A trait-based modelling approach towards dynamic predictions of understorey communities in temperate forests

Dries Landuyt, Haben Blondeel, Eline Lorer, Michael P. Perring, Kathy Steppe and Kris Verheyen

Ecological Modelling, 2024, vol. 498, issue C

Abstract: Understorey communities in temperate forests have often been ignored in the study of the dynamics of forest structure and function, while evidence for the importance of this biotic layer is accumulating. Scarcity in understorey data with a high temporal resolution, and understorey data types that do not match popular vegetation modelling concepts, have limited previous modelling attempts to empirical models that are hard to extrapolate to new environmental conditions. Here we introduce a new process-based modelling approach designed specifically for understorey communities, whose dynamics are generally characterised by changes in (species-specific) cover data, while species characterisation is largely based on plant functional trait measurements. By confronting the model to data gathered in a large understorey mesocosm experiment, we show that our model concept is promising, and is able to predict performance differences within a species. Predictions across species were found to be more challenging, and will likely require new data on understorey traits and processes. In particular, new data on understorey carbon assimilation rates, vegetative phenology, plant architecture and belowground processes, are needed to advance the field of process-based understorey modelling.

Keywords: Process-based modelling; Herbaceous vegetation; Understory; Global change; Functional traits; DynaFORb (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380024002618
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:498:y:2024:i:c:s0304380024002618

DOI: 10.1016/j.ecolmodel.2024.110873

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().