Projection and Uncertainty in the Vegetation Growth and Carbon Cycle of a Transiting Temperate-Subtropical Mixed Forest in Jeju Island
Abstract
There are various ways in the response of terrestrial ecosystems to the ongoing climate changes, (e.g., changing its growing season length or shifting vegetation composition). In this study, we estimate changes in vegetation composition and carbon cycle of a temperate-subtropical mixed forest in Jeju island in South Korea by the end of this century and also assess uncertainty in the projections. The individual cohort-based model Ecosystem Demography Biosphere Model (ED2) was implemented with four behavioral parameter (PRM) sets under the climate inputs from four global climate models (GCMs) based on four Representative Concentration Pathway (RCP) scenarios. We then analyzed the long-term (2021 - 2099) changes in the vegetation species composition (i.e., basal areas of five plant function types), phenological timings, and carbon flux (i.e., net ecosystem productivity, NEP). We also applied the analyses of variance (ANOVA) to further decompose the contribution of each of the factors (i.e., PRM, GCM, and RCP) on the total uncertainty in the projected leaf area index (LAI) and NEP, seasonally and annually. We found the noticeable growth of subtropical species (from 11% in 2013 to 41.1% by 2099) and increases in LAI during dormancy season as with the growth of subtropical evergreen species. There are differences in the major uncertainty source between LAI and NEP; the uncertainty in LAI mainly result from the PRM (and interaction with climate inputs), while the one in NEP was from the climate inputs (GCM and RCP and their interaction). Our results suggest that it is important to consider the uncertainties resulting from the combination of different terrestrial models and climate inputs.
This study is supported by the National Research Foundation of Korea (NRF) grants funded by the Korea government (MSIT) (2020R1A2C2007670, 2020R1C1C1014886 and 2022R1C1C2009543).- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.B55D1002K