99. Peña-Villalobos, I., Casanova-Maldonado, I., Lois, P., Palma, V. & Sabat, P. (2020). Costs of exploratory behavior: the energy trade-off hypothesis and the allocation model tested under caloric restriction. Sci. Rep., 10, 4156. 100. Peter, H., Beier, S., Bertilsson, S., Lindstrom, E.S., Langenheder, S. & Tranvik, L.J. (2011a). Function-specific response to depletion of microbial diversity. ISME J., 5, 351-361. 101. Peter, H., Ylla, I., Gudasz, C., Romaní, A.M., Sabater, S. & Tranvik, L.J. (2011b). Multifunctionality and diversity in bacterial biofilms. PLoS One, 6, e23225. 102. Peterson, G., Allen, C.R. & Holling, C.S. (1998). Ecological resilience, biodiversity, and scale. Ecosystems, 1, 6-18. 103. Petruzzella, A., da S. S. R. Rodrigues, T.A., van Leeuwen, C.H.A., de Assis Esteves, F., Figueiredo-Barros, M.P. & Bakker, E.S. (2020). Species identity and diversity effects on invasion resistance of tropical freshwater plant communities. Sci. Rep., 10, 5626. 104. Pires, A.P.F., Srivastava, D.S., Marino, N.A.C., MacDonald, A.A.M., Figueiredo-Barros, M.P. & Farjalla, V.F. (2018). Interactive effects of climate change and biodiversity loss on ecosystem functioning. Ecology, 99, 1203-1213. 105. Preston-Mafham J, B.L., Randerson PF. (2002). Analysis of microbial community functional diversity using sole-carbon-source utilisation profiles - a critique. FEMS Microbiol. Ecol., 1;42(1):1-14. 106. Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P. et al. (2013). The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res, 41. 107. Remold, S. (2012). Understanding specialism when the jack of all trades can be the master of all. Proc. R. Soc. B: Biol. Sci., 279, 4861-4869. 108. Richardson, A.D., Braswell, B.H., Hollinger, D.Y., Burman, P., Davidson, E.A., Evans, R.S. et al. (2006). Comparing simple respiration models for eddy flux and dynamic chamber data. Agr. Forest. Meteorol., 141, 219-234. 109. Richardson, A.D., Hollinger, D.Y., Aber, J.D., Ollinger, S.V. & Braswell, B.H. (2007). Environmental variation is directly responsible for short- but not long-term variation in forest-atmosphere carbon exchange. Global Change Biol., 13, 788-803. 110. Richmond, C.E., Breitburg, D.L. & Rose, K.A. (2005). The role of environmental generalist species in ecosystem function. Ecol. Model., 188, 279-295. 111. Rivett, D.W. & Bell, T. (2018). Abundance determines the functional role of bacterial phylotypes in complex communities. Nat. Microbiol., 3, 767. 112. Rognes, T., Flouri, T., Nichols, B., Quince, C. & Mahé, F. (2016). VSEARCH: a versatile open source tool for metagenomics. PeerJ, 4, e2584. 113. Rose, K.C., Greb, S.R., Diebel, M. & Turner, M.G. (2017). Annual precipitation regulates spatial and temporal drivers of lake water clarity. Ecol. Appl., 27, 632-643. 114. Schimel, J.P. (1995). Ecosystem consequences of microbial diversity and community structure. Springer, Berlin, Heidelberg. 115. Schramski, J.R., Dell, A.I., Grady, J.M., Sibly, R.M. & Brown, J.H. (2015). Metabolic theory predicts whole-ecosystem properties. P. Natl. Acad. Sci. USA, 112, 2617-2622. 116. Schulze, E., Mooney, HA. (1993). Biodiversity and Ecosystem Function. Berlin: Springer-Verlag. 117. Sexton, J.P., Montiel, J., Shay, J.E., Stephens, M.R. & Slatyer, R.A. (2017). Evolution of Ecological Niche Breadth. Annu. Rev. Ecol. Evol. Syst., 48, 183-206. 118. Strock, K.E., Saros, J.E., Nelson, S.J., Birkel, S.D., Kahl, J.S. & McDowell, W.H. (2016). Extreme weather years drive episodic changes in lake chemistry: implications for recovery from sulfate deposition and long-term trends in dissolved organic carbon. Biogeochemistry, 127, 353-365. 119. Tan, W., Wang, J., Bai, W., Qi, J. & Chen, W. (2020). Soil bacterial diversity correlates with precipitation and soil pH in long-term maize cropping systems. Sci. Rep., 10, 6012. 120. Tilman, D. (1999). The ecological consequences of changes in biodviersity: a search for general principles. Ecology, 80, 1455-1474. 121. Tilman, D., Downing, JA. (1994). Biodiversity and stability in grasslands. Nature 367:363–65. 122. Tilman, D., Isbell, F. & Cowles, J.M. (2014). Biodiversity and Ecosystem Functioning. Annu. Rev. Ecol. Evol. S., 45, 471-493. 123. Torsvik, V., Goksoyr, J. & Daae, F.L. (1990). High diversity in DNA of soil bacteria. Appl Environ Microbiol, 56, 782-787. 124. Tranvik, L.J. & Jorgensen, N.O.G. (1995). Colloidal and dissolved organic-matter in lake water - carbohydrate and amino-acid-composition, and ability to support bacterial-growth. Biogeochemistry, 30, 77-97. 125. Trenberth, K.E. (2011). Changes in precipitation with climate change. Clim. Res., 47, 123-138. 126. Tseng, Y.F., Hsu, T.C., Chen, Y.L., Kao, S.J., Wu, J.T., Lu, J.C. et al. (2010). Typhoon effects on DOC dynamics in a phosphate-limited reservoir. Aquat. Microb. Ecol., 60, 247-260. 127. Turner, P.E. & Elena, S.F. (2000). Cost of host radiation in an RNA virus. Genetics, 156, 1465-1470. 128. van Buuren, S. & Groothuis-Oudshoorn, K. (2011). mice: Multivariate Imputation by Chained Equations in R. J. Stat. Softw., 45, 1-67. 129. van der Plas, F. (2019). Biodiversity and ecosystem functioning in naturally assembled communities. Biol. Rev., 94, 1220-1245. 130. Villarreal-Chiu, J.F., Quinn, J.P. & McGrath, J.W. (2012). The genes and enzymes of phosphonate metabolism by bacteria, and their distribution in the marine environment. Front. Microbiol., 3. 131. Wallenstein M., A.S.D., Ernakovich J., Steinweg J.M., Sinsabaugh R. (2010). Controls on the temperature sensitivity of soil enzymes: a key driver of In situ enzyme activity rates. Springer, Berlin, Heidelberg. 132. Weaver, S.C., Brault, A.C., Kang, W.L. & Holland, J.J. (1999). Genetic and fitness changes accompanying adaptation of an arbovirus to vertebrate and invertebrate cells. J. Virol., 73, 4316-4326. 133. Weiss, M.S., Abele, U., Weckesser, J., Welte, W., Schiltz, E. & Schulz, G.E. (1991). Molecular architecture and electrostatic properties of a bacterial porin. Science, 254, 1627-1630. 134. Wilkinson, G.M., Walter, J., Fleck, R. & Pace, M.L. (2020). Beyond the trends: The need to understand multiannual dynamics in aquatic ecosystems. Limnol Oceanogr Lett, 5, 281-286. 135. Willett, C.S. (2010). Potential Fitness Trade-Offs for Thermal Tolerance in the Intertidal Copepod Tigriopus Californicus. Evolution, 64, 2521-2534. 136. Wilson, D.S. & Yoshimura, J. (1994). On the Coexistence of Specialists and Generalists. Am. Nat., 144, 692-707. 137. Wongsai, N., Wongsai, S. & Huete, A.R. (2017). Annual Seasonality Extraction Using the Cubic Spline Function and Decadal Trend in Temporal Daytime MODIS LST Data. In: Remote Sensing. 138. Xiao, N. (2018). Multi-step adaptive estimation methods for sparse regressions 3.0. 139. Xiao, N. & Xu, Q.S. (2015). Multi-step adaptive elastic-net: reducing false positives in high-dimensional variable selection. J. Stat. Comput. Sim., 85, 3755-3765. 140. Xun, W.B., Li, W., Xiong, W., Ren, Y., Liu, Y.P., Miao, Y.Z. et al. (2019). Diversity-triggered deterministic bacterial assembly constrains community functions. Nat. Commun., 10. 141. Yang, J.W., Chang, F.-H., Yeh, Y.-C., Tsai, A.-Y., Chiang, K.-P., Shiah, F.-K. et al. (2023). Trade-Offs between Competitive Ability and Resistance to Top-Down Control in Marine Microbes. Msystems, 8, e01017-01022. 142. Yang, J.W., Wu, W.X., Chung, C.C., Chiang, K.P., Gong, G.C. & Hsieh, C.H. (2018). Predator and prey biodiversity relationship and its consequences on marine ecosystem functioning-interplay between nanoflagellates and bacterioplankton. ISME J., 12, 1532-1542. 143. Zavaleta, E.S., Pasari, J.R., Hulvey, K.B. & Tilman, G.D. (2010). Sustaining multiple ecosystem functions in grassland communities requires higher biodiversity. P. Natl. Acad. Sci. USA, 107, 1443-1446. 144. Zou, H. & Hastie, T. (2005). Regularization and variable selection via the elastic net J. R. Stat. Soc. B, 67, 768-768.
指導教授	謝志豪 潘任飛(Chih-hao Hsieh Iam-Fei Pun)	審核日期	2023-6-12
推文	facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu
網路書籤	Google bookmarks   del.icio.us   hemidemi   myshare