What is it about?
Numerous empirical analyses have revealed how net primary production responds to climate change and variability over time. However, linear approaches predominantly used in previous studies often generate a weak relationship between climate factors and productivity, which greatly limits our understanding of the mechanism associated with this fundamental ecological process. We demonstrated dryland sensitivity to climate change and variability by incorporating nonlinear dynamics. Dryland sensitivity patterns revealed in this study are largely unrecognized and partly counterintuitive; however, the underlying mechanisms are inferable and cannot be fully revealed by linear approaches. Our work highlights the importance of nonlinear, state-dependent sensitivity of productivity to climate change and variability, accurately forecasting potential biosphere feedback to the climate system.
Photo by Peter Burdon on Unsplash
Why is it important?
Dryland sensitivity to climate change and variability was visualized at the regional scale, by using nonlinear time series analysis. Annual precipitation, temperature, aridity and their interannual variabilities causally drive dryland productivity. Previous studies have shown that dryland productivity is mainly driven by precipitation, but we show that temperature and its interannual variability are equally or more important drivers of dryland productivity than precipitation. The considerable, but until now underappreciated, importance of temperature and its interannual variability in driving dryland productivity are particularly notable given that the future increase in aridity will be driven by a steady increase in global surface temperature in response to elevated atmospheric CO2 levels. Dryland sensitivity to climate change depends on the time-delayed climate effects and the proportion of plant species resistant to water and temperature stresses at a site. Notably, our results suggest that the sensitivity of annual productivity to increasing annual precipitation and decreasing annual aridity can even be negative when the negative time-delayed effects of annual precipitation and aridity on productivity prevail across time. Thus, we highlight the importance of nonlinear, state-dependent sensitivity of productivity to climate change and variability, accurately forecasting potential biosphere feedback to the climate system.
Read the Original
This page is a summary of: Dryland sensitivity to climate change and variability using nonlinear dynamics, Proceedings of the National Academy of Sciences, August 2023, Proceedings of the National Academy of Sciences,
You can read the full text:
The following have contributed to this page