临城县古鲁营岗开发现划方案的研究

采用线性规划方法，利用计算机，以水和投资限额为限制因素，从２３个方案中选出了效益较高的方案，总投资４０万元，年供水量４５．３６ｍ３，栽苹果树９６．０９ｈｍ２，梨２０ｈｍ２，山楂２７ｈｍ２，杏１７ｈｍ２，石榴７ｈｍ２，枣２．７２，柿１６．７ｈｍ２，小麦１１４．３ｈｍ２，花生５．７ｈｍ２，棉花６ｈｍ２，年总产值可达３００万元以上。     

用线性规划方法优化景谷县"山区综合开发‘十五''规划"

景谷县“山区综合开发‘十五’规划”提出 10个主要建设项目 ,以此为基础 ,利用线性规划方法 ,对此10个项目进行优化配置。在不增加投资 ,不增加年生产经费的前提下 ,找出年均产值和年均净收益有明显增长的最佳方案 :停建葡萄种植基地、削减咖啡、柴胶寄主树改造两个建设项目规模 ,保持橡胶、蔬菜、小耳猪、沼气、杨梅基地 5个项目的建设规模 ,适当增加茶叶和芒果基地两个项目的建设规模。     

杭州城市热岛的变化趋势

对杭州，萧山，临安近30年的气象资料分析，可看出，杭州和萧山的年平均气温越来越高，而临却有下降的局势，萧山比杭州增温更快，杭州与临安的温差越来越大，其中除7，11，12月份外，其余9个月温差增大比较显著，从调查的1，4，7，8，10有5个月各时段杭州与临安的温差情况看出，7，8月以晚上20时温差显著，1，4，10月以下午4时显著，人工下垫面增加是气温增高的重要因素，良好的生态环境，较高的森林覆盖率，有助于减轻热岛效应。     

Genetic evaluation of calf and heifer survival in Iranian Holstein cattle using linear and threshold models

Calf and heifer survival are important traits in dairy cattle affecting profitability. This study was carried out to estimate genetic parameters of survival traits in female calves at different age periods, until nearly the first calving. Records of 49 583 female calves born during 1998 and 2009 were considered in five age periods as days 1–30, 31–180, 181–365, 366–760 and full period (day 1–760). Genetic components were estimated based on linear and threshold sire models and linear animal models. The models included both fixed effects (month of birth, dam's parity number, calving ease and twin/single) and random effects (herd‐year, genetic effect of sire or animal and residual). Rates of death were 2.21, 3.37, 1.97, 4.14 and 12.4% for the above periods, respectively. Heritability estimates were very low ranging from 0.48 to 3.04, 0.62 to 3.51 and 0.50 to 4.24% for linear sire model, animal model and threshold sire model, respectively. Rank correlations between random effects of sires obtained with linear and threshold sire models and with linear animal and sire models were 0.82–0.95 and 0.61–0.83, respectively. The estimated genetic correlations between the five different periods were moderate and only significant for 31–180 and 181–365 (r_g = 0.59), 31–180 and 366–760 (r_g = 0.52), and 181–365 and 366–760 (r_g = 0.42). The low genetic correlations in current study would suggest that survival at different periods may be affected by the same genes with different expression or by different genes. Even though the additive genetic variations of survival traits were small, it might be possible to improve these traits by traditional or genomic selection.     

Modeling Landscape Vegetation Pattern in Response to Historic Land-use: A Hypothesis-driven Approach for the North Carolina Piedmont,USA

Current methods of vegetation analysis often assume species response to environmental gradients is homogeneously monotonic and unimodal. Such an approach can lead to unsatisfactory results, particularly when vegetation pattern is governed by compensatory relationships that yield similar outcomes for various environmental settings. In this paper we investigate the advantages of using classification tree models (CART) to test specific hypotheses of environmental variables effecting dominant vegetation pattern in the Piedmont. This method is free of distributional assumptions and is useful for data structures that contain non-linear relationships and higher-order interactions. We also compare the predictive accuracy of CART models with a parametric generalized linear model (GLM) to determine the relative strength of each predictive approach. For each method, hardwood and pine vegetation is modeled using explanatory topographic and edaphic variables selected based on historic reconstructions of patterns of land use. These include soil quality, potential soil moisture, topographic position, and slope angle. Predictive accuracy was assessed on independent validation data sets. The CART models produced the more accurate predictions, while also emphasizing alternative environmental settings for each vegetation type. For example, relic hardwood stands were found on steep slopes, highly plastic soils, or hydric bottomlands – alternatives not well captured by the homogeneous GLM. Our results illustrate the potential utility of this flexible modeling approach in capturing the heterogeneous patterns typical of many ecological datasets.     

The Influence of Landscape Structure on Female Roe Deer Home-range Size

Animal distribution and abundance are greatly affected by the availability of their food resources, which also depends on landscape structure. Lothar hurricane in 1999 had profoundly modified the structure of the forests in France, affecting the habitat quality of ungulates. We tested whether the variations in home-range size of 23 female roe deer were influenced by the fragmentation of the landscape caused by Lothar in the Chizé forest, namely by the increase in heterogeneity associated with the localized massive tree felling. Home-range size was studied in the summers of 2001 and 2002 and we found that variation in home-range size was mainly explained by only one landscape variable: edge density. Home-range size decreased as edge density increased, which is consistent with the fact that edges are good browsing habitats for roe deer. The result of this study suggests that, after 2 years, the hurricane had improved the quality of the home ranges by creating more forest heterogeneity and increasing the contacts between the different vegetation patches within the home range. These results highlight the fact that spatial heterogeneity is likely to be a key factor influencing the distribution and local population density.     

目标规划和线性规划两步优化法在生态农业系统优化中的应用初探

本文以张西楼村生态农业系统的优化设计为例,对线性规划和目标规划两步优化方法进行了探讨。结果表明,两步优化法可使线性规划、目标规划两种方法互相补充,使优化方案更具可行性,并提出了有待进一步研究的问题。     

长三角地区碳排放量分析及预测

在“双碳”背景下,控制碳排放量对可持续发展具有重要意义。为精确测量经济发展中,各影响因素对碳排放量的影响,以长三角地区为例,将灰色回归组合模型应用于碳排放量的预测,选取了第一产业生产总值、第二产业生产总值、第三产业生产总值和能源消耗量4个主要影响因素构建影响因素指标体系,分析各影响因素与碳排放量之间的灰色关联关系,通过对2005—2021年长三角地区碳排放量进行建模,建立各影响因素为自变量的回归预测模型,对2023—2025年长三角地区碳排放量进行了预测。实证结果表明：未来三年长三角地区碳排放量仍具有明显的上升趋势,增速在4%～10%左右,持续的高碳排放量对可持续发展产生深远影响。基于关联分析和预测模型结果,提出通过加快产业转型、提高清洁能源的使用等方式减少碳排放量,促进长三角地区绿色低碳发展。     

Automatic detection of oestrus and health disorders using data from electronic sow feeders

This article suggests a method for detecting oestrus, lameness and other health disorders for group housed sows fed by electronic sow feeders (ESF). The detection method is based on the measure of the individual eating rank, modeled using a univariate dynamic linear model. Differences between the predicted values of the model and the observations are monitored using a control chart: a V-mask is applied on the cumulative sum of the standardized forecast errors of the model. According to the respective V-mask parameters, alarms are given for each of the three states (oestrus, lameness, others) when the deviations between model predicted values and observations exceed some defined parameters. External information is incorporated into the model to limit the number of false alarms when a subgroup of sows enters and exits a group or both. The detection method was implemented on data collected within three production herds over 12 months. Visual recordings were performed to identify sows in oestrus or with health disorders. The detection method showed a high specificity. For oestrus detection, there was a sensitivity of 59%, 70% and 75% for the three herds as compared to 9% (herd 1) and 20% (herd 2) using lists of sows as alarms. Monitoring lameness results in a sensitivity of 56%, 70% and 41%, vs. 39%, 32% and 22% using the lists; monitoring other health disorders resulted in a sensitivity of 0%, 75% and 39% for the three respective herds, vs. 34% and 16% for herds 2 and 3 using the lists. To limit the number of false alarms, it is suggested to expand the model by including daily feed intake or body activity as other response variables.     

The range of influence between cattle herds is of importance for the local spread of Salmonella Dublin in Denmark

The objective of the study was to estimate the range of influence between cattle herds with positive Salmonella Dublin herd status. Herd status was a binary outcome of high/low antibody levels to Salmonella Dublin in bulk-tank milk and blood samples collected from all cattle herds in Denmark for surveillance purposes. Two methods were used. Initially, a spatial generalised linear mixed model was developed with an exponential correlation function to estimate the range of influence simultaneously with the effect of potential risk factors. An iteratively reweighted generalised least squares procedure was used as a second method for verifying the range of influence estimates. With this iterative procedure, deviance residuals were calculated based on a generalised linear model and the range of influence was estimated based on the residuals using an exponential semivariogram. The range of influence was estimated for six different regions in Denmark using both methods. The analyses were performed on data collected during 1 year after initiation of the Salmonella Dublin surveillance program providing herd classifications for the 4th year-quarter of 2003 and 2 years later for the 4th year-quarter of 2005. The prevalence of dairy herds with a positive Salmonella Dublin herd classification status in this period had decreased from 22.1 to 17.0%. In non-dairy herds, the prevalence was nearly unchanged during the same period (3.4 and 3.7% in 4th quarter of 2003 and 2005, respectively). For all cattle herds, the range of influence was 2.3–6.4 km in 2003 and 1.5–8.3 km in 2005. There seemed to be no association between the range of influence and the density of herds in the different regions.