Turbidity‐induced changes in emergent effects of multiple predators with different foraging strategies

Abstract – In natural systems, prey frequently interact with multiple predators and the outcome often cannot be predicted by summing the effects of individual predator species. Multiple predator interactions can create emergent effects for prey, but how those change across environmental gradients is poorly understood. Turbidity is an environmental factor in aquatic systems that may influence multiple predator effects on prey. Interactions between a cruising predator (largemouth bass Micropterus salmoides) and an ambush predator (muskellunge Esox masquinongy) and their combination foraging on a shared prey (bluegill Lepomis macrochirus) were examined across a turbidity gradient. Turbidity modified multiple predator effects on prey. In clear water, combined predators consumed in total more prey than expected from individual predator treatments, suggesting risk enhancement for prey. In moderately turbid water, the predators consumed fewer prey together than expected, suggesting a risk reduction for prey. At high turbidity, there were no apparent emergent effects; however, the cruising predator consumed more prey than the ambush predator, suggesting an advantage for this predator. Understanding multiple predator traits across a gradient of turbidity increases our understanding of how complex natural systems function.     

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.     

北方农牧交错带土地利用结构的线性规划——以定西县为例

探讨了用线性规划方法优化土地利用结构,并以北方农牧交错带定西县土地利用结构的经济效益作为目标函数,以人口和自然条件作为约束条件,进行优化分析,规划结果为定西县土地利用结构由2005年的农、林、草面积比例54:10:36调整为30:13:57.     

我国松毛虫发生率的空间分布格局及其驱动因子

了解我国松毛虫发生的空间分布格局及其驱动因子, 对松毛虫暴发的预防?控制和治理具有重要意义?本研究基于我国各行政区2004年-2012年间每年松毛虫发生面积及其寄主植物面积, 使用一般线性模型分析气候因子是否以及如何驱动我国松毛虫发生的空间分布格局?结果表明:在全国尺度上, 最暖季降水量是松毛虫发生的主要气候驱动因子, 松毛虫平均发生率与最暖季降水量显著正相关?在最暖季降水量的作用下, 我国松毛虫的发生呈现明显的空间分布格局, 最暖季降水量较高的南方和北方部分地区松毛虫发生率较高, 而降水量较低的西北和青藏地区松毛虫发生率较低?我们的研究结果可为松毛虫暴发的预防和管理工作提供指导?