# Stronger Cumulative than Lagged Effects of Drought on Vegetation in Central Asia
## 3 Results
### Lagged Effect of Drought on Vegetation GPP  
The space distribution of Rmax_lag of the lagged effect of drought on vegetation GPP was obtained from the analysis of the correlation of GPP with the SPEI with a 1-month scale lag, as shown in Figure 7a. In Central Asia, 99.87% and 0.13% of the regions showed positive and negative correlations between vegetation GPP and SPEI, respectively, and 38.80% of the regions were significantly correlated (\(p<0.05\)). Rmax_lag had a mean value of 0.25, and the Rmax_lag values in most regions were concentrated in the range of 0.15-0.35. In the lagged effect, higher correlations greater than 0.45 were mainly distributed in southern and northwestern Kazakhstan, and a small number of regions were distributed in northwestern Kyrgyzstan and northern Tajikistan. Negative correlations were mainly distributed in the northern area of Xinjiang, China. Lagged months in Central Asia were mainly found in shorter time scales (1-3 months), as shown in Figure 7b, where a 2-month lag was more widespread, with a percentage of the area as high as 37%, followed by a 1-month lag, accounting for 23% of Central Asia. These two lag time scales were widely distributed across Central Asia. Droughs with a 5-month lag were more widespread (10%), mainly in eastern and southern Kazakhstan, western Tajikistan, eastern Uzbekistan, and western Kyrgyzstan. None of the other lag time scales exceeded 10%. The smallest lag was 10-12 months (<3%) and was prominent in northeastern Kazakhstan and the northern Xinjiang region of China. We further analyzed the response of GPP to drought lag months for different vegetation types, as shown in Figure 7c. The average number of lag months for vegetation was 3 months, and forests had the most lag months, with a mean of 4.96 months, followed by cropland (3.98 months), grassland (2.92 months), and shrublan (2.02 months). Figure 6: Change in average annual SPEI over time in Central Asia from 2000 to 2018. Figure 7: Distribution of the lagged effect of drought on vegetation. (**a**) Spatial distribution of Rmax_lag of vegetation GPP and 1-month SPEI from 2000 to 2018. The blue areas indicate statistically significant correlations (\(p<0.05\)) and gray areas indicate statistically insignificant correlations (\(p>0.05\)); (**b**) Spatial distribution and percentage area of lag months corresponding to Rmax_lag; (**c**) Distribution of lag months corresponding to Rmax_lag for different vegetation types. The percentage area of the correlation coefficient ranks differed significantly on the lag time scale, as shown in Figure 8a. Rmax_lag in the range of 0.10-0.15 occurred in the 8-month lag time scale, with the largest percentage of the area of 40.43%. Across the lag time scale, 65.56% of the correlation coefficients were concentrated in the 0.10-0.25 range. Relatively few had an Rmax_lag greater than 0.40, accounting for 1.01% of the correlation areas. There was no strong correlation (Rmax_lag > 0.40) between GPP and SPEI on a long time scale (6-12 months) for multiple lagged time scales. Accordingly, the average coefficients of the correlation with GPP and the SPEI varied across vegetation types on lagged time scales, as shown in Figure 8b. The largest correlation coefficient (r = 0.28) was for a 2-month lag, followed by the coefficients for 1- and 3-month lags (r = 0.25), and the correlation coefficients for all the other lag time series were less than 0.24, which was generally the same as the percentage variation in the area of Rmax_lag. Among them, the lagged correlation coefficients of the forest GPP and SPEI were lower overall than the mean value, and the lag to drought was relatively weak. In contrast, the lagged correlation coefficients of grassland and shrubland were mostly higher than the mean value, and the lag to drought was relatively strong.