Defining and Assessing Benthic Recovery Following Dredging and Dredged Material Disposal
Type:
Presented during:
WODCON XVIII - 2007 Orlando, Florida, USA
Authors:
Wilber
Abstract: Assessing the recovery of benthic habitats disturbed by dredging and dredged material disposal operations is an important and growing management issue throughout the world. Although many projects have been monitored and a substantial literature on the subject exists, few generalizations can be made about typical recovery rates because biological responses are influenced by numerous factors, including site-specific bathymetry, hydrodynamics, depth of deposited sediments, the spatial scale of the disturbance, sediment type, and the timing and frequency of the disturbance. Additionally, there is no accepted definition of what constitutes “recovery.” In various studies, recovery has been defined as a return of benthic resources to a baseline (pre-impact) condition, a reference (neighboring unimpacted) condition and/or both. Infaunal macroinvertebrates are most commonly monitored to assess benthic recovery, usually by sampling the substrate, preserving organisms in formalin, and identifying and enumerating the organisms in the laboratory. Methods used to analyze these data vary and may influence study conclusions just as much as the aforementioned physical factors. Study results are generally presented through some combination of three methods of data analysis, i.e., univariate statistics (very common and used almost exclusively in early studies), multivariate statistics (increasingly common), and benthic indices. We review benthic recovery rates reported for approximately 50 dredging-related (disposal and dredging sites) projects and explore the relative influence of both physical and analytical factors in the determinations of recovery status. Although early impact assessments relied heavily upon univariate diversity indices that were derived from species level identifications of macroinvertebrates, it has become increasingly apparent that multivariate analyses of the same data sets provide more sensitive measures of ecological status.
Keywords: Meta-analysis, infauna, thin-layer, salt marsh, mud flat habitat