Predicting effects of drainage water management in Iowa's subsurface drained landscapes

Long-term hydrologic simulations are presented predicting the effects of drainage water management on subsurface drainage, surface runoff and crop production in Iowa's subsurface drained landscapes. The deterministic hydrologic model, DRAINMOD was used to simulate Webster (fine-loamy, mixed, superactive, mesic) soil in a Continuous Corn rotation (WEBS_CC) with different drain depths from 0.75 to 1.20 m and drain spacing from 10 to 50 m in a combination of free and controlled drainage over a weather record of 60 (1945-2004) years. Shallow drainage is defined as drains installed at a drain depth of 0.75 m, and controlled drainage with a drain depth of 1.20 m restricts flow at the drain outlet to maintain a water table at 0.60 m below surface level during the winter (November-March) and summer (June-August) months. These drainage design and management modifications were evaluated against conventional drainage system installed at a drain depth of 1.20 m with free drainage at the drain outlet. The simulation results indicate the potential of a tradeoff between subsurface drainage and surface runoff as a pathway to remove excess water from the system. While a reduction of subsurface drainage may occur through the use of shallow and controlled drainage, these practices may increase surface runoff in Iowa's subsurface drained landscapes. The simulations also indicate that shallow and controlled drainage might increase the excess water stress on crop production, and thereby result in slightly lower relative yields. Field experiments are needed to examine the pathways of water movement, total water balance, and crop production under shallow and controlled drainage in Iowa's subsurface drained landscapes.     

An entropy approach to spatial disaggregation of agricultural production

While agricultural production statistics are reported on a geopolitical – often national – basis we often need to know the status of production or productivity within specific sub-regions, watersheds, or agroecological zones. Such re-aggregations are typically made using expert judgments or simple area-weighting rules. We describe a new, entropy-based approach to making spatially disaggregated assessments of the distribution of crop production. Using this approach, tabular crop production statistics are blended judiciously with an array of other secondary data to assess the production of specific crops within individual ‘pixels’ – typically 25–100 square kilometers in size. The information utilized includes crop production statistics, farming system characteristics, satellite-derived land cover data, biophysical crop suitability assessments, and population density. An application is presented in which Brazilian state level production statistics are used to generate pixel level crop production data for eight crops. To validate the spatial allocation we aggregated the pixel estimates to obtain synthetic estimates of municipality level production in Brazil, and compared those estimates with actual municipality statistics. The approach produced extremely promising results. We then examined the robustness of these results compared to short-cut approaches to allocating crop production statistics and showed that, while computationally intensive, the cross-entropy method does provide more reliable estimates of crop production patterns.     

基于Pro/E的播种机零部件参数化造型

针对旱作节水播种机设计中存在的设计手段落后、设计效率低下等问题，应用基于特征的参数化造型软件Pro/E对旱作节水播种机的零部件进行参数化造型，在对该类播种机开沟器、排种器、地轮等零部件的造型设计中探讨了技术要点，提高了旱作节水播种机修改设计和系列化设计的效率。     

基于距离反比法的土壤盐分三维空间插值研究

以新疆兵团一块面积约70 hm2的盐碱地为研究对象,采用EM38与土钻取样相结合的方法得到了126个点不同土层(0~200 cm)的1 386个土壤盐分数据,应用三维距离反比法(3D-IDW)对土壤盐分进行了空间插值,探讨了垂向坐标扩大倍数和搜索点数对插值结果精度的影响。结果表明,研究区0~140 cm土层盐分平均含量较高,为1.84~2.11 g/kg,盐分变异较大,而140~200 cm土层盐分平均含量较低,为1.74~1.79 g/kg。所有土层盐分含量的统计特征值(平均值、标准差和变异系数等)均随土层加深而呈现递减的趋势。土壤盐分实测值和估计值的均方根误差随垂向坐标扩大倍数的增大而减小,随搜索点数的增加而增大,其值在0.1~0.4 g/kg范围内变化,当垂向坐标扩大300倍、搜索点数为6个时,插值效果较优。采用确定的参数对研究区的土壤盐分进行了三维空间插值,结果表明土壤盐分空间分布特征与实测值比较吻合,大部分区域土壤盐分含量小于2.5 g/kg,靠近北部和南部边界区土壤含盐量较低,属于非盐化土区,而大于4 g/kg盐化土主要分布在中间和南部局部区域。研究区80%土壤为非盐化土和轻度盐化土,20%为中度和重度盐化土。影响该区盐化土分布的主要因素有灌溉、局部地形、粘土层位置、地下水埋深和矿化度。当不同方向的取样间距相差很大时,选取合适的垂向坐标扩大倍数和搜索点数对保障3D-IDW法的插值结果精度至关重要。     

基于Pro/E的装配体三维设计

介绍了使用Pro/E计算机软件作为计算机设计绘图工具，建立3D实体模型，然后根据零件间的位置关系将所涉及的零件逐个地进行装配；并简单阐述了其工程图的制作及齿轮三维造型的方法。     

日光温室蔬菜智能化管理系统建模

随着精准农业的发展,智能化管理将在现代农业中广泛应用。针对智能化管理在日光温室蔬菜生产中尚鲜见报道的情况,该研究以日光温室蔬菜为研究对象,通过对日光温室环境特征的分析,设计一种基于无线传感器网络技术的低成本温室监测系统,用于监测温度、湿度、二氧化碳浓度等关键环境参数,并建立日光温室蔬菜系统,通过建模,建立不同子模块,实现蔬菜生产的智能化管理。     

数据仓库逻辑建模的初步探讨

针对逻辑建模在数据仓库构建过程中的重要性,介绍了数据仓库创建的基本步骤,并利用实例深入而详细地研究了逻辑模型的设计,分析了几种逻辑模型的特点及其使用场合。     

Spatiotemporal Distribution of Two Euschistus spp. Stink Bugs (Hemiptera: Pentatomidae) in Southeastern Farmscapes

Stink bugs (Hemiptera: Pentatomidae) are ubiquitous, cryptic, phytophagous pests that are found in many crops. In agroecosystems, individuals disperse from adjacent noncrop hosts and tend to aggregate or cluster within fields. In this study, we characterized the distribution of Euschistus servus (Say) and Euschistus tristigmus (Say) (Hemiptera: Pentatomidae) over 2 yr at three southeastern United States farmscapes. Stink bugs were captured in pheromone-baited traps, and Spatial Analysis by Distance Indices (SADIE) used to identify the location of significant aggregations by habitat type and season. Euschistus servus adults were more likely to be captured in pecan orchards, cotton, other crops, or unmanaged habitats than in woodland habitats. Significant aggregations of E. servus were detected in a variety of habitats including pecan, corn, cotton, peanut, and tobacco, as well as fallow and hay fields, pastures, and hedgerows. Fewer adult E. tristigmus were captured than E. servus adults, and E. tristigmus adults were typically trapped and aggregated in woodland habitats. The resulting data provide an important understanding regarding the seasonal movement and relative abundance levels of stink bug populations, which are critical to the development of integrated pest management strategies.     

Predicting the potential geographic distribution of Bactrocera bryoniae and Bactrocera neohumeralis(Diptera: Tephritidae) in China using MaxEnt ecological niche modeling

Bactrocera bryoniae and Bactrocera neohumeralis are highly destructive and major biosecurity/quarantine pests of fruit and vegetable in the tropical and subtropical regions in the South Pacific and Australia. Although these pests have not established in China, precautions must be taken due to their highly destructive nature. Thus, we predicted the potential geographic distribution of B. bryoniae and B. neohumeralis across the world and in particular China by ecological niche modeling of the Maximum Entropy(Max Ent) model with the occurrence records of these two species. Bactrocera bryoniae and B. neohumeralis exhibit similar potential geographic distribution ranges across the world and in China, and each species was predicted to be able to distribute to over 20% of the globe. Globally, the potential geographic distribution ranges for these two fruit fly species included southern Asia, the central and the southeast coast of Africa, southern North America, northern and central South America, and Australia. While within China, most of the southern Yangtze River area was found suitable for these species. Notably, southern China was considered to have the highest risk of B. bryoniae and B. neohumeralis invasions. Our study identifies the regions at high risk for potential establishment of B. bryoniae and B. neohumeralis in the world and in particular China, and informs the development of inspection and biosecurity/quarantine measures to prevent and control their invasions.     

Mapping the current and future distributions of Onosma species endemic to Iran

Climate change may cause shifts in the natural range of species especially for those that are geographically restricted and/or endemic species. In this study, the spatial distribution of five endemic and threatened species belonging to the genus Onosma (including O. asperrima, O. bisotunensis, O. kotschyi, O. platyphylla, and O. straussii) was investigated under present and future climate change scenarios: RCP2.6 (RCP, representative concentration pathway; optimistic scenario) and RCP8.5 (pessimistic scenario) for the years 2050 and 2080 in Iran. Analysis was conducted using the maximum entropy (MaxEnt) model to provide a basis for the protection and conservation of these species. Seven environmental variables including aspect, depth of soil, silt content, slope, annual precipitation, minimum temperature of the coldest month, and annual temperature range were used as main predictors in this study. The model output for the potential habitat suitability of the studied species showed acceptable performance for all species (i.e., the area under the curve (AUC)>0.800). According to the models generated by MaxEnt, the potential current patterns of the species were consistent with the observed areas of distributions. The projected climate maps under optimistic and pessimistic scenarios (RCP2.6 and RCP8.5, respectively) of 2050 and 2080 resulted in reductions and expansions as well as positive range changes for all species in comparison to their current predicted distributions. Among all species, O. bisotunensis showed the most significant and highest increase under the pessimistic scenario of 2050 and 2080. Finally, the results of this study revealed that the studied plant species have shown an acute adaptability to environmental changes. The results can provide useful information to managers to apply appropriate strategies for the management and conservation of these valuable Iranian medicinal and threatened plant species in the future.