Modeling Study Projects by 2100 Dryland Expansion Will Result in Lower Global Gross Primary Production

Expansion and conversion changes among different dryland subtypes will lead to variability in regional and subtype contributions to the global GPP of drylands.

The Science

Drylands, such as grasslands, savannas, and deserts, are expected to expand and become more arid at an accelerating rate over the next century. The effects of this expansion and degradation on their gross primary production (GPP) remain elusive. Using model projections coupled with data from a number of FLUXNET sites, a multi-institutional team of scientists quantified the impact of accelerated dryland expansion on their productivity through the end of this century. In addition, as different subtypes of drylands expand and convert into other types, large changes will be seen in how regional drylands and subtypes will contribute to gross primary production.

The Impact

Drylands are the largest source of interannual variability in the global carbon sink. Any changes in dryland ecosystems under future climate scenarios would have large implications for the global carbon cycle. This work improves the understanding of how accelerated dryland expansion affects the productivity of drylands.

Dryland expansion and climate-induced conversions among subhumid, semiarid, arid, and hyperarid subtypes will lead to substantial changes in regional and subtype contributions to global dryland GPP variability.


Drylands, such as grasslands, savannas, and deserts, cover approximately 41% of the Earth’s land surface and support more than 38% of the global population. Global dryland ecosystems with high plant productivity account for approximately 40% of global land net primary production (NPP). They also act as the dominant global land carbon dioxide (CO2) sink and, over recent decades, have contributed the largest amount of net CO2 flux, which affects interannual variability.

To study the impact of accelerated dryland expansion and degradation on global dryland GPP, researchers from Washington State University and Pacific Northwest National Laboratory assessed MODIS GPP data from 2000–2014 and the 5th Coupled Model Intercomparison Project (CMIP5) aridity index (AI). Results from this modeling study show a positive relationship between GPP and AI over dryland regions, with total dryland GPP increasing by the end of the 21st century by 12% ± 3% relative to the 2000–2014 baseline. However, GPP per unit dryland area will decrease with degradation of currently existing drylands, meaning that global GPP may not increase. Changes in the expansion and conversions among different subtypes of drylands will lead to variability in regional and subtype contributions to the global GPP of drylands.

Researchers in this study used a cubic fitting method to find the relationship between dryland GPP and AI data from CMIP5. With long-term GPP data, they analyzed the trend and interannual variability of dryland GPP through the end of the century. To verify the accuracy of projected GPP data, the team compared projected GPP data to GPP data from 15 CMIP5 models. The results showed agreement with the modeling data in eight regions during the same period.

Principal Investigator(s)

Heping Liu
Washington State University

Xingyuan Chen
Pacific Northwest National Laboratory


This work is supported by the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy (DOE) Office of Science, as part of BER’s Subsurface Biogeochemical Research Program (SBR) at the Pacific Northwest National Laboratory (PNNL). We also acknowledge support by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP), Grant No. 2019QZKK0602; the National Natural Science Foundation of China under grants 41521004, 41991231 and 41975075; the Foundation of Key Laboratory for Semi-Arid Climate Change of the Ministry of Education in Lanzhou University; the China 111 Project (No. B13045); and the Fundamental Research Funds for the Central Universities (lzujbky-2017-it18).


Yao, J., Liu, H., Huang, J. et al. “Accelerated dryland expansion regulates future variability in dryland gross primary production.” Nature Communications 11,1665 (2020). [DOI:10.1038/s41467-020-15515-2]