Reproducing static and dynamic biodiversity patterns in tropical forests: the critical role of environmental variance
Reproducing static and dynamic biodiversity patterns in tropical forests: the critical role of environmental variance
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DOI：
10.1890/15-0984.1
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发表时间：
2016-05-01
期刊：
影响因子：
4.8
通讯作者：
Chisholm, Ryan A.
中科院分区：
文献类型：
--
作者：
Fung, Tak;O'Dwyer, James P.;Chisholm, Ryan A.
生态群落以人口和环境方差的形式受到随机性的影响。仅包含人口统计方差的随机模型（中性模型）提供了与观测到的物种丰度分布（SAD）的密切定量拟合，但大大低估了观测到的物种丰度波动。为了提供一个全面的评估，是否与人口和环境方差模型比中性模型表现得更好，适合SAD和时间物种丰度波动在同一时间进行了定量测试。在这项研究中，我们定量地测试如何密切的人口和环境方差模型再现物种总数，总丰度，SAD和时间物种多度波动的两个热带森林树木群落，使用长期监测地块的十年数据，并考虑每个社区大于两个大小阈值的个人。我们发现，该模型确实可以密切再现这些静态和动态模式的生物多样性在两个社区的两个大小阈值，更好的整体拟合比相应的中性模型。因此，我们的研究结果提供的证据表明，随机模型结合人口和环境的变化，可以同时捕捉重要的静态和动态的生物多样性模式在热带森林群落。
Ecological communities are subjected to stochasticity in the form of demographic and environmental variance. Stochastic models that contain only demographic variance (neutral models) provide close quantitative fits to observed species-abundance distributions (SADs) but substantially underestimate observed temporal species-abundance fluctuations. To provide a holistic assessment of whether models with demographic and environmental variance perform better than neutral models, the fit of both to SADs and temporal species-abundance fluctuations at the same time has to be tested quantitatively. In this study, we quantitatively test how closely a model with demographic and environmental variance reproduces total numbers of species, total abundances, SADs and temporal species-abundance fluctuations for two tropical forest tree communities, using decadal data from long-term monitoring plots and considering individuals larger than two size thresholds for each community. We find that the model can indeed closely reproduce these static and dynamic patterns of biodiversity in the two communities for the two size thresholds, with better overall fits than corresponding neutral models. Therefore, our results provide evidence that stochastic models incorporating demographic and environmental variance can simultaneously capture important static and dynamic biodiversity patterns arising in tropical forest communities.