Using integrated models to analyze and predict the variance of diatom community composition in an agricultural area.

With the growing demand of assessing the ecological status, there is the need to fully understand the relationship between the planktic diversity and the environmental factors. Species richness and Shannon index have been widely used to describe the biodiversity of a community. Besides, we introduced the first ordination value from non-metric multidimensional scaling (NMDS) as a new index to represent the community similarity variance. In this study, we hypothesized that the variation of diatom community in rivers in an agricultural area was influenced by hydro-chemical variables. We collected daily mixed water samples using ISCO auto water samplers for diatoms and for water-chemistry analysis at the outlet of a lowland river for a consecutive year. An integrated modeling was adopted including random forest (RF) to decide the importance of the environmental factors influencing diatoms, generalized linear models (GLMs) combined with 10-folder cross validation to analyze and predict the diatom variation. The hierarchical analysis highlighted antecedent precipitation index (API) as the controlling hydrological variable while water temperature, Si

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Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.