Both below-ground and above-ground functional traits can help predict levee grassland root length density as a proxy for flow erosion resistance

• Published in: Journal of vegetation science Vol. 27; no. 6; pp. 1254 - 1263
• Main Authors: Helsen, Kenny, Vannoppen, Wouter, Honnay, Olivier, Poesen, Jean
• Format: Journal Article
• Language: English
• Published: Blackwell Publishing Ltd 01.11.2016; John Wiley & Sons Ltd
• Subjects: Belgium; biomass; Biomass ratio effect; Erosion resistance; estuaries; Functional composition; Functional diversity; grasslands; least squares; Non-additive diversity effect; Partial least square regression; prediction; rivers; Soil detachment ratio; Soil erosion; species diversity; ANE, Belgium, Schelde Estuary; ANE, Belgium; Belgium
• ISSN: 1100-9233; 1654-1103
• DOI: 10.1111/jvs.12442

Aims: Concentrated flow erosion resistance of herbaceous vegetation is linked to vegetation-level root length density (RLD). However, RLD measurements involve destructive and time-consuming sampling. Since plant species richness, functional diversity and functional composition are expected to affect RLD through either non-additive diversity effects or biomass ratio effects, we evaluated whether these measures can be used as a proxy for RLD in levee grassland communities. Location: Levee grassland communities, Scheldt estuary, northern Belgium. Methods: We assessed the strength of correlation between empirically quantified RLD and species richness, functional diversity and functional composition of levee grasslands. More specifically, we used nine below-ground and ten above-ground plant traits retrieved from public databases, and applied linear regressions and partial least square regressions. Results: Plant functional diversity was a better proxy for RLD than plant species richness, with better predictive performance for below-ground than for aboveground traits. More specifically, the highest predictive power was achieved through integration of functional diversity, functional composition and species richness. This suggests that variation in RLD is driven by a combination of both non-additive diversity effects and biomass ratio effects. Conclusions: This study provides a first positive indication of the value of plant functional traits retrieved from databases to predict RLD for river levee grasslands. Furthermore, although less reliable than below-ground traits, above-ground traits are still useful for RLD prediction when information on below-ground traits is lacking.