Simulation of future dissolved oxygen distribution in pond culture based on sliding window-temporal convolutional network and trend surface analysis

Dissolved oxygen (DO) is a key ecological factor to measure the quality of water in the aquaculture. As the pond water body is affected by the breeding environment, the spatial distribution of DO shows a certain law in the entire pond. Therefore, to simulate the distribution of DO in aquaculture waters and grasp the temporal and spatial variation of DO is the key to achieving precise regulation of DO. For this purpose, this paper proposed a method for simulating the temporal and spatial distribution of DO in pond culture based on a sliding window-temporal convolutional network together with trend surface analysis (SW-TCN-TSA). This paper first utilized SW to construct DO data sets with different prediction durations, and then used the improved TCN model to realize one-dimensional time series prediction for DO at single monitoring point. Based on the prediction results of DO, a TSA method was performed on the predicted values of DO at the extreme moments of all discrete monitoring points, so as to realize the simulation of the temporal and spatial distribution of DO in the pond. Experimental results show that the SW-TCN model has better prediction performance for one-dimensional time series prediction of DO. Compared with traditional deep networks, such as CNN, GRU, LSTM, CNN-GRU and CNN-LSTM, the values of evaluation indicators (MSE, MAE and RMSE) have been greatly improved. In the process of trend surface fitting, all fitting R² of DO at different water depths are higher than 0.9, indicating that the TSA can accurately reflect the temporal and spatial distribution of DO. This method can provide a basis for the prediction and early warning of DO in the three-dimensional space of the pond and has high practicability in aquaculture.     

The research in processing fMRI data using temporal-spatial model based on CCA

In the analysis of cognition of human brain,the fMRI is often used.Corelation is a common method in fMRI data detecting,but its ability should be improved.Based on the Canonical Correlation Analysis(CCA),the temporal correlation and spatial correlation are used together to detect the activated area in the fMRI data.By the application of the method in simulation data and fMRI data,it shows that this method is effective in the detecting.     

Differential and successive effects of residue quality and soil mineral N on water-stable aggregation during crop residue decomposition

Residue quality has been shown to influence soil water-stable aggregation (WSA) during crop residue decomposition, but there is still little information about its interactive effect with soil mineral N availability. The aim of this study was to determine the effect of soil mineral N on WSA during the decomposition of two high-C/N crop residues (wheat straw with C/N = 125.6 and miscanthus straw with C/N = 311.3). The two crop residues were combined with three mineral N addition rates (0, 60, and 120 mg N kg⁻¹ dry soil). Respiration, soil mineral N content, and WSA (expressed as mean-weight diameter, MWD) were measured on several dates during a 56-d incubation. The effect of decomposing crop residues on WSA followed two phases. (i) Between 0 and 7 d, the increase in WSA was related to intrinsic residue quality with higher decomposability of the wheat straw resulting in higher WSA. (ii) Thereafter, and until the end of the experiment, mineral N addition rates had a predominant but negative influence on WSA. In this second phase, the average MWD of residue-treated soils was 0.92, 0.55, and 0.44 mm for the 0, 60 and 120 mg N kg⁻¹ dry soil addition rates, respectively. Mineral N addition which did result in higher crop residue decomposition did not lead to higher WSA. WSA during crop residue decomposition is therefore not simply positively related to the induced microbial activity, and changes in microbial community composition with differential effects on WSA must be involved. The impact of high-C/N crop residues inputs on WSA, initially assumed to be low, could actually be strong and long-lasting in situations with low soil mineral N content.     

Temporal shifts in diversity and quantity of nirS and nirK in a rice paddy field soil

Denitrification is an important part of the nitrogen cycle in the environment, and diverse bacteria, archaea, and fungi are known to have denitrifying ability. Rice paddy field soils have been known to have strong denitrifying activity, but the microbes responsible for denitrification in rice paddy field soils are not well known. Present study analyzed the diversity and quantity of the nitrite reductase genes (nirS and nirK) in a rice paddy field soil, sampled four times in one rice-growing season. Clone library analyses suggested that the denitrifier community composition varied over sampling time. Although many clones were distantly related to the known NirS or NirK, some clones were related to the NirS from Burkholderiales and Rhodocyclales bacteria, and some were related to the NirK from Rhizobiales bacteria. These denitrifiers may play an important role in denitrification in the rice paddy field soil. The quantitative PCR results showed that nirK was more abundant than nirS in all soil samples, but the nirK/nirS ratio decreased after water logging. These results suggest that both diversity and quantity changed over time in the rice paddy field soil, in response to the soil condition.     

石羊河流域冬季冻土深度变化趋势及原因

利用1961~2007年石羊河流域上游、中游、下游当地气象站的冬季最大冻土深度、气温、地温、日照时数、降水量、相对湿度、蒸发、积雪资料,分析了近47 a石羊河流域冬季最大冻土深度的空间分布以及时间变化特征,进而采用相关系数法进一步探讨了冬季最大冻土深度变化的原因。结果表明:在空间分布上,石羊河流域冬季最大冻土深度分布与本地地理位置、土壤类型和海拔高度密切相关。石羊河流域冬季最大冻土深度梯度呈南—北走向,最大值出现在南部古浪,最小值出现在北部民勤。时间变化上,近47 a,石羊河流域以及流域上、中游冬季最大冻土深度呈下降趋势,而下游民勤冬季最大冻土深度则呈上升趋势,石羊河流域冬季最大冻土深度在不同时段内存在明显的6~7 a和9~10 a的周期反映,除下游民勤外在20世纪90年代都发生了突变。相关系数法分析表明,影响石羊河流域冬季最大冻土深度的气象因子是主要是热力因子,热力因子中关联最强的是极端最低地温和气温;水分因子中蒸发和冬季最大冻土深度的关联最明显。     

区域土地集约利用程度及其时空差异研究——以安徽省11个地级市为样本

从利用强度、社会效益、经济效益和生态效益4个准则层、8个指标层构建区域土地集约利用程度评价指标体系,运用多因素综合评价法对安徽省11个地级市2010年、2012年、2014年三年的土地集约利用程度进行评价,揭示各地级市土地集约利用程度的时序变化和空间分异特征。结果表明:(1)安徽省各地级市土地集约利用程度总体较低;(2)从2010年到2014年安徽省各地级市土地集约利用程度总体提升幅度较小;(3)安徽省各地级市土地集约利用程度存在明显的区域差异。因此,要实行差别化的城市发展战略,充分考虑各地级市的土地利用现状和自身特点,遵循因地制宜原则,采取差异化措施积极提高各地级市土地利用集约度;同时,各地级市之间应加强经济等方面的合作,减少城市间的"两极分化",共同提升土地利用集约度。     

额济纳不同植被覆盖类型土壤氮素时空分异特征

量化土壤时空变化对生态系统模型、精准农业和自然资源管理有重要意义。为了更好地控制环境问题,本文把传统统计方法、地统计学方法和地理信息系统三者结合起来,研究了中国西北部额济纳旗(1480 km~2)不同植被覆盖类型土壤氮的时空变化。于2011年与2015年从49个样点采集了98个0~15 cm土壤样品,测量了土壤全氮和硝态氮的含量,比较了不同植被覆盖类型土壤全氮和硝态氮的空间变化和时间变化。结果表明:土壤全氮含量明显受植被覆盖类型影响;土壤全氮平均值变幅为0.259~0.904 g kg~(-1),胡杨林地土壤全氮含量柽柳地土壤全氮含量梭梭地土壤全氮含量;2011年与2015年同一植被覆盖类型下土壤全氮含量差异不显著;2011年胡杨林地、柽柳地、梭梭地土壤硝态氮含量分别为45.185 mg kg~(-1)、76.95mg kg~(-1)、39.335 mg kg~(-1),2015年胡杨林地、柽柳地、梭梭地土壤硝态氮含量分别为2.259 mg kg~(-1)、21.546 mg kg~(-1)、14.554 mg kg~(-1);胡杨林地和柽柳地土壤全氮呈中等强度空间相关性,梭梭地土壤全氮呈强空间相关性;植被覆盖类型明显影响着植被中氮的转移、转化和吸收;研究区土壤氮素含量呈现剧烈的时空变化。     

陆生植物对全球环境变化的适应

全球环境变化对陆地生态系统产生了深刻影响,而陆生植物对环境变化具有一定的适应机制。在生理过程中,信号物质能够对植物的生理过程进行调节,植物会主动积累或合成小分子物质以减轻逆境的伤害。在个体水平上,植物通过调节同化物在不同器官中的分配来适应环境条件的变化;植物对水氮资源的权衡利用可以使其适应不同的资源环境条件;由于对非结构碳水化合物的奢侈利用,植物生长不会受碳供应的限制。植物生理生态过程中的适应机制会影响陆地生态系统的碳收支。只有在综合分析的基础上建立整合植物适应机理的数学模型,才能准确预测环境变化对陆地生态系统的影响。     

太行山山前平原土壤有效水动态分析

利用栾城试验站1998—2002年的降水和土壤水观测资料,探讨太行山山前平原的土壤有效水量和土壤水有效性的时间变化特征。结果表明,①土壤有效水量年内变化明显,受降水影响显著;年际变化呈减少趋势,秋季变化幅度最大;作物的主要供水层下移。②作物根系层土壤水的总体有效性在全年基本为“中效”;在冬小麦生育期,深层的土壤水逐渐转为“难效”,经过雨季能基本得到缓解;自1998年至2001年土壤水分有效性等级由浅层至深层依次降低。     

中国粮食主产区参考作物蒸散量演变特征与成因分析

在全球变暖的背景下,参考作物蒸散量（reference crop evapotranspiration,ET0）的改变及其空间分布势必对中国粮食主产区农业水资源规划、农业用水管理等产生重要影响。本文将中国粮食主产区划分为温带湿润半湿润地区（I区）、温带干旱半干旱地区（II区）、暖温带半湿润地区（III区）和亚热带湿润地区（IV区）4个子区域,基于粮食主产区265个站点1961-2013年53a气象数据,采用FAO-56 Penman-Monteith公式计算各站点逐日ET0,利用ArcGIS空间插值、Mann-Kendall趋势检验、敏感性分析和贡献率分析等方法,对该区域ET0的时空分布规律及其成因进行分析。结果表明：（1）近53a来,中国粮食主产区年均ET0为878.9mm,整体呈显著下降趋势,速率为0.47mm·a^-1（P＜0.05）,I、II区和IV区年均ET0分别为741.8、1079.8和924.2mm且均有所减小,但变化趋势并不明显,III区年均ET0为940.2mm,呈极显著下降趋势,速率为1.21mm·a^-1（P＜0.01）。（2）全区及I-IV区ET0最敏感气象因子均为相对湿度,其敏感系数分别为-1.060、-1.232、-0.784、-1.114和-1.009。（3）全区及I-III区对ET0变化贡献最大的气象因子为风速,IV区为相对湿度。（4）风速的减小是造成粮食主产区全区及I-III区ET0减小的首要原因,风速减小和日照时数缩短是造成IV区ET0减小的主要原因。