Spatial distribution of benthic algae in the Gangqu River, Shangrila, China

This study consisted of sampling benthic algae at 32 sites in the Gangqu River, an important upstream tributary of the Yangtze River. Our aims were to characterize the benthic algae communities and relationships with environmental variables. Among the 162 taxa observed, Achnanthes linearis and Achnanthes lanceolata var. elliptica were the dominant species (17.10% and 14.30% of the total relative abundance, respectively). Major gradients and principal patterns of variation within the environmental variables were detected by principal component analysis (PCA). Then non-metric multidimensional scaling (NMS) divided all the sites into three groups, which were validated by multi-response permutation procedures (MRPP). Canonical correspondence analysis (CCA) indicated that three environmental variables (TN, TDS, and TP) significantly affected the distribution of benthic algae. Weighted averaging regression and cross-calibration produced strong models for predicting TN and TDS concentration, which enabled selection of algae taxa as potentially sensitive indicators of certain TN and TDS levels: for TN, Achnanthes lanceolata, Achnanthes lanceolata var. elliptica, and Cymbella ventricosa var. semicircularis; for TDS, Cocconeis placentula, Cymbella alpina var. minuta, and Fragilaria virescens. The present study represents an early step in establishing baseline conditions. Further monitoring is suggested to gain a better understanding of this region.

This study consisted of sampling benthic algae at 32 sites in the Gangqu River, an important upstream tributary of the Yangtze River. Our aims were to characterize the benthic algae communities and relationships with environmental variables. Among the 162 taxa observed, Achnanthes linearis and Achnanthes lanceolata var. elliptica were the dominant species (17.10% and 14.30% of the total relative abundance, respectively). Major gradients and principal patterns of variation within the environmental variables were detected by principal component analysis (PCA). Then non-metric multidimensional scaling (NMS) divided all the sites into three groups, which were validated by multi-response permutation procedures (MRPP). Canonical correspondence analysis (CCA) indicated that three environmental variables (TN, TDS, and TP) significantly affected the distribution of benthic algae. Weighted averaging regression and cross-calibration produced strong models for predicting TN and TDS concentration, which enabled selection of algae taxa as potentially sensitive indicators of certain TN and TDS levels: for TN, Achnanthes lanceolata, Achnanthes lanceolata var. elliptica, and Cymbella ventricosa var. semicircularis; for TDS, Cocconeis placentula, Cymbella alpina var. minuta, and Fragilaria virescens. The present study represents an early step in establishing baseline conditions. Further monitoring is suggested to gain a better understanding of this region.

National Natural Science Foundation of China [30330140]; Key Project of Knowledge Innovation Program of the CAS [KSCX2-YW427]; National Basic Research Priorities Program [2002CD412310]; Nature Conservancy