Interspecific relationships and biogeography of some Bornean tree shrews (Tupaiidae: Tupaia), based on DNA hybridization and morphometric comparisons1

The interspecific relationships and biogeography of seven southeast Asian tree shrew species in the genus Tupaia were examined by DNA hybridization and multivariate morphometric analysis. Urogale everetti served as the outgroup. DNA hybridization data indicate that T. tana is most closely related to T. tnontana, and they form a clade with T. minor. Morphometric comparisons indicate that T. tana and 77 minor, and 7. montana and T palawanensis, form groups that, together, are most similar to T. glis. T. javanica and U. everetti cluster outside the rest of Tupaia. The DNA hybridization data support a model of Bornean speciation driven by sea‐level changes. They also indicate either (1) that there is a large variation in the rate of tree shrew evolution or (2) that U. everetti may in fact be a member of the ingroup. When considered in light of the phylogenetic results, the morphometric data suggest substantial convergence in body size or correlation in character changes.     

A highly invasive malaria parasite has expanded its range to non-migratory birds in North America

Parasite range expansions are a direct consequence of globalization and are an increasing threat to biodiversity. Here, we report a recent range expansion of the SGS1 strain of a highly invasive parasite, Plasmodium relictum, to two non-migratory passerines in North America. Plasmodium relictum is considered one of the world''s most invasive parasites and causes the disease avian malaria: this is the first reported case of SGS1 in wild non-migratory birds on the continent. Using a long-term database where researchers report avian malaria parasite infections, we summarized our current understanding of the geographical range of SGS1 and its known hosts. We also identified the most likely geographical region of this introduction event using the MSP1 allele. We hypothesize that this introduction resulted from movements of captive birds and subsequent spillover to native bird populations, via the presence of competent vectors and ecological fitting. Further work should be conducted to determine the extent to which SGS1 has spread following its introduction in North America.     

基于激光雷达数据的物种分布模拟: 以美国加州内华达山脉南部区域食鱼貂分布模拟为例

生态位模型通过拟合物种分布与环境变量之间的关系提供物种空间分布预测, 在生物多样性研究中有广泛应用。激光雷达(LiDAR)是一种新兴的主动遥感技术, 已被大量应用于森林三维结构信息的提取, 但其在物种分布模拟的应用研究比较缺乏。本研究以美国加州内华达山脉南部地区的食鱼貂(Martes pennanti)的分布模拟为例, 探索LiDAR技术在物种分布模拟中的有效性。生态位模型采用5种传统多类分类器, 包括神经网络、广义线性模型、广义可加模型、最大熵模型和多元自适应回归样条模型, 并使用正样本-背景学习(presence and background learning, PBL)算法进行模型校正; 同时对这5种模型使用加权平均进行模型集成, 作为第6个模型。此外, 一类最大熵模型也被用于模拟该物种的空间分布。模型的连续输出和二值输出分别使用AUC (area under the receiver operating characteristic curve)以及基于正样本-背景数据的评价指标F_pb进行评价。结果表明, 仅考虑气候因子(温度和降水)时, 7个模型的AUC和F_pb平均值分别为0.779和1.077; 当考虑LiDAR变量(冠层容重、枝下高、叶面积指数、高程、坡度等)后, AUC和F_pb分别为0.800和1.106。该研究表明, LiDAR数据能够提高食鱼貂空间分布的预测精度, 在物种分布模拟方面存在一定的应用价值。     

印度野牛在中国的分布及其栖息地适宜性分析

印度野牛(Bos gaurus)在中国分布在云南省南部和西藏藏南地区。2016年2-3月和2016年11-12月, 我们在西双版纳州、普洱市及高黎贡山区域开展印度野牛调查, 并对藏南地区进行文献调研, 共获得47处印度野牛有效出现位点数据。目前云南地区印度野牛种群数量约180-210头, 面临着严重的生存危机; 在高黎贡山未发现印度野牛。利用印度野牛分布位点数据, 选取地形、土地覆被类型、人类足迹指数、距水源和道路距离以及气候共5类14种因子作为自变量建立MaxEnt生态位模型, 通过模拟云南和西藏印度野牛的适宜分布区, 分析各环境因子对该物种分布的影响。结果表明: 模型预测精度较高, 平均AUC (area under the curve)值为0.994。印度野牛潜在适宜栖息地可划分为高适宜、次适宜、低适宜和不适宜4个等级。高适宜栖息地主要分布在云南省西双版纳和藏南地区, 其中西双版纳部分镶嵌有次适宜和低适宜栖息地斑块, 面积为4,987 km²; 藏南部分高适宜栖息地面积为13,995 km²。次适宜栖息地主要分布于云南省南部、高黎贡山区域以及藏南高适宜栖息地区的边缘, 总面积为32,778 km²。低适宜和不适宜栖息地区连接成片, 位于云南省中部、北部地区和藏南地区北部。Jackknife检验结果显示, 季节温度变化和等温线对印度野牛潜在分布区的影响较大, 而地形因子和降水变化的影响较弱。遥感地物分类结果表明: 橡胶林等人工经济林的种植占据了西双版纳野牛的适宜栖息地, 降低了景观连接度。建议管理部门加大对天然林的保护力度, 控制橡胶林等人工林在野牛适宜栖息地的扩张, 提高景观连接度, 以促进该物种种群的恢复。     

Colony‐level behavioural variation correlates with differences in expression of the foraging gene in red imported fire ants

Among social insects, colony‐level variation is likely to be widespread and has significant ecological consequences. Very few studies, however, have documented how genetic factors relate to behaviour at the colony level. Differences in expression of the foraging gene have been associated with differences in foraging and activity of a wide variety of organisms. We quantified expression of the red imported fire ant foraging gene (sifor) in workers from 21 colonies collected across the natural range of Texas fire ant populations, but maintained under standardized, environmentally controlled conditions. Colonies varied significantly in their behaviour. The most active colonies had up to 10 times more active foragers than the least active colony and more than 16 times as many workers outside the nest. Expression differences among colonies correlated with this colony‐level behavioural variation. Colonies with higher sifor expression in foragers had, on average, significantly higher foraging activity, exploratory activity and recruitment to nectar than colonies with lower expression. Expression of sifor was also strongly correlated with worker task (foraging vs. working in the interior of the nest). These results provide insight into the genetic and physiological processes underlying collective differences in social behaviour. Quantifying variation in expression of the foraging gene may provide an important tool for understanding and predicting the ecological consequences of colony‐level behavioural variation.     

水文变异下长江荆南三口河道内生态需水量变化及贡献因素

基于1951—2015年长江荆南三口5站实测原型年径流量序列,采用Mann-Kendall等方法检测其径流序列的突变年份.在此基础上,运用GEV概率密度最大流量法计算荆南三口河道内生态需水量,并从多时空尺度视角分析河道内生态需水量的时空差异及其贡献因素.结果表明: 研究期间,新江口、沙道观、康家岗、管家铺和弥陀寺水文站的第一次径流突变年份分别为1990、1959、1959、1972和1972年,并将第一次突变以前的月均流量序列作为水文变异前的水文序列.在水文变异条件下,长江荆南三口1—12月的各月生态需水量分别为69.63、26.15、55.65、452.65、2166.44、4660.83、10875.66、9966.49、7868.38、4773.60、1655.01和338.49 m³·s^-1.新江口、沙道观、康家岗、管家铺和弥陀寺5个水文站的年均生态需水量分别为901.57、507.00、221.30、1438.03和581.62 m³·s^-1.水文变异后,荆南三口满足河道内生态需水的频率大幅下降,由变异前的55%以上下降至变异后的20%以下,生态需水缺乏现象严重.影响荆南三口河道内生态需水时空变化的因素主要为不同时期水利工程、各行业用水量等人类活动.     

生态贫困视角下的贫困县多维贫困综合度量

作为国家扶贫开发决策实施的重要单元,贫困县贫困程度及其致贫原因的识别和评估是国家“精准扶贫”战略实施的前提和保障.本文从生态贫困的视角,设计了顾及自然环境-经济-社会可持续协调发展的县级别多维贫困度量指标体系,构建基于贫困指数-最小方差模型(PI-MVM)的县级多维贫困度量模型,以6个连片特困区的249个县为典型研究区,系统揭示片区-县级层面上的贫困程度、致贫原因及其空间分布特征.结果显示: 各片区的综合贫困程度由北向南逐渐加重,各片区县存在“从北向南、从东到西,贫困程度逐渐加重”的趋势;乌蒙片区西部、秦巴片区西北部各县贫困程度的高-高聚集现象突出;秦巴中南部以及乌蒙片区受自然环境因素影响较大,贫困程度较深.一般致贫型片区县较多,主导致贫型片区县聚集在贫困程度较低的片区;经济因素对贫困的缓解作用逐渐下降,自然环境、社会发展因素的影响逐渐明显.研究结果可以更加精准地全面把握贫困县的贫困区划特征,为指导研究区早日脱贫提供辅助决策技术支撑.