Functionally distinct tree species support long-term productivity in extreme environments

Simulated forest biomass and productivity data from the ForCEEPS gap model, supporting research on how functionally distinct tree species maintain long-term productivity. The dataset contains outputs grouped by 11 environmental conditions and species richness gradients, including 30 random species orders. It was created by Léo Delalandre of the Centre National de la Recherche Scientifique for a study submitted to Proceedings of the Royal Society B.

Use Cases

• Modeling long-term forest productivity based on simulated biomass and species richness data.
• Analyzing the effect of species functional distinctiveness on ecosystem output across environmental gradients.
• Testing biodiversity-ecosystem function theories using aggregated community-level and species-level productivity data.

Strengths

• Data is derived from a named and documented forest simulation model (ForCEEPS).
• Simulations cover 11 distinct environmental conditions, allowing for comparative analysis.
• Includes multiple data aggregations (individual, community, species level) for the same richness gradients.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Centre National de la Recherche Scientifique (CNRS)

Collection Method

Output from simulations performed with the ForCEEPS forest gap model.