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作 者:张石宝[1]
机构地区:[1]中国科学院昆明植物研究所资源植物与生物技术所级重点实验室,云南昆明650201
出 处:《植物分类与资源学报》2014年第1期47-55,共9页Plant Diversity
基 金:National Natural Science Foundation of China(31170315);the West Light Foundation of the Chinese Academy of Sciences
摘 要:松属的思茅松(Pinus kesiya var.langbianensis)、云南松(P.yunnanensis)和高山松(P.densata)是组成中国西南不同海拔针叶森林的主要树种,然而这三个树种在发育速度尤其是高生长方面表现出明显的差异。为了弄清引起这些变异的生理和形态学原因,本文将三种松树种植于同一环境下,对其光合作用、生物量分配、生长速率和叶片性状进行了研究。研究发现,与来源于高海拔的树种相比,低海拔的树种有更高的株高、以及更大的干物质重量、相对生长速率、叶质比、茎质比和比叶面积,但叶片氮含量、碳含量和根质比较低。高海拔树种的光合速率并不明显低于低海拔树种。相对生长速率和树高均与叶质比呈显著正相关,与根质比负相关,但与最大光合速率没有显著关系。这些结果表明,生物量的分配式样和长期的形态特性能够更好地预测不同海拔松树的生长表现。The conifer forests in southwestern China are mainly dominated by three vicariant species within Pinus: P. kesiya vat. langbianensis, P. yunnanensis, and P. densata. Their sites range from lower to higher elevations, re spectively, and each species shows differences in rates of development, especially with regard to height. To identify the physiological and morphological causes of this inherent variation, photosynthesis, biomass partitioning, growth rates and leaf traits were investigated of plants cultivated under the same environmental conditions. Trees of the spe cies native to the lower elevation were taller, and had higher values for dry weight, relative growth rate (RGR) , leaf mass fraction (LMF) , stem mass fraction (SMF) , and specific leaf area per unit mass (SLA), relative to those from the higher elevations. However, their leaf N and C contents per unit area, and their root mass fraction (RMF) , were smaller than those of high-elevation trees. Photosynthetic capacity in species from high elevations was not signif icantly reduced from the level calculated for trees from lower elevations. Both RGR and tree height were positively correlated with LMF and negatively with RMF, but no significant positive correlations were found with maximum pho- tosynthetic rate determined on both an area-basis (Amax ) and mass-basis (A ). These findings suggest that the patterns of biomass partitioning and long-term morphological traits are better predictors of performance among trees of different Pinus species growing along an elevational gradient.
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