The role of plant traits in shaping local plant communities (ComTrait)
Main funder
Funder's project number: 347558
Funds granted by main funder (€)
- 268 957,00
Funding program
Project timetable
Project start date: 01/09/2022
Project end date: 31/08/2025
Summary
Biotic interactions are central functions of ecological communities but hard to quantify. Biotic processes such as competition and facilitation are traditionally studied as simple interactions or co-occurrence patterns of species pairs. However, I hypothesize that specific species species interactions are relatively rare in plant communities and biotic processes are mediated by the traits of plant individuals instead. For instance, a tall plant shades its small neighbors irrespective of its taxonomic status. Thus, simply recording heights of the plants can provide a more mechanistic way of describing biotic processes than inference from multidimensional community composition.
Plant functional traits, such as height or specific leaf area, are a common language in ecology as they can be measured on any species in any plant community. Functional traits have been empirically linked to local adaptations and competitive ability of the plants and their effects on ecosystems. Thus, they provide a generalizable toolset to model and predict the outcome of complex biotic interactions in a hierarchical framework where the key abiotic factors, species’ traits and community composition can all be studied at once. However, such frameworks have rarely been adopted in predictive ecology.
Here, I will promote the inclusion of plant traits and biotic interactions into predictive ecology by using both observational and experimental approaches. The observational studies will be based on a unique –and largely existing– dataset from northern Fennoscandia along wide natural gradients. Multifaceted in-situ measured data on community compositions, plant functional traits and fitness will be combined with key abiotic conditions such as microclimate, soil moisture and nutrient levels. Hierarchical and semi-causal models will be employed to extract the trait-mediated biotic signals from the direct and indirect effects of more traditionally used abiotic factors. Moreover, I will conduct a plant removal experiment by removing plants from natural communities depending on their functional traits. Special attention will be paid on harmonizing the observational and experimental study settings so that the results can be synthetized and compared to increase the credibility and impact of the results. The project aims to shift the community ecology from the science of species towards a science of individuals — the biological level where local adaptations and ecological filters ultimately work.
Plant functional traits, such as height or specific leaf area, are a common language in ecology as they can be measured on any species in any plant community. Functional traits have been empirically linked to local adaptations and competitive ability of the plants and their effects on ecosystems. Thus, they provide a generalizable toolset to model and predict the outcome of complex biotic interactions in a hierarchical framework where the key abiotic factors, species’ traits and community composition can all be studied at once. However, such frameworks have rarely been adopted in predictive ecology.
Here, I will promote the inclusion of plant traits and biotic interactions into predictive ecology by using both observational and experimental approaches. The observational studies will be based on a unique –and largely existing– dataset from northern Fennoscandia along wide natural gradients. Multifaceted in-situ measured data on community compositions, plant functional traits and fitness will be combined with key abiotic conditions such as microclimate, soil moisture and nutrient levels. Hierarchical and semi-causal models will be employed to extract the trait-mediated biotic signals from the direct and indirect effects of more traditionally used abiotic factors. Moreover, I will conduct a plant removal experiment by removing plants from natural communities depending on their functional traits. Special attention will be paid on harmonizing the observational and experimental study settings so that the results can be synthetized and compared to increase the credibility and impact of the results. The project aims to shift the community ecology from the science of species towards a science of individuals — the biological level where local adaptations and ecological filters ultimately work.
Principal Investigator
Primary responsible unit
Related publications and other outputs
- High-resolution spatial patterns and drivers of terrestrial ecosystem carbon dioxide, methane, and nitrous oxide fluxes in the tundra (2024) Virkkala, Anna-Maria; et al.; A1; OA
- Variability and drivers of winter near-surface temperatures over boreal and tundra landscapes (2024) Tyystjärvi, Vilna; et al.; A1; OA
- Local snow and fluvial conditions drive taxonomic, functional and phylogenetic plant diversity in tundra (2023) Rissanen, Tuuli; et al.; A1; OA
- Soil moisture variations from boreal forests to the tundra (2023) Kemppinen, J.; et al.; A1; OA
