Using interview surveys and multispecies occupancy models to inform vertebrate conservation

Species distribution data are an essential biodiversity variable requiring robust monitoring to inform wildlife conservation. Yet, such data remain inherently sparse because of the logistical challenges of monitoring biodiversity across broad geographic extents. Surveys of people knowledgeable about the occurrence of wildlife provide an opportunity to evaluate species distributions and the ecology of wildlife communities across large spatial scales. We analyzed detection histories of 30 vertebrate species across the Western Ghats biodiversity hotspot in India, obtained from a large-scale interview survey of 2318 people who live and work in the forests of this region. We developed a multispecies occupancy model that simultaneously corrected for false-negative (non-detection) and false-positive (misidentification) errors that interview surveys can be prone to. Using this model, we integrated data across species in composite analyses of the responses of functional species groups (based on disturbance tolerance, diet, and body mass traits) to spatial variation in environmental variables, protection, and anthropogenic pressures. We observed a positive association between forest cover and the occurrence of species with low tolerance of human disturbance. Protected areas were associated with higher occurrence for species across different functional groups compared with unprotected lands. We also observed the occurrence of species with low disturbance tolerance, herbivores, and large-bodied species was negatively associated with developmental pressures, such as human settlements, energy production and mining, and demographic pressures, such as biological resource extraction. For the conservation of threatened vertebrates, our work underscores the importance of maintaining forest cover and reducing deforestation within and outside protected areas, respectively. In addition, mitigating a suite of pervasive human pressures is also crucial for wildlife conservation in one of the world's most densely populated biodiversity hotspots.     

交易费用视角下农地整理管护绩效的影响因素研究

农地整理建成设施及设备的管护是权利让渡和责任主体迁移的过程,对农地整理管护绩效开展研究是破解当前管护困境的有效途径。论文在构建农地整理管护绩效测度体系及其评估方法基础之上,运用威廉姆森交易费用“维度论”分析框架阐述农地整理管护绩效的影响因素。实证研究结果表明,实物资产专用性、人力资产专用性、交易不确定性、交易频率等维度要素对管护绩效的影响较为显著;论文运用工具变量方法解决计量模型中解释变量内生性问题,探讨了内生变量与工具变量以及其他解释变量的作用关系。研究结果验证了威廉姆森分析框架的有效性,并建议管理部门重视耕地生产水平的改善程度、村干部的表率示范作用以及管护人员的明确落实等关键影响要素。     

基于模糊综合评价方法的通用桥式起重机风险评价

文章通过层次分析法构建了通用桥式起重机评价指标体系,并构建判断一致矩阵,得到了各层次的权重向量,结合由隶属函数得到的隶属矩阵,运算得到综合评价向量.再利用可变模糊集理论中的等级识别法结合未确知测度理论中的置信度准则确定评价对象的安全评价等级.经过实例分析表明,该方法能够充分利用评价信息,极大地减小评价信息在评价过程中的...     

基于决策树的矿井通风阻变型故障诊断及传感器优化布置

为实现矿井通风阻变型故障智能诊断,解决风速传感器优化布置与诊断模型不匹配的问题,提出基于决策树的矿井通风故障位置分类判断、故障量回归预测及嵌入式风速传感器优化布置一体化方法;以唐安矿为例对上述方法进行验证.结果表明:矿井通风空间数据集无量纲化能提高故障诊断准确率、提升模型收敛速度,剪枝能提高模型泛化能力;以基尼系数为嵌...     

低分子量有机酸对几种可变电荷土壤吸附氟的影响

用一次平衡法研究了四种低分子量有机酸对几种可变电荷土壤吸附氟的影响，结果表明，低分子量有机酸可以通过竞争吸附作用抑制土壤对氟的吸附，化学结构相对简单的草酸和丙二酸对氟吸附的抑制作用大于柠檬酸和苹果酸。有机酸对氟吸附的抑制作用随土壤氧化铁含量的增加而增加，并随体系pH的增加而增强。在低pH和氟加入量较高的情况下，有机酸通过与氟竞争可溶性铝而增加土壤对氟的吸附量，这在对铝溶解度较高的酸性土壤中尤为明显。     

基于变权欧氏距离的矿山生态环境评价与分析

在对欧式距离模型进行优化的基础上,根据不同评价指标对矿山生态环境影响程度的不同,得出评价指标的权重,以环境指标为轴,以Ⅰ等级环境质量水平为原点,结合不同因子权重求出待评价对象的变权欧氏距离。通过对某金属矿山生态环境进行监测,用变权欧氏距离方法建立评价模型,可知月恢复治理/破坏土地面积这一指标对环境影响最大,并得出了环境质量等级以及具体细化数值。与其他评价方法相比,变权欧氏距离可以得出矿山生态环境质量等级和具体等级数值,能够精确地反映出矿山生态环境质量水平。     

低分子量有机酸影响可变电荷土壤吸附铜的机制

采用平衡实验法研究了水杨酸和邻苯二甲酸对砖红壤吸附铜的影响,并通过吸附铜的解吸实验探讨了有机酸对铜吸附的影响机制.结果表明,有机酸可以增加土壤对铜的吸附量,与对照相比,有机酸体系中吸附的铜的解吸量高.有机酸对铜吸附的影响随体系pH值的增加而增大,约在pH4.3(水杨酸体系)或pH4.5(邻苯二甲酸体系)达最大,然后逐渐减小.土壤对有机酸的吸附量越高,有机酸对铜吸附的影响程度越大.有机酸可以通过形成表面三元络合物和改变土壤的表面电荷2种机制影响土壤对铜的吸附.水杨酸体系中铜的解吸增量与吸附增量的百分比在76%～89%之间,说明水杨酸主要是通过增加土壤表面的净负电荷量来增加铜的静电吸附量.