*2.1. Study Area*

Longkaikou hydroelectric station, in Yongsheng County of Yunnan Province, is the sixth of eight cascade reservoirs constructed in the Jinsha River basin. Construction began in 2007, and it began operation in 2014. The reservoir's main purpose is power generation, but it also provides water for irrigation and an urban and industrial water supply. The dam height is 119 m, the normal storage water level is 1298 m asl (above sea level), the backwater length is 41 km, the water area is about 17 ha, and the total reservoir capacity is 5 × 10<sup>8</sup> m3. The reservoir is located in a typical alpine canyon area with complex topography and diverse local microclimates. The difference between the rainy and dry seasons is obvious, with an annual average precipitation of 936 mm, of which 82% falls between June and September (Figure S1). Figure S1 shows the annual changes of temperature and precipitation in our study area, based on data from the Yongsheng meteorological station, which is located 37.8 km from our study sites at an elevation of 2151 m asl. The land below an elevation of 1500 m asl has an arid-hot valley climate; above this elevation, there is greater precipitation and the temperatures are

much colder. The vegetation, including *D. viscosa*, *P. yunnanensis*, and *Ageratina adenophora*, is widely distributed in the reservoir region, but has been seriously disturbed by construction of the reservoir, as well as by grazing of livestock and cutting. In local vegetation restoration projects, *P. yunnanensis* is used on barren mountain slopes [24]. *D. viscosa* is a perennial evergreen shrub or small tree of the genus *Dodonaea*. It can adapt to a wide range of sites due to its high tolerance of drought and low soil fertility, and is therefore one of the main native plants used for vegetation restoration in the study area. Our study area covers nearly 300 km2, with a length of 41 km along the river and a width of 7.0 km (Figure 1).

**Figure 1.** Map of the study region: (**a**) location of Yunnan Province; (**b**) location of the Jinsha River in Yunnan Province; (**c**) map of the reservoir of the Longkaikou Hydropower Station and sample bands; (**d**) and (**e**) locations of the sampling sites; and (**f**) an example of the location of the quadrats at a sampling site.

#### *2.2. Sample Collection and Processing*

We conducted field surveys three times (in April and August 2017, and in April 2018) in the study area, and collected soil and vegetation samples during each sampling period. We combined the April data to produce a single dataset for the dry season; the August data represented the end of the rainy season (the rain was too frequent to reach high area with elevation above 1640 m). For each sample, we recorded the elevation, slope, and aspect simultaneously (Table S1). We attempted to establish 3 quadrats at each of 21 sampling sites, for a total of 63 quadrats (*n*); however, some sampling sites had two or four quadrats, due to the nature of the topographic conditions. All of the samples were evenly distributed bath left bank (marked LPx-x) and right bank (marked RPx-x) at five elevations that ranged from the river (ca. 1380 m asl) to the top of the mountains (ca. 1940 m asl), and included shade slopes, sunny slopes, and half-shaded slopes. We established sampling bands at elevations of 1380, 1440, 1520, 1640, and 1940 m asl. For each sampling site, we recorded the slope and aspect (*Asp*) using a DQY-1 compass (Geological Compass; Haerbin, Heilongjiang Province, China), and obtained the elevation and the longitude and latitude using a GPS receive (GPSmap 62sc; Garmin, Lenexa, KS, USA). We calculated the topographic wetness index and the distance from the quadrats to the river are calculated from a digital elevation model (http://www.gscloud.cn/sources/?cdataid=302&pdataid=10) using version 10.2 of the ArcGIS software (www.esri.com).

In total, we established 57 *D. viscosa* quadrats and 38 *P. yunnanensis* quadrats, and recorded number of branches, plant density, and vegetation cover, diameter at breast height, crown width, and height. We collected the aboveground biomass for 25 *D. viscosa* plants, and dried the samples at 60 ◦C until constant weight in the laboratory; we then weighed the oven-dry biomass using a laboratory electronic balance with a precision of 0.01 g.

We collected 64 soil samples (each ca. 1 kg) to a depth of 10 cm with a shovel, as the soil was too rocky below this depth to allow sampling. We measured soil moisture, organic matter, total nitrogen, total potassium, hydrolyzable nitrogen, and available phosphorus in the laboratory according to the standards of the Chinese Forestry Bureau (http://www.zbgb.org/StandardCList25C.htm) using the air-dry soil for all parameters except soil moisture. Soil moisture was measured based on the difference between the fresh and oven-dry mass (after drying at 105 ◦C for 24 h until all the moisture was driven off). The organic matter was determined by the potassium dichromate oxidation method with external heating (LY/T 1237-1999), total nitrogen was measured by the Kjeldahl method (LY/T 1228-2015), total potassium was determined by NaoH flame photometry (LY/T 1234-2015), hydrolyzable nitrogen was determined by the alkaline hydrolysis-diffusion method (LY/T 1228-2015), and available phosphorus was determined by colorimetry (LY/T 1232-2015).

#### *2.3. Estimation of Soil Fertility and Vegetation Biomass*

We established a holistic index of soil fertility (*SF*) as follows:

$$SF = \sum\_{i=1}^{5} \frac{\mathbf{x}\_i - \mathbf{x}\_{\text{min}i}}{\mathbf{x}\_{\text{min}i}},\tag{1}$$

where *xi* represents the value of nutrient indicator *i* (organic matter, total nitrogen, total potassium, hydrolyzable nitrogen, and available phosphorus), and *x*min*i* is the lowest value for each of the five nutrient indicators in the soil nutrient grading standards of the second national land survey.

The growth model for *D. viscosa* is region-dependent, since this species lives in different areas [25], so we established a relative growth model.

Due to the multiple branches produced by this shrub, we defined the total diameter (*D*) based on the sum of the squared branch diameters:

$$D = \sqrt{\sum\_{i=1}^{n} D\_{i'}^2} \tag{2}$$

where *Di* is the diameter (cm) of branch *i*, and *n* is the number of branches contained in each shrub [26]. We then adopted a relative growth model in the form of a power function based on a previously determined growth model for the shrub [27]:

*Sustainability* **2018**, *10*, 4774

$$Bio = 44.047 \, D^2 \, H^{0.467} \, (R^2 = 0.94, p < 0.01), \tag{3}$$

where *Bio* = aboveground biomass, *D* is the total diameter from Equation (2), and *H* is the height at the end of the tallest branch.

We obtained an equation from Huo et al. [28] to determine the relative growth of *P. yunnanensis.*

$$
\dot{m} = 0.026 \,\text{D}^{2.83} \tag{4}
$$
