Improving leaf spring phenology modelling for temperate tree species: An integration of the Farquhar–Medlyn photosynthesis model with the optimality‐based approach

Gu, Yating; Wu, Zejun; Detto, Matteo; Yang, Dedi; Wang, Jiayue; Zhao, Yingyi; Yang, Xi; Wu, Jin

doi:10.1111/2041-210X.70181

Improving leaf spring phenology modelling for temperate tree species: An integration of the Farquhar–Medlyn photosynthesis model with the optimality‐based approach

Journal Article · Tue Oct 21 00:00:00 EDT 2025 · Methods in Ecology and Evolution (Online)

DOI:https://doi.org/10.1111/2041-210X.70181· OSTI ID:3011569

^[1]; Wu, Zejun ^[2]; Detto, Matteo ^[3]; ^[4]; Wang, Jiayue ^[2]; Zhao, Yingyi ^[2]; Yang, Xi ^[5]; ^[6]

Univ. of Hong Kong (Hong Kong); Hohai University, Nanjing (China)
Univ. of Hong Kong (Hong Kong)
Princeton Univ., NJ (United States)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Univ. of Virginia, Charlottesville, VA (United States)
Univ. of Hong Kong (Hong Kong); State Key Laboratory of Agrobiotechnology (CUHK), Hong Kong (China)

Spring leaf phenology in temperate tree species is highly sensitive to climate change and significantly affects plant photosynthetic performance, resource utilization, competition and trophic interactions, thereby impacting various ecosystem functions. Although optimality-based (OPT) approaches for modelling spring phenology are increasingly recognized, the optimal representation of the underlying principle (balancing photosynthesis gains with chilling risks) remains controversial. Here, we integrated a coupled Farquhar–Medlyn photosynthesis model into an existing OPT model, and termed the resulting model R-OPT, and evaluated its performance using the PEP725 dataset, which includes 409,144 site-species-year records from across Europe. Our results show that R-OPT outperforms both the default OPT and non-optimality-based models (e.g. the chilling-forcing trade-off and growing degree day models). This improved performance is consistent within and across five focal tree species but varies by region: R-OPT excels in lowland, moist environments but is less effective in high-altitude, cold, and dry areas, possibly due to an incomplete representation of environmental constraints on photosynthetic carbon gain in these regions. Our research advances leaf spring phenology modelling by emphasizing an optimality principle that balances photosynthetic carbon gain with chilling risk, improving the representation of plant photosynthesis processes and enhancing understanding of environmental factors influencing phenology in the context of climate change.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: Hong Kong Research Grant Council Collaborative Research Fund; Hong Kong Research Grant Council General Research Fund; Natural Science Foundation of China; Natural Science Foundation of Jiangsu Province; USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 3011569

Journal Information:: Methods in Ecology and Evolution (Online), Journal Name: Methods in Ecology and Evolution (Online) Journal Issue: 12 Vol. 16; ISSN 2041-210X

Publisher:: British Ecological SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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coupled Farquhar–Medlyn photosynthesis model
maximizing carbon gain
minimizing chilling risk
optimality principle
spring phenology
temperate tree species

Improving leaf spring phenology modelling for temperate tree species: An integration of the Farquhar–Medlyn photosynthesis model with the optimality‐based approach

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