I usually recommend pooling samples for OTU clustering, for the following reasons.
Comparing samples
Creating a single set of OTUs is the most natural and intuitive basis for sample
comparison, e.g. using a beta diversity metric. If you create separate OTUs for
each sample, they are not directly comparable.
Improved amplicon abundance estimation and singleton
detection
Samples are pooled, then a sequence that appears as a singleton in one
sample may also appear in another sample. If singletons are discarded after
pooling (as usually recommended in order to reduce spurious OTUs), then more
low-abundance species will be retained.
Chimera detection
The UPARSE-OTU and
UCHIME de novo algorithms both require
that a chimera has lower read abundance than its parents. Chimeras are not
detected if a parent has the same number or fewer reads. This
most often happens with low-abundance parents, e.g. when a chimera and one of
its parents are both present in exactly two reads. If samples are pooled, parent
abundances usually increase because they are found in multiple samples, while
chimeras are only rarely reproduced so will usually be found only in a single
sample. Even if chimeras are reproduced, pooling will tend to increase both
chimera and parent abundances, leading to a more accurate reflection of amplicon
abundance so that parent abundances become greater than their chimeras.
Conversely, pooling is highly unlikely to increase the abundance of a chimera
relative to its parents. Pooling is therefore effective in reducing the number
of spurious OTUs due to chimeras.
Samples should be combined after non-biological
sequences such as barcodes have been stripped from the reads, and before
dereplication. This is required so that dereplication reflects the abundances of
unique biological sequences across all samples.