Nevin Manimala Statistics

Diatom community composition on submerged macrophyte species from an Ontario (Canada) lake

J Phycol. 2022 Jun 11. doi: 10.1111/jpy.13273. Online ahead of print.


The introduction of invasive macrophyte species can affect submerged macrophyte community composition and abundance, which in turn can alter the functions of lake ecosystems. Knowing when and how invasive macrophytes arrive and spread can help disentangle the effects of invasive species from other stressors on lake ecosystems. This requires a long-term (decades) perspective of macrophyte community composition, which is rarely available. An alternative is paleolimnological inferences of macrophyte community composition from fossil diatom assemblages, which requires knowledge of epiphytic diatom communities. Here, we investigated the epiphytic diatom community composition of three common submerged macrophyte species (Chara sp., Potamogeton robbinsii, and the invasive Myriophyllum spicatum) in a typical temperate, mixed forest lake, Chandos Lake, Ontario, Canada, to provide a basis for future paleolimnological research. Non-parametric, multivariate analysis of variance indicated a statistically significant difference in the epiphytic diatom communities of different macrophyte species, despite principal components analysis showing some overlap among the diatom communities. Diatom community composition of all macrophytes had abundant Achnanthidium minutissimum and Cocconeis placentula. Generalised linear models and univariate analysis of variance identified six diatoms (Encyonopsis microcephala, Epithemia turgida, Gomphonema pavulum var. parvulius, Navicula gerloffi, Rhopalodia gibba, and Rossithidium anastasiae) that were significantly different among macrophyte species. Although it remains uncertain whether these differences are sufficient to infer historical macrophyte community composition from epiphytic diatom fossil assemblages, our results indicate the potential of such an approach and offer suggestions for future research.

PMID:35689727 | DOI:10.1111/jpy.13273

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