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Biodiversity hotspots and conservation priorities in Central African rain forests
squares on a standard distribution map, gold stars 4-14, blue stars 15-30, and green
star more than 30 degree squares.
Hawthorne (1996) defined the guild as a flexible concept used to circumscribe a group
of plant species with a similar ecology and way of life. All the species were grouped
into guild classes as defined in Table 5.2 and a PI score was calculated as an
expression of the relative contribution contribution of pioneers. Five classes of human
disturbance were used to evaluate the forest quality and condition as defined in Table
5.3. These classes were mainly based on the field observation of the level of human
disturbance and the state of forest degradation.
The GHI and PI values of each sample were calculated using the TREMA database as
follows:
GHI = (BK x BK weight) + (GD x GD weight) + (BU x BU weight) + (RD x RD weight) x 100
BK + GD + BU + GN + RD
Where: GHI = Genetic Heat Index; BK = number of black star species; GD = number of gold
star species; BU = number of blue star species; GN = number of green star species; and RD =
number of red, scarlet and pink star species.
Pioneer Index (PI) = (Pioneer x PI weight) + (NP x NP weight) x 100
Total number of species
Where: PI = number of pioneer species and NP = number of non-pioneer light demanding
species.
Geostatistical analysis
Conservation indices such GHI and PI are likely to vary throughout a region.
Geostatistics (Isaaks & Srivastava, 1989; Webster & Oliver, 2001) were applied to
quantify the spatial distribution of GHI within the Campo-Ma’an forest. Geographic
analyses were done using ILWIS software (ILWIS, 2001) and GSTAT package
(Pebesma & Wesseling, 1998) of R software (R Development Core Team, 2002). The
semivariance was calculated for GHI data on a minimum lag distance of 1250 m and
each lag distance class contained at least 105 pairs of points. The semivariogram
parameters (nugget, sill and range) were computed using the GSTAT fit variogram
function. During the study of GHI spatial variability, the main objective was to obtain
a map from point observations. Since this also required the estimation of a value at unvisited
locations, the technique commonly used is known as kriging (Isaaks &
Srivastava, 1989). The semivariogram function was then used to extrapolate the GHI
values in the Campo-Ma’an forest at 100 m x 100 m grid, using Ordinary Kriging.
The output map was reclassified into five classes of conservation value (Hawthorne,
1996).
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