---
title: "Eco‑Evolutionary Optimal Carbon Allocation Model DAESIM2‑Plant: Theory and Wheat Application"
id: "biorxiv-14-eco-evolutionary-optimal-carbon-allocation-in-a-mechanisticcrop-growth-model"
canonical_url: "https://medichelpline.com/clinical-feed/biorxiv-14-eco-evolutionary-optimal-carbon-allocation-in-a-mechanisticcrop-growth-model"
content_type: "clinical_feed_article"
specialty: "General"
source_name: "bioRxiv (Biomedical Preprints)"
source_url: "https://www.biorxiv.org/content/10.64898/2026.09.20.753045v1?rss=1"
published_at: "2026-09-23T09:50:14.000Z"
evidence_level: "Verified Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Eco‑Evolutionary Optimal Carbon Allocation Model DAESIM2‑Plant: Theory and Wheat Application
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/biorxiv-14-eco-evolutionary-optimal-carbon-allocation-in-a-mechanisticcrop-growth-model
- **Specialty:** [General](https://medichelpline.com/clinical-feed/general.md)
- **Primary Source:** bioRxiv (Biomedical Preprints)
- **Source URL:** [Original Journal Publication](https://www.biorxiv.org/content/10.64898/2026.09.20.753045v1?rss=1)
- **Published At:** 2026-09-23T09:50:14.000Z
- **Evidence Rating:** Verified Feed
## Executive GIST (TL;DR)
- Carbon allocation determines how plants distribute assimilates among **leaves, roots, stems, and reproductive organs**, directly affecting growth and yield. - Typical crop models use fixed or empirical partitioning coefficients, limiting prediction of allocation responses to genotype, environment, or their interaction. - Eco‑evolutionary optimality theory allows allocation strategies to emerge from marginal costs and benefits of investing carbon in each organ rather than being prescribed. - The authors developed **DAESIM2‑Plant**, a mechanistic plant growth model that couples photosynthesis, stomatal conductance, plant hydraulics, and canopy radiative transfer with an eco‑evolutionary optimal allocation scheme for leaves and roots. - DAESIM2‑Plant is coupled to a source–sink grain production module to apply the framework to **wheat**, enabling simulation of vegetative growth and grain filling under the same assimilate constraints. - Idealized sensitivity experiments reproduced known allocation patterns: diminishing returns on leaf investment near canopy closure and under water limitation; increased root allocation under drier conditions; and root:shoot responses that depend on soil moisture and existing root:leaf balance. - Full‑season simulations across a soil moisture gradient revealed a threshold‑like response in canopy development, biomass accumulation, and grain yield, with yield constrained by assimilate supply during the critical period and grain filling. - The model provides a promising basis for generalizing behaviour across environmental conditions, but evaluation against experimental and field trial data is identified as an important next step. - The study is a preprint and has not undergone peer review. The authors declared no competing interests and reported funding from the Australian National Environmental Science Program (NESP) – Climate Systems Hub and an Australian Research Council Linkage Project.
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Alexander J Norton 1 CSIRO; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Alexander%2BJ%2BNorton%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Norton%20AJ&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AAlexander%2BJ%2BNorton%2B) * [ORCID record for Alexander J Norton](http://orcid.org/0000-0001-7708-3914 "Open in new tab") * For correspondence: alex.norton@csiro.au Justin O Borevitz 2 Australian National University * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Justin%2BO%2BBorevitz%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Borevitz%20JO&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AJustin%2BO%2BBorevitz%2B) * [Abstract](https://www.biorxiv.org/content/10.64898/2026.09.20.753045v1)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_art/node:5802676/1) * [Info/History](https://www.biorxiv.org/content/10.64898/2026.09.20.753045v1.article-info)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_info/node:5802676/1) * [Metrics](https://www.biorxiv.org/content/10.64898/2026.09.20.753045v1.article-metrics)[](https://www.biorxiv.org/panels_ajax_tab/article_tab_metrics/node:5802676/1) * [Supplementary material](https://www.biorxiv.org/content/10.64898/2026.09.20.753045v1.supplementary-material)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_data/node:5802676/1) * [ Preview PDF](https://www.biorxiv.org/content/10.64898/2026.09.20.753045v1.full.pdf+html)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_pdf/node:5802676/1) ![Loading](https://www.biorxiv.org/sites/all/modules/contrib/panels_ajax_tab/images/loading.gif) ## Abstract Carbon allocation governs how plants partition assimilates among leaves, roots, stems, and reproductive organs, directly shaping growth and yield. Most crop models represent this partitioning using fixed or empirically derived coefficients, which limits their ability to predict how allocation responds to genotype, environment, or their interaction. Eco-evolutionary optimality theory offers an alternative where the allocation strategy is allowed to emerge from the marginal costs and benefits of investing carbon in each organ. While this approach has been applied successfully to trees, it has not previously been developed for herbaceous plants. Here, we present DAESIM2-Plant, a mechanistic plant growth model that couples physiological processes including photosynthesis, stomatal conductance, plant hydraulics, and canopy radiative transfer, with an eco-evolutionary optimal allocation scheme for leaves and roots. This is applied to wheat by coupling it to a source-sink grain production module. Using a series of idealized sensitivity experiments, we show that the model reproduces well-documented patterns of plasticity in carbon allocation: diminishing returns on leaf investment as canopy closure and water limitation are approached, a shift in allocation toward roots under drier conditions, and a root:shoot response that depends jointly on soil moisture and the plant's existing root:leaf balance. Simulating a full growing season across a gradient of soil moisture levels reveals a threshold-like response in canopy development, biomass accumulation, and grain yield, with yield constrained by the same assimilate supply that governs vegetative growth during the critical period and grain filling. This provides a promising basis for generalizing model behaviour across a wide range of environmental conditions. Evaluating these results against experimental and field trial data remains an important next step. ### Competing Interest Statement The authors have declared no competing interest. ## Funder Information Declared Australian National Environmental Science Program (NESP) - Climate Systems Hub Australian Research Council, https://ror.org/05mmh0f86, Linkage Project LP19010106 Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a [CC-BY 4.0 International license](http://creativecommons.org/licenses/by/4.0/). bioRxiv and medRxiv thank the following for their generous financial support: > The Chan Zuckerberg Initiative, Cold Spring Harbor Laboratory, the Sergey Brin Family Foundation, California Institute of Technology, Centre National de la Recherche Scientifique, Fred Hutchinson Cancer Center, Imperial College London, Massachusetts Institute of Technology, Stanford University, The University of Edinburgh, University of Washington, and Vrije Universiteit Amsterdam. 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[ Download PDF](https://www.biorxiv.org/content/10.64898/2026.09.20.753045v1.full.pdf) Print/Save Options [Download PDF](https://www.biorxiv.org/content/biorxiv/early/2026/09/23/2026.09.20.753045.full.pdf)Full Text & In-line FiguresXML [More Info](https://www.biorxiv.org/about/FAQ#PrintOptions "More Information on Print/Save Options") [Supplementary Material ](https://www.biorxiv.org/content/10.64898/2026.09.20.753045v1.supplementary-material) [ Email](https://www.biorxiv.org/ "Email this Article") [ Share](https://www.biorxiv.org/) Eco-Evolutionary Optimal Carbon Allocation in a Mechanistic Crop Growth Model: Theory and Application to Wheat Alexander J Norton, Justin O Borevitz bioRxiv 2026.09.20.753045; doi: https://doi.org/10.64898/2026.09.20.753045 This article is a preprint and has not been certified by peer review [[what does this mean?](https://www.biorxiv.org/about/FAQ#unrefereed)]. 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