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where α and A are the average wall absorption coefficient and total wall surface area, respectively.
This results in a distinct subsurface maximum in burrow wall surface area at approximately 10 cm depth (Fig. 3A).
Nasal resistance increased and the wall heat transfer decreased in model (3) due to sudden airway expansion and excessive reduction of the mucosal wall surface area.
For each stochastic realization of the burrow network (Fig. 2), the burrow volume, density and burrow wall surface area are calculated within each depth interval of the 3D grid.
Simulated burrow wall surface area profiles for U. pugilator and U. pugnax both exhibit a subsurface maximum at approximately 10 cm depth (Fig. 6A,B), with few burrows extending deeper than 20 25 cm into the sediment.
This results in a distinct increase in burrow wall surface area at approximately 10 cm, which is not dissimilar from the subsurface maxima resulting from simulations using U- and Y-shaped burrows (Fig. 3C).
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X-radiography of sediment slabs from box cores has also been used to estimate burrow shapes and burrow wall surface areas.
herbsti burrows results in much higher burrow wall surface areas in the upper few cm of sediment and a more rapid decay of the burrow surface areas with depth (Fig. 10B).
In this study, stochastic simulations of 3D burrow networks are used to calculate mean densities, volumes and wall surface areas of burrows, as well as their variabilities, as a function of sediment depth.
Burrow network simulations of even relatively simple model organisms are found to result in depth-dependent burrow wall surface areas that are neither constant nor exponentially decreasing over a given interval, as is commonly assumed in bioirrigation models.
Burrow wall surface areas for polychaetes, shrimp and fiddler crabs only are highest near the sediment-water interface and decay gradually to a depth of approximately 30 cm (Fig. 10A).
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