城市公园绿地水、热与CO2通量观测与分析

水、热和CO2通量是评价城市绿地生态效益的重要指标。在北京海淀公园中部和边缘架设涡度相关系统,连续观测和定量研究城市公园绿地影响下的通量变化特征。结果表明,公园绿地所获得的净辐射在植被生长季节大部分用于植被的蒸散作用,潜热大于显热;而在植被非生长季节大部分用于显热,潜热数值非常小。晴天显热与潜热的比值在春季随着植被枝叶的生长逐渐减少,到夏季达到最小值约1/3,在秋季随着植被叶片枯黄逐渐变大,冬季达到数倍。公园绿地能量平衡率在52%～83%,普遍存在能量不平衡。公园中部的潜热观测值大于公园边缘,而显热小于公园边缘;公园中部CO2通量日均值为负,公园绿地是CO2汇。公园绿地在植被生长季节具有明显的降温增湿、吸收CO2等生态效应。     

基于过程模型的长白山自然保护区森林植被净第一性生产力空间尺度转换方法

净第一性生产力(Net Primary Productivity,NPP)是反映林分和生态系统结构特征的最重要的参数之一,其空间分布可为自然资源管理和可持续发展提供高度综合的信息,是全球变化和碳循环研究中的一个非常重要的组成部分。为了得到NPP的空间尺度转换算法,利用改进的北部生态系统生产力模拟模型(Improved Boreal Ecosystem Productivity Simulator,IBEPS),分别采用高分辨率(30m)的ETM 和低分辨率(1km)的MODIS遥感数据,模拟了长白山自然保护区不同分辨率森林植被的净第一性生产力。对模拟得到的30m分辨率的NPP结果,采用尺度上推(upscaling)的方法将其转换为1km分辨率的NPP结果(分布式的NPP,Distributed NPP),并将转换后的NPP与直接利用1km分辨率的遥感数据计算得到的NPP结果(聚合式的NPP,Lumped NPP)进行比较,以分布式模式计算的结果为基准,对聚合式的计算结果进行尺度效应校正。在对NPP进行尺度效应校正时,根据不同分辨率下土地覆盖类型(Land cover)的亚像元面积比信息,采用基于结构的分析方法对模拟的NPP结果进行校正,结果表明经过尺度效应校正后NPP的模拟精度要比原始的NPP计算精度有所提高,相关系数从校正前的0.898提高到0.960,标准偏差由校正前的49.84gC/m2减小到41.02gC/m2。采用这种方法可以很好的解决大尺度遥感应用的需要,为定量遥感分析和应用提供理论基础。     

Culture and neural differentiation of rat bone marrow mesenchymal stem cells in vitro

Adult bone marrow mesenchymal stem cells (MSCs) can differentiate into several types of mesenchymal cells, including osteocytes, chondrocytes, and adipocytes, but can also differentiate into non-mesenchymal cells, such as neural cells, under appropriate experimental conditions. Until now, many protocols for inducing neuro-differentiation in MSCs in vitro have been reported. But due to the differences in MSCs' isolation and culture conditions, the results of previous studies lacked consistency and comparability. In this study, we induced differentiation into neural phenotype in the same MSCs population by three different treatments: beta-mercaptoethanol, serum-free medium and co-cultivation with fetal mouse brain astrocytes. In all of the three treatments, MSCs could express neural markers such as NeuN or GFAP, associating with remarkable morphological modifications. But these treatments led to neural phenotype in a non-identical manner. In serum-free medium, MSCs mainly differentiated into neuron-like cells, expressing neuronal marker NeuN, and BME can promote this process. Differently, after co-culturing with astrocytes, MSCs leaned to differentiate into GFAP(+) cells. These data confirmed that MSCs can exhibit plastic neuro-differentiational potential in vitro, depending on the protocols of inducement.     

Characterization and flocculating properties of an extracellular biopolymer produced from a Bacillus subtilis DYU1 isolate

Biopolymer DYU500 produced from Bacillus subtilis DYU1 was found to have excellent flocculating ability. With the addition of 40 mg-DYU500/L and 50 mM CaCO₃, the optimum temperature for flocculation performance of DYU500 was 30 °C, giving the highest flocculating activity and rate of 13.5 and 97%, respectively. Analysis with Fourier transform infrared spectrophotometry (FT-IR), nuclear magnetic resonance spectrometry (NMR) and amino acid identification shows that the DYU500 biopolymer mainly possesses the structure of poly-glutamic acid (PGA). The average molecular weight of DYU500 was about (3.16–3.20) × 10⁶ Da as determined by gel permeation chromatography. The major components of biopolymer DYU500 were total sugars, uronic acids, proteins and polyamides (homopolymer of glutamic acid), accounting for a weight ratio of approximate 14.9, 2.7, 4.4 and 48.7% (w/w), respectively. The flocculating activity of DYU500 in the kaolin suspension was markedly stimulated by the addition of bivalent cations Ca²⁺ or Mg²⁺ in optimum concentration ranges of about 0.15–0.90 and 0.10–0.90 mM, respectively. The synergistic effect of cations was most effective at a weak acidic or neutral pH (6.0–7.0). The flocculating activity of DYU500 linearly decreased with an increase in incubation temperature and the activity was completely lost when heating upon 120 °C, arising from the destruction of the polyamides structure of DYU500. Moreover, mechanisms describing the flocculation process with DYU500 were proposed based on the experimental observations.     

How climate and soil properties affect the abundances of nitrogen-cycling genes in nitrogen-treated ecosystems: a meta-analysis

Plant and Soil - The abundance of nitrogen (N)-cycling genes is frequently used to indicate N cycling and predict N2O emissions. However, it remains difficult to clearly define how soil N-cycling...     

城市生态韧性时空变化及情景模拟研究——以杭州市为例

从韧性的特征角度研究城市生态韧性水平的变化机制,探究城市防范化解生态风险能力的时空差异,以此明确城市分区生态治理的重要任务,是实现韧性城市生态风险防控的有利途径。从抵抗力、适应力和恢复力3个方面构建了城市生态韧性评估模型,并以杭州为例,评估了其1995—2015年城市生态韧性时空变化格局,再者利用空间自相关模型对2015年杭州生态韧性分区管理模式进行了探究。最后,基于FLUS模型模拟了2035年基准和创新创业导向的两种情景下的城市土地利用空间格局,并评估了不同城市发展情景下的生态韧性水平空间分布情况。基于以上研究得到以下结论:(1)1995—2005年,生态韧性低值区域向东北和东南方向扩张,而生态韧性高值水平区域明显减少。2005—2015年,杭州西北部和西部原本存在的中等韧性水平区域也转为低等水平。(2)2015年,城市东北区域呈现低韧性水平-高排污企业密度的集聚分布,说明该区域环境生态风险防范化解能力比较低,需要加大环境监测和生态治理的资金投入,严防重大环境污染事件的发生。(3)创新创业导向的"创新天堂"城市发展情景比基准情景下2035年杭州整体生态韧性水平更高,主要影响因素在于前...     

基于土地利用/覆被变化的伊河流域生态系统服务供需风险时空演变

生态系统服务的供需矛盾造成土地利用方式不合理,引发各种生态环境问题,制约和影响流域可持续发展和居民福祉提升,加强生态系统服务供需关系的研究具有重大意义。以具有“山地—丘陵—平原”景观的河南省伊河流域为研究区,首先利用基于土地利用的生态系统服务矩阵对生态系统服务的供给与需求进行制图,分析生态系统服务供需的时空变化;其次,结合供给动态趋势、需求动态趋势、供需比及供需比趋势比4个指标对伊河流域生态系统服务供需风险时空演变特征分析。结果表明：(1)1980—2018年伊河流域生态系统服务需求水平持续增加,供给水平持续降低,上游调节服务供给水平较强,中下游的供给服务提供水平较高,下游生态系统服务需求远大于上游。(2)栅格尺度下,1980—2018年流域生态系统服务供需高、低风险区占比分别为3.57%、96.43%,2000—2018年高风险等级面积较1980—2000年有所增加。(3)1980—2018年伊河流域7.69%的子流域高风险等级面积大于10%,7号和26号子流域风险等级相对本流域而言处于较高风险程度,2000—2018年的子流域这一比例达15.38%,且都分布于下游,整体上看,近20...     

基于FORCCHN模型的中国典型森林生态系统碳通量模拟

森林生态系统是陆地碳循环的重要组成部分,其固碳能力显著高于其他陆地生态系统,研究森林生态系统碳通量是认识和理解全球变化对碳循环影响的关键。碳循环模型是研究森林生态系统碳通量有效工具。以长白山温带落叶阔叶林、千烟洲亚热带常绿针叶林、鼎湖山亚热带常绿阔叶林和西双版纳热带雨林等4种中国典型森林生态系统为研究对象,利用涡度相关2003-2012年观测数据,评估FORCCHN模型对生态系统呼吸（ER）,总初级生产力（GPP）,净生态系统生产力（NEP）的模型效果。结果表明：（1） FORCCHN模型能够较好的模拟中国4种典型森林生态系统不同时间尺度的碳通量。落叶阔叶林和常绿针叶林ER和GPP的逐日变化模拟效果较好（ER的相关系数分别为0.94和0.92,GPP的相关系数分别为0.86和0.74）;（2）4种森林生态系统碳通量季节动态模拟值和观测值显著相关（P<0.01）,ER、GPP、NEP的观测值和模拟值的R²分别为0.77-0.93、0.54-0.88和0.15-0.38;模型可以很好地模拟森林生态系统不同季节碳汇（NEP>0）,碳源（NEP<0）的变化规律;（3）4种森林生态系统碳通量模拟值与观测值的年际变化有很好的吻合度,但在数值大小上存在差异,模型高估了常绿阔叶林的ER和GPP,略微低估了其他3种森林生态系统ER和GPP。