北长山岛森林乔木层碳储量及其影响因子

人工林是庙岛群岛典型的陆地生态系统的组成部分,对维护海岛地区生态环境具有重要作用。采用现有生物量相对生长方程和样地调查数据相结合的方法,以庙岛群岛中北长山岛为研究区,对海岛黑松纯林与黑松×刺槐混交林两种林型的碳储量进行了估算,并分析了土壤质地及其理化性质对海岛乔木层碳储量的影响。结果表明:黑松乔木层平均碳储量为84.00 t/hm²,接近于世界平均水平(86.00 t/hm²);黑松×刺槐混交林乔木层平均碳储量为29.60 t/hm²,高于山东省乔木层的平均碳储量(27.62 t/hm²)。应用因子分析法研究影响乔木层碳储量的主要因子,结果表明:土壤质地、pH值、含水量及含盐量是影响海岛乔木碳储量重要的影响因子。北长山岛土壤全氮、总磷、土壤有机质、碳氮比等其他理化性质对乔木层碳储量影响不是非常明显。

Storage and drivers of forests carbon on the Beichangshan Island of Miaodao Archipelago

The artificial plantations is a typical terrestrial ecosystem on the island of Miaodao Archipelago, which plays a key role in regional ecological environment. The Pinus thunbergii and Pinus thunbergii×Robinia pseudoacacia are the typical trees on the Beichangshan island of Miaodao Archipelago in Shandong Province. But they are often disregarded due to their ecosystem services, particularly the carbon sequestion, which are not well understood or quantified. This paper is to estimate the trees carbon storage on the island with the biomass allometric equation and the data investigation in stand sample plot, and discuss the impact of different parameters in the island on trees carbon storage. The results showed that the average carbon storage was 84.00 t/hm² for the Pinus thunbergii, which was close to the average level in the world (86.00 t/hm²), and the average carbon storage was 29.60 t/hm² for the Pinus thunbergii×Robinia pseudoacacia, which was higher than that of the average carbon stock in Shandong Province (27.62 t/hm²). The average carbon storage of the Pinus thunbergii was higher than that of the Pinus thunbergii×Robinia pseudoacacia, which the difference was significant (P < 0.05). The allocation of carbon storage in their different organs for the Pinus thunbergii and mixed forest in tree layer was trunk> root> branch> leaf. The Pinus thunbergii forests is more suitalbe for carbon storage than that of Pinus thunbergii×Robinia pseudoacacia forests on the Beichangshan island. In order to investigate the impact of different parameters in the island on trees carbon storage, a correlation matrix including environmental factors and soil texture was calculated. The carbon storage in the island forests showed significant (P < 0.05) correlations with soil class, slope, aspect, elevation. However, all these parameters were interrrelated, and cannot be regarded as independent determining factors. Therefore, the principal component analysis (PCA) was carried out in order to extract the main factors controlling carbon storage in the island forests. The PCA extracted two factors that explained 50% of the total variance. Factor 1 was characterized by high loadings of the parameters clay soil (-0.898), silt soil (0.893), sand soil (0.922). Factor 2 was driven by slope (0.770), aspect (-0.722), elevation (0.946). A multiple linear regression model revealed factor 1 as most important factor (Beta value of 0.290) for carbon storage in the island forests followed by factor 2 (Beta value of 0.019). To gain insight into the driving factors for carbon storage in the island forests over soil physical-chemical properties, the correlations of moisture, pH, salinity, total nitrogen, total phosphorus, total organic carbon, total carbon, C/N ratios in the island soil was calculated. Factor 1 was characterized by high loadings of the parameters total nitrogen (0.842), total organic carbon (0.899), total carbon (0.990). Factor 2 was driven by total phosphorus (0.931), C/N ratios (-0.925). Factor 3 was characterized by moisture (0.694), pH (0.744), salinity (-0.666). A multiple linear regression model showed factor 3 as most important factor (Beta value of-0.694) for the carbon storage in the island forests followed by factor 1 (Beta value of-0.192) and factor 2 (Beta value of-0.106). We conclude that soil texture, pH, moisture and salinity in the island soil were primary controlling factors on the average carbon stock of the forests on the Beichangshan island.