知识与财富的链接
稻田轮作氮素动态循环对于保障居民食物需求,实现区域生态可持续发展等目标具有重要现实意义.从区域尺度视角分析各氮素指标空间分异状态,及其驱动影响因素,可为农田管理措施的实施提供宏观决策依据.选取晋江流域内的稻田轮作区作为研究对象,运用反硝化分解(denitrification decomposition, DNDC)模型、热点分析以及地理加权回归(geographical weighted regression, GWR)建模等技术,模拟了稻田生态系统内氮素循环,分析了各氮素指标空间分异特征与驱动归因.结果表明:①经过参数率定与结果验证的DNDC模型体现出较好的区域适应性;②不同轮作模式间对比发现,稻-蔬轮作模式表现为最大氮肥输入量、最高作物氮素吸收效率以及最大氮素损失量,其次为稻-稻轮作模式,最后为稻-空闲轮作模式;③在各氮素指标空间分布方面,除作物氮素吸收量呈随机分布,NH3排放量、N2O排放量和氮素淋失表现为空间聚类分布,基于标准差椭圆的集约主趋势线主要以"感德镇—长坑乡"一线为主;④由各氮素指标空间影响因素分析发现,土壤属性因子具有最强...
Cycling dynamics of nitrogen in paddy rotation areas have a practical significance for ensuring food supply and realizing sustainable development of the regional ecology in the Min delta urban agglomeration. However, with rapid urbanization, the negative externalities of paddy rotation areas have been gradually increased because of unreasonable utilization behavior, and the environmental costs are increasing. Therefore, the spatial differentiation of nitrogen indicators and its driving factors were analyzed, which provides a macro-decision making basis for the implementation of farmland management measures. In this study, the paddy rotation area in Jinjiang River watershed was selected as the research object. The denitrification decomposition (DNDC) model was used to simulate the nitrogen cycle in the paddy rotation area. The hot spot analysis and geographical weight regression (GWR) model were used to analyze the spatial otherness characteristics and driving attribution of various nitrogen indices. The main results showed that: ① The DNDC model was validated by parameters, and the results showed preferably regional adaptability. ② Based on the comparison of different rotation patterns, the rice-vegetable rotation pattern not only established the maximum input of nitrogen fertilizer but also revealed the highest nitrogen absorption efficiency and the maximum values of nitrogen loss, followed by the rice-rice rotation pattern and rice-fallow rotation pattern. ③ In the spatial distribution of nitrogen indicators, except for the crop nitrogen absorption, the NH3 emission, N2O emission and nitrogen leaching showed a spatial clustering distribution, and the main trend line based on the standard deviation ellipse was mainly "Gande-Changkeng" township.④ According to the analysis of spatial influence factors for various nitrogen indices, soil attribute factors had the strongest effect; the SOCmax was the strongest influential factor for both NH3 and N2O emissions, and the spatial distribution was "west high, east low". The pHmin was the strongest influential factor in nitrogen leaching, and the spatial distribution was "north and south high, east and west low".
