Phytoplankton in dryland riverine waterholes: environmental drivers, variability and ecosystem-monitoring potential using different levels of taxonomic resolution and dataset reduction
Carrie K. Preite A B and Richard G. Pearson
A C
+ Author Affiliations
- Author Affiliations
A College of Science and Engineering, James Cook University, Townsville, Qld 4811, Australia.
B Department of Biological Sciences, College of Southern Nevada, 3200 East Cheyenne Avenue, North Las Vegas, NV 89030, USA.
C Corresponding author. Email: richard.pearson@jcu.edu.au
Marine and Freshwater Research 72(2) 244-255 https://doi.org/10.1071/MF19343
Submitted: 29 October 2019 Accepted: 19 May 2020 Published: 1 July 2020
Abstract
Waterholes that remain in the dry season in intermittent dryland rivers are important biotic refugia, but detailed ecological descriptions of these habitats and their plankton are scarce. We aimed to determine spatial and temporal variation in phytoplankton assemblages in a tropical Australian dryland river system, their main environmental determinants and the potential of the phytoplankton for ecosystem monitoring. We sampled nine sites in three rivers over 2 years using standard methods. Water quality and phytoplankton assemblages varied considerably among sites, rivers and seasons, reflecting lithology, hydrology, bathymetry and local catchment influences. Major environmental drivers included conductivity, pH, temperature and species of N and P. We analysed several derived versions of the original dataset by using density and presence–absence data, eliminating rarer species and grouping species into higher taxa. We found substantial consistency among analyses in environmental drivers, identified using distance-based linear modelling, and in variability among systems, identified using nested permutational multivariate analysis of variance (PERMANOVA). Responsiveness of the algal assemblages to environmental drivers and consistency among analyses, even using subsamples at low taxonomic resolution, suggests potential for ecosystem monitoring and optimising of sample throughput, although variability among systems requires substantial effort to determine the range of reference conditions.
Additional keywords: algae, Australia, methods, river health, tropics.
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