The effect of proximity to protected areas on community adaptation to environmental change

2022 ◽  
Vol 301 ◽  
pp. 113805
Author(s):  
Josephine Gillespie ◽  
Dan Penny
2021 ◽  
Vol 12 ◽  
Author(s):  
Lena A. Schallenberg ◽  
John K. Pearman ◽  
Carolyn W. Burns ◽  
Susanna A. Wood

Picocyanobacteria (Pcy) are important yet understudied components of lake foodwebs. While phylogenetic studies of isolated strains reveal a high diversity of freshwater genotypes, little is known about abiotic drivers associated with Pcy in different lakes. Due to methodological limitations, most previous studies assess potential drivers using total cell abundances as a response, with often conflicting and inconsistent results. In the present study, we explored how picocyanobacterial communities respond to environmental change using a combination of epifluorescence microscopy and community data determined using 16S rRNA gene metabarcoding. Temporal shifts in picocyanobacterial abundance, diversity and community dynamics were assessed in relation to potential environmental drivers in five contrasting lakes over 1year. Cell abundances alone were not consistently related to environmental variables across lakes. However, the addition of metabarcoding data revealed diverse picocyanobacterial communities that differed significantly between lakes, driven by environmental variables related to trophic state. Within each lake, communities were temporally dynamic and certain amplicon sequence variants (ASVs) were strongly associated with specific environmental drivers. Rapid shifts in community structure and composition were often related to environmental changes, indicating that lacustrine Pcy can persist at high abundances through collective community adaptation. These results demonstrate that a combination of microscopy and metabarcoding enables an in-depth characterisation of picocyanobacterial communities and reveals strain-specific drivers. We recommend that future studies cease referring to picocyanobacterial as one functional group and take strain specific variability into consideration.


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