Multi-scale analysis of plant species richness in Serengeti grasslands
Multi-scale analysis of plant species richness in Serengeti grasslands
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DOI：
10.1111/j.1365-2699.2006.01598.x
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发表时间：
2007-02-01
影响因子：
3.9
通讯作者：
McNaughton, Samuel J.
中科院分区：
文献类型：
--
作者：
Anderson, T. Michael;Metzger, Kristine L.;McNaughton, Samuel J.
目的研究环境因子与植物物种丰富度之间的尺度依赖关系。此外，我们的目的是确定生态位关系和栖息地异质性的尺度，如A。Shmida & MY. Wilson（1985）Journal of Biogeography，12，1-20，operate in the savanna graduates that are the focus of this study.Location Savanna graduate plants communities of Serengeti国家公园，Tanzania.Methods植物物种丰富度在10（2）个修改的Whittaker样地中取样，并测试与两个气候因子的关联，平均年降雨量（MAP）和潜在蒸散量（PET），景观变量：样地纵横比（ASP）和地形变异（TOPO）。尺度依赖性进行评估后，改变三个方面的空间尺度：粮食，程度和重点进行回归。通过分析1、10、10（2）和10（3）m（2）处的植物丰富度来改变谷物;通过将样本之间的最大距离限制在75、100、125和150 km来调查范围;通过根据地理陆地区域在空间上平均样本来操纵焦点。在我们的数据范围内，我们假设生态位关系由气候因子和生境异质性景观factor.Results在所有10（2）的地块，植物物种丰富度1和10（2）m2之间有一个负相关的PET和MAP弱的正相关。10（3）m（2）处的植物物种丰富度与TOPO呈正相关，与气候因子的相关性较弱。ASP在10 ~ 10（3）m（2）粒级之间的模型中存在，但与丰富度的正相关性很弱。当焦点转移到陆地区域时，植物物种丰富度和解释变量之间的关联加强，但没有质的不同。在75和100公里的空间范围内，PET是最强的植物物种丰富度在所有空间颗粒的相关性。在空间范围>= 125 km时，PET解释了空间颗粒= 150 km时的大部分模型方差。最后，塞伦盖蒂的植物物种丰富度关系的迹象，强度和形状与描述整个非洲大陆木本植物物种丰富度的宏观模式密切相关。
Aim To assess scale dependence between environmental factors and plant species richness. Additionally, we aimed to identify the scales at which niche relations and habitat heterogeneity, as hypothesized by A. Shmida & MY. Wilson (1985) Journal of Biogeography, 12, 1-20, operate in the savanna grasslands that were the focus of this study.Location Savanna grassland plant communities of Serengeti National Park, Tanzania.Methods Plant species richness was sampled in 10(2) modified Whittaker plots and tested for associations with two climate factors, mean annual rainfall (MAP) and potential evapotranspiration (PET), and two landscape variables, plot aspect (ASP) and topographic variation (TOPO), using multiple regressions. Scale dependence was assessed by conducting regressions after altering three aspects of spatial scale: grain, extent and focus. Grain was altered by analysing plant richness at 1, 10, 10(2) and 10(3) m(2); extent was investigated by restricting the maximum distance between samples to 75, 100, 125 and 150 km; and focus was manipulated by averaging samples spatially according to geographical land regions. Within the context of our data, we assumed that niche relations were represented by climate factors and habitat heterogeneity by landscape factors.Results Across all 10(2) plots, plant species richness between 1 and 10(2) m(2) had a negative relation to PET and a weak positive relation to MAP. Plant species richness at 10(3) m(2) had a positive association with TOPO and weaker associations with climate factors. ASP stayed in the model between grains of 10 and 10(3) m(2), but had a very weak positive association with richness. When the focus was changed to land regions, associations between plant species richness and explanatory variables strengthened, but were not qualitatively different. At spatial extents of 75 and 100 km, PET was the strongest correlate of plant species richness across all spatial grains. At spatial extents >= 125 km, PET explained the majority of the model variance at spatial grains = 150 km). Finally, the signs, strength and shape of plant species richness relationships in Serengeti closely match those that describe macro-scale patterns of woody plant species richness across the entire African continent.