Plant Community Structure, Fire Disturbance, and Recovery in ...

Contributions to the Study of Biological Diversity Vol. 3
as a group to explore at what level they might
bear similarity to any of the other plant
communities. NTSYSpc (Rohlf 1997) statistical
software was used for the clustering of those
plant community data. Clustering was
performed using simple matching coefficients,
with the Sequential, Agglomerative,
Hierarchical, and Nested clustering method
(SAHN) and the Unweighted Pair-Group
Method, Arithmetic average (UPGMA), based
on algorithms from Sneath and Sokal (1973).
Possible sources of error in comparisons of
plant communities included misidentification of
plant specimens, which could change the
amounts of overlap between communities.
Misidentification was minimized by
determination of specimens at major botanical
institutions that host many specialists and have
fairly complete, up to date collections for
reference. Also of concern are incomplete or
biased sampling, which may include undersampling
of trees and of plants sterile at the time
of sampling, and differences in sampling effort
and scale. Problems from assignment of species
to particular vegetation types must be
considered. Some of the species may be present
in the beach community, since they are found
in beach substrate, but are primarily on the
margins of a neighboring community and might
be best treated as outliers from that community.
As with many of these vegetation groups, the
beach community itself could be subdivided into
finer units such as ocean front, central beach
ridge, and back beach near mangrove swamps;
similar concerns could be formed for a unit
regarding boundaries. A final consideration is
sampling bias, particularly the Quackal and
Manicole samples which were obtained from
one hectare plots, while the Waini samples were
taken during sampling transects. However, these
do represent a similar degree of sampling
intensity for each vegetation type, and
substantial possible disparity may be mitigated
by the use of qualitative (presence/absence)
rather than quantitative comparisons.
Northwest District
A checklist of plants of the Northwest
District was assembled from five sources: 1)
collections made on the Waini Peninsula during
this study, 2) collections made in the Northwest
37
District by the BDG program since 1986, 3) the
dataset of Northwest District collections held
at the US herbarium, 4) the 625 species listed
by van Andel (2000b) based on her collections
made in Guyana from 1995 to1997, and 5) some
specimen information from online databases,
e.g., the Missouri Botanical Garden’s (1995present)
TROPICOS database, and the New
York Botanical Garden’s website (1996present).
The resulting names at the species level
were matched with the database for the
Checklist of the Plants of the Guiana Shield
(Hollowell et al. 2001) to standardize
nomenclature and correct errors. Those species
known only from cultivation were not used in
analyses but were included in the full checklist
for the Northwest District (Appendix 3), and
noted as cultivated. The status of species as
cultivated was determined by literature checks
in DeFilipps (1992), Boggan et al. (1997), van
Andel (2000b), and Hollowell et al. (2001).
Species that had apparently escaped cultivation
and become naturalized were also noted. Taxa
determined only to genus were included if they
represented the only record for that genus.
Contributions of recent collections to the lists
were calculated as an indication of the status of
knowledge of the region’s flora.
Figure 2.3. Nested floristic distribution zones used
in analysis of plant species affinities for the Waini
Peninsula. 1. Guiana Shield. 2. Northern South
America. 3. Neotropical. 3a. Neotropical including
Caribbean. 4. Neotropical and Western Africa. 5.
South America (not indicated). 6. Western
Hemisphere. 7. Pantropical, between 23.5° N and
23.5° S. 8. Cosmopolitan (not indicated). The Waini
Peninsula flora had the greatest affinity (33%) with
the Neotropical + Caribbean zone, followed by the
Pantropical zone (27%).