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).