荒漠植物是干旱区具有独特功能性状与资源权衡表征的地带性植物。植物功能性状及其多样性格局与资源权衡策略对群落结构优化和生态系统功能改善起着关键作用。该综述主要从荒漠植物组织、器官功能性状特征、功能性状权衡策略、功能多样性组分及测度3个方面梳理了荒漠植物性状权衡策略与功能多样性研究的进展脉络：1)荒漠植物独特的根、茎、叶功能性状特征揭露了植被对环境变化的响应以及对生态系统功能的影响，基于植物功能性状的研究有助于解决许多生态学的关键性问题；2)作为植物功能性状之间存在的最普遍的联系，权衡策略是经过自然筛选后形成的性状组合，关键性状已经被发掘并创造性的提出了“经济谱”概念。荒漠植物研究过程中，应分析其根、茎、叶的特征属性筛选关键性状，着眼于关键性状间及整株植物性状间的权衡策略；3)功能多样性是影响生态系统运行和发挥作用的生物多样性的重要组成部分，荒漠植物功能多样性能预测和指示群落中物种对于荒漠生态系统功能发挥和过程变化的影响。功能多样性的组分可以从不同角度反映群落的生态位占据状况和资源利用程度，指数的选择要体现在群落内部物种的功能特征之间的差异程度，同时要考虑这些物种自身在群落内的优势程度。本研究为未来荒漠植物功能性状及多样性研究梳理了一些新的研究方向和内容，期望为荒漠植物生理生态学研究的选题和发展提供一些新的思路。

荒漠土壤中微生物生存适应机制及其生态系统功能对揭示干旱区物质转化过程具有重要意义.沿河西走廊东南至西北自然降水递减梯度下设置16个样带,采用高通量测序技术探究土壤细菌和真菌群落多样性特征,揭示微生物多样性、优势菌群与土壤机械组成、养分关系.结果显示:河西走廊荒漠土壤细菌中厚壁菌门(Firmicutes)、变形菌门(Proteobacteria)、放线菌门(Actinobacteria)、拟杆菌门(Bacteroidetes)为优势群落,部分样带厚壁菌门相对丰度最高达85％;真菌中子囊菌门(Ascomycota)和担子菌门(Basidiomycota)为优势群落,其相对丰度均大于>5％.相关性分析显示:粗粉粒(0.05～0.02 mm)、细粉粒(0.25～0.10 mm)、黏粒(<0.002 mm)、有效磷(AP)和解碱氮(AN)对细菌多样性影响极显著,细粉粒(0.25～0.10 mm)、黏粒(<0.002 mm)、有效磷(AP)和解碱氮(AN)对真菌多样性影响极显著(P<0.01).冗余分析显示:细粉粒(0.25～0.10 mm)、有效磷(AP)和有机碳(SOC)对细菌群落影响显著,黏粒(<0.002 mm)和有效磷(AP)对真菌群落影响显著(P<0.05).研究表明了河西走廊荒漠土壤微生物群落结构的组成、变化及影响因子,解释了土壤环境对微生物分布的影响及微生物对土壤生态系统系统发展的作用,为保护生物多样性及荒漠生态服务提供理论参考.

The place of production is closely related to the quality, safety and nutritional quality of Lanzhou lily (Lilium davidii var. unicolor), and its geographical origin traceability and origin confirmation is beneficial to the implementation of the protection of the place of production, the fidelity of characteristic products and the sustainable development of the industry. In this study, isotope ratio mass spectrometry (IRMS) and inductively coupled plasma mass spectrometry (ICP-MS) were used to determine the ratios of 3 stable isotopes (δ13C, δ15N, δ18O) and the content of 16 mineral elements (K, Mg, Ca, Na, B, Fe, Zn, Al, Mn, Cu, Mo, Cr, Cd, Se, As, Pb) in samples from the four main producing areas of Lanzhou lily. Combining principal component analysis (PCA), orthogonal partial least squares discrimination analysis (OPLS-DA) and linear discriminant analysis (linear discriminant analysis, LDA), the classification model of Lanzhou lily from different producing areas was constructed to verify the geographical origin traceability and origin confirmation. The results of the study showed that: δ13C, δ15N, K, Mg, Na, B, Fe, Mn, Cu, Mo, Cr, Cd were significantly different among the production areas (P<0.05); 5 principal components were extracted by PCA analysis, and the cumulative variance contribution rate was 84.36%; LDA original discrimination accuracy rate was 100%; Leave-one-out cross validation (LOO-CV) discrimination accuracy rate was 88.89%; OPLS-DA model correct discrimination rate was 100%, of which the classification effect was optimal. This study shows that a multivariate statistical classification model based on the stable isotope and mineral element contents of Lanzhou lily can effectively distinguish lily from different production areas, promote the establishment and improvement of its traceability system, and is of great significance to the protection and quality control of Lanzhou lily's production area.

Background Place of origin is an important factor when determining the quality and authenticity of Angelica sinensis for medicinal use. It is important to trace the origin and confirm the regional characteristics of medicinal products for sustainable industrial development. Effectively tracing and confirming the material’s origin may be accomplished by detecting stable isotopes and mineral elements. Methods We studied 25 A. sinensis samples collected from three main producing areas (Linxia, Gannan, and Dingxi) in southeastern Gansu Province, China, to better identify its origin. We used inductively coupled plasma mass spectrometry (ICP-MS) and stable isotope ratio mass spectrometry (IRMS) to determine eight mineral elements (K, Mg, Ca, Zn, Cu, Mn, Cr, Al) and three stable isotopes (δ13C, δ15N, δ18O). Principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were used to verify the validity of its geographical origin. Results K, Ca/Al, δ13C, δ15N and δ18O are important elements to distinguish A. sinensis sampled from Linxia, Gannan and Dingxi. We used an unsupervised PCA model to determine the dimensionality reduction of mineral elements and stable isotopes, which could distinguish the A. sinensis from Linxia. However, it could not easily distinguish A. sinensis sampled from Gannan and Dingxi. The supervised PLS-DA and LDA models could effectively distinguish samples taken from all three regions and perform cross-validation. The cross-validation accuracy of PLS-DA using mineral elements and stable isotopes was 84%, which was higher than LDA using mineral elements and stable isotopes. Conclusions The PLS-DA and LDA models provide a theoretical basis for tracing the origin of A. sinensis in three regions (Linxia, Gannan and Dingxi). This is significant for protecting consumers’ health, rights and interests.