Organism functional traits and ecosystem supporting services – A novel approach to predict bioirrigation. (August 2018)

• Record Type: Journal Article
• Authors: Wrede, Alexa; Beermann, Jan; Dannheim, Jennifer; Gutow, Lars; Brey, Thomas
• Is Part Of: Ecological indicators. Volume 91(2018)
• Page Start: 737
• Page End: 743
• Publication Date: 2018-08
• Subjects: Bioturbation -- Biogeochemical cycling -- Bentho-pelagic coupling -- Bioturbation potential -- Trait based indices -- Marine Strategy Framework Directive; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2018.04.026
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: We propose a novel trait based index: the bioirrigation potential IPc. Multi factorial experiments validate the bioirrigation potential IPc. Spatial mapping highlights differences between IPc and the bioturbation potential. IPc improves quantitative spatial assessment of bioirrigation activity distinctly. IPc can be expanded easily to accommodate seasonal and temporal assessments. Abstract: Increasing anthropogenic activities on land and at sea underline the demand for easily applicable indices to effectively predict human mediated changes in ecosystem functioning. Here, we propose a novel bioirrigation index (IPc ) that is based on body mass, abundance, burrow type, feeding type and injection pocket depth of bottom dwelling animals. The index was validated with combined field (in situ communities) and manipulative (single species) experiments. Results from both community and single-species experimental incubations indicate that IPc is able to predict the bioirrigation rate in different sediment types (mud, fine sand, sand). The trait-based index thus demonstrates robustness in the prediction of animal-mediated functional processes that support biogeochemical functions under variable environmental conditions. Accordingly, we argue that trait-based indices provide a useful tool for the quantitative prediction of ecosystem processes as effect traits provide a direct link to the behavioral mechanisms that drive ecosystem functioning.