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Water use efficiency of China's terrestrial ecosystems and responses to drought.

Liu Y, Xiao J, Ju W, Zhou Y, Wang S, Wu X - Sci Rep (2015)

Bottom Line: Droughts usually increased annual WUE in Northeast China and central Inner Mongolia but decreased annual WUE in central China. "Turning-points" were observed for southern China where moderate and extreme droughts reduced annual WUE and severe drought slightly increased annual WUE.The cumulative lagged effect of drought on monthly WUE varied by region.WUE is expected to continue to change under future climate change particularly as drought is projected to increase in both frequency and severity.

View Article: PubMed Central - PubMed

Affiliation: Jiangsu Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, China.

ABSTRACT
Water use efficiency (WUE) measures the trade-off between carbon gain and water loss of terrestrial ecosystems, and better understanding its dynamics and controlling factors is essential for predicting ecosystem responses to climate change. We assessed the magnitude, spatial patterns, and trends of WUE of China's terrestrial ecosystems and its responses to drought using a process-based ecosystem model. During the period from 2000 to 2011, the national average annual WUE (net primary productivity (NPP)/evapotranspiration (ET)) of China was 0.79 g C kg(-1) H2O. Annual WUE decreased in the southern regions because of the decrease in NPP and the increase in ET and increased in most northern regions mainly because of the increase in NPP. Droughts usually increased annual WUE in Northeast China and central Inner Mongolia but decreased annual WUE in central China. "Turning-points" were observed for southern China where moderate and extreme droughts reduced annual WUE and severe drought slightly increased annual WUE. The cumulative lagged effect of drought on monthly WUE varied by region. Our findings have implications for ecosystem management and climate policy making. WUE is expected to continue to change under future climate change particularly as drought is projected to increase in both frequency and severity.

No MeSH data available.


Spatial distribution of the correlations between monthly WUE and SPI for the period of 2000–2011.(a) The values represent the maximum correlation recorded (Pearson coefficient, R) for each pixel, independently of the month of the year and the SPI time-scale. (b) SPI time-scales at which the maximum correlation between SPI and WUE recorded. Areas with no significant correlations (p>0.05) are indicated in white. This figure was produced using ArcGIS 10.0.
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f5: Spatial distribution of the correlations between monthly WUE and SPI for the period of 2000–2011.(a) The values represent the maximum correlation recorded (Pearson coefficient, R) for each pixel, independently of the month of the year and the SPI time-scale. (b) SPI time-scales at which the maximum correlation between SPI and WUE recorded. Areas with no significant correlations (p>0.05) are indicated in white. This figure was produced using ArcGIS 10.0.

Mentions: Drought and the resulting changes in WUE may not occur simultaneously because of the different responses of carbon uptake and ET to drought. The correlation coefficient (Pearson coefficient, R) between monthly WUE values and monthly standardized precipitation index (SPI) at different time scales were calculated to assess the accumulative lagged effects of droughts on WUE. Figure 5 shows the spatial distribution of maximum correlation coefficient between SPI and monthly WUE for the period 2000–2011 and the corresponding SPI timescales. WUE was significantly correlated with SPI (p < 0.05) in more than 68% vegetated areas (Fig. 5a). SPI and WUE exhibited strongest relationship in central, southwestern, and northeastern China affected by several droughts during the study period. Weak relationships between SPI and WUE were observed only in some western regions.


Water use efficiency of China's terrestrial ecosystems and responses to drought.

Liu Y, Xiao J, Ju W, Zhou Y, Wang S, Wu X - Sci Rep (2015)

Spatial distribution of the correlations between monthly WUE and SPI for the period of 2000–2011.(a) The values represent the maximum correlation recorded (Pearson coefficient, R) for each pixel, independently of the month of the year and the SPI time-scale. (b) SPI time-scales at which the maximum correlation between SPI and WUE recorded. Areas with no significant correlations (p>0.05) are indicated in white. This figure was produced using ArcGIS 10.0.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4562296&req=5

f5: Spatial distribution of the correlations between monthly WUE and SPI for the period of 2000–2011.(a) The values represent the maximum correlation recorded (Pearson coefficient, R) for each pixel, independently of the month of the year and the SPI time-scale. (b) SPI time-scales at which the maximum correlation between SPI and WUE recorded. Areas with no significant correlations (p>0.05) are indicated in white. This figure was produced using ArcGIS 10.0.
Mentions: Drought and the resulting changes in WUE may not occur simultaneously because of the different responses of carbon uptake and ET to drought. The correlation coefficient (Pearson coefficient, R) between monthly WUE values and monthly standardized precipitation index (SPI) at different time scales were calculated to assess the accumulative lagged effects of droughts on WUE. Figure 5 shows the spatial distribution of maximum correlation coefficient between SPI and monthly WUE for the period 2000–2011 and the corresponding SPI timescales. WUE was significantly correlated with SPI (p < 0.05) in more than 68% vegetated areas (Fig. 5a). SPI and WUE exhibited strongest relationship in central, southwestern, and northeastern China affected by several droughts during the study period. Weak relationships between SPI and WUE were observed only in some western regions.

Bottom Line: Droughts usually increased annual WUE in Northeast China and central Inner Mongolia but decreased annual WUE in central China. "Turning-points" were observed for southern China where moderate and extreme droughts reduced annual WUE and severe drought slightly increased annual WUE.The cumulative lagged effect of drought on monthly WUE varied by region.WUE is expected to continue to change under future climate change particularly as drought is projected to increase in both frequency and severity.

View Article: PubMed Central - PubMed

Affiliation: Jiangsu Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, China.

ABSTRACT
Water use efficiency (WUE) measures the trade-off between carbon gain and water loss of terrestrial ecosystems, and better understanding its dynamics and controlling factors is essential for predicting ecosystem responses to climate change. We assessed the magnitude, spatial patterns, and trends of WUE of China's terrestrial ecosystems and its responses to drought using a process-based ecosystem model. During the period from 2000 to 2011, the national average annual WUE (net primary productivity (NPP)/evapotranspiration (ET)) of China was 0.79 g C kg(-1) H2O. Annual WUE decreased in the southern regions because of the decrease in NPP and the increase in ET and increased in most northern regions mainly because of the increase in NPP. Droughts usually increased annual WUE in Northeast China and central Inner Mongolia but decreased annual WUE in central China. "Turning-points" were observed for southern China where moderate and extreme droughts reduced annual WUE and severe drought slightly increased annual WUE. The cumulative lagged effect of drought on monthly WUE varied by region. Our findings have implications for ecosystem management and climate policy making. WUE is expected to continue to change under future climate change particularly as drought is projected to increase in both frequency and severity.

No MeSH data available.