Scale‐dependent species–area relationship: Niche‐based versus stochastic processes in a typical subtropical forest. (30th May 2022)

• Record Type: Journal Article
• Authors: Ren, Haibao; Svenning, Jens‐Christian; Mi, Xiangcheng; Lutz, James A.; Zhou, Jinxing; Ma, Keping
• Is Part Of: Journal of ecology. Volume 110:Number 8(2022)
• Page Start: 1883
• Page End: 1895
• Publication Date: 2022-05-30
• Subjects: community assembly -- Gutianshan forest dynamics plot -- niche versus neutrality -- passive sampling -- power‐law model -- resource availability and heterogeneity -- spatial effect -- variance partitioning; Plant ecology -- Periodicals; 577.05
• DOI: 10.1111/1365-2745.13924
• Languages: English
• ISSNs: 0022-0477

Abstract

Abstract: Determining the patterns and drivers of the small‐scale species–area relationship (SAR) is crucial for improving our understanding of community assembly and biodiversity patterns. Niche‐based and stochastic processes are two principal categories of mechanisms potentially driving SARs. However, their relative importance has rarely been quantified rigorously owing to scale dependence and the simplified niche volumes often used. In a fully mapped, 24‐hm 2 plot of a typical subtropical forest, we built the SARs and well‐defined niche hyper‐volumes of a broad range of environmental variables at scales of 10–70 m (cell sizes). We then simulated passive sampling and partitioned the variances of the SAR slopes to disentangle these two contrasting mechanisms. We found that the small‐scale SAR best followed a power‐law relationship, consistent with large‐scale SARs. The SAR slope declined with increasing scale; it was lower than expected under passive sampling at scales below 30 m and higher at larger scales. Environmental niches explained more (39%–64%) of the slope at larger scales, exceeding 50% at scales >30 m, and these niches always captured the majority of the structured slopes. Environmental position (environmental mean values) effects were steady in absolute strength across scales and explained most (98%–68%) of the niche effect, but this proportion decreased with increasing scale. The effect of environmental heterogeneity increased with spatial scales, starting to rise at the 30 m scale after controlling for environmental position. Excluding soil properties from analyses strongly reduced these niche effects, highlighting the importance of soils for structuring the small‐scale SAR. There was also substantial stochasticity in the SAR slopes, which was only partially explained by passive sampling. Synthesis . Our results show that the small‐scale SAR in the studied subtropical forest follows a power law, exhibits a scale shift in SAR slope at 30 m, and is strongly shaped by niche effects that are dominated by environmental position relative to heterogeneity. However, soil heterogeneity controls the increase in niche effect and the shift in the SAR slope with increasing spatial scales. Hence, edaphic factors can be responsible for scale dependence in small‐scale SARs, thereby linking small‐scale and large‐scale SARs. Abstract : Our results show that the small‐scale species‐area relationship (SAR) in a typical subtropical forest follows a power law, exhibits a scale shift in SAR slope at 30 m scale, and is strongly shaped by niche effects that are dominated by environmental position relative to heterogeneity. However, soil heterogeneity controls the increase in niche effect and shift in the SAR slope with increasing spatial scales. Hence, edaphic factors can be responsible for scale dependence in small‐scale SARs, thereby linking small‐scale and large‐scale SARs. 摘要: 揭示小尺度种‐面积关系变化及其驱动机制对我们深入理解群落构建和生物多样性格局至关重要。生态位和随机过程是种‐面积关系变化的两大主要驱动机制，但由于尺度依赖和当前常用的生态位维度过于简化，很少有研究对这两大主要机制在驱动种‐面积关系变化中的相对重要性进行严格的量化分析。 本研究以典型的亚热带常绿阔叶林24‐ha样地为研究对象，样地内木本植物个体和环境因子变量空间信息明确；在10 ‐ 70 m 尺度（样地网格单元边长大小），对每个网格单元，我们建立了种‐面积关系曲线和由大量环境变量组成的生态位超维空间，同时模拟了被动取样过程，利用方差分解的方法量化区分两大主要驱动机制对种‐面积关系的相对重要性。 我们发现，如同大尺度种‐面积关系，幂函数模型（power‐law model）也是小尺度种‐面积关系的最优拟合。种‐面积关系斜率随尺度增加而减小，当尺度小于30 m时，该斜率小于被动取样过程产生的期望斜率；当尺度大于30 m时，该斜率大于被动取样过程产生的期望斜率。环境生态位在较大尺度解释了更多的种‐面积斜率的空间变异（39% ‐ 64%），当尺度大于30 m，该解释率大于50%；环境生态位主导了种‐面积关系斜率在空间的结构性变化。在环境生态位中，环境位置（environmental position），即环境变量的平均值，对种‐面积关系斜率的绝对效应随尺度变化是稳定的，其解释了大部分的环境生态位效应（98% ‐ 68%），但解释比例随尺度增加而下降；相对而言，生境异质性对种‐面积关系斜率的效应随尺度增加而增加，控制生境位置效应后，生境异质性效应自30 m尺度开始增加。将土壤变量从分析中移除导致环境生态位效应被严重低估，这一结果突显了土壤变量在决定小尺度种‐面积关系中的重要性。同时，种‐面积关系斜率也表现出很强的随机性，这种随机性仅部分被动取样过程解释。 4. 综上所述，该研究表明典型亚热带森林小尺度种‐面积关系遵循幂函数变化规律，其斜率在30 m尺度呈现尺度转换。环境生态位过程强烈地影响着小尺度种‐面积关系的变化；相对于环境异质性，环境位置主导了小尺度上环境生态位效应。但是，土壤异质性是导致环境生态效应随尺度增加而增加的原因，并控制了种‐面积关系斜率的尺度转换。因此，土壤因素决定了小尺度种‐面积关系的尺度依赖性，从而将小尺度和大尺度种‐面积曲线关联起来。