Understanding Interaction Effects of Climate Change and Fire Management on Bird Distributions through Combined Process and Habitat Models

Abstract: Avian conservation efforts must account for changes in vegetation composition and structure associated with climate change. We modeled vegetation change and the probability of occurrence of birds to project changes in winter bird distributions associated with climate change and fire management in the northern Chihuahuan Desert (southwestern U.S.A.). We simulated vegetation change in a process‐based model (Landscape and Fire Simulator) in which anticipated climate change was associated with doubling of current atmospheric carbon dioxide over the next 50 years. We estimated the relative probability of bird occurrence on the basis of statistical models derived from field observations of birds and data on vegetation type, topography, and roads. We selected 3 focal species, Scaled Quail (Callipepla squamata), Loggerhead Shrike (Lanius ludovicianus), and Rock Wren (Salpinctes obsoletus), that had a range of probabilities of occurrence for our study area. Our simulations projected increases in relative probability of bird occurrence in shrubland and decreases in grassland and Yucca spp. and ocotillo (Fouquieria splendens) vegetation. Generally, the relative probability of occurrence of all 3 species was highest in shrubland because leaf‐area index values were lower in shrubland. This high probability of occurrence likely is related to the species’ use of open vegetation for foraging. Fire suppression had little effect on projected vegetation composition because as climate changed there was less fuel and burned area. Our results show that if future water limits on plant type are considered, models that incorporate spatial data may suggest how and where different species of birds may respond to vegetation changes.     

Modelling the abundance of three key plant species in New Zealand hill-pasture using a decision tree approach

Decision tree models were developed to investigate and predict the relative abundance of three key pasture plants [ryegrass (Lolium perenne), browntop (Agrostis capillaris), and white clover (Trifolium repens)] with integration of a geographical information system (GIS) in a naturalised hill-pasture in the North Island, New Zealand, and were compared with regression models with respect to model fit and predictive accuracy. The results indicated that the decision tree models had a better model fit in terms of average squared error (ASE) and a higher percentage of adequately predicted cases in model validation than the corresponding regression models. These decision tree models clearly revealed the relative importance of environmental and management variables in influencing the abundance of these three species. Hill slope was the most significant environmental factor influencing the abundance of ryegrass while soil Olsen P and annual P fertilizer input were the most significant factors influencing the abundance of browntop, and white clover, respectively. Soil Olsen P of approximately 10 μg/g, or a slope of about 10.5° was critical points where the competition between ryegrass and browntop tended to come to an equilibrium. Integrating the decision tree models with a GIS in this study not only facilitated the model development and analyses, but also provided a useful decision support tool in pasture management such as in assisting precision fertilizer placement. The insights obtained from the decision tree models also have important implications for pasture management, for example, it is important to maintain a soil Olsen P higher than 10 μg/g in order to keep the dominance of ryegrass in the hill-pasture.     

空气质量数值模型的构建及应用研究进展

综述了近年来国内外空气质量模型的发展历程、空气质量数值模型构建的关键技术以及应用研究。指出了目前空气质量数值预报及应用主要面临气象条件,尤其是大气边界层模拟、大气污染物排放源和大气物理化学过程等问题。提出,应当通过规范化制作和完善排放源清单数据,建立统一的排放源分析标准,提高排放源数据的准确性;多向发展观测手段,加大监测密度和频率,并进行实验室化学分析,提出适合我国的大气物理化学机制。就空气质量模式而言,对模式方案进行优化,以及使用气象、卫星资料同化等技术手段,将其与观测相结合,构建监测与预报系统相结合的统一体系,应用于多平台。     

工作场所空气中硫酸雾（SO3）的分析

采用碘量法测定工作场所空气中的三氧化硫及硫酸雾，三氧化硫及硫酸雾经中性水吸收后与碘化钾和碘酸钾反应，析出的碘与淀粉指示剂作用产生蓝色，进行比色测定。     

佛山市臭氧浓度时间变化特征及主要影响因子

对佛山市2011—2014年O_3监测数据进行分析,结果表明,ρ(O_3)日变化呈现明显的单峰特征,2011—2014年O_3日最大8小时滑动均值(O3-8 h)的年评价值没有出现显著的下降趋势,超标值多出现在8—10月。夏季O3-8 h与日平均气温的相关系数较高,O_3污染多发生在气温30℃,相对湿度为50%~70%的气象条件下。相对湿度60%,气温为20~25℃,也可能出现O3污染。10℃时,不同的温度条件下,O_3与PM_(2.5)存在正相关关系。在不同的季节时段,O_3-8 h基本随着ρ(NO_2)/ρ(NO)增大而增大。     

浅谈GAM与GM（1,1）模型

对ＧＡＭ水环境预测模型提出了四点不同看法，与有关作者商榷，指出ＧＭ（１，１）模型与ＧＡＭ模型二者并无优劣之差，精度亦相当。     

基于改进DEA交叉效率模型的洪水灾害区域脆弱性评价

为了评价洪水灾害区域脆弱性,提出了应用改进DEA交叉效率模型和熵权法相结合的洪水灾害区域脆弱性评价方法。首先,在洪灾形成理论的基础上,构建洪灾区域脆弱性指标体系和评价标准;其次,应用改进DEA交叉效率模型计算不同区域的成灾效率,利用熵权法计算权重集结全局成灾效率。根据成灾效率的实际意义分析不同区域脆弱性的相对大小。最后,选取我国各省份洪灾作为实证分析的研究对象。研究结果表明:该方法能够准确评价区域洪灾脆弱性程度,评价结果与实际情况一致,具有较好的适用性。     

海洋平台圆柱体坠落运动轨迹及落点分析

传统的角度偏差经验值方法导致落物风险评价过程中的落点和危险区预测存在较大误差,科学化、立体化、完整化、多因素概化的落物轨迹和落点分析方法及工具缺位。为此,以海洋平台圆柱体落物为研究对象开展先导研究,在2D运动理论模型基础上,考虑3维、6度受力与运动参数,引入粘性拖曳力系数经验公式、海流运动、旋转升力和力矩项,建立了具有普适性的落物水下3D运动轨迹预测模型,并以现场实验数据校验表明模型方法可行、结果更可信;据此以Matlab 2016为程序设计平台编制了海洋平台圆柱体坠落运动预测分析工具（MREDP）,分析了坠落运动落点分布规律。研究结果表明:随着初始倾斜角度的增大,落点偏移距离呈现先增后降的趋势,于62°时达到最大值,运动轨迹整体呈现螺线曲率减小、向轨迹曲线外开口侧偏移趋势;落点分布变化可分为Y轴偏移稳定主导阶段、X轴偏移实力型快速主导阶段和X轴偏移机会型主导阶段3个阶段;相对MREDP预测结果,DNVGL-RP-F107经验性角度偏差推荐结果较为保守,MREDP可为DNVGL-RP-F107提供更加准确、可信的轨迹曲线和落点取值。基于分析结果,提出了采用Monte Carlo方法表征实际工程中起始运动参数随机性和入水撞击产生的不确定性等建议。     

生态缺水条件下流域生态经济系统安全性分析

生态用水和社会经济用水的竞争状况使得研究水资源短缺地区的流域生态经济系统安全状况、有效进行生态缺水条件下流域生态经济系统的调控十分必要.从宏观角度出发,首先分析了流域生态经济系统演化的机制和影响因素,在此基础上,通过建立指标体系,提出了构建流域主要指标为状态变量的生态经济系统演化模型,并利用模型进行系统安全性分析.以潮白河流域为例,构建了人口数量、人均GDP、生态系统指数以及生态用水比例为状态变量的生态经济系统演化模型.模型模拟结果表明,如果不加以调控,该流域将无法提供生态经济系统的安全保障.提出了提高生态用水比例、控制经济增长速度和积极进行生态建设、控制水土流失的对策,为实现潮白河流域的生态经济系统安全保障服务.     

基于人工神经网络理论的船舶动力装置安全综合评价模型

为提高船舶动力装置安全综合评价水平，依据人工神经网络的基本原理，分析了BP神经网络模型的基本原理和优化策略，将其应用于船舶动力装置的安全评价之中。提出了基于神经网络理论的船舶动力装置综合安全评价模型及实现方法，并以实例论证了此方法的可行性。