Evaluating the UK forest demography and carbon cycle using a process-based Land Surface Model, JULES-RED

Hsi-Kai Chou,Anna Harper,Arthur Argles, Carolina Duran-Rojas,Emma Littleton,Peter Cox

crossref(2024)

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摘要
Global warming and climate change caused by greenhouse gas (GHG) emission is projected to have multiple impacts on the forest ecosystems. To mitigate these impacts, the UK Government has set a goal of net zero emissions of GHG by 2050. One core strategy is to use afforestation and forestry management to implement large-scale Greenhouse Gas Removal (GGR). However, the effectiveness of afforestation as a GGR strategy is difficult to fully evaluate with standard empirical models due to the complexities of environmental conditions under a changing climate. Alternatively, process-based land surface models (LSM), such as the Joint UK Land Environment Simulator (JULES), are increasingly being used to evaluate forest growth within a national GGR context as they are driven by environmental drivers. By coupling the Robust Ecosystem Demography (RED) model with JULES, we model the forest dynamic and carbon sequestration among a set of Representative Concentration Pathway (RCP) projections geographically across the UK up to 2080. Our results demonstrate the capability of mapping the potential GGR across the UK while also accounting for the changing environment and risks of climate change. The results show that JULES-RED can provide an effective tool for national-scale afforestation evaluation toward the 2050 net-zero targets.
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