Key Edaphic Properties Largely Explain Temporal and Geographic Variation in Soil Microbial Communities across Four Biomes.
Key Edaphic Properties Largely Explain Temporal and Geographic Variation in Soil Microbial Communities across Four Biomes.
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DOI：
10.1371/journal.pone.0135352
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Gallery RE
中科院分区：
文献类型：
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作者：
Docherty KM;Borton HM;Espinosa N;Gebhardt M;Gil-Loaiza J;Gutknecht JL;Maes PW;Mott BM;Parnell JJ;Purdy G;Rodrigues PA;Stanish LF;Walser ON;Gallery RE
土壤微生物群落在所有生态系统的养分转化和储存中起着关键作用。量化土壤微生物的遗传和功能变化的季节性和长期时间范围，以应对生态系统内和跨生态系统的生物和非生物变化，将为我们了解气候变化对这些过程的影响提供信息。我们研究了基于16 S rRNA基因测序和磷脂脂肪酸（PLFA）组成的微生物群落在四个生物群落的空间和季节变化：热带阔叶林（夏威夷），针叶林（阿拉斯加），半干旱草原灌木林（犹他州），和亚热带针叶林（佛罗里达）。在这项研究中，我们使用了一个基于团队的教学方法，利用iPlant协作检查公开的国家生态观测网络（氖）16 S基因和PLFA测量，量化微生物多样性，组成和生长。这两种分析技术表明，微生物群落强烈的生态系统分组，并主要受三个土壤因素：pH值，土壤含水量和阳离子交换能力。不同的分析技术的微生物群落的时间变异性; 16 S为基础的社区测量显示显着的时间变异性，仅在亚热带针叶林群落，特别是通过亚组内的变化的酸细菌。相反，PLFA为基础的社区测量表明，在针叶林和热带阔叶林系统的季节性变化。这些差异可能是由于基于16 S的测量主要受非生物土壤环境中的大变化的影响，而基于PLFA的分析反映了微生物群落的代谢活性部分，这对局部干扰和生物相互作用更敏感。为了解决土壤微生物群落对样品储存温度的响应的技术问题，我们比较了在-80 ° C和-20 ° C下储存的土壤中基于16 S的群落结构，发现基于储存温度的群落组成没有显著差异。免费、开放获取的数据集和数据共享平台是整合本科生和研究生课堂研究和教学的强大工具。它们是促进跨学科合作，测试生态理论，模型开发和验证以及产生新假设的宝贵资源。通过基于项目的学习，在大学课堂上进行数据分析和大型数据集解释的培训，改善了学生的学习体验，并使他们能够在整个职业生涯中使用这些重要的资源。
Soil microbial communities play a critical role in nutrient transformation and storage in all ecosystems. Quantifying the seasonal and long-term temporal extent of genetic and functional variation of soil microorganisms in response to biotic and abiotic changes within and across ecosystems will inform our understanding of the effect of climate change on these processes. We examined spatial and seasonal variation in microbial communities based on 16S rRNA gene sequencing and phospholipid fatty acid (PLFA) composition across four biomes: a tropical broadleaf forest (Hawaii), taiga (Alaska), semiarid grassland-shrubland (Utah), and a subtropical coniferous forest (Florida). In this study, we used a team-based instructional approach leveraging the iPlant Collaborative to examine publicly available National Ecological Observatory Network (NEON) 16S gene and PLFA measurements that quantify microbial diversity, composition, and growth. Both profiling techniques revealed that microbial communities grouped strongly by ecosystem and were predominately influenced by three edaphic factors: pH, soil water content, and cation exchange capacity. Temporal variability of microbial communities differed by profiling technique; 16S-based community measurements showed significant temporal variability only in the subtropical coniferous forest communities, specifically through changes within subgroups of Acidobacteria. Conversely, PLFA-based community measurements showed seasonal shifts in taiga and tropical broadleaf forest systems. These differences may be due to the premise that 16S-based measurements are predominantly influenced by large shifts in the abiotic soil environment, while PLFA-based analyses reflect the metabolically active fraction of the microbial community, which is more sensitive to local disturbances and biotic interactions. To address the technical issue of the response of soil microbial communities to sample storage temperature, we compared 16S-based community structure in soils stored at -80°C and -20°C and found no significant differences in community composition based on storage temperature. Free, open access datasets and data sharing platforms are powerful tools for integrating research and teaching in undergraduate and graduate student classrooms. They are a valuable resource for fostering interdisciplinary collaborations, testing ecological theory, model development and validation, and generating novel hypotheses. Training in data analysis and interpretation of large datasets in university classrooms through project-based learning improves the learning experience for students and enables their use of these significant resources throughout their careers.