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

Landuyt, Dries; Blondeel, Haben; Lorer, Eline; Perring, Michael P. ORCID: https://orcid.org/0000-0001-8553-4893; Steppe, Kathy; Verheyen, Kris. 2024 A trait-based modelling approach towards dynamic predictions of understorey communities in temperate forests. Ecological Modelling, 498, 110873. 11, pp. 10.1016/j.ecolmodel.2024.110873

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Abstract/Summary

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.

Item Type: Publication - Article
Digital Object Identifier (DOI): 10.1016/j.ecolmodel.2024.110873
UKCEH and CEH Sections/Science Areas: Soils and Land Use (Science Area 2017-)
ISSN: 0304-3800
Additional Keywords: process-based modelling, herbaceous vegetation, understory, global change, functional traits, DynaFORb
NORA Subject Terms: Ecology and Environment
Related URLs:
Date made live: 20 Sep 2024 13:20 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/538052

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