Incorporating dominant species as proxies for biotic interactions strengthens plant community models

• Published in: The Journal of ecology 2014-05, Vol.102 (3), p.767-775
• Main Authors: Roux, Peter C, Pellissier, Loïc, Wisz, Mary S, Luoto, Miska, Heard, Matthew
• Format: Article
• Language: English
• Subjects: abiotic gradients; Animal and plant ecology; Animal ecology; Animal, plant and microbial ecology; Biological and medical sciences; Biomass; biotic interactions; community composition; Community ecology; community structure; data collection; Determinants of plant community diversity and structure; dry matter content; Ecological modeling; Environmental conditions; Flowers & plants; functional structure; Fundamental and applied biological sciences. Psychology; General aspects; General aspects. Techniques; global change; Human ecology; leaf dry matter content; leaves; Mathematical models; Methods and techniques (sampling, tagging, trapping, modelling...); Plant communities; Plant ecology; Plant interaction; Plants; Roux; species distribution modelling; Species diversity; species richness; Synecology; Vascular plants
• ISSN: 0022-0477; 1365-2745
• DOI: 10.1111/1365-2745.12239

Biotic interactions exert considerable influence on the distribution of individual species and should, thus, strongly impact communities. Implementing biotic interactions in spatial models of community assembly is therefore essential for accurately modelling assemblage properties. However, this remains a challenge due to the difficulty of detecting the role of species interactions and because accurate paired community and environment data sets are required to disentangle biotic influences from abiotic effects. Here, we incorporate data from three dominant species into community‐level models as a proxy for the frequency and intensity of their interactions with other species and predict emergent assemblage properties for the co‐occurring subdominant species. By analysing plant community and field‐quantified environmental data from specially designed and spatially replicated monitoring grids, we provide a robust in vivo test of community models. Considering this well‐defined and easily quantified surrogate for biotic interactions consistently improved realism in all aspects of community models (community composition, species richness and functional structure), irrespective of modelling methodology. Dominant species reduced community richness locally and favoured species with similar leaf dry matter content. This effect was most pronounced under conditions of high plant biomass and cover, where stronger competitive impacts are expected. Analysis of leaf dry matter content suggests that this effect may occur through efficient resource sequestration. Synthesis. We demonstrate the strong role of dominant species in shaping multiple plant community attributes, and thus the need to explicitly include interspecific interactions to achieve robust predictions of assemblage properties. Incorporating information on biotic interactions strengthens our capacity not only to predict the richness and composition of communities, but also how their structure and function will be modified in the face of global change.