Incorporating roots into Plant-FATE, a dynamic eco-evolution trait-based vegetation model

Maxwell, T., Stefaniak, E., Hofhansl, F. ORCID: https://orcid.org/0000-0003-0073-0946, & Joshi, J. (2024). Incorporating roots into Plant-FATE, a dynamic eco-evolution trait-based vegetation model. DOI:10.5194/egusphere-egu24-5706. In: EGU General Assembly 2024, 14-19 April 2024, Vienna.

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Abstract

To predict the response of forest ecosystems and how projected climate change will shift plant species composition, we need models that can account for adaptations encompassing multiple temporal and organizational scales. Recently, eco-evolutionary optimality-based models have emerged, which need fewer parameters than their empirical counterparts, i.e. standard dynamic global vegetation models. The new Plant-FATE (Plant Functional Acclimation and Trait Evolution) model embodies functional diversity through the representation of species across trait space. It integrates ecosystem adaptations across three distinct levels: firstly, it captures the acclimation of plastic traits in individual plants by harnessing the principles of eco-evolutionary optimality. Secondly, to simulate shifts in species composition through demographic changes and species immigration, a trait-size-structured demographic vegetation model is implemented. Lastly, the model addresses the long-term genetic evolution of species by incorporating novel evolutionary theory tailored for trait-size-structured communities. Currently, Plant-FATE implements fine roots by scaling these to total leaf area, and coarse roots as a fraction of stem mass. Thus, rooting structures, plant root traits, and belowground trade-offs are not represented.

To expand the modelling framework, we are implementing fine roots in a similar way as the crown, as a function of the root length profile and the root projection area. We are maintaining the current model structure so that total fine root mass is related to total leaf mass, which reduces the additional parameters needed to model. Instead, we are incorporating one additional trait, specific root length (SRL), which will determine the rooting profile, and which can evolve by natural selection in response to environmental changes. This allows for a depth distribution of fine roots, and for the plant water uptake to be dependent on both soil water potential and root distribution. At a community level, this implementation now means that changes in soil water content, e.g., during drought, can influence belowground competition and trade-offs between above- and below-ground biomass for different species. By modelling rooting strategies of deep-rooted vs shallow-rooted species, or evergreen vs deciduous species, the new root implementation in Plant-FATE will enable correct prediction of differential drought and climate response of coexisting plant species in line with the observed trade-offs in relative investment in above- and belowground tissues in association with their life-history strategy. It will thus allow to create a continuum of plants and their eco-evolutionary niches, which will allow us to predict plant functional diversity in response to environmental cues. Ultimately, incorporating roots in Plant-FATE will better represent ecosystem adaptation and community shifts in response to a changing climate.

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