厄瓜多尔亚马逊地区受石油影响土壤上木本植物的功能特征和表现

Jaime Villacís, F. Casanoves, Susana Hang, Cristina Armas
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摘要

引言植物功能性状被广泛用于预测群落生产力。然而,它们很少被用来预测种植在退化土壤中的木本物种的表现(生长直径、生长高度、存活率和综合反应指数)。目的评估厄瓜多尔亚马逊地区受石油开采活动影响的受干扰土壤中种植的 25 种木本植物的功能特征与表现之间的关系。方法测定每个物种的八个定量功能特征(叶片大小、比叶面积、叶片氮浓度、叶片磷浓度、叶片最小单位、叶片干物质含量、茎比密度和叶片抗张强度)。结果表现优异的木本植物在叶片大小、比叶面积和茎比密度方面均优于表现较差的木本植物。叶氮浓度和茎比密度与综合反应指数有直接关系。叶片大小、叶片磷浓度、叶片干物质含量和叶片抗张强度与积分反应指数呈负相关。结论我们的研究表明,通过叶片和茎的功能性状可以很好地预测受干扰土壤中木本植物的表现,这可能是因为这些性状捕捉到了大部分环境和邻近条件。
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Functional traits and performance of woody species on oil- affected soils of the Ecuadorian Amazon
Introduction: Plant functional traits are widely used to predict community productivity. However, they are rarely used to predict the performance (in terms of growth diameter, growth height, survival, and integral response index) of woody species planted in degraded soils. Objective: To evaluate the relationship between the functional traits and the performance of 25 woody species planted in disturbed soils affected by oil extraction activities in Ecuadorian Amazon. Methods: Eighteen permanent sampling plots were established and five 6-month-old seedlings of each 25 species were randomly planted in each plot (125 individuals per plot), at a distance of 4×4 m. Eight quantitative functional traits (leaf size, specific leaf area, leaf nitrogen concentration, leaf phosphorus concentration, leaf minimum unit, leaf dry matter content, stem specific density and leaf tensile strength) were determined for each species. Results: The woody species with high performance shows greater leaf size, specific leaf area and Stem Specific Density than those showing low performance. Leaf nitrogen concentration and stem specific density had a direct relationship with the integral response index. The leaf size, leaf phosphorus concentration, leaf dry matter content and leaf tensile strength sows a negative relationship with the integral response index. Conclusions: Our study showed that the performance of woody species o disturbed soils can be predicted satisfyingly by leaf and stem functional traits, presumably because these traits capture most of environmental and neighborhood conditions.
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