Optimality Theory informed Carbon Storage Allocation under drought

Stefaniak, E., Tissue, D., Dewar, R., Hofhansl, F. ORCID: https://orcid.org/0000-0003-0073-0946, Joshi, J., & Medlyn, B. (2023). Optimality Theory informed Carbon Storage Allocation under drought. In: 2nd Workshop Carbon Allocation in Plants - Advances in carbon allocation and acquisition, 20-21 NOVEMBER 2023, Versailles, France.

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Understanding forest ecosystem functioning has never been more pressing in the context of projected climate change and human-induced disturbance. Both are major stressors on plants competing for limiting nutrients. In the face of such stressors, allocation of carbon to storage reserves in the form of non-structural carbohydrates (NSC) allows plants to maintain a reserve carbon pool in anticipation of future stresses that may limit photosynthesis. However, investing in storage reserves comes at the cost of foregoing the immediate use of the carbon for growth, creating a trade-off between storage and growth. Here, we propose a framework for optimality-based modelling of carbon storage allocation based on a plant population dynamics model for simulating changes in plant carbon allocation in response to drought. First, we use optimal control theory to identify patterns of plant growth and carbon storage based on the ‘active carbon storage’ hypothesis. Second, we use a gap model to explore differences in traits that determine plants’ carbon storage strategies, such as, carbon utilisation rate (fast-slow spectrum) and the latency of switching between growth and storage (risky-safe spectrum). Third, we will apply an eco-evolutionary vegetation model to elucidate the underlying mechanisms driving trait evolution across stress gradients, quantified by stress stochasticity (variance of stress duration) and stress intensity (average stress duration). Our framework provides an evolutionarily consistent way to simulate plant carbon allocation in response to drought, and can therefore be applied to investigate the functional response of global forest ecosystems under unprecedented future climatic conditions.

Item Type: Conference or Workshop Item (Poster)
Research Programs: Advancing Systems Analysis (ASA)
Advancing Systems Analysis (ASA) > Exploratory Modeling of Human-natural Systems (EM)
Depositing User: Luke Kirwan
Date Deposited: 19 Dec 2023 10:49
Last Modified: 19 Dec 2023 10:49
URI: https://pure.iiasa.ac.at/19358

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