油松木材物理力学性质的研究

本文研究了山西中条山油松木材的物理力学性质,并与其它产地的油松材性进行了比较。讨论分析了密度对油松木材各项力学性质的影响,给出了密度与力学性质间的回归方程。密度对顺纹抗压、横纹抗压、硬度、顺纹抗剪、抗弯强度等力学性质影响显著,而对顺纹抗拉强度、冲击韧性等影响较小。顺纹抗拉强度主要受管胞长度、管胞强度、纤丝角度、结晶度等因子的控制。     

延边黄牛幼牛正常生长发育的曲线研究

本研究是应用复合函数回归式，对延边黄牛０～２４个月龄体重、体尺的６６项实测资料计算平均值和上下限，求出其曲线回归式和各月龄理论值．其结果：公母牛体重平均值曲线与实测值之间的分别为２８６．５６、１７６．２４，拐点偏差为０．７、０．３个月龄，比应用计算的低５２１４．２３、４００７．０５．计算公、母牛２０项体尺资料的平均值和实测资料的的结果，除母牛胸宽平均值外都比应用计算结果低，与实测值的吻合度较好，并能克服二次回归式和布劳迪回归式所存在的缺点．     

梭梭林生物量研究

吉兰泰地区现存梭梭林中梭梭生物量占全林地的９５％以上，达６．４２ｔ／ｈｍ＿２，且随着生长状况、密度而变化。梭梭单株生物量（地上部分ＢＷ，地下部分ＲＷ，）与梭梭的高度（Ｈ）、地径（Ｒ）、冠幅面积（Ｅ）三项生长指标之间关系密切，可用下面二个方程进行预测：２４３ＨＥＲ０．３９９ＨＥＲ梭梭地上生物量约占总生物量的５３％，以中等直径枝条为主，占地上生物量的８４％。地下生物量占总生物量的４７％，主根（粗根）发达占总根量的７３％，细根占７％密集分布于０～１００ｃｍ的表层。地上与地下关系为：ＲＷ＝０．９０４８＋０．８１１９ＢＷ     

上证综合指数(日收盘)线性回归模型

根据技术分析的理论和基本假设,利用收盘价、最高价、最低价和成交量,以及前几个交易日的收盘点、最高点、最低点和成交量对上证综合指数999999收盘点位建立的多元线性回归模型显示,当期上证综合指数999999确实与前3个交易日的收盘价、最高价、最低价和成交量有线性关系,模型拟合得很好,但估计的个别值与实际值偏离较大,用模型进行预测时还得用其他方法予以佐证。     

间作大豆的竞争性分析

通过多因素和单因素试验资料的相关和回归分析,证明玉米和大豆对光照和肥料的竞争明显,但水分与间作大豆产量无显著相关。玉米通过株型、叶面积等影响大豆冠层光照度,光照度与大豆产量呈正相关。N肥降低间作大豆产量,NPK复合肥增加大豆产量。本文还提出了提高间作大豆产量的栽培主攻方向。     

Impacts of coffee agroforestry management on tropical bee communities

Though it is undoubted that tropical bees are influenced by habitat composition, few studies have investigated the relative importance of both local and landscape-level habitat parameters in supporting large and diverse bee communities. The conservation of native bee communities within agroforestry landscapes is particularly urgent given the importance of pollination services within these systems. In this study, we examined tropical bee communities within a largely deforested shade coffee-growing region in Chiapas, Mexico. We used regression tree modeling to examine the response of bee functional groups to local and landscape-level habitat management. Our models revealed that the most predictive factors for bee abundance and species richness were the number of tree species, the number of tree species in flower, and the canopy cover of the local agroforestry landscape. Solitary bees were most abundant in habitats with high canopy cover, while social bees were most abundant in habitats with greater tree species richness. Cavity-nesting and wood-nesting bee abundance was positively affected by the amount of canopy cover in the farm, while ground-nesting bees were most abundant in habitats with a large number of tree species in flower. Our results demonstrate that across bee sociality groups, nesting guilds, and tribes, the most critical factor impacting native bee communities was within-farm local vegetation management. These results reveal the important role that agroforestry managers can have on biodiversity conservation, and the potential contribution they can make by creating resource-rich agricultural matrices. Specifically, our findings highlight the importance of diverse overstory tree management in supporting native bee communities within tropical agroforestry systems.     

三疣梭子蟹形态性状对体重影响的分析

通过对鸭绿江口、莱州湾、海州湾和舟山4个采样地点的三疣梭子蟹Portunus tritubercula-tus12项形态性状的测量,采用相关分析和通径分析方法,计算了以形态性状为自变量对体重作依变量的相关系数、通径系数、决定系数及相关指数,定量分析了形态性状对体重的影响效果。结果表明,三疣梭子蟹12个形态性状均与体重的相关系数达到极显著水平(P<0.01);通径分析揭示了多元分析中多个自变量与依变量的真实关系。全甲宽、甲长、体高、第1侧齿间距、第2侧齿间距、大螯不动指长对体重的通径系数达到显著水平。所选形态性状与体重的复相关指数为R2=0.8826,说明影响体重的主要自变量指标已经找到;多元回归分析建立了全甲宽(X1)、甲长(X2)、体高(X4)、第一侧齿间距(X5)、大螯不动指长(X7)对体重(Y)的回归方程,为三疣梭子蟹育种提供理论依据。     

玉米秸秆青贮饲料贮存期的营养品质变化规律

为探讨玉米秸秆青贮饲料营养物质随时间变化规律,选取生长期为105d的青玉米秆调制青贮饲料,50d后开窖,考察了青贮饲料在50～290 d贮存期间7种主要营养物质随时间的变化规律.研究了营养物质与贮存时间以及纤维类成分与干物质之间的相关关系,并建立了一元回归模型.     

High-resolution leaf area index inversion based on the Kernel Ridge Regression algorithm and PROSAIL model北大核心CSCD

Accurate estimation of leaf area index（LAI）plays an important role in ecological，environmental and climate change research. Large-scale LAI estimates can be obtained from satellite remote sensing technology，but they rely on a large amount of ground-measured data with and they have low spatial resolution，which often does not meet the needs of high-precision and large-scale research. In this study，using surface reflectance data with a spatial resolution of 30 m，we tested an inversion method combining the Kernel Ridge Regression（KRR）algorithm and the PROSAIL physical model to invert LAI without a large number of ground measured data. First，the sensitivity analysis was performed on the input parameters of the PROSAIL model to determine the input parameters and generate the simulated data sets. Then，the KRR model inversion between the simulated reflectance and LAI was established. For comparison，we linked two other models，the Multilayer Perceptron（MLP）algorithm and the Random Forest Regression（RFR）algorithm，with the PROSAIL model，to perform high spatial resolution LAI inversion. Finally，we used ground measured data to compare the outputs and performance of the three inversion models. We found that the LAI inversion accuracy of the KRR-PROSAIL model was the highest with an R2 of 0. 8089 and root-mean-square error（RMSE）of 0. 2492. The inversion accuracies of the PROSAIL model linked with MLP and RFR were inferior with R2 values of 0. 7726 and 0. 7118，respectively and RMSE values of 0. 2781 and 0. 2432，respectively. Based on this study we recommend the combination of the Kernel Ridge Regression algorithm and PROSAIL models to invert satellite data to LAI for improved accuracy and high spatial resolution of the inverted LAI data. This methodology provides a method for rapid and accurate inversion of regional high-precision LAI information. © 2022 Editorial Office of Acta Prataculturae Sinica. All rights reserved.