Gradient analysis of soil-plant interactions from the alpine-nival ecotone to the snowline on slopes of the Central Great Caucasus (Kazbegi Region, Georgia)

Tamar Jolokhava, Otar Abdaladze, Khatuna Gigauri, Z. Kikvidze
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Abstract

Alpine ecosystems are especially sensitive to climatic changes which affect the relationships among glaciers, snow, vegetation and soils. Our aim was to examine how the variation in the abiotic environment affected soil properties and plant species distribution at regional and local scales. We sampled soil and vegetation along two transects set on the opposite-facing slopes (North versus South), from the alpine-nival ecotone to the snowline (Central Great Caucasus, Kazbegi, Georgia). We measured also soil temperature and controlled for the slope inclination. Multivariate ordination methods were used to link abiotic factors, soil properties and plant species distribution along the gradients. We found that ordination models were better resolved when soil properties were used as environmental variables instead of abiotic ones such as elevation, inclination and slope aspect. Soil pH and plant available potassium were the best predictors of plant species distribution in these habitats. We conclude that the models that account for the role of soils as a mediator between the abiotic environment and vegetation can more accurately describe plant species distribution at local and regional scales: a potentially important amendment with implications for the monitoring of the effects of climate change on vegetation at least in high mountain systems.
格鲁吉亚卡兹贝格地区中高加索高寒交错带到雪线土壤-植物相互作用的梯度分析
高山生态系统对气候变化特别敏感,气候变化会影响冰川、雪、植被和土壤之间的关系。我们的目的是研究非生物环境的变化如何在区域和地方尺度上影响土壤特性和植物物种分布。我们沿着两个位于相对斜坡(北部和南部)的样带对土壤和植被进行了采样,从高山草原交错带到雪线(大高加索中部、格鲁吉亚卡兹贝吉)。我们还测量了土壤温度并控制了坡度。采用多元排序方法将非生物因素、土壤性质和植物物种分布沿梯度联系起来。我们发现,当土壤性质被用作环境变量而不是海拔、倾斜度和坡向等非生物变量时,排序模型可以更好地求解。土壤pH值和植物有效钾是这些生境中植物物种分布的最佳预测因子。我们得出的结论是,考虑到土壤作为非生物环境和植被之间媒介的作用的模型可以更准确地描述地方和区域尺度上的植物物种分布:这是一个潜在的重要修正,对监测气候变化对植被的影响有影响,至少在高山系统中是这样。
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来源期刊
CiteScore
0.80
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0.00%
发文量
36
审稿时长
8 weeks
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