MEPS 271:1-12 (2004)  -  doi:10.3354/meps271001

ABSTRACT: In order to link actual biological data on bioturbation to the abstract parameters in bioturbation models, high-resolution data on the frequency and lengths of particle displacements are required. The temporal variation in bioturbation for a subtidal macrofaunal assemblage was studied non-invasively and in situ using an optically modified fluorescence sensitive time-lapse sediment profile imaging camera (f-SPI), fluorescent-dyed sediment particles (luminophores) and mathematical modelling. This combined approach allowed tracer particles to be non-invasively tracked and their displacements monitored at an unprecedented spatial (78 µm) and temporal (every 10 min) resolution for extended periods of time (16 h). The redistribution of luminophores was digitally acquired from sequential images and compared to model predictions, with particle transport modelled as (1) a diffusive process, allowing the biodiffusion coefficient, D_b, to be estimated, and (2) a non-local process, allowing a reworking activity constant, a, to be calculated. Model predictions of luminophore particle transport for the final image of the f-SPI sequence gave: D_b = 1.26 × 10² cm² yr^-1; a = 5.23 × 10^-2 cm^-1 yr^-1. Discrete values of a fluctuated widely throughout the sequence and allowed discrete bioturbation events to be identified. Time-lapse movie sequences revealed that most of the bioturbation observed during the deployment could be directly attributed to the behaviour of the brachyuran crab Hyas araneus. Our findings demonstrate that f-SPI provides a rapid and non-invasive means to visualise and quantify, in situ, the extent and influence of discrete infaunal bioturbation events on particle mixing. This technique provides detailed information on the spatial and temporal resolution of such bioturbation events, which could significantly improve existing models of bioturbation.

KEY WORDS: Sediment profile imaging · Luminophore tracer · Bioturbation · Biodiffusion coefficient · Reworking activity constant · Non-local modelling · Benthic