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Potential mechanisms related to the spatial synchrony of phytoplankton is dependent on the type of data

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Abstract

Spatial synchrony occurs when the temporal dynamics of local populations are correlated. Correlated environmental variations (Moran effect), dispersal, and trophic interactions are theoretically the main mechanisms underlying population synchrony. We estimated spatial synchrony for total biomass, community density, densities of genera, and phytoplankton classes in a reservoir. We tested the hypotheses that synchrony levels would be high because all sites were sampled in a single waterbody; the Moran effect would be the main synchronizing mechanism; and synchrony should increase with environmental specialization of taxa. We also conducted an exploratory analysis to identify the regions of the reservoir contributing most to synchrony. We found low levels of synchrony, indicating that local factors were more important in controlling the dynamics of the local phytoplankton populations. Environmental synchrony and geographic distance were not significantly correlated with the synchrony matrices derived from genera data; however, synchrony matrices of the most abundant phytoplankton classes were mainly correlated with environmental synchrony. These results indicate that the detection of the Moran effect depends on the type of data used. As predicted, our results indicated that the dynamics of specialist genera were more synchronized than that of generalist genera. Finally, the lower reach of the reservoir contributed most to synchrony.

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Acknowledgements

We would like to thank CAPES for granting a scholarship to the first author. This work was developed in the context of the National Institutes for Science and Technology (INCT) in Ecology, Evolution and Biodiversity Conservation, supported by MCTIC/CNPq (proc. 465610/2014-5) and FAPEG. Luis Mauricio Bini has been supported by CNPq productivity Grants.

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Zanon, J.E., de Carvalho, P., Rodrigues, L.C. et al. Potential mechanisms related to the spatial synchrony of phytoplankton is dependent on the type of data. Hydrobiologia 841, 95–108 (2019). https://doi.org/10.1007/s10750-019-04009-y

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