# The Observed Impacts of Wind Farms on Local Vegetation Growth in Northern China
## 5 Conclusions  
In this study, the effects of WFs on the underlying vegetation growth in the Bashang area of Northern China are analyzed. The results show that WFs inhibit local vegetation growth and productivity, decreasing LAI, EVI, and NDVI by approximately 14.5%, 14.8%, and 8.9% from 2003 to 2014. There is an inhibiting effect of 8.9% on summer GPP and 4.0% on annual NPP over WFs. Potential reasons for the inhibiting effects are as follows: (1) inhibited photosynthesis through increasing water stress and enhanced autotrophic respiration through increasing daytime and nighttime temperatures and (2) downwind inhibited growth status and photosynthesis induced by the downwind warming effect. Our analysis provides clear observational evidence of the inhibiting effect on vegetation growth caused by WFs in the Bashang area of Northern China.  
As the analysis is from a short period over a local region with rapid growth of wind farms, it should be kept in mind that the estimated inhibiting effects cannot be generally applied to other  
Figure 8: Histogram of MERRA hourly 50 m (**a**) wind speed (m/s) and (**b**) direction in summer averaged over the study area during the period 2003–2014. Wind direction is determined by U- and V-components and measured in terms of degrees clockwise between 0 and 360(\({}^{\circ}\)). The wind from the North corresponds to 360\({}^{\circ}\) (0\({}^{\circ}\)), from the East corresponds to 90\({}^{\circ}\), from the South corresponds to 180\({}^{\circ}\), and from the West corresponds to 270\({}^{\circ}\).  
WFs. Wind farms affect the vegetation growth by changing local climate and damaging vegetation structures through constructions. For a given wind farm, the inhibiting effect should be quantified by fully considering local background environmental factors (e.g., temperature and soil moisture) and the recovery of vegetation with different vegetation conditions. Our results raise intriguing questions whether these suppressing patterns are observed in other WFs as well, and about trade-offs between production of clean energy and potential suppression of ecosystem functions.  
The following are available online at www.mdpi.com/2072-4292/9/4/332/s1. Figure S1: FROM-GLC land cover map in 2000 and their changes in 2010 at spatial resolutions of \(\sim\)30 m; Figure S2. MODIS summer EVI climatology (2003-2011 averages); Figure S3: Summer MODIS EVI and NDVI differences between post- and pre-turbine-construction years; Figure S4: Inter-annual variations of area mean daytime LST and LAI differences in July, August and September; Figure S5: Inter-annual variations of area mean LAI and GPP differences of crop and grass between WFPs and NNWFPs; Figure S6: Summer MODIS ET and Albedo (%) differences between post- and pre-turbine-construction years; Figure S7: The spatial distribution map of the coefficient between summer MODIS LAI anomalies and LST anomalies.  
The authors thank [PERSON], [PERSON], and [PERSON] for help in field measurements. We also thank [PERSON] for helpful comments that improved this manuscript. This work was supported by the National Key Research and Development Program of China (No. 2016 YFB0501404) and National Natural Science Foundation of China (No. 41331173). Data associated with this research (location of wind turbines and other climate data) can be obtained from the corresponding author via e-mail ([EMAIL_ADDRESS]).  
[PERSON] and [PERSON] conceived of and designed the experiments. [PERSON] processed and analyzed the data. All authors contributed to the ideas, writing, and discussion.  
The authors declare no conflict of interest.