Relationship between stand characteristics and soil properties of two typical forest plantations in the mountainous area of Western Sichuan, China

There is uncertainty and limited knowledge regarding stand characteristics and soil properties of middle-aged pure forest plantations in the mountainous area of Western Sichuan. Plantation forests are almost exclusively planted as monocultures in the Pengzhou forest farm in the western mountainous area of Sichuan Province. This study aimed to assess the spatial and ecological characteristics of middle-aged Cunninghamia lanceolata(Lamb.) Hook. and Cryptomeria fortunei Hooibr. in the Pengzhou forest farm. The relationships and differences between stand growth characteristics and forest soil composition were assessed on the two forests planted simultaneously within the same area and exposed to the same environmental conditions. Cr. fortunei grew sparse, and slower than Cun. lanceolata. Principal component analysis indicated that the soil properties in the Cr. fortunei plantation were better than those in the Cun. lanceolata plantation. Redundancy analysis revealed that the differences in stand structure were affected significantly by the total nitrogen content and pH value. Thus, we propose that Cr. fortunei is planted for priority consideration in the subtropical high mountain area. Further, tending operations and application of fertilizers need to be conducted in Cun. lanceolata forests. Based on theoretical and experimental data, the present study explains why local farmers are more willing to plant Cr. fortunei, and thus provides a useful theoretical reference for the development of sustainable plantations in the future.

松栎林天然更新模拟与不确定性分析

森林天然更新的复杂性和不确定性是森林生态系统动态预测中的关键问题。本研究引入贝叶斯技术和全局敏感性分析,构建基于竞争、气候和地形3类因子的秦岭松栎林天然更新模型。备选模型形式以泊松(Poisson)模型、负二项(negative binomial,NB)模型、零膨胀泊松(zero-inflated Poisson,ZIP)模型和零膨胀负二项(zero-inflated negative binomial,ZINB)模型为基础。同时,根据模型参数传递的不确定性量化分析结果,阐释影响森林更新小概率事件的主导因子。结果表明:ZINB模型在油松和锐齿栎更新模拟中均优于其他模型。林分总断面积、光截留、坡位和生长季最低温是影响松栎林中油松天然更新的最关键因子;而林分总断面积、坡向与海拔的组合、年均温和最热季节降水量则是影响松栎林中锐齿栎天然更新的关键因子。油松更新模拟中,各类因子对模型输出的不确定性贡献率从小到大依次为:竞争因子(25%)<气候因子(29%)<地形因子(46%);锐齿栎更新模拟中为:气候因子(12%)<竞争因子(24%)<地形因子(64%)。油松天然更新数量对生长季最低温和最干季节降水量为正响应,对最干季节均温为负响应;锐齿栎天然更新数量对年均温、生长季最低温和最热季节降水量为正响应,对最干季节均温为负响应。基于贝叶斯技术的ZINB模型可以量化森林更新的影响因子,并解释参数传递的不确定性,是预测森林天然更新的有力工具。

西南地区壳斗科物种丰富度和特有性分布格局模拟及其环境解释

如何准确地模拟物种宏观丰富度格局和特有性中心是生物多样性保护工作的重点,也是生物地理学的热点话题。西南地区是我国壳斗科植物最丰富的地区之一,但物种多样性格局及环境驱动机制尚不清楚。本研究基于西南地区161种壳斗科植物7258个分布点位数据,利用点格局法和物种分布模型两种方式构建了物种丰富度、加权特有性指数和校正加权特有性指数的分布格局,并采用空间自回归模型(SAR)分析上述3个多样性指数与环境因子间的关系。总体上看,物种分布模型模拟的3个指数在空间上比点格局法更为连续,但数值高低分布情况具有相似性:两种方式模拟的物种丰富度高值区主要分布在滇南边缘、桂北部和桂西南部地区(62~89种);加权特有性指数最大值集中在滇南和桂西地区(1.77~5.02);藏东南、秦岭-大巴山、桂西南部和滇东南地区具有最高的校正加权特有性指数(0.07~0.17)。SAR模型结果显示:最干月降雨量、温度季节性变化标准差、海拔变幅和土壤有机碳含量对物种丰富度的影响均显著,最干月降雨量、温度季节性变化标准差、潜在蒸散量和海拔变幅对加权特有性有着显著影响,温度季节性变化标准差、最干月降雨量、历史温度变化、增强型植被指数变异系数和海拔变幅对校正加权特有性的影响显著;SAR模型对物种丰富度、特有性指数和加权特有性指数的拟合效果(R2=0.857、0.733、0.593)分别优于普通线性模型(R2=0.689、0.425、0.422)。综上,水分可获得性、气候季节性、生境异质性、历史气候变化和土壤状况是制约西南地区壳斗科丰富度和特有性分布的最重要因素。滇南、滇东南、桂西南、桂西、秦岭-大巴山以及藏东南地区是壳斗科物种丰富度中心或特有性中心,应受到重点关注和保护。