The LPJmL-FIT model (Lund Potsdam Jena managed Land - Flexible Individual Traits) represents a significant advancement in natural forest ecosystem modeling. Built on the established LPJmL modelling framework, LPJmL-FIT simulates individual trees with unique combinations of functional traits. This allows for a highly detailed, process-based understanding of biodiversity, vegetation dynamics and forest functioning under climate change.
The model simulates natural forests by capturing key processes such as tree establishment, growth, competition and mortality. To represent these dynamics, the model divides the simulated forest into 10m x 10m patches. Driven by daily climate data (temperature, precipitation, radiation), atmospheric CO₂ levels and soil properties, LPJmL-FIT effectively captures the intricate relationships between environmental conditions and plant performance.
Key Features:
- Functional Trait Diversity: Each tree is assigned a unique combination of functional traits, including specific leaf area (SLA), leaf longevity (LL), wood density (WD), leaf nitrogen content (Narea) and maximum carboxylation rate (Vcmax).
- Plant Functional Types (PFTs): The model classifies trees into plant functional types (PFTs), which group species with similar responses to environmental conditions and competition. The model randomly assigns one of the following PFTs to each newly established tree: Temperate broad-leaved summergreen, Broad-leaved evergreen, Boreal needle-leaved evergreen, Temperate needle-leaved evergreen or Boreal needle-leaved summergreen. To capture functional trait variability within these PFTs, individual tree traits are drawn from PFT-specific ranges based on plant trait data, such as those from the TRY global plant trait database.
- Forest Assembly Through Competition and Climate: As trees grow through different canopy layers, they compete for essential resources such as, light and water. Their survival and growth depend on photosynthesis, respiration and environmental conditions. Forest composition emerges through environmental and competitive filtering which gradually eliminates trait combinations that perform poorly under specific environmental conditions and local competition. Over time, this process results in forests dominated by trees with locally adapted trait combinations.
This video is published in Billing et al. Global Change Biology, 30, e17258. https://doi.org/10.1111/gcb.17258 2024.
