中国生物多样性核心监测指标遥感产品体系构建与思考

生物多样性的稳定维持关乎人类生存发展与地球健康。生物多样性核心监测指标(Essential Biodiversity Variables, EBVs)旨在结合地面调查与遥感技术, 为大尺度、长时间序列的生物多样性监测提供新的解决方案。然而, 目前学界仍然缺乏一套国家尺度标准化EBVs遥感监测产品数据集, 以进行生物多样性评估。本研究旨在对中国生物多样性核心监测指标遥感产品进行体系构建与思考, 首先综述了目前EBVs的遥感研究概况, 并根据EBVs研究文献的数量进行调研分析; 同时, 本文在已有遥感生物多样性产品优先标准的基础上, 添加了“可重复性”的新标准, 并据此构建了中国EBVs遥感产品体系与监测数据集的指标清单, 最终对中国EBVs遥感研究存在的问题进行思考与讨论。本研究可为中国的生物多样性遥感监测提供科学依据, 有望为中国生物多样性政策的制定提供支撑。     

On the independence of time and strain effects in the stress relaxation of ligaments and tendons

The hypothesis of variables separation, namely the time and the strain separation in the relaxation function, is widely used in soft tissue biomechanics. Although this hypothesis is central to several biomechanical models, only few experimental works have tried to verify it. From these studies, contradictory results have been found. Moreover, it has recently been noted that no such experimental verification has been performed for ligament tissues. In this paper, an experimental method is developed to test the hypothesis of variables separation. This method is then used with human cruciate ligaments and patellar tendons. It is shown that the use of the variables separation hypothesis is justified at least for strain values lower than 16% for anterior cruciate ligament, lower than 12% for posterior cruciate ligament and lower than 6% for patellar tendon. The method presented in this paper could be used to verify the validity of variables separation for other tissues.     

太行山猕猴髋骨变量研究初报

本文对22例（♂11,♀11）成年太行山地区猕猴髋骨有关变量进行测量,通过有关变量单因素方差分析、R型聚类和回归分析,结果表明：太行山猕猴的髋骨变量有较明显的自身特征,髋骨有关变量在雌雄之间有明显差异。     

普通鳾的巢位选择和繁殖成功巢特征

普通对巢位具有选择性,利用树种共7种,利用率不同,利用树洞类型有两种,啄洞利用率高,结洞低。洞口朝向在西至西偏北45°方向的树洞利用率最低,其它方向差异不大。洞口处树的直径、洞口纵径、洞内径、洞深和洞周围10m范围,树的密度5个巢位变量在利用和未利用树洞之间差异极显著(P<001),洞口横径,洞口处树干与垂直方向夹角和洞口方向90°角10m范围树的密度差异显著(P<005),其余变量差异不显著(P>005)。23巢平均窝卵数778±095,孵化率8994%,出飞率9627%。30个巢中成功巢和失败巢的11个巢位特征比较发现,洞高和洞口方向90°角10m范围内树的密度差异极显著,洞口纵径和洞口横径差异显著,其余变量差异不显著。     

Fuzzy Rough Set algorithm with Binary Shuffled Frog-Leaping (BSFL-FRSA): An innovative approach for identifying main drivers of carbon exchange in temperate deciduous forests

The spatial variability, driving forces, and uncertainties of the net ecosystem exchange (NEE) of carbon between the temperate forests and the atmosphere remain elusive. Here, we proposed a fuzzy rough set algorithm with binary shuffled frog leaping (BSFL-FRSA) to identify main driving variables and define the contribution rate of main drivers to NEE. As a case study, we applied the approach to nine deciduous forest eddy covariance flux sites in the northeastern United States. The results show that the BSFL-FRSA effectively retained most information using just a few variables, and it performed better than the GA-FRSA (fuzzy rough set with genetic algorithm). Temperature, radiation, and soil water content were identified as the most influential variables (impact in descending order) to NEE across all sites. Soil temperature was the most important variable explained 59.6% of the NEE variance. Soil temperature and net radiation together, explained 72.7% of the NEE variance, was the most important two variables among all possible two-variable combinations. The most influential three variables on NEE among all possible three-variable combinations were soil temperature, net radiation, and soil water content or relative humidity (explained 81.1% of the NEE variance). The variance attribution approach presented here is generic and can be applied to other studies; the dominant influence of soil temperature begs for accurate characterization of soil temperature dynamics in time and space particularly in the global warming context.     

A thermodynamic view of networks

Networks can be described by the frequency distribution of the number of links associated with each node (the degree of the node). Of particular interest are the power law distributions, which give rise to the so-called scale-free networks, and the distributions of the form of the simplified canonical law (SCL) introduced by Mandelbrot, which give what we shall call the Mandelbrot networks. Many dynamical methods have been obtained for the construction of scale-free networks, but no dynamical construction of Mandelbrot networks has been demonstrated. Here we develop a systematic technique to obtain networks with any given distribution of the degrees of the nodes. This is done using a thermodynamic approach in which we maximise the entropy associated with degree distribution of the nodes of the network subject to certain constraints. These constraints can be chosen systematically to produce the desired network architecture. For large networks we therefore replace a dynamical approach to the stationary state by a thermodynamical viewpoint. We use the method to generate scale-free and Mandelbrot networks with arbitrarily chosen parameters. We emphasise that this approach opens the possibility of insights into a thermodynamics of networks by suggesting thermodynamic relations between macroscopic variables for networks.