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Dense
algae
Sparse algae/
seagrass
(a)
Emergent
sand
Coral
Dense
seagrass
Submerged
sand
Sealevel
-
(b)
Increased absorption
at lower facies boundary
Increased reflection
at upper facies boundary
Sealevel
Fig. 14. If we accept that the spatial
digraph is also a proxy for temporal
transitions, we can predict changes
in facies abundance in reaction to a
changing environment by modifying
the transition probabilities between
vertices. (a) The digraph of the present
situation from which the changes in
sea-level were derived. Facies distribu-
tion along a transect shown in Fig. 12c
is illustrated. The thickness of arrows
in (b) and (c) shows the preferred direc-
tion of facies transition and the wedge
underneath the digraphs thickens in
the direction of preferential facies
change. (b and c). Digraphs of transition
changes and anticipated changed facies
distribution according to the models of
sea-level change. Facies frequency in
the transect follow the FPVs in Fig. 15.
(c)
-
Increased absorption
at lower facies boundary
Increased reflection
at upper facies boundary
S
Sealevel
Dense coral
Dense algae
Dense seagrass
Sparse algae/seagrass
Subtidal sand
Emergent sand
(the islands are not that big) and the gently
sloping edges of the platform will provide much
suitable new habitat for algae and corals without
much habitat loss due to drowning. Emergent
sand would be fl ooded and colonized by algae and
seagrass. The newly fl ooded areas of formerly dry
land (the islands) would become shallow, at least
partly emergent sand. In the falling sea-level scen-
ario, emergent and shallow subtidal sands would
greatly expand at the cost of the deeper facies,
which would move into yet deeper areas (masked
pixels) and maybe decline less dramatically than
illustrated in Fig. 15. However, since the deeper,
masked areas were not included in the analysis,
a precise numeric evaluation was not possible.
Within the 0-10 m depth zone the decline was
adequately represented (Fig. 15).
DISCUSSION
A computationally and conceptually simple way
of harnessing spatial patterns in a landscape to
extrapolate information for modifying spatial into
 
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