Abstract
This study examines distributional patterns of benthic diatom assemblages in relation to environmental characteristics in streams and rivers in the California Central Valley ecoregion. Benthic diatoms, water quality, and physical habitat conditions were characterized from 53 randomly selected sites. The stream sites were characterized by low mid-channel canopy cover and high channel substrate embeddedness. The waters at these sites were enriched with minerals and turbidity varied from 1.3 to 185.0 NTU with an average of 13.5 NTU. A total of 249 diatom taxa were identified. Average taxa richness was 41 with a range of 7-76. The assemblages were dominated by Staurosira construens (11%), Epithemia sorex (8%), Cocconeis placentula (7%), and Nitzschia amphibia (6%). Multivariate analyses (cluster analysis, classification tree analysis, and canonical correspondence analysis) all showed that benthic diatom assemblages were mainly affected by channel morphology, in-stream habitat, and riparian conditions. The 1st CCA axis negatively correlated with mean wetted channel width (r = -0.66) and thalweg depth (r = -0.65) (Table 4). The 2nd axis correlated with % coarse substrates (r=0.60). Our results suggest that benthic diatoms can be used for assessing physical habitat alterations in streams.
Original language | English (US) |
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Pages (from-to) | 119-130 |
Number of pages | 12 |
Journal | Hydrobiologia |
Volume | 561 |
Issue number | 1 |
DOIs | |
State | Published - May 2006 |
Bibliographical note
Funding Information:Field work and data collection were undertaken by California Division of Game and Fish and USEPA Region 9, with funding from USEPA’s Office of Research and Development as part of the REMAP program. Susanna DeCelles identified and enumerated all benthic diatom samples. The data analyses and preparation of this manuscript were supported by USEPA STAR stream classification grant to the first author (R-82949801). We thank Dr. R. J. Stevenson and an anonymous reviewer for their comments on earlier versions of this paper.
Keywords
- Canonical correspondence analysis
- Classification tree analysis
- Cluster analysis
- TWINSPAN
- UPGMA