Investigation
The Ankang Reservoir (32°36′6.11′′ N, 108°53′21.26′′ E), also referred to as Yinghu, is in the upper reaches of the Hanjiang River, which is the largest tributary to the Yangtze River. The reservoir area is 38,625 km2 and the total capacity is 25.8 × 108 m3, with a multiyear mean discharge of 190 million m3. The multiyear mean water temperature is 14-16°C, and the multiyear mean rainfall is 800-1,100 mm.
Water samples were collected in mid-July from 17 sample locations in the reservoir that were 1 to 33 km from the dam, with 2 km between neighboring sample locations. Samples were taken from five depth levels (0.5, 2.5, 5, 10, and 20 m) at each location. Nine sampling locations were downstream in the river, 1 km to 17 km from the dam, with 2 km between neighboring locations. Because water depth in the river was less than 4 m, the water samples were taken at 0.5 and 2.5 m depth levels at each location. One liter of water was fixed with 1% Logul’s solution to measure the diversity and abundance of algae, while 500 ml of water was refrigerated at 4°C for subsequent nutrient analyses. Each sample was replicated in triplicate.
Temperature, pH, dissolved oxygen, and salinity were measured with a portable water quality analyzer (Hydrolab DS5, HACH, America). Total nitrogen and total phosphorus were measured with a spectrophotometer (DR6000, HACH, America). One liter of water was used for algal identification analysis after letting settle for 48 h. The upper 950 ml of water was then removed and 0.1 ml of water was taken from the remaining 50 ml for microscopic identification of algal abundances and species.
Principal component analysis (PCA) was used to analyze the variation in the six measured environmental variables. The first two axes explained 82.67% of the variation in the environmental parameters in the reservoir samples (PC1=58.89% and PC2=23.78%) and 81.10% of the variation in the variables in the downstream river samples (PC1=54.46% and PC2=26.65%). The percentage of explained variance by each axis (i.e., PC1 and PC2 values) was taken as its weight of the PCA score for each axis. The value of the PCA score for each axis was multiplied by its weight, and the two products were added to determine the environmental value at each site. The environmental values for the reservoir and downstream river sites were then calculated.
The local MoranI (\(I_{i}\)) values of the reservoir and downstream sites were calculated to measure the EGUS of water as follows (Massicotte et al . 2015):
\(I_{i}=\frac{z_{i}-\overset{\overline{}}{z}}{\sigma^{2}}\sum_{j=1,j\neq i}^{n}\left[W_{\text{ij}}\left(z_{j}-\overset{\overline{}}{z}\right)\right]\)
where zi and zj are the environmental values for sites i and j , respectively.\(\overset{\overline{}}{z}\) is the environmental average value of all the sites and n is the number of sites.σ2 is the variance of\(\overset{\overline{}}{z}\) and Wij is a distance weighting factor between site i and site j that is the inverse of the distance. A lower Moran’s I value of a site represent a more significant difference between the site and adjacent sites. I values were calculated in Stata 12.0 (STATA, America).
Negative binomial regression test was used to evaluate the relationship between each Moran I value and algal richness in the reservoir and downstream river sites. A significance level was set as 0.05. These analyses were performed in the SPSS 19.0 software package (IBM, America).