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Publication Detail
Coupling physical and ecological models: A new approach to predicting the impacts of aggregate extraction on biological recoverability.
  • Publication Type:
    Conference
  • Authors:
    Saunders J, Harris JM, Bishop SR, Schinaia SA, Simons R, Newell RC, Frost NJ
  • Publication date:
    01/09/2007
  • Status:
    Published
  • Name of conference:
    Change In Aquatic Ecosystems: natural and human influences
  • Conference place:
    Plymouth University, UK
  • Conference start date:
    04/07/2007
  • Conference finish date:
    06/07/2007
  • Notes:
    http://www.aquaticchange07.org/Aquatic_Change_Abstract_Volume.pdf
Abstract
4-6 July 2007, Plymouth, UK Currently, no quantitative tools have been tested for their ability to predict the long-term recovery of benthic communities from dredging. Recoverability is typically inferred from conceptual models. Therefore, there is a need to develop a quantitative model to allow regulators and managers to predict the impacts that dredging operations may have on the seabed and its ecology and to estimate the time for its recovery. The aim of the project was to develop cellular grid-based models predicting the impacts on physical and biological components of the marine environment. Cellular Automata (CA) are a class of cell-based mathematical model, discrete in time and space. The evolution of each cell over time is dependent on rules governing the nature of its interactions with other neighbouring cells. The dynamics of sediment transport are simulated by the movement of blocks, simplified as a series of iterations of the saltation process and deformational shaping by gravity, or avalanching. Our initial conceptual model considers a Test Field composed of uniformly distributed, sandy sediments. A trench is created to simulate the physical impact from dredging with lateral deposits left on either side and screened material deposited at the end. Tidal reversal is applied assuming parallel flows with a 10% asymmetry. Under these conditions, infilling of the trench is predicted to occur over 250 days. The physical model successfully reproduced changes to the seabed that broadly matched those of a typical case study site, including the steady-state topography, height of modelled bedforms, distance between bedforms and the movement of the bedforms. The characteristics of the biological model were determined by generating a series of simplified rules that governed species responses to physical change, food and space. A model based on five species groups was developed to take into account the range of species compositions present in a number of marine sedimentary environments. Initial models have been run describing the change in distribution of two species groups in response to various dredging scenarios. Importantly, the biological model is able to reproduce species responses to change as expected from case studies. The actual patterns are less meaningful at this stage, as interaction between the various species is not yet fully coupled. Future research is focussed on refining the physical model to represent a range of different dredging activities and sedimentary environments; incorporating the modelling of natural impacts such as those from storms; developing biological models for the remaining species groups; incorporating interaction among species groups with respect to predation and competition; and considering potential feedback into the physical model due to the role that some organisms play in sediment stabilisation.
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