| 论文标题： |
Intra-annual fluctuations dominating temporal dynamics of benthic diatom assemblages in a Chinese mountainous river |
| 作者： |
Guo, Shuhan; He, Fengzhi; Tang, Tao; Tan, Lu; Cai, Qinghua |
| 出版刊物： |
ANNALES DE LIMNOLOGIE-INTERNATIONAL JOURNAL OF LIMNOLOGY |
| 出版日期： |
AUG 10 |
| 出版年份： |
2020 |
| 卷/期： |
|
| DOI： |
10.1051/limn/2020020 |
| 论文摘要： |
Intra-annual fluctuations dominated temporal dynamics of benthic diatom communities. Moreover, component species within the communities displayed distinct dynamics and were driven by different environmental variables. Our findings provide new insights to community dynamics in stream ecosystems. Understanding temporal dynamics of community may provide insights on biological responses under environmental changes. However, our knowledge on temporal dynamics of river organisms is still limited. In the present study, we employed a multivariate time-series modeling approach with a long-term dataset (i.e.72 consecutive months) to investigate temporal dynamics of benthic diatom communities in four sites located in a Chinese mountainous river network. We hypothesized that: (1) there are multi-scale temporal dynamics within the diatom community; (2) intra-annual fluctuations dominate the community dynamics; (3) diatom species composing the community respond distinctly to environmental changes. We found that intra-annual fluctuations with periodicities <12 months explained 8.1-16.1% of community variation. In contrast, fluctuations with periodicities of 13-36 months and 37-72 months only accounted for 1.1-5.9% and 2.8-9.7% of variance in diatom community dynamics, respectively. Taxa correlating significantly to each significant RDA axis (namely, RDA taxa group) displayed distinct temporal dynamics. Conductivity, total nitrogen, and pH were important to most RDA taxa groups across the four sites while their effects were group-specific. We concluded that intra-annual dynamics dominated temporal variation in diatom communities due to community responses to local environmental fluctuations. We suggest that long-term monitoring data are valuable for identifying multiple-scale temporal dynamics within biological communities. |
