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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 林裕彬(Yu-Pin Lin) | |
dc.contributor.author | Hussnain Mukhtar | en |
dc.contributor.author | 木胡南 | zh_TW |
dc.date.accessioned | 2021-06-17T09:06:53Z | - |
dc.date.available | 2019-12-26 | |
dc.date.copyright | 2019-12-26 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-12-19 | |
dc.identifier.citation | References
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74747 | - |
dc.description.abstract | 在全球氮循環中,土壤硝化作用對溫度的反應具有重要意義,然而不同豐富度之氨氮化族群及硝化抑制劑在此過程中所扮演的角色,至今尚未有研究進行探討。本研究採實驗室規模進行,首先經由20種不同的有機或無機肥沃土壤,調查其中氨氧化古細菌(Ammonia oxidizing archaea, AOA)與氨氧化細菌(Ammonia oxidizing bacteria, AOB)之相對豐富度,對於土壤潛在硝化的溫度反應之影響,其次,從不同的土地覆蓋類型蒐集共16種土壤樣本,並藉助馬可夫鏈蒙地卡羅(Markov Chain Monte Carlo)模擬,以SQRT及MMRT模式評估兩種溫度梯度下所測量的土壤潛在硝化之溫度敏感度參數。研究結果顯示,土壤硝化作用對溫度的反應會受到氨氮化族群的相對豐富度與模式參數預估的敏感度所影響,以不同族群豐富度來說,氨氧化古細菌對氨氧化細菌比例高的土壤,亦會有較高的最適溫度,而兩者比例相近的土壤,其硝化作用的溫度差距不大,此情況表示在定溫下所測量的土壤潛在硝化作用,並無法說明氨氧化族群在之中的實際貢獻;以參數敏感度來說,其中兩個熱力參數特別顯著,為中至高之敏感度,且不論何種溫度範圍皆可在模式中單獨識別,此外,控制最小溫度的參數(Tmin)及潛在硝化曲率(〖〖ΔC〗_ 〗_P^‡)分別在SQRT及MMRT模式下僅有微小之敏感度,建議在土壤硝化作用之溫度敏感度模式選擇上應更加謹慎。
硝化抑制劑實驗根據農地或非農地土壤,其資料顯示兩者的硝化抑制劑之抑制效果皆會隨著潛在硝化而減少,且對於最低潛在硝化速率的土壤,需達到抑制效果約50%之硝化抑制劑數量明顯降低,特別是DMPP。然而,硝化抑制劑在溫度梯度下明顯使潛在硝化降低,推測其潛在硝化速率在不同溫度之差異不太可能受到硝化抑制劑之應用所影響。 本研究架構在於提升闡述土壤硝化作用在不同溫度及氨氮化族群豐富度下之準確度,而敏感度分析有助於準確解釋其代表土壤硝化溫度敏感度之既有熱力參數,並提供未來溫度敏感度研究之參考方法。 | zh_TW |
dc.description.abstract | Soil nitrification responses to temperature have significant implications for the global nitrogen cycle. However, no studies have addressed the role of different relative abundance of ammonia oxidizers and nitrification inhibitors on the temperature response of soil nitrification. Here, laboratory-scale experiments were conducted to firstly investigate the effect of the different relative abundance of ammonia-oxidizing archaea (AOA) and bacteria (AOB) on the temperature response of soil nitrification potential (NP), imposed on twenty different organic and inorganic fertilized soils. Furthermore, sixteen soil samples were collected from the different land cover types, and NP response was measured across two different temperature gradients to estimate the sensitivity of SQRT and MMRT model-based estimated parameters with the help of Markov Chain Monte Carlo simulation. Our results showed that nitrification response to temperature influences by both relative abundances of ammonia oxidizers and sensitivity of models estimated parameters. Among the different relative abundance of ammonia oxidizers, the soil with high AOA to AOB ratios showed high optimum temperature, but narrow temperature ranges for nitrification compare to the soil where AOA to AOB ratio was within the same order of magnitude. These results suggest that measuring soil NP at a fixed temperature does not represent the actual contribution of ammonia oxidizers for nitrification. Regarding parameter sensitivity, we found that two thermodynamic parameters stand out as moderately to highly sensitive, and are uniquely identifiable in each model (the parameters a and maximum temperature for SQRT, and the parameters change in enthalpy and change in entropy for MMRT model), regardless of the temperature range. However, parameters that control the minimum temperature and curvature of the NP response curve (Tmin and 〖〖ΔC〗_ 〗_P^‡) were found to have little to no sensitivity to SQRT and MMRT models output, respectively, suggesting a careful selection of complementary model while describing the temperature sensitivity of soil nitrification.
Nitrification inhibition experiment based on cropped and non-cropped soil data showed that the IE of both NIs decreased with NP, and the amount of NI required to achieve an IE of approximately 50% was significantly reduced for soils that exhibited the lowest NP rates, especially for DMPP. However, both NIs significantly reduce the NP across the temperature gradient, suggesting that the difference in temperature is less likely to influences the effectiveness of NIs. These results could help to accurately simulate the temperature response of nitrification in a variety of soils. Moreover, this study’s framework provides meaningful ranges for the model’s sensitivity in the simulation of thermodynamically explain soil nitrification kinetics, which may enhance the accurate interpretation of soil biochemical processes and to improve fertilized soil management. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T09:06:53Z (GMT). No. of bitstreams: 1 ntu-108-D04622005-1.pdf: 4757359 bytes, checksum: 990933ca11a994ab665d39606425cba7 (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | Table of contents
口試委員會審定書……………………………………………………………... I 誌謝……………………………………………………………………………... II 中文摘要……………………………………………………………………...… III Abstract ……………………………………………………………………..….. IV Acknowledgment……………………………………………...………………… VI Table of contents ……………………………………………...………………... VII List of tables ………………………………………………………………...….. X List of figures ………………………………………………………………...… XI 1. Introduction ………………………………………………………………. 1 1.1 Objectives …………………………………………………………… 3 1.2 Chapters description ………………………………………………… 3 2. Literature review ………………………………………………………… 5 2.1 Nitrification process in soil ………………………………………..... 5 2.2 Abundance and composition of ammonia oxidizers ……………...… 5 2.3 Nitrification responses to temperature ……………………………… 9 2.4 Nitrification inhibitors ………………………………………………. 11 2.5 Modeling biochemical response to temperature …………………..... 13 2.6 Uncertainty in the estimation of thermodynamic parameters ………. 14 2.7 Techniques for parameter sensitivity analysis …………………...…. 16 3. Material and methods ……………………………………………………. 17 3.1 Study area and soil sampling ………………………………………... 17 3.2 Nitrification potential measurement ………………………………… 20 3.3 DNA extraction and quantification of ammonia oxidizer populations 22 3.4 Model development …………………………………………………. 24 3.4.1 Square root growth model ………………………………...... 25 3.4.2 Macromolecular rate theory ………………………………… 25 3.5 Sensitivity and uncertainty analysis …………………………...……. 27 3.6 Nitrification inhibition experiment ………………………...……….. 28 3.7 Statistical analysis …………………………………...……………… 31 4. NP response to temperature influences by AOA to AOB ratios.............. 34 4.1 Effect of AOA to AOB ratios on nitrification potential over-temperature gradient ………………………………………………… 34 4.2 Variation in temperature sensitivity traits …………………………… 36 5. Thermodynamic Parameter Sensitivity varies among complementary models ……...…………………………………………………………….... 40 5.1 Comparisons between SQRT and MMRT models for curve fitting ... 40 5.2 Parameter estimation across different temperature ranges ………….. 41 5.3 Identification of sensitive parameters ……………………………..... 43 6. Effect of nitrification inhibitors on soil NP responses to temperature .. 51 6.1 Nitrification potential over a temperature gradient………………….. 51 6.2 Variation among NI application rates and temperature …………….. 52 7. Discussion and implications …………………………………………...… 60 7.1 Temperature response of nitrification varies among AOA to AOB ratios…………………………………………………………………. 60 7.2 Model performance analysis…………………………………………. 64 7.3 Parameter sensitivity and its significance in simulating NP responses.. 66 7.4 Effect of nitrification inhibitors on the temperature response of soil nitrification ……………………..…………………………………… 70 Conclusions and recommendations …………………………………...… 76 References ………………………………………………………………… 78 Appendix A (Tables) …………………………………………………….. 94 Appendix B (Figures)…………………………………………………….. 103 | |
dc.language.iso | en | |
dc.title | 表土內氨氧化古菌與細菌的豐富度對於不同溫度下之硝化作用的影響 | zh_TW |
dc.title | The Influences of Ammonia Oxidizing Archaeal and Bacterial Abundances on Nitrification Responses to Temperature in Topsoil | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-1 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 任秀慧(Rita Sau-Wai Yam),范致豪(Chihhao Fan),童心欣(Hsin-Hsin Tung),林彥蓉(Yann-Rong Lin) | |
dc.subject.keyword | 古細菌,菌,抑制劑,氮,有机,溫度, | zh_TW |
dc.subject.keyword | Archaea,Bacteria,Inhibitors,Nitrogen,Organic,Temperature, | en |
dc.relation.page | 103 | |
dc.identifier.doi | 10.6342/NTU201904387 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-12-20 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物環境系統工程學研究所 | zh_TW |
顯示於系所單位: | 生物環境系統工程學系 |
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