CHAPTER 7 • The Implications of Oceanographic Chaos for Coastal Management
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It is only recently that modellers have tried to understand this patchiness at a scale
of tens to hundreds of metres (Wolanski and Sarsenski 1997). The verification of these
models is extremely difficult because the biological data are collected at different times
at different sites in a tidal cycle; hence a synoptic picture of the distribution in the field
is unavailable. For the case of coral eggs spawned at Bowden Reef, the model predicts
the formation of a plume entraining eggs away from the reef (Oliver et al. 1992). As can
be seen in Anim. 23, the predicted plume is extremely patchy, if not chaotic. Model verification was carried out by comparing, at a given instant of time, observed and predicted concentrations. In some cases, such as in Fig. 16, where biological data were available simultaneously at different points (the exception rather than the rule because it
requires several small boats operating simultaneously), the comparison is pleasing.
However, when all the data over several days and at about twenty sites are used, no significant correlation is found between observed mean concentrations (calculated from
triplicate samples) and the instantaneous predicted concentrations (Oliver et al. 1992).
It is not clear if this model failure is due to the model underestimating the patchiness
due to sub-grid scale aggregating processes (Wolanski and Hamner 1988) or to the
patchiness being so large that triplicate samples are not enough to reliably estimate
the mean values.
For prawn larvae, modellers did not attempt to reproduce patchiness. They focused
instead on the process of recruitment into the mangroves. The adult prawns spawn at
sea and the larvae find a refuge in mangroves where they mature. The modellers used
the observed prawn larvae concentrations at sea to seed advection-diffusion models
and predicted the fate of the larvae over the subsequent two weeks (Anim. 24). The
distribution is chaotic. The only available information to verify the models was the
relative distribution of prawns in the mangroves, and comparison with predictions was
favourable.
For coral fish larvae, the field data suggest that the bulk of the recruits immigrate
from reefs further upstream (Wolanski et al. 1997a). Advection-diffusion models of the
fate of a cloud of larvae carried passively by the prevailing currents and coming into
contact with a reef are unable to reproduce the patchiness (Anim. 25). Indeed, the model
predicts that most of the larvae are simply deflected around the reef and do not aggregate. This prediction is contrary to the observations shown in Anims. 20 and 21. However, if larval swimming behaviour is included in the model, the model predicts the
formation of patches in agreement with the observations (Anim. 26). Because the larval fish patches are not static but move around the reef, the distribution is chaotic.
The longevity and size of these patches depend on larval swimming speed. The predicted location of recruitment zones agrees with observations if the larvae swim at
about 0.05 m S-1 (aggregation is downstream) to 0.15 m S-1 (aggregation is upstream).
These swimming speeds are realistic, based on visual observations (Leis et al. 1996).
The predictions are also sensitive to the distance to the reef that fish larvae are "aware"
of the reef and swim toward it. Direct observations suggest this distance is at least 1 km
(Leis et al. 1996). In the model a distance of 2-3 km gave the best match of the predictions to the observations.
Chaos is also observed in the horizontal distribution of sprat larvae even in a much
simpler topography, e.g. the German Bight (Bartsch and Knust 1994). Their attempt to
model this was unsuccessful, maybe because the larvae were assumed not to swim
horizontally.
135
It is only recently that modellers have tried to understand this patchiness at a scale
of tens to hundreds of metres (Wolanski and Sarsenski 1997). The verification of these
models is extremely difficult because the biological data are collected at different times
at different sites in a tidal cycle; hence a synoptic picture of the distribution in the field
is unavailable. For the case of coral eggs spawned at Bowden Reef, the model predicts
the formation of a plume entraining eggs away from the reef (Oliver et al. 1992). As can
be seen in Anim. 23, the predicted plume is extremely patchy, if not chaotic. Model verification was carried out by comparing, at a given instant of time, observed and predicted concentrations. In some cases, such as in Fig. 16, where biological data were available simultaneously at different points (the exception rather than the rule because it
requires several small boats operating simultaneously), the comparison is pleasing.
However, when all the data over several days and at about twenty sites are used, no significant correlation is found between observed mean concentrations (calculated from
triplicate samples) and the instantaneous predicted concentrations (Oliver et al. 1992).
It is not clear if this model failure is due to the model underestimating the patchiness
due to sub-grid scale aggregating processes (Wolanski and Hamner 1988) or to the
patchiness being so large that triplicate samples are not enough to reliably estimate
the mean values.
For prawn larvae, modellers did not attempt to reproduce patchiness. They focused
instead on the process of recruitment into the mangroves. The adult prawns spawn at
sea and the larvae find a refuge in mangroves where they mature. The modellers used
the observed prawn larvae concentrations at sea to seed advection-diffusion models
and predicted the fate of the larvae over the subsequent two weeks (Anim. 24). The
distribution is chaotic. The only available information to verify the models was the
relative distribution of prawns in the mangroves, and comparison with predictions was
favourable.
For coral fish larvae, the field data suggest that the bulk of the recruits immigrate
from reefs further upstream (Wolanski et al. 1997a). Advection-diffusion models of the
fate of a cloud of larvae carried passively by the prevailing currents and coming into
contact with a reef are unable to reproduce the patchiness (Anim. 25). Indeed, the model
predicts that most of the larvae are simply deflected around the reef and do not aggregate. This prediction is contrary to the observations shown in Anims. 20 and 21. However, if larval swimming behaviour is included in the model, the model predicts the
formation of patches in agreement with the observations (Anim. 26). Because the larval fish patches are not static but move around the reef, the distribution is chaotic.
The longevity and size of these patches depend on larval swimming speed. The predicted location of recruitment zones agrees with observations if the larvae swim at
about 0.05 m S-1 (aggregation is downstream) to 0.15 m S-1 (aggregation is upstream).
These swimming speeds are realistic, based on visual observations (Leis et al. 1996).
The predictions are also sensitive to the distance to the reef that fish larvae are "aware"
of the reef and swim toward it. Direct observations suggest this distance is at least 1 km
(Leis et al. 1996). In the model a distance of 2-3 km gave the best match of the predictions to the observations.
Chaos is also observed in the horizontal distribution of sprat larvae even in a much
simpler topography, e.g. the German Bight (Bartsch and Knust 1994). Their attempt to
model this was unsuccessful, maybe because the larvae were assumed not to swim
horizontally.