Moisture legacy effects shape vegetation productivity across East Asia ecosystems, 2001-2020

Area of Science:

• Ecology
• Climate Science
• Remote Sensing

Background:

• Growing season gross primary productivity (GPP) is a key indicator of ecosystem health and carbon sequestration.
• Understanding climate-vegetation relationships is crucial for predicting ecosystem responses to global change.

Purpose of the Study:

• To investigate spatiotemporal patterns of GPP in East Asia from 2001-2020.
• To examine the influence of climate variables on GPP across different vegetation types.
• To identify drivers of a notable GPP divergence around 2014.

Main Methods:

• Utilized MODIS satellite data to extract GPP and phenological parameters.
• Combined satellite data with meteorological records for trend and correlation analyses.
• Employed statistical methods to assess climate-GPP relationships and identify key drivers.

Main Results:

• Overall GPP_GS increased significantly (4.12 gC/m2/yr), with deciduous broad-leaved forest (DBF) showing the highest productivity.
• A divergence occurred around 2014, with grassland and deciduous needle-leaved forest (DNF) growth rates declining while DBF continued to increase.
• Relative humidity (RH), especially from the previous year, was the dominant driver of GPP, explaining the observed divergence.

Conclusions:

• Legacy effects of atmospheric moisture, particularly RH, are critical drivers of vegetation productivity and explain the 2014 GPP divergence.
• Increasing atmospheric dryness and temperature pose risks to vegetation carbon storage and ecosystem services.
• Water availability is increasingly important for maintaining ecosystem productivity under global warming.