Florian Hartig Theoretical Ecology & Ecological Data Science

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Linking functional traits and demography to model species-rich communities

Loïc Chalmandrier, Florian Hartig, Daniel C. Laughlin, Heike Lischke, Maximilian Pichler, Daniel B. Stouffer, Loïc Pellissier

Nature Communications, 12(1), 2724 (2021)
Cite this
@article{chalmandrier2021linking,
  author = {Loïc Chalmandrier and Florian Hartig and Daniel C. Laughlin and Heike Lischke and Maximilian Pichler and Daniel B. Stouffer and Loïc Pellissier},
  title = {Linking functional traits and demography to model species-rich communities},
  journal = {Nature Communications},
  volume = {12},
  number = {1},
  pages = {2724},
  year = {2021},
  doi = {10.1038/s41467-021-22630-1},
}

DOI: 10.1038/s41467-021-22630-1
Cited by 53 (Google Scholar) · 73 (OpenAlex), as of 07 September 2026

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Abstract

It has long been anticipated that relating functional traits to species demography would be a cornerstone for achieving large-scale predictability of ecological systems. If such a relationship existed, species demography could be modeled only by measuring functional traits, transforming our ability to predict states and dynamics of species-rich communities with process-based community models. Here, we introduce a new method that links empirical functional traits with the demographic parameters of a process-based model by calibrating a transfer function through inverse modeling. As a case study, we parameterize a modified Lotka-Volterra model of a high-diversity mountain grassland with static plant community and functional trait data only. The calibrated trait-demography relationships are amenable to ecological interpretation, and lead to species abundances that fit well to the observed community structure. We conclude that our new method offers a general solution to bridge the divide between trait data and process-based models in species-rich ecosystems.

What the paper shows and why it matters (AI-generated)

Ecologists have long hoped that functional traits could stand in for hard-to-measure demographic parameters in process-based community models — if a trait-demography relationship existed, entire species-rich communities could be modelled from trait surveys alone. This paper builds and tests exactly that link, calibrating a Lotka-Volterra model of a high-diversity mountain grassland from trait data via inverse modelling, and getting species abundances that fit the observed community well. The trait-based framing has since spread widely through community ecology, from multi-scale plant-network segregation to trait-mediated shifts in species associations across microenvironments.