評估土壤與沈積物中氨氧化微生物及硝化抑制劑對於氧化亞氮生成與抑制之效果

Abstract

環境及人為因子會影響陸地生態系統中，土壤微生物活動所產生氧化亞氮(N2O)，進而改變土壤碳氮循環之平衡，因此針對土壤中氮循環之研究，將有助於擬定適當減緩溫室氣體（GHG）排放之策略。本研究藉由實驗和模擬方法，研析影響土壤和沉積物中之氨氧化菌生成N2O之環境驅動因子。於不同pH和溫度梯度，針對對土壤和沉積物中促進硝化作用之主要兩個關鍵微生物-氨氧化古菌（AOA）和氨氧化細菌（AOB），使用特殊硝化抑制劑PTIO和1-Octyne，以及農務操作上廣泛使用之硝化抑制劑DCD和DMPP下，量測N2O之生成。結果顯示，AOA和AOB分別在不同的生態棲位下，成為主要的潛在氨氧化菌（PAO），而土壤溫度則是生態棲位重要環境決定因子。AOA在溫度較高的環境中為主導的PAO，N2O通量高於AOB；而在酸性條件下，亦較適於AOA生存與作用，隨著pH值增加，AOA和AOB主導的N2O通量減少。此外，溫度和氧氣供應控制著N2O之生成，由AOB促進的硝化反硝化反應（NDB），對於N2O生成影響較為顯著。本研究中將溫度反應曲線利用平方根理論（SQRT）和大分子速率理論（MMRT）兩種模型進行分析。藉由似然函數、r（判定系數）和NSE（納什-薩特克利夫效率）驗證相關數值。SQRT模型之平均r值為0.95±0.06，顯示預測值與觀測值之間存在著很強的相關性。同樣，MMRT模型的平均r值為0.95±0.05，顯示在不同反應路徑和環境中，溫度敏感特性一致。由SQRT模型計算AOB促進之硝化反硝化路徑（NDB）的最適溫度（Topt）相對於AOA硝化路徑（NtA）高0.94°C，比AOB的硝化路徑（NtB）高12.4°C。而MMRT模型計算Topt值時也呈現了類似的趨勢。在氧化作用中，SQRT和MMRT模型計算之NtA的Topt值為11.5°C，比NtB的估計值高13.5°C（p < 0.05）。NtB通量的平均最高溫度（Tmax）為69.0°C，與NtA（67.1°C）相似，但明顯高於NDB（64.3°C）。另一方面，NtB通量之平均最低溫度（Tmin）低於冰點（-4.4°C），顯示NtB反應路徑於低溫下較為敏感；相反的，NtA和NDB反應路徑之Tmin值分別為8.8°C和2.3°C，顯示它們能夠在相對較低溫之條件下發揮作用。NtA的溫度範圍（Trange）（58.3°C）顯著低於NtB（68.7°C）（p < 0.05）。然而，NtB和NDB路徑之間的Trange沒有顯著差異（p > 0.05），顯示這些反應路徑之的溫度敏感性範圍相似。硝化抑制劑可以減少土壤中N2O排放，但可能改變NH3揮發和土壤中CH4通量，這對環境和經濟有重要影響。當以45kg/ha 之DCD與9 kg/ha之DMPP處理之土壤，可分別減少溫室氣體（GHG）排放34.2%和36.6%；然而，不同的DCD與DMPP處理，對氣體N損失之影響則相反，空氣中N損失增加了6.7%至36.7%，以及13.2%至45.9%。N2O的直接排放是造成全球暖化潛勢（GWP）的主因，以未施肥作為對照組，N2O佔比範圍從53.3%至68.9%，而CH4之佔比則從23.7%至39.5%。施用兩種硝化抑制劑DCD和DMPP可以抑制N2O和CH4排放，但隨著劑量增加，反而促進更多的NH3損失。因此，本研究針對硝化作用及硝化抑制劑之有效性，為建立溫室氣體排放減緩方法提供了重要之見解。透過探討環境驅動因子、微生物活動和減緩措施間之相互作用，研究結果將有助於永續農業發展與環境管理，以應對全球變暖及其相關影響所帶來的挑戰。

Understanding the effect of environmental drivers on nitrous oxide production in terrestrial ecosystems is crucial for developing appropriate mitigation strategies to reduce greenhouse gas (GHG) emissions from microbial activities in the soil. This study examines the impact of environmental drivers on N2O production in soil and sediment from ammonia oxidizers, with a particular focus on reducing greenhouse gas (GHG) emissions, by experimental and modeling approaches to find suitable management practices to reduce GHG emissions. Two key groups involved in nitrification and nitrous oxide (N2O) production, ammonia-oxidizing archaea (AOA) and bacteria (AOB), were measured using specific inhibitors, PTIO and 1-Octyne, over a wide range of pH and temperature gradients in soils and sediments, which further applied on reducing GHG using common used nitrification inhibitors, DCD and DMPP. Results showed that AOA and AOB occupied different niches for potential ammonia oxidizer (PAO), and soil temperature was a significant determinant of niche specialization. AOA-dominated PAO and N2O fluxes were predicted to have a higher optimum temperature than AOB's. AOA dominated PAO in acidic conditions, whereas AOA- and AOB-dominated N2O fluxes decreased with increasing pH. Moreover, N2O production was controlled by temperature and oxygen supply, with AOB-supported nitrifier-denitrification (NDB) contributing significantly to the suboxic N2O budget. The temperature response curves were analyzed using two models: the qquare root theory (SQRT) and the macromolecular rate theory (MMRT) model. Both models exhibited a good fit to the data, as evidenced by the likelihood functions, r (coefficient of determination), and NSE (Nash-Sutcliffe Efficiency). The average r values for the SQRT model were 0.95±0.06, indicating a strong correlation between the predicted and observed values. Similarly, the average r values for the MMRT model were 0.95±0.05, indicating a consistent and reliable estimation of the temperature sensitivity traits across different pathways and environments. The SQRT-estimated optimum temperature (Topt) for the Nitrifier-Denitrification by AOB (NDB) pathway was 0.94°C higher compared to the nitrification by AOA (NtA) pathway and 12.4°C higher compared to the nitrification by AOB (NtB) pathway. The MMRT model showed a similar trend in estimating Topt values. Among the oxic pathways, the SQRT and MMRT models estimated Topt values for NtA that were 11.5°C and 13.5°C higher (p < 0.05) than the corresponding estimates for NtB. The average maximum temperature (Tmax) for NtB fluxes was 69.0°C, similar to NtA (67.1°C), but considerably higher than NTB (64.3°C). On the other hand, the average minimum temperature (Tmin) for NtB fluxes was below the freezing point (-4.4°C), indicating the sensitivity of NtB pathway to low temperatures. In contrast, both NtA and NDB pathways exhibited higher Tmin values of 8.8°C and 2.3°C, respectively, suggesting their ability to function under relatively cooler conditions. The temperature range (Trange) for NtA (58.3°C) was significantly (p < 0.05) lower compared to NtB (68.7°C). However, there was no significant difference (p > 0.05) in Trange between NtB and NDB pathways, indicating a similar range of temperature sensitivity for these pathways. The application of nitrogen (N) had a profound impact on ammonia (NH3) volatilization, nitrous oxide (N2O), and methane (CH4) in both fallow-fertilized and cropped soils. Nitrification inhibitors can decrease N2O emissions but may alter NH3 volatilization and soil CH4 fluxes, which have important environmental and economic implications. DCD and DMPP treatments reduced greenhouse gas (GHG) emissions by up to 34.2% and 36.6%, respectively, when applied at rates of 45 and 9 kg/ha. However, an opposite trend was observed for gaseous N losses, which increased by 6.7% to 36.7% and 13.2% to 45.9%, respectively, with different DCD and DMPP treatments. Direct N2O emissions were found to be the major contributor to global warming potential (GWP), ranging from 53.3% to 68.9%, while CH4 contributed from 23.7% to 39.5%, except in the unfertilized controls. The intensive application of two nitrification inhibitors, DCD and DMPP, strongly inhibited N2O emission and CH4 emission but promoted greater NH3 losses in a dose-dependent manner. Therefore, this study emerges understanding of the role of nitrification and the effectiveness of nitrification inhibitors provides valuable insights into the development of targeted approaches for mitigating greenhouse gas emissions. By exploring the interplay between environmental drivers, microbial activities, and mitigation practices, these findings contribute to the ongoing efforts in sustainable agriculture and environmental management to address the challenges posed by global warming and its associated impacts.