Jay E. Diffendorfer Melanie K. Vanderhoof Zachary H. Ancona 20220927 CSV/SHAPEFILE/R Code Denver, CO U.S. Geological Survey https://doi.org/10.5066/P9P3J7GR Jay E. Diffendorfer Melanie K. Vanderhoof Zachary H. Ancona 2022 JOURNAL Environmental Research Letters Volume 17 Number 10 https://doi.org/10.1088/1748-9326/ac8da9 Global wind energy has expanded 5-fold since 2010 and is predicted to expand another 8–10-fold over the next 30 years. Wakes generated by wind turbines can alter downwind microclimates and potentially downwind vegetation. However, the design of past studies has made it difficult to isolate the impact of wake effects on vegetation from land cover change. We used hourly wind data to model wake and non-wake zones around 17 wind facilities across the U.S. and compared remotely-sensed vegetation greenness in wake and non-wake zones before and after construction. We located sampling sites only in the dominant vegetation type and in areas that were not disturbed before or after construction. We found evidence for wake effects on vegetation greenness at 10 of 17 facilities for portions of, or the entire growing season. Evidence included statistical significance in Before After Control Impact statistical models, differences >3% between expected and observed values of vegetation greenness, and consistent spatial patterns of anomalies in vegetation greenness relative to turbine locations and wind direction. Wakes induced both increases and decreases in vegetation greenness, which may be difficult to predict prior to construction. The magnitude of wake effects depended primarily on precipitation and to a lesser degree aridity. Wake effects did not show trends over time following construction, suggesting the changes impact vegetation greenness within a growing season, but do not accrue over years. Even small changes in vegetation greenness, similar to those found in this study, have been seen to affect higher trophic levels. Given the rapid global growth of wind energy, and the importance of vegetation condition for agriculture, grazing, wildlife, and carbon storage, understanding how wakes from wind turbines impact vegetation is essential to exploit or ameliorate these effects. The data release has the purpose of serving all the data (that can be released to the public) in a way that can be machine readable. All of the data used in the report is included in tables within the report itself, this data just serves the purpose of providing those datasets in a CSV format, shapefiles, and R code. 2022 1998-2019 Complete None planned -124.762779 -66.948891 49.383297 24.520416 USGS Thesaurus Wind Wakes NDVI vegetation condition land cover change USGS Metadata Identifier USGS:61d34259d34ed79293fe6d46 GNIS United States none Unless otherwise states, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviews for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general scientific purposes, nor shall the act of distribution constitute any such warranty. Zach Ancona United States Geological Survey mailing and physical

PO Box 25046, MS 980

Denver CO 80225 United States 303-236-1886 zancona@usgs.gov No formal attribute accuracy tests were conducted No formal logical accuracy tests were conducted Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. No formal positional accuracy tests were conducted No formal positional accuracy tests were conducted The files included in this data release can help replicate our analysis of wind wake effects on vegetation condition. The facility_CSVs, bacibarcharts, and facility_parameter files are to be used as inputs to the R code we are releasing. The shapefiles help to define the facilities we analyzed and the sample points used in our statistical analysis. We include the spreadsheets used to create any of the tables or figures in the paper or supplemental information. We also include the wind speed and direction data that was used to create our wake zones and wind rose diagram found in the supplement. 2021 United States Point NAD_1983_2011_Contiguous_USA_Albers 29.5 45.5 -96.00 23.00 0.0 0.0 coordinate pair 0.0001 0.0001 Meter NAD 83 GRS 1980 6378137.0 298.257222101 Zipped Files---------------------------------------------------------------------------------------------------------------------------- Facility_TurbinePoints.zip Facility_SamplePoints.zip Facility_WakeZones.zip Facility_Extents.zip Facility_CSVs.zip Facility_WindSpeed.zip Supplemental_CSVs.zip R_Code.zip Descriptions of files in Zipped folder----------------------------------------------------------------------------------------------- Facility_TurbinePoints.zip: Ainsworth_Turbines.shp Anacacho_Turbines.shp Bingham_Turbines.shp CampSprings_Turbines.shp DryLake_Turbines.shp ElkhornRidge_Turbines.shp Evanston_Turbines.shp HatchettRidge_Turbines.shp LaurelMountain_Turbines.shp MachoSprings_Turbines.shp PerrinRanch_Turbines.shp PostRockSmokyHills_Turbines.shp RedHills_Turbines.shp Rugby_Turbines.shp SpionKop_Turbines.shp Tatanka_Turbines.shp WildHorse_Turbines.shp Facility_SamplePoints.zip: Ainsworth_SamplePoints.shp Anacacho_SamplePoints.shp Bingham_SamplePoints.shp CampSprings_SamplePoints.shp DryLake_SamplePoints.shp ElkhornRidge_SamplePoints.shp Evanston_SamplePoints.shp HatchettRidge_SamplePoints.shp LaurelMountain_SamplePoints.shp MachoSprings_SamplePoints.shp PerrinRanch_SamplePoints.shp PostRockSmokyHills_SamplePoints.shp RedHills_SamplePoints.shp Rugby_SamplePoints.shp SpionKop_SamplePoints.shp Tatanka_SamplePoints.shp WildHorse_SamplePoints.shp Facility_WakeZones.zip: Ainsworth_WakeZones.shp Anacacho_WakeZones.shp Bingham_WakeZones.shp CampSprings_WakeZones.shp DryLake_WakeZones.shp ElkhornRidge_WakeZones.shp Evanston_WakeZones.shp HatchettRidge_WakeZones.shp LaurelMountain_WakeZones.shp MachoSprings_WakeZones.shp PerrinRanch_WakeZones.shp PostRockSmokyHills_WakeZones.shp RedHills_WakeZones.shp Rugby_WakeZones.shp SpionKop_WakeZones.shp Tatanka_WakeZones.shp WildHorse_WakeZones.shp Facility_Extents.zip: Ainsworth_10km_Extent.shp Anacacho_10km_Extent.shp Bingham_10km_Extent.shp CampSprings_10km_Extent.shp DryLake_10km_Extent.shp ElkhornRidge_10km_Extent.shp Evanston_10km_Extent.shp HatchettRidge_10km_Extent.shp LaurelMountain_10km_Extent.shp MachoSprings_10km_Extent.shp PerrinRanch_10km_Extent.shp PostRockSmokyHills_10km_Extent.shp RedHills_10km_Extent.shp Rugby_10km_Extent.shp SpionKop_10km_Extent.shp Tatanka_10km_Extent.shp WildHorse_10km_Extent.shp Facility_CSVs.zip: Ainsworth_monthly_data_all.csv Anacacho_monthly_data_all.csv Bingham_monthly_data_all.csv CampSprings_monthly_data_all.csv DryLake_10km_monthly_data_all.csv ElkhornRidge_monthly_data_all.csv Evanston_monthly_data_all.csv HatchettRidge_monthly_data_all.csv LaurelMountain_monthly_data_all.csv MachoSprings_monthly_data_all.csv PerrinRanch_monthly_data_all.csv PostRockSmokyHills_monthly_data_all.csv RedHills_monthly_data_all.csv Rugby_monthly_data_all.csv SpionKop_monthly_data_all.csv Tatanka_monthly_data_all.csv WildHorse_monthly_data_all.csv Facility_WindSpeed.zip: Ainsworth_Wind_Speed.csv Anacacho_Wind_Speed.csv Bingham_Wind_Speed.csv CampSprings_Wind_Speed.csv DryLake_Wind_Speed.csv ElkhornRidge_Wind_Speed.csv Evanston_Wind_Speed.csv HatchettRidge_Wind_Speed.csv LaurelMountain_Wind_Speed.csv MachoSprings_Wind_Speed.csv PerrinRanch_Wind_Speed.csv PostRockSmokyHills_Wind_Speed.csv RedHills_Wind_Speed.csv Rugby_Wind_Speed.csv SpionKop_Wind_Speed.csv Tatanka_Wind_Speed.csv WildHorse_Wind_Speed.csv Supplemental_CSVs.zip: baci_table.csv facility_summary_table.csv rvi_summary_table.csv wind_summary_table.csv ndvi_charts.csv model_summary_table.csv R_Code.zip: facility_parameters.csv bacibarcharts.csv Figure_S1_WindRoses.r Figure_2_BarChart_Plotting.r Figure_2_Time_Series_Plotting.r Figure_4_BiPlots.r Anomaly_LMER_Monthly_Loop.r BACI_LMER_Monthly_Loop.r Overview of Attributes for files------------------------------------------------------------------------------------------------------- Facility_TurbinePoints.zip: FID Auto-assigned ArcGIS identification field Shape Auto-assigned ArcGIS geometry identification field t_state State facility is located in t_county County facility is located in p_name Name of facility from the USGS Wind Turbine Database p_year Year of facility commission t_cap Turbine capacity in kilowatts t_hh Turbine hub height (used in wake decay formula) t_rd Turbine rotor diameter (used in wake decay formula) All "_Turbines.shp" shapefiles have identical column names Facility_SamplePoints.zip: FID Auto-assigned ArcGIS identification field Shape Auto-assigned ArcGIS geometry identification field site Unique identifier for each sample point in the dataset, can be joined to other tables and data provided siteclass Identifies if the sample site was in the wake or control group mean_ndvi The mean NDVI value over the entire time period (different for each facility, only used for display purposes) Difference The mean difference in NDVI from before installation years vs. after installation years (different for each facility, only used for display purposes) All "_SamplePoints.shp" shapefiles have identical column names Facility_WakeZones.zip: FID Auto-assigned ArcGIS identification field Shape Auto-assigned ArcGIS geometry identification field gridcode Coded value for each wake zone calculated through dominant wind direction and turbine wake decay models Zone Zones defined for control and impact analysis, buffer is included but not used in analysis All "_WakeZones.shp" shapefiles have identical column names Facility_Extents.zip: FID Auto-assigned ArcGIS identification field Shape Auto-assigned ArcGIS geometry identification field Fac_Name Coded value used to refer to turbine facilities in the tables and figures seen in the report All "_10km_Extent.shp" shapefiles have identical column names Facility_CSVs.zip: site Unique identifier for each sample point in the dataset, can be joined to other tables and data provided year Year of observation month Month of observation siteclass Sample point location defined as a "wake" zone or "control" zone period Labels for "before" or "after" commission date mean.ndvi Mean NDVI value for the month and year identified for each site sd.ndvi Standard deviation of NDVI value for the month and year identified for each site mean.logndvi Logarithmic mean of the NDVI value sd.logndvi Standard deviation of the logarithmic mean of the NDVI value mean.anomaly Mean of the NDVI anomaly value sd.anomaly Standard deviation of the mean of the NDVI anomaly value DEM Elevation value in meters unique to each site FoldA Folded aspect value derived from elevation where the highest values are southwest and the lowest values are northeast identifying warmer temperatures Pslope Percent slope, derived from elevation EucDist Distance from nearest turbine to sample location in meters DEM_Avg Average elevation for all facility turbines in meters DEM_TURB Elevation of nearest turbine to sample location in meters PRECIP_30 30-year climate normal for precipitation in mm TMAX_30 30-year climate normal for maximum temperature in Celsius VPDMAX_30 30-year climate normal for maximum vapor-pressure deficit in hPA (hectopascals) PET Potential evapotranspiration in mm, used to calculate aridity Precip Monthly averaged precipitation value in mm Precip_lag 3-Month lagged average precipitation value in mm Precip_lag_month Monthly lagged precipitation value in mm Tmax Maximum temperature averaged value in Celsius VPDmax Maximum vapor-pressure deficit averaged value in hPA (hectopascals) PET_ORG Original PET value in mm (contains zeros) PET_lag 3-Month lagged average PET value in mm PRECIP_ANOM Precipitation anomaly in mm PRECIP_lag_ANOM Lagged monthly precipitation anomaly in mm TMAX_ANOM Maximum temperature anomaly in Celsius VPDMAX_ANOM Maximum vapor-pressure deficit anomaly in hPA (hectopascals) ARIDITY Monthly aridity value calculated by dividing monthly precipitation by monthly PET ARIDITY_lag 3-Month lagged aridity value calculated by dividing monthly precipitation by monthly PET DEM_ANOM Elevation anomaly in meters yearf Year as a factor for code purposes monthf Month as a factor for code purposes sc_DEM_ANOM Scaled (centered on mean) Elevation anomaly in meters sc_FoldA Scaled (centered on mean) Folded aspect value derived from elevation where the highest values are southwest and the lowest values are northeast identifying warmer temperatures sc_Pslope Scaled (centered on mean) percent slope, derived from elevation sc_EucDist Scaled (centered on mean) distance from nearest turbine to sample location in meters sc_VPDMAX_ANOM Scaled (centered on mean) maximum vapor-pressure deficit averaged value in hPA (hectopascals) sc_TMAX_ANOM Scaled (centered on mean) maximum temperature anomaly in Celsius sc_PRECIP_ANOM Scaled (centered on mean) precipitation anomaly in mm sc_PRECIP_lag_ANOM Scaled (centered on mean) lagged monthly precipitation anomaly in mm sc_ARIDITY Scaled (centered on mean) monthly aridity value calculated by dividing monthly precipitation by monthly PET sc_ARIDITY_lag Scaled (centered on mean) 3-Month lagged aridity value calculated by dividing monthly precipitation by monthly PET date Date centered on mid-point in month for code purposes All "_monthly_data_all.csv" spreadsheets have identical column names Facility_WindSpeed.zip: day Day of year hour Hour of day year Year of observation (starting from facility commission date) u U-wind velocity component for eastward wind speed v V-wind velocity component for northward wind speed U_V_spd Wind speed in meters per second for each observation U_V_dir Direction wind is coming from in degrees Direction Abbreviation indicating direction of wind (8 possible options: NNE, ENE, ESE, SSE, SSW, WSW, WNW, NNW) All "_Wind_Speed.csv" spreadsheets have identical column names Supplemental_CSVs.zip: wind_summary_table.csv- Facility ID ID assigned to each facility for use in figure identification Facility Name Name of facility from the USGS Wind Turbine Database Variable Speed or distance identifier for each facility NNE Speed or distance value for the NNE direction ENE Speed or distance value for the ENE direction ESE Speed or distance value for the ESE direction SSE Speed or distance value for the SSE direction SSW Speed or distance value for the SSW direction WSW Speed or distance value for the WSW direction WNW Speed or distance value for the WNW direction NNW Speed or distance value for the NNW direction Average Average speed from all direction (not applicable for direction) rvi_summary_table.csv- Facility ID ID assigned to each facility for use in figure identification Facility Name Name of facility from the USGS Wind Turbine Database Variable Climate or physical variable identifier for each facility Relative Variable Influence Relative variable influence value with high value of 1 and decreasing with less variable importance Model Averaging Standardized Estimate The model averaging standardized estimate to pair with the RVI value to determine variable importance Model Averaging Standardized Standard Error The model averaging standard error of the estimate to pair with the RVI value to determine variable importance Model Averaging Raw Estimate The model averaging raw estimate to pair with the RVI value to determine variable importance Model Averaging Raw Standard Error The model averaging raw standard error of the estimate to pair with the RVI value to determine variable importance R2 The R2 value for the model averaging (only 1 estimate per facility) facility_summary_table.csv- Facility ID ID assigned to each facility for use in figure identification Name in USWTDB Name of facility from the USGS Wind Turbine Database State State abbreviation for where facility is located Turbine Count Turbine count per facility Hub Height Average hub height of turbines in facility Rotor Diameter Average rotor diameter of turbines in facility Dominant Land Cover Dominant land cover class for each facility Before-After Installation Year The before/after year used in the analysis representing the commissioning year of each facility Green Up Months Set of two numbers representing months of green up based on NDVI Peak Green Months Set of three numbers representing months of peak green based on NDVI Green Down Months Set of two numbers representing months of green down based on NDVI baci_table.csv- Facility ID ID assigned to each facility for use in figure identification Facility Name Name of facility from the USGS Wind Turbine Database Time Period Seasonal and climate based time period splits Before-After-Control-Impact Contrast The BACI contrast value for each time period Before-After-Control-Impact Standard Error The BACI contrast standard error value for each time period P-value The p value showing significance at .05 Lower Limit The lower-limit of the BACI value analysis Upper Limit The upper-limit of the BACI value analysis Control After NDVI The control zone after construction value from the BACI analysis over the time period Control Before NDVI The control zone before construction value from the BACI analysis over the time period Wake After NDVI The wake zone after construction value from the BACI analysis over the time period Wake Before NDVI The wake zone after construction value from the BACI analysis over the time period Relative Difference from Expected NDVI The relative change in NDVI from the expected value based on BACI analysis R2 The R2 value for the BACI analysis model_summary_table.csv- Facility ID ID assigned to each facility for use in figure identification Facility Name Name of facility from the USGS Wind Turbine Database forumla Formula built from R code showing top variables present in each model df The degrees of freedom for each model logLik The log-likelihood value of a regression model as a way to measure the goodness of fit for the model AICc The Akaike information criterion value of a regression model as a way to measure the goodness of fit for the model delta The difference from the best model to the model in question weight Value showing how much weight the specific model carried in the analysis ndvi_charts.csv- Months Month of NDVI average value NE-1 Average NDVI value for month in question at the NE-1 facility used to determine periods of Up, Down and Peak NDVI TX-1 Average NDVI value for month in question at the TX-1 facility used to determine periods of Up, Down and Peak NDVI ME-1 Average NDVI value for month in question at the ME-1 facility used to determine periods of Up, Down and Peak NDVI TX-2 Average NDVI value for month in question at the TX-2 facility used to determine periods of Up, Down and Peak NDVI AZ-1 Average NDVI value for month in question at the AZ-1 facility used to determine periods of Up, Down and Peak NDVI OR-1 Average NDVI value for month in question at the OR-1 facility used to determine periods of Up, Down and Peak NDVI WY-1 Average NDVI value for month in question at the WY-1 facility used to determine periods of Up, Down and Peak NDVI CA-1 Average NDVI value for month in question at the CA-1 facility used to determine periods of Up, Down and Peak NDVI WV-1 Average NDVI value for month in question at the WV-1 facility used to determine periods of Up, Down and Peak NDVI NM-1 Average NDVI value for month in question at the NM-1 facility used to determine periods of Up, Down and Peak NDVI AZ-2 Average NDVI value for month in question at the AZ-2 facility used to determine periods of Up, Down and Peak NDVI KS-1 Average NDVI value for month in question at the KS-1 facility used to determine periods of Up, Down and Peak NDVI OK-1 Average NDVI value for month in question at the OK-1 facility used to determine periods of Up, Down and Peak NDVI ND-1 Average NDVI value for month in question at the ND-1 facility used to determine periods of Up, Down and Peak NDVI MT-1 Average NDVI value for month in question at the MT-1 facility used to determine periods of Up, Down and Peak NDVI ND-SD-1 Average NDVI value for month in question at the ND-SD-1 facility used to determine periods of Up, Down and Peak NDVI WA-1 Average NDVI value for month in question at the WA-1 facility used to determine periods of Up, Down and Peak NDVI R_Code.zip: facility_parameters.csv- FileName Simplified facility name with no spaces for use in R code dateymd Date in year/month/day format for code BeforeAfterYear Commissioning date of turbine facility used to define before/after year in code GR_UP Month of green up start GR_PEAK Month of peak green GR_DOWN Month of green end GR_UPM1 Green up first month GR_UPM2 Green up last month GR_PEAKM1 Green peak first month GR_PEAKM2 Green peak middle month GR_PEAKM3 Green peak last month GR_DOWNM1 Green down first month GR_DOWNM2 Green down last month bacibarcharts.csv- Name Simplified facility name for use in R code BA_year Commissioning date of turbine facility used to define before/after year in code Gr_Peak Month of peak green Greenup Month of green up Greendown Month of green down Time Defines the period as all, up, peak, down, Phigh and Plow BACI_contrast The Before-After-Control-Impact value generated by the code BACI_SE The standard error from the BACI model pvalue The p value showing significance at .05 LL The lower-limit of the BACI value analysis UL The upper-limit of the BACI value analysis CA The control zone after construction value from the BACI analysis over the time period CB The control zone before construction value from the BACI analysis over the time period WA The wake zone after construction value from the BACI analysis over the time period WB The wake zone after construction value from the BACI analysis over the time period Rel_diff The relative change in NDVI from the expected value based on BACI analysis Data_Dictionary_WindWakes.csv U.S. Geological Survey - Science Base mailing and physical

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Denver CO 80225-0046 USA 1-888-275-8747 sciencebase@usgs.gov Any use of trade, product or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Geological Survey. Although this information product, for the most part, is in the public domain, it also contains copyrighted materials as noted in the text. Permission to reproduce copyrighted items for other than personal use must be secured from the copyright owner. This database has been approved for release and publication by the Director of the USGS. Although this database has been subjected to rigorous review and is substantially complete, the USGS reserves the right to revise the data pursuant to further analysis and review. Furthermore, it is released on condition that neither the USGS nor the United States Government may be held liable for any damages resulting from its authorized or unauthorized use. Although these data have been processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data on any other system, or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and/or contained herein. CSV SHP R Code https://doi.org/10.5066/P9P3J7GR None 20220927 Zachary H Ancona U.S. Geological Survey mailing and physical

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Denver CO 80225-0046 United States 303-236-1886 zancona@usgs.gov Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998