Convergence of global hydrothermal pattern leads to an increase in vegetation net primary productivity

Changes in terrestrial net primary productivity (NPP) with climate were thought to arise from the direct effects of temperature and precipitation on plant metabolism. However, the change of NPP may be due to the indirect effect of global hydrothermal pattern changes caused by climate change on veget...

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Bibliographic Details
Published in:Ecological Indicators
Main Authors: Chuanhua Li, Min Zhou, Tianbao Dou, Tongbin Zhu, Huanhuan Yin, Lihui Liu
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2021
Subjects:
Online Access:https://doi.org/10.1016/j.ecolind.2021.108282
https://doaj.org/article/f2209ecbe6e64749989e3a69df53f662
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Summary:Changes in terrestrial net primary productivity (NPP) with climate were thought to arise from the direct effects of temperature and precipitation on plant metabolism. However, the change of NPP may be due to the indirect effect of global hydrothermal pattern changes caused by climate change on vegetation distribution. To prove this hypothesis, this study uses land outside Antarctica as the study area, combines temperature and precipitation into standard scores, classifies the globe into four hydrothermal types: warm-wet, warm-dry, cold-wet and cold-dry, analyses changes in hydrothermal patterns since 2000, relates them to changes in NPP, to explains the relationship between changes in global hydrothermal patterns and NPP of vegetation. We found that climate warming reduced the area difference of the four hydrothermal types, which led to the increase of vegetation NPP. The mechanism is mainly manifested in a convergence model of hydrothermal pattern of dry wet transformation (i.e. dry to wet, wet to dry). This shows that the global water and heat distribution has a balanced trend, which is shown as a better resource allocation scheme. This perspective provides a new explanation for the increase in global NPP in terms of global hydrothermal resource allocation, which could enhance the understanding of the impact of global warming on terrestrial vegetation productivity and improve the predictions of global carbon cycle models.