Water Addition Prolonged the Length of the Growing Season of the Desert Shrub Nitraria tangutorum in a Temperate Desert
Fang Bao, Fang Bao, Minghu Liu and 9 more
Frontiers in Plant Science · 2020
doi:10.3389/fpls.2020.01099 (opens in a new tab)
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Abstract
Climate models often predict that more extreme precipitation events will occur in arid and semiarid regions, where plant phenology is particularly sensitive to precipitation changes. To understand how increases in precipitation affect plant phenology, this study conducted a manipulative field experiment in a desert ecosystem of northwest China. In this study, a long-term in situ water addition experiment was conducted in a temperate desert in northwestern China. The following five treatments were used: natural rain plus an additional 0%, 25%, 50%, 75%, and 100% of the local mean annual precipitation. A series of phenological events, including leaf unfolding (onset, 30%, 50%, and end of leaf unfolding), cessation of new branch elongation (30%, 50%, and 90%), and leaf coloration (80% of leaves turned yellow), of the locally dominant shrub Nitraria tangutorum were observed from 2012 to 2018. The results showed that on average, over the seven-year-study and in all treatments water addition treatments advanced the spring phenology (30% of leaf unfolding) by 1.29–3.00 days, but delayed the autumn phenology (80% of leaves turned yellow) by 1.18–11.82 days. Therefore, the length of the growing season was prolonged by 2.11–13.68 days, and autumn phenology contributed more than spring phenology. In addition, water addition treatments delayed the cessation of new branch elongation (90%) by 5.82–12.61 days, and nonlinear relationships were found between the leaves yellowing (80% of leaves) and the amount of watering. Linear relationships were found between the cessation of new branch elongation (90%), the length of the growing season, and amount of water addition. The two response patterns to water increase indicated that predictions of phenological events in the future should not be based on one trend only.
Abstract licence: CC BY
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