基于贝叶斯模型平均法构建杉木林分蓄积量生长模型

目的 探究杉木林分蓄积量变化的影响因素,为在气候变化背景下科学经营管理杉木人工林提供理论支撑。 方法 以福建邵武卫闽林场的杉木（Cunninghamia lanceolata）人工密度试验林为研究对象,分别利用贝叶斯模型平均法（BMA）和逐步回归法（SR）构建杉木林分蓄积量与林分变量因子（包括初植密度、每公顷胸高断面积、每公顷株数、平方平均胸径、林分优势高、年龄）和气候因子（包括年均气温、最热月平均温度、最冷月平均温度、年均降水量、年均湿热指数、低于0℃天数、夏季平均最高温度、冬季平均最低温度、春季平均气温）的关系模型。 结果 杉木林分蓄积量随着每公顷胸高断面积、平方平均胸径、林分优势高、年龄、夏季平均最高温、春季平均温和低于0℃天数的增加而增加,对于诸多的影响因子,SR法所确定的模型并不在BMA选出的后验概率较高的前5个模型中,模型表现出一定的不确定性,从模型后验概率角度看,SR模型精度较低。 结论 杉木林分蓄积量受到林分变量因子和气候因子的显著影响。相比于SR法,在构建杉木林分蓄积量模型方面,BMA方法考虑了模型的不确定性,模型表现更好。     

Enhancing pedotransfer functions with environmental data for estimating bulk density and effective cation exchange capacity in a data‐sparse situation

Soil bulk density (BD) and effective cation exchange capacity (ECEC) are among the most important soil properties required for crop growth and environmental management. This study aimed to explore the combination of soil and environmental data in developing pedotransfer functions (PTFs) for BD and ECEC. Multiple linear regression (MLR) and random forest model (RFM) were employed in developing PTFs using three different data sets: soil data (PTF‐1), environmental data (PTF‐2) and the combination of soil and environmental data (PTF‐3). In developing the PTFs, three depth increments were also considered: all depth, topsoil (<0.40 m) and subsoil (>0.40 m). Results showed that PTF‐3 (R²; 0.29–0.69) outperformed both PTF‐1 (R²; 0.11–0.18) and PTF‐2 (R²; 0.22–0.59) in BD estimation. However, for ECEC estimation, PTF‐3 (R²; 0.61–0.86) performed comparably as PTF‐1 (R²; 0.58–0.76) with both PTFs out‐performing PTF‐2 (R²; 0.30–0.71). Also, grouping of data into different soil depth increments improves the estimation of BD with PTFs (especially PTF‐2 and PTF‐3) performing better at subsoils than topsoils. Generally, the most important predictors of BD are sand, silt, elevation, rainfall, temperature for estimation at topsoil while EVI, elevation, temperature and clay are the most important BD predictors in the subsoil. Also, clay, sand, pH, rainfall and SOC are the most important predictors of ECEC in the topsoil while pH, sand, clay, temperature and rainfall are the most important predictors of ECEC in the subsoil. Findings are important for overcoming the challenges of building national soil databases for large‐scale modelling in most data‐sparse countries, especially in the sub‐Saharan Africa (SSA).     

"早稻-冬草莓"轮作模式最佳种植期研究

[目的]研究"早稻-冬草莓"轮作模式最佳种植期.[方法]根据双流县气象局1971 ～ 2010年气象资料,采用滑移气候相似距及数理统计方法,对"早稻-冬草莓"轮作模式最佳种植期进行分析.[结果]冬草莓最佳种植期在8月1日～翌年3月31日,其小苗移栽最早在7月中旬,最晚在8月中旬,最佳移栽时期平均在8月19日.早稻移栽时间平均为3月26日,拟收获期平均为7月26日.[结论]从气象角度研究了"早稻-冬草莓"轮作模式最佳种植期,为双流县推广该模式,最大限度地发挥光、温、水、土地的生态效益提供了科学的决策依据.     

Potato absorption and phytoavailability of Cd,Ni, Cu,Zn and Pb in sierozem soils amended with municipal sludge compost

Effects of sludge utilization on the mobility and phytoavailability of heavy metals in soil-plant systems have attracted broad attention in recent years. In this study, we analyzed the effects of municipal sludge compost(MSC) on the solubility and plant uptake of Cd, Ni, Cu, Zn and Pb in a soil-potato system to explore the mobility, potato plant uptake and enrichment of these five heavy metals in sierozem soils amended with MSC through a potato cultivation trial in Lanzhou University of China in 2014. Ridge regression analysis was conducted to investigate the phytoavailability of heavy metals in amended soils. Furthermore, CaCl_2, CH_3 COONH_4, CH_3COOH, diethylene triamine pentacetic acid(DTPA) and ethylene diamine tetraacetic acid(EDTA) were used to extract the labile fraction of heavy metals from the amended soils. The results show that the MSC could not only improve the fertility but also increase the dissolved organic carbon(DOC) content of sierozem soils. The total concentrations and labile fraction proportions of heavy metals increase with increasing MSC percentage in sierozem soils. In amended soils, Cd has the highest solubility and mobility while Ni has the lowest solubility and mobility among the five heavy metals. The MSC increases the concentrations of heavy metals in the root, stem, peel and tuber of the potato plant, with the concentrations being much higher in the stem and root than in the peel and tuber. Among the five heavy metals, the bioconcentration factor value of Cd is the highest, while that of Ni is the lowest. The complexing agent(DTPA and EDTA) extractable fractions of heavy metals are the highest in terms of phytoavailability. Soil properties(including organic matter, p H and DOC) have important impacts on the phytoavailability of heavy metals. Our results suggest that in soil-potato systems, although the MSC may improve soil fertility, it can also increase the risk of soils exposed to heavy metals.     

大白菜花青素含量及色差指标相关性研究

为了探寻大白菜花青素含量快速测定的方法,本文利用pH差计法和色差仪分别测定了‘城阳青’(普通大白菜)、‘秋宝黄’(黄心白菜)和‘彩凤’3个不同叶色大白菜品种花青素含量以及色差指标,并对6个色泽参数与花青素含量进行了相关和回归分析。结果表明:6个色泽参数均能反映白菜叶片间叶色的细微变化,‘城阳青’和‘秋宝黄’不含花青素,紫色白菜‘彩凤’的花青素主要分布于由外向内的第1～4层叶片。色泽参数L,b,h和C分别与花青素含量呈极显著或显著负相关关系(相关系数分别为-0.85**,-0.58**,-0.49*,-0.58**)。以色泽参数值L、a、h与花青素含量建立了多元回归方程:y=90.24-1.07x1+5.65x2-142.71x3(x1为L值,x2为a值,x3为h值,y为花青素含量),该回归方程相关系数为0.9629。通过色差计依据建立的回归方程可快速测定紫色大白菜花青素的含量。     

基于广告、技术、奖励的二级供应链效益最大化研究

基于技术进步视角，构建服务业FDI影响产业安全的理论模型，并采用1996-2013年的时序数据和分位数回归方法进行检验。实证结果表明，服务业FDI对技术进步的总效应为正；分位数回归进一步揭示，服务业FDI对技术进步的直接效应为正、间接效应为负，并在技术进步的低中分位点上，服务业FDI的直接效应大于间接效应，而在技术进步的高分位点上，服务业FDI的直接效应小于间接效应。研究证实，在技术进步的初期，服务业FDI会对产业安全发展产生直接的正向推动作用，但随着时间的推移，服务业FDI会威胁其产业安全。     

Predicting the degree of phosphorus saturation using the ammonium acetate–EDTA soil test

As a result of the important role played by phosphorus (P) in surface water eutrophication, the susceptibility of soils to release P requires evaluation. The degree of phosphorus saturation, assessed by oxalate extraction (DPS_ox), has been used as an indicator. However, most laboratories do not include DPS_ox in routine soil tests because of cost and time. This study evaluates the suitability of the ammonium acetate extraction in the presence of EDTA (AAEDTA), the standard soil test P (STP) in Wallonia (Southern Belgium), to predict DPS_ox; we also compared it with the Mehlich 3 extraction. Ninety‐three topsoil samples were collected in agricultural soils throughout Wallonia. Good correlations were found between the AAEDTA and the Mehlich 3 methods for P, Fe and Al (r = 0.85, 0.77 and 0.86, respectively). An exponential relationship was found between P_AAEDTA and DPS_ox. Results of principal component analysis and regression demonstrated that STP can be used to predict DPS_ox (r = 0.93) after logarithmic transformation. Soil test Al was also a good indicator of the P sorption capacity (PSC_ox) of soils (r = 0.86). Including the clay fraction in regression equations only slightly improved the prediction of PSC_ox (r = 0.90), while other readily available data (such as pH or organic carbon) did not significantly improve either DPS_ox or PSC_ox predictions.     

Relationship between corn yield and chemical composition of the ear leaf measured with different regression models

Abstract

Corn yields and leaf samples were obtained from experimental plots receiving varying rates of N, P and K. Yields were regressed on leaf levels of N, P, K, Ca, Mg, B, Cu, Fe, Mn and Zn as independent variables. Various polynomial regressions were fitted to the yields and “goodness of fit”; of particular mathematical models was used as a basis for evaluating particular biological and statistical concepts.

It was found that no regression, where chemical elements were used as ratios, fit the observations as well as a quadratic polynomial or its square root transformation. This suggests that within the set of data used, emphasis on particular cation or anion ratios does not necessarily result in the “best”; explanation of variation in yield.

“Classical”; growth equations were fitted to corn yields, but were not as precise in predicting yields as the polynomials. A modified stagewise regression procedure was used for fitting one mathematical model, but results were less satisfactory than those obtained with usual least squares procedures.     

基于社会燃烧理论的耕地非农化驱动因素分析

中国耕地非农化现象日益明显。基于社会燃烧理论分析了耕地非农化的驱动原理,建立了耕地非农化影响机制模型,并运用SPSS 19.0软件对分类驱动因素进行了主成分及回归分析。结果表明,人均GDP和固定资产投资所占GDP比重等经济发展变量对耕地非农化水平的正向影响最大;粮食单产、总产等农业技术变量对耕地非农化水平具有最大的逆向影响。最后在模型拟合的基础上提出了相应的对策与建议,旨在为合理有效保护耕地提供参考。     

Influence of Soil Particle Size on the Measurement of Sodium by Near-Infrared Reflectance Spectroscopy

This study evaluates the effect of soil particle size (SPS) on the measurement of exchangeable sodium (Na) (EXC-Na) by near-infrared reflectance (NIR) spectroscopy. Three hundred thirty-two (n = 332) top soil samples (0–10 cm) were taken from different locations across Uruguay, analyzed by EXC-Na using emission spectrometry, and scanned in reflectance using a NIR spectrophotometer (1100–2500 nm). Partial least squares (PLS) and principal component regression (PCR) models between reference chemical data and NIR data were developed using cross validation (leaving one out). The coefficient of determination in calibration (R²) and the root mean square of the standard error of cross validation (RMSECV) for EXC-Na concentration were 0.44 (RMSECV: 0.12 mg kg^–1) for soil with small particle size (SPS-0.053) and 0.77 (RMSECV: 0.09 mg kg^–1) for soils with particle sizes greater than 0.212 mm (SPS-0.212), using the NIR region after second derivative as mathematical transformation. The R² and RMSECV for EXC-Na concentration using PCR were 0.54 (RMSECV: 0.07 mg kg^–1) and 0.80 (RMSECV: 0.03 mg kg^–1) for SPS-0.053 and SPS-0.212 samples, respectively.