Bio-irrigation in permeable sediments: An assessment of model complexity
Clicks: 2
ID: 296756
2006
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
0.3
/100
2 views
1 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #875 of 1,397 articles by views in journal of marine research
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,397 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Burrowing benthic animals ventilate their burrow networks, and this enhances the transport of solutes in the sediment and exchange with the overlying water column, a process referred to as bio-irrigation. Various models have been proposed to model bio-irrigation, with different levels of sophistication related to model dimensionality and parameter numbers. Here we address the issue of model complexity for bio-irrigation in permeable sediments. To this end, we simulated flowline patterns and tracer signals using (1) a full 3D model that explicitly models the J-shaped geometry of the burrow in a suitable microenvironment surrounding the burrow, (2) a simplified 2D axisymmetric analogue, which neglects the burrow shaft and only models the location of burrow water injection, (3) a highly simplified 1D model obtained by laterally averaging the microenvironment. Simulation of two separate inert tracer experiments shows that the 2D pocket injection model includes essential features (downward advective transport, spatial heterogeneity of pore water velocity, mechanistic specification of the seepage area) that are lost upon averaging to the corresponding 1D model. This loss of model detail must be compensated for by the introduction of additional, non-mechanistic fitting parameters in the 1D description. Similarly, the extension of the 2D model to a full sophisticated 3D description requires a major increase in computational resources, but only leads to a marginal improvement in the data simulation. Accordingly, we conclude that the 2D description provides an optimal balance between model simplicity and predictive capacity.
| Reference Key |
openalex_W1975807878
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Filip J. R. Meysman, O.S. Galaktionov, Britta Gribsholt, Jack J. Middelburg |
| Journal | journal of marine research |
| Year | 2006 |
| DOI |
10.1357/002224006778715757
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.