Seasonal Nutrient Resorption and Lignin Change in leaves of Turkey Oak on Northern and Southern Slope Aspects

IF 0.4 4区 环境科学与生态学 Q4 ECOLOGY
B. Sürmen
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引用次数: 0

Abstract

ABSTRACT Nutrient resorption is a critical factor for nutrient use strategies developed by plants. Especially nitrogen (N) and phosphorus (P) are the most essential reabsorbed nutrient elements. The leaves' N and P concentrations are closely related to foliar lignin contents. The study aimed to investigate the effects of northern and southern slope aspects on the foliar nutrient resorption in the Mediterranean species of Turkey oak (Quercus cerris var. cerris). The relationships among selected leaf traits, foliar nutrient resorption of N and P, the seasonal lignin change, and the soil traits were analyzed. A principal component analysis was performed to interpret the effect of soil properties on foliar N, P, and lignin concentrations. N resorption efficiency (78.84%) was higher on the northern slope. P resorption efficiency (53.87%) and seasonal lignin change (69.87) were higher on the southern slope. As a result, the slope aspect affects the foliar N, P, and lignin concentrations. Also, foliar lignin concentration was negatively correlated with N resorption efficiency and positively correlated with P resorption efficiency.
南北坡土耳其栎叶片养分吸收和木质素的季节性变化
摘要养分吸收是植物制定养分利用策略的关键因素。尤其是氮(N)和磷(P)是最重要的再吸收营养元素。叶片氮、磷含量与叶片木质素含量密切相关。本研究旨在研究北部和南部斜坡对地中海土耳其栎(Quercus cerris var.cerris)叶片养分吸收的影响。分析了所选叶片性状、叶片氮磷养分吸收、木质素季节变化和土壤性状之间的关系。进行了主成分分析,以解释土壤性质对叶面氮、磷和木质素浓度的影响。北坡的氮吸收效率较高(78.84%)。P吸收效率(53.87%)和木质素季节性变化(69.87)在南坡较高。因此,坡度影响叶片的氮、磷和木质素浓度。叶片木质素浓度与氮吸收效率呈负相关,与磷吸收效率呈正相关。
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来源期刊
Polish Journal of Ecology
Polish Journal of Ecology 环境科学-生态学
CiteScore
1.10
自引率
0.00%
发文量
9
审稿时长
18-36 weeks
期刊介绍: POLISH JOURNAL OF ECOLOGY (formerly Ekologia polska) publishes original scientific research papers dealing with all aspects of ecology: both fundamental and applied, physiological ecology, evolutionary ecology, ecology of population, community, ecosystem, landscape as well as global ecology. There is no bias regarding taxons, ecosystems or geographical regions.
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