Changes in assembly processes in soil bacterial communities following a wildfire disturbance
Changes in assembly processes in soil bacterial communities following a wildfire disturbance
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DOI：
10.1038/ismej.2013.11
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发表时间：
2013-06-01
期刊：
影响因子：
11
通讯作者：
Nemergut, Diana R.
中科院分区：
文献类型：
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作者：
Ferrenberg, Scott;O'Neill, Sean P.;Nemergut, Diana R.
虽然最近的工作表明，确定性和随机过程都是重要的结构微生物群落，影响生态位和中性过程的相对贡献的因素知之甚少。宏观生物学文献表明，生态干扰可以影响组装过程。因此，我们在野火后4周和16周对细菌群落进行了采样，并使用零偏差分析来研究自干扰以来的时间在群落组装中的作用。火灾显着改变了细菌群落结构和多样性，以及土壤化学的两个时间点。被烧毁和未被烧毁的社区的社区结构在4至16周之间发生变化。火灾后4周，在烧毁的网站社区集会显着更随机比未烧毁的网站。然而，16周后，烧毁的社区显着不那么随机比未烧毁的社区。因此，我们提出了一个三阶段模型，其特点是小生境和中性过程的相对重要性的变化作为时间的函数，因为干扰。由于中性过程的特点是环境参数和社区结构之间的脱钩，我们假设，更好地了解社区组装可能是重要的，在确定何时何地详细的研究社区组成是有价值的预测生态系统功能。
Although recent work has shown that both deterministic and stochastic processes are important in structuring microbial communities, the factors that affect the relative contributions of niche and neutral processes are poorly understood. The macrobiological literature indicates that ecological disturbances can influence assembly processes. Thus, we sampled bacterial communities at 4 and 16 weeks following a wildfire and used null deviation analysis to examine the role that time since disturbance has in community assembly. Fire dramatically altered bacterial community structure and diversity as well as soil chemistry for both time-points. Community structure shifted between 4 and 16 weeks for both burned and unburned communities. Community assembly in burned sites 4 weeks after fire was significantly more stochastic than in unburned sites. After 16 weeks, however, burned communities were significantly less stochastic than unburned communities. Thus, we propose a three-phase model featuring shifts in the relative importance of niche and neutral processes as a function of time since disturbance. Because neutral processes are characterized by a decoupling between environmental parameters and community structure, we hypothesize that a better understanding of community assembly may be important in determining where and when detailed studies of community composition are valuable for predicting ecosystem function.