三江源区不同建植年限人工草地根系动态特征

根系动态特征能够反映人工草地植物利用土壤资源的效率和群落恢复演替的程度。本研究以三江源区不同建植年限（5、6、9和13年）人工草地植物根系为研究对象，利用“微根管”技术，连续两个生长季（2015年5-9月和2016年5-9月）探究了4个建植年限人工草地根系动态特征。结果表明：地上生物量和丰富度在建植5~9年呈下降趋势，建植9~13年显著上升；土壤理化性质呈“N”字型变化，不同建植年限间差异显著；随建植年限增加，根系寿命、累积生产量和累积死亡量均波动上升，根系的生长和死亡主要发生在0~10 cm土层；根系平均现存量随建植年限增加持续增加，建植6~9年趋于深层化；根系生产量、死亡量和现存量具有明显季节变化，6月为生长高峰期，7月为现存量高峰期，8月为死亡高峰期，建植9年人工草地根系正生长高峰期迟于其他建植年限；建植年限和土层深度直接影响根系寿命，其余环境因子通过影响土壤速效养分或地上生物量间接影响根系现存量。综上所述，建植人工草地能够增加地上生物量和丰富度，改善土壤质量，促进根系现存量的增加，建植6~9年人工草地的二次退化现象只是暂时性过渡阶段，可在此阶段制定合理的人工管理措施来保证土壤养分的稳定输入，加快群落正向演替的进程，从而提高人工草地的群落稳定性和恢复力。     

Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.     

Predictive modes of action of pesticides in uterine adenocarcinoma development in rats

Endometrial adenocarcinoma in the uterine corpus is a malignant cancer that occurs in menopausal women and aged rodents. Because of the similarities in pathogenesis and morphology of endometrial adenocarcinoma in rodents and humans, prediction of the modes of action (MOA) in uterine carcinogenesis is important for extrapolation of rodent data to humans. Three MOAs have been accepted as major pathways for uterine carcinogenesis in rodents: 1) estrogenic activity, 2) increased serum 17beta-estradiiol (E2) to progesterone (P4) ratio and 3) modulation of estrogen metabolism to produce 4-hydroxyestradiol via P450 induction. Inhibition of estrogen excretion and increased aromatase in situ in the tumor are also a potential pathway. Here, chemicals showing uterine carcinogenicity were chosen from approximately 300 pesticides evaluated in Japan within the past decade, and their mechanisms were predicted using parameters from mechanistic and toxicity studies. Seven pesticides increased uterine tumor formation in rats, and the pathways of 4 pesticides could be predicted based on various mechanistic studies. The MOAs of cyenopyrafen and benthiavalicarb-isopropyl were predicted to be modulation of estrogen metabolism, while those of pyriminobac-methyl and spirodiclofen were predicted to be increased E2 to P4 ratio. The driven pathways of metazosulfuron and isopyrazam could not be predicted using several mechanistic studies. No mechanistic studies have been reported for sedaxane, which has a chemical structure and toxicological profile similar to isopyrazam. Our results indicated that appropriate mechanistic studies are useful for mechanism prediction in risk assessment. From this analysis, a flowchart showing a decision tree for predictive MOAs in uterine carcinogenesis was proposed.     

猪饲料有效能值预测模型的构建

为探索饲料常规成分及碳水化合物组分与饲料有效能值之间的关系方程,本研究以NRC第11版《猪营养需要量》中发布的122套饲料营养成分表为基础,将饲料中11种基础成分[6项常规成分:干物质、粗蛋白质(CP)、粗纤维(CF)、粗脂肪(EE)、酸性醚提取物、粗灰分(ash);5项碳水化合物组分:淀粉(ST)、中性洗涤纤维(NDF)、酸性洗涤纤维(ADF)、半纤维素、酸性洗涤木质素]作为自变量,将饲料中的消化能(DE)、代谢能(ME)及净能(NE)作为因变量,采用SAS软件中的REG过程,分别建立不同性质饲料、自变量的不同组合与DE、ME及NE之间的回归关系方程,并以相关系数(R2)及变异系数(CV)作为评价回归模型的优劣。研究表明,有效能值与CP、ST及纤维类指标显著或极显著相关(P0.05或P0.01)。将所有饲料作为研究对象时,饲料的DE、ME及NE与上述11种基础成分之间建立的普适性回归模型预测效果较差。当将14种玉米及其加工产品形成子集时,建立饲料基础营养成分与DE、ME及NE的关系方程分别为7、6和7套(P0.05),且3组回归模型R2分别为0.632 8~0.772 3、0.646 9~0.684 9和0.670 5~0.822 1,CV分别为6.61%~8.40%、6.58%~7.34%和6.21%~8.27%;当将13种大豆及其加工产品形成子集时,共建立饲料基础成分与DE、ME关系方程分别有3和4套,回归模型R2分别为0.907 1~0.926 9、0.890 7~0.922 3,CV分别为5.40%~6.09%、5.79%~6.78%,NE与基础营养成分指标之间无法建立具有营养学意义的有效回归方程。对于同类饲料中具有相同自变量组合的DE及ME预测模型而言,两者之间的差异主要是自变量CP的系数上,且CP部分对ME的正效应低于DE,这保证模型预测的ME低于DE。同时选用本研究构建的适宜模型,补充了NRC第11版成分表中第97(去皮大豆粕,低寡糖,浸提)、101(全脂大豆,高蛋白质)及102号(全脂大豆,低寡糖)饲料的DE值分别为15.99、17.35、17.27 MJ/kg,ME值分别为14.53、16.15和16.14 MJ/kg。综上,以NRC(2012)饲料营养成分表为基础,建立的普适性有效能值回归模型预测效果较差。按照玉米类和大豆类进行分类,可建立DE、ME和NE与饲料化学成分之间的多元回归方程,其中最优的预测因子为CP、EE、ST、ash、NDF、ADF。具有相同自变量的同类饲料DE和ME预测模型之间的差异是CP系数,CP影响DE转化为ME的效率。     

西昌地区实施退耕还林工程后的景观格局变化

利用西昌市1996和2004年2期TM影像数据,对西昌地区实施退耕还林工程以来的景观格局变化进行分析.结果表明:1996-2004年,西昌地区林地面积增长明显,草地面积迅速减少,耕地面积略有增长,耕地、林地和草地类型间的转化频繁;耕地景观随着斑块数和斑块密度的减少破碎度降低,而林地和草地的破碎度增加;耕地和林地斑块形状不规则性增强;就整体景观而言,西昌地区林地的优势度进一步提高,景观均匀度下降.建议在今后实施退耕还林工程时,合理安排还林和还草任务,同时对退耕后耕地面积仍有增长的现象给予关注.     

鲁中南山地刺槐萌生更新林经济效果评价

采用企业动态经济评价方法对刺槐萌生林不同轮伐期的经济效果进行了评价；按ＮＰＶ最大、ＩＲＲ最大确定了林分经济成熟龄；通过敏感性分析确定了经济成熟龄区间。     

动态经济评价模块原理及其在林分经营模型中的应用*

通过动态经济评价模块，将成本构成要素分解成材料消耗，用工消耗和资金换算单位乘子等基本元素，而用以基本元素以自变量的函数描述成本及收入核算项目，借助模块内专门设计的解码过程，通过外部文件，修改成本构成要素的分解层次和描述单位，重新设计成本核算项目的描述函数，实现了经济评价模块同林分生长模型间的柔性结构匹配。压缩数据向量及其相应算法的引入，不仅减少了内存空间的占用量，而且提高了经济评价模块的运行速度，     

森林资源动态变化预测模型

本文给出了不等间隔时序数列的CM(1,1)模型,并对广西融水县森林资源动态变化进行了预测。预测结果比较理想,模型精度97.2％,从而为森林资源部分数据更新提供了一个新方法。     

饶河县森林资源动态分析

用最新的调查数据对饶河县近年来的森林资源变化情况进行了分析,并且提出了未来森林经营过程中的一些建议和措施。