基于PCA-SVR-ARMA的狮头鹅养殖禽舍气温组合预测模型

为提高狮头鹅养殖禽舍气温预测精度,提出了基于主成分分析(Principal Component Analysis,PCA)、支持向量回归机(Support Vector Regression,SVR)融合自回归滑动平均(Autoregressive Moving Average,ARMA)模型的狮头鹅养殖禽舍气温组合预测模型。在建模过程中,运用主成分分析法筛选狮头鹅养殖禽舍气温的关键影响因子,消除变量之间冗余信息,约简预测模型结构;采用SVR-ARMA构建狮头鹅禽养殖舍气温组合预测模型,先通过SVR对气温进行预测,再由基于ARMA模型的残差预测值修正气温预测结果。利用该模型对广东省汕尾市2018年7月21日至2018年7月30日期间的狮头鹅养殖禽舍气温进行预测。结果表明,该组合预测模型取得了良好的预测性能,与标准BP神经网络、标准SVR、PCA-BPNN(反向传播神经网络,BackPropagationNeuralNetwork)、PCA-SVR和PCA-BPNN-ARMA等模型对比分析,其评价指标平均绝对误差、均方根误差和平均绝对百分比误差分别为0.183 2℃、0.454 0℃和0.005 9,均表明所提出的组合模型具有更高的预测效果,不仅能够满足狮头鹅养殖禽舍气温实际精准调控的需要,还为狮头鹅健康养殖和种苗繁育环境精细化管理提供决策。     

基于农田管理分区的制种玉米产量估算与限制因子评价

为了提升规模化农田不同管理分区的玉米产量,实现精准管理,该研究使用相关成分回归法(Correlated Component Regression,CCR),考虑地形因素(高程)、土壤理化性质(砂粒、粉粒、黏粒、容重、土壤含水率、土壤有机碳、全氮、全磷、速效氮、电导率)11个因子,评估规模化农田和聚类分析得到的3个管理区(M1、M2和M3)内产量的限制因子,并在不同分区内建立产量估算模型。模型验证结果表明:未分区的情况下,产量限制因子为土壤粉粒、砂粒、土壤有机碳、土壤含水率、速效氮和全氮,经验证,产量估算模型的决定系数(R~2)为0.70,标准均方根误差(Normalized Root Mean Square Error,nRMSE)为0.21。分区后,M1的产量限制因子为土壤粉粒、砂粒、黏粒、速效氮、电导率、全氮和全磷,M2的产量限制因子为土壤粉粒、砂粒和土壤含水率,M3的产量限制因子为高程、土壤砂粒、黏粒和电导率,产量估算模型的精度高(经验证,0.71R20.83,0.16nRMSE0.18)。对农田进行分区管理,并根据各管理区内作物产量的限制因素制定分布式管理策略,可以更具针对性地提升作物产量。     

明胶骨原料碳、氮稳定同位素的地域性差异研究

为探讨不同地域来源的明胶骨原料中碳、氮稳定同位素的分布特征及其相关性,本试验采用元素分析-稳定同位素比率质谱仪测定了广西、内蒙古和山东3个主产区的牛骨样品及当地牧草饲料样品中的¹³C和¹⁵N同位素组成,并结合线性回归讨论了牛骨样品中δ¹³C和δ¹⁵N值的相关性与牛食谱组成的关系。结果表明,广西地区骨样品中δ¹³C和δ¹⁵N值的相关性较好(R²=0.401 8),而内蒙古和山东地区骨样品中δ¹³C和δ¹⁵N值的相关性较差(R²<0.1),反映了3地牛食物的来源稳定性及主要成分存在明显差异,对各地牛食谱结构推测的结果与实际牧草饲料样品中δ¹³C和δ¹⁵N值的地区分布规律也较为一致。本研究初步揭示了明胶骨原料中碳、氮稳定同位素产生地域性差异的原因,不仅为动物生态学研究提供了有益信息,更为动物制品产地溯源研究提供了新思路。     

湿地松产脂量与生长及树冠性状多点遗传相关及通径分析

为研究湿地松生长及树冠性状与产脂量之间的遗传相关关系及其对产脂量的控制途径,以赣北、赣中和赣南等多种典型立地条件下的28年生湿地松家系试验林为研究对象,对112个湿地松家系进行产脂量、生长及树冠性状全林调查,并对测定数据进行分析。结果表明,除枝下高外,产脂量与生长及树冠性状均呈显著或极显著遗传正相关关系,遗传相关系数排名前四的性状分别为胸径(R=0.93)、树冠表面积(R=0.83)、冠长(R=0.78)和冠幅(R=0.73);通径分析中,胸径、树高、树冠表面积和冠幅通过直接和间接作用成为影响产脂量的主导因素,其决定系数贡献率分别为0.557、0.507、0.424和0.240;产脂量与生长、树冠性状的线性回归方程为:y=-0.255+0.040x_(DBH)+0.004x_(HGT)+0.006x_(CSA)+0.036x_(CW)(F=955.907^**, R²=0.559),模型的预估精度为99.64%。本试验结果明确了湿地松生长及树冠性状与产脂量之间的关系,其中,树高、胸径、冠幅和树冠表面积对产脂量影响较大;建立的产脂量多元回归模型具有一定的现实意义,实现了对树高、胸径和树冠表面积等性状的快速测定预估产脂量,为湿地松产脂量的科学、准确与高效预测提供了依据。     

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。     

Preliminary recovery of coastal sharks in the south‐east United States

Relative abundance of many shark species in the Atlantic is assessed by compiling data from several independently conducted, but somewhat spatially limited surveys. Although these localized surveys annually sample the same populations, resulting trends in yearly indices often conflict with one another, thereby hindering interpretation of abundance patterns at broad spatial scales. We used delta‐lognormal generalized linear models (GLMs) to generate indices of abundance for seven Atlantic coastal shark species from six fishery‐independent surveys along the US east coast and Gulf of Mexico from 1975 to 2014. These indices were further analysed using dynamic factor analysis (DFA) to produce simplified, broad‐scale common trends in relative abundance over the entire sampled distribution. Effects of drivers including the North Atlantic Oscillation index, the Atlantic Multidecadal Oscillation index, annually averaged sea surface temperature and species landings were evaluated within the DFA model. The two decadal oscillations and species landings were shown to affect shark distribution along south‐east US coast. Estimated common trends of relative abundance for all large coastal shark species showed similar decreasing patterns into the early 1990s, periods of sustained low index values thereafter and recent indications of recovery. Small coastal shark species exhibited more regional variability in their estimated common trends, such that two common trends were required to adequately describe patterns in relative abundance throughout the Gulf of Mexico and Atlantic. Overall, all species’ (except the Gulf of Mexico blacknose shark) time series concluded with an increasing trend, suggestive of initial recovery from past exploitation.     

Prey and non‐native fish predict the distribution of Colorado pikeminnow (Ptychocheilus lucius) in a south‐western river in North America

Colorado pikeminnow (Ptychocheilus lucius) has been extirpated from a large portion of its historical range in the Colorado River basin, USA. A repatriation effort via stocking of juvenile P. lucius in the San Juan River, NM, CO and UT has resulted in limited recruitment of individuals into an adult population. Understanding biotic and abiotic factors that limit their persistence in the Colorado River basin will be a critical step in providing for their recovery. To elucidate potential recruitment barriers in the San Juan River, we assessed relationships between the numbers of two age classes of P. lucius and prey, competitors and predators collected at a 1.6 km reach scale between 2003 and 2012. We used an information theoretical approach to rank candidate models testing the relative importance of these biotic conditions in predicting the spatial distribution of P. lucius. We found positive relationships between the numbers of P. lucius ≤200 mm total length (TL) collected and catch per unit effort (CPUE) of native prey among reaches. For P. lucius >200 mm TL (individuals that are likely completely piscivorous), we found positive associations between the numbers of P. lucius collected and CPUE of total prey and CPUE of potential non‐native competitors in each reach. Our data suggest size‐specific affinities of P. lucius for native and non‐native prey as well as the potential for negative interactions between P. lucius and non‐native competitors may contribute to limited recruitment of juvenile P. lucius into an adult population in the San Juan River.     

土壤因子与小粒咖啡品质产量形成关系研究

土壤因子是影响小粒咖啡品质产量的主要因子。本研究通过对土壤因子进行相关性分析、改进的灰色关联分析、通径分析及多元线性回归分析,明确影响小粒咖啡品质和产量的主要因子,以指导科学施肥。结果表明:小粒咖啡咖啡因含量的土壤决定因子为海拔（-0.296^*）,总糖含量的土壤决定因子为有机质（0.607^**）和速效磷（-0.232^*）,蛋白质的土壤决定因子为pH（-0.387^**）和有机质（0.227^*）,灰分含量的土壤决定因子为速效磷（0.334^**）,水溶性浸出物含量的土壤决定因子为海拔（-0.494^**）,脂肪含量的土壤决定因子为碱解氮（-0.461^**）,产量的土壤决定因子为速效钾（0.339^**）和有机质（0.248^*）。研究结果可为小粒咖啡优质高产的土壤条件筛选和肥料的减施增效提供一定的理论基础,以期增强优质咖啡种质的适宜性和目的性。     

Analysis of green total factor productivity trend and its determinants for the countries along silk roads

In coping with increasing energy consumption and the consequential environmental pollution, green development is becoming an important part of social development. Since the inauguration of China’s Silk Road Economic Belt Initiative (BRI), economic cooperation between China and other countries along BRI has seen much growth. Therefore, it is of great significance to study the levels of green total factor productivity (GTFP) of the countries in the Silk Roads Economic Belt (B&R) and examine how these levels vary spatially and evolve temporally. In this paper, a panel regression analysis with DEA windows is used to study the spatiotemporal trends of the levels of GTFP. The results are: (1) The B&R countries have seen an increase in their overall levels of GTFP over time; (2) There are regional differences in the levels of GTFP, with higher efficiency in Western Asia and Central and Eastern Europe, and lower efficiency in Southeast and Central Asia; (3) The analysis of GTFP for countries in these regions shows that the efficiencies of most countries have been improving, with that of only a few countries have been decreasing; (4) By using regression analysis, we find that variables such as import, export, industrial structure, and urban affect the B&R countries with growing GTFP.     

Multiple resistance of Papaver rhoeas L. to 2,4‐D and acetolactate synthase inhibitors in four European countries

The issue of cross‐ or multiple resistance to acetolactate synthase (ALS) inhibitors and the auxinic herbicide 2,4‐D was investigated in Papaver rhoeas L., a common and troublesome weed in winter cereals, in a broad‐scale study across four European countries. A combination of herbicide sensitivity bioassays and molecular assays targeting mutations involved in resistance was conducted on 27 populations of P. rhoeas originating from Greece (9), Italy (5), France (10) and Spain (3). Plants resistant to the field rate of 2,4‐D were observed in 25 of the 27 populations assayed, in frequencies ranging from 5% to 85%. Plants resistant to ALS‐inhibiting herbicides (sulfonylureas) were present in 24 of the 27 populations, in frequencies ranging from 4% to 100%. Plants resistant to 2,4‐D co‐occurred with plants resistant to sulfonylureas in 23 populations. In four of these, the probability of presence of plants with cross‐ or multiple resistance to 2,4‐D and sulfonylureas was higher than 0.5. ALS genotyping of plants from the field populations or of their progenies, identified ALS alleles carrying a mutation at codon Pro197 or Trp574 in 2,4‐D‐sensitive and in 2,4‐D‐resistant plants. The latter case confirmed multiple resistance to 2,4‐D and ALS inhibitors at the level of individual plants in all four countries investigated. This study is the first to identify individual plants with multiple resistance in P. rhoeas, an attribute rarely assessed in other weed species, but one with significant implications in designing chemical control strategies.