期刊
MARINE AND FRESHWATER RESEARCH
卷 72, 期 2, 页码 244-255出版社
CSIRO PUBLISHING
DOI: 10.1071/MF19343
关键词
algae; Australia; methods; river health; tropics
资金
- James Cook University
The study investigated phytoplankton assemblages in a tropical Australian dryland river system, finding significant variations in water quality and phytoplankton among different sites, rivers, and seasons. Major environmental drivers included conductivity, pH, temperature, and species of nitrogen and phosphorus. The results showed a consistent responsiveness of algal assemblages to environmental drivers, indicating potential for ecosystem monitoring, but variability among systems requires substantial effort to determine the range of reference conditions.
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.
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