Mbalmayo, Cameroon
“Best bet” Land-use Systems
Thematic reports
Impact of different land uses on biodiversity
Biodiversity and Productivity Assessment for Sustainable Agroforest Ecosystems
Unique id: IDA1AIXB
Source file: D:\Projects\ASB\ASB Country and Thematic reports\Above ground biodiversity assessmet WG\CamRep4.xml
Authors: A.N. Gillison
--------------------------------------------------------------------------
Period: August 1996 to November 1999
Funding agency: DANIDA; CIFOR
code: R-BIO-14-1-DNK01
Summary
This study is part of an integrated approach to assessing
the impact of land use on biodiversity across tropical forested landscapes in
ecoregional study sites in the Western Amazon basin,
Introduction
The loss of plant and animal habitat in many tropical
countries continues unabated because as yet, there is no direct means of
attaching a value to biological diversity and thereby balancing its loss
against economic gain. Despite global
concern, there is no operational definition for biodiversity and no ready means
of measuring biodiversity in tropical landscapes where most of the world's
terrestrial plant and animal species reside. The present study is part of an
integrated series of investigations in other tropical lands (mainly
Training workshop
In order to assist in-country partners and other associated
interested parties a training workshop was held from 27-29 May 1997 that
included 20 participants from various locations and institutions in
Methods
A detailed account of the methods used in this survey is
described by Gillison and Liswanti (1999). In general terms the survey
technique uses gradient-based transects or gradsects (Gillison and Brewer,
1985; Wessels et al., 1998) in which
a hierarchy of physical environments is used to frame site location (e.g.
rainfall seasonality, parent rock type, drainage patterns, land cover, soil
catenary sequences, land use pattern..). It has been shown elsewhere (Gillison
and Brewer, 1985; Wessels et al.,
1998) that gradsect sampling improves the efficiency of recovering information
about the distribution of biota. The primary ecoregional gradient within
The following method of recording site physical features and vegetation was applied: At each site a 40 x 5m transect is laid out in which all vascular plant species are recorded together with plant functional types (PFTs) (formal combinations of specific plant functional attributes or PFAs that are primarily morphological adaptations of plant rsponse to environment). The recording of PFTs in addition to species complements the taxonomic information in a way that helps to interpret vegetation response to environment. Because PFTs are independent of species (more than one PFT can occur within a species and more than one species can occur as the same PFT), from a biodiversity standpoint they provide potentially useful, additional information that indicates a genetically based response to environment (see also Vanclay et al., 1997). By recording PFTs using a generic protocol, it becomes possible to compare for example, data from geographically remote locations where the species my differ but where environments and plant response may be similar. The underlying ecophysiological rationale and supporting theory for the use of PFTs of functional modi is described by Gillison and Carpenter (1997). In addition to species and PFTs vegetation structure (mean canopy height, crown cover %, litter depth, furcation index, cover-abundance of woody plants <1.5m tall and cover-abundance of bryophytes) is also recorded. Site physical variables include geo-reference with a portable, global positioning system, slope percent, aspect (deg.), elevation (m), parent rock type, soil type and soil depth. Additional notes include names of observers, relevant site history, and a profile sketch of the vegetation along the 40m transect.
At the time of the survey a computer software program FUNDAT was used to collate and store field data. FUNDAT was subsequently replaced with PFAPro, a more efficient, Windows-based program, that includes an error-checking protocol, a facility for tabulation of data and graphs and the estimation of several ecological diversity measures based on PFTs. Photographs of each site were taken and filed together with the cross-referenced data.
Visits
were made to field sites at Mengomo, Akok, Mbalmayo, Awae, Nkol Foulou,
Nkometou, Bafia and Batoum II. A range of about 500km from humid forest to
savanna. I was accompanied by three Cameroonian botanists: Dr Zapfack Louis (
Data
analyses included standard regression measures and exploratory data analysis
using the PATN program (Belbin, 1992). In addition to these a single index that
represented key elements of vegetation structure, total plant species, total
PFTs per plot and their ratios, was extracted using multi-dimensional scaling
(MDS) as described by Gillison (1999) and Box 2 below. This is termed a
"V" index and is an exploratory attempt to seek a relative ranking of
vegetation that may have the potential to serve as a useful correlate for
biodiversity and site productivity potential or carbon sequestration. To assist
in the construction of a Policy Analysis Matrix (PAM) data used in the
compilation of the "V" index
were supplied to Dr J. Gockowski (see
Box 1 The IITA Benchmark program The IITA benchmark
concept was initiated by Doyle Baker (IITA). After a countrywide study
about 2/3rds of the current Mbalmayo benchmark template was in place by
1993. ASB provided the stimulus to follow through and this resulted in
IITA/IRA collaboration and use by ASB (mainly environmental). EPHTA (Ecoregional Program for Humid and
Sub-Humid Tropics of Sub-Saharan Africa) is coordinated by IITA now
cooperates with ASB on benchmark research. Both programs are interested in
developing alternative farming systems (not necessarily with environment or
biodiversity in mind). They aim at maintaining a resource base for
production systems – e.g. managing short-fallow systems and community
forestry. Another area of rsearch is concerned with diversification of land
use systems and conservation of the national resource base. They are
targetting specific LUSs and are especially focussed on: Renewal of traditional
plantations Development of home
garden systems Annual and perennial crop
multistrata systems Northern Guinea savanna
(N. Nigeria) Southern Guinea savanna
(Côte d’Ivoire) Coastal savanna (S.Benin) Forest pilot sites will
be located in Gabon, Côte d’Ivoire, Republic of the Congo, Congo
(Brazzaville) and for ASB possibly another BM in Ghana. GIS plays a
critical role in the ecoregional programs and uses area-based sampling on a
10’X10’ (80km x 80km) grid cell for ASB. Approximately 30-40 villages are
typically involved (one village per grid cell). These are characterised
according to ‘resource use domains’. From these are selected representative
sites for more detailed investigation at higher spatial resolution
according to farmer circumstances. The studies are entirely correlative
with no mechanistic or dynamic models. Linear programming is used to
manipulate tradeoffs between biophysical and socioeconomic conditions
Results
Both
classification and ordination (MDS) (Figs 1a & 1b) reveal three readily
distinguishable clusters of LUTs. The first is represented by closed canopy
forest including both 'jungle' Cacao
and '
The cumulative species, PFT and ratio /area curves (Annex III) give an indication of the level of representativeness of each LUT. Steep curves suggest additional samples are needed. Of particular interest are the relatively depressed curves of the long-term, short-cycle fallows compared with those of the richer fallows that immediately follow forest clearance. The ratios of species to PFTs show that whereas in the more complex forests more species collapse into PFTs, in the recent gardens and savannas these are flattened. This reflects the greater varuiability of available ecological niches per species as well as the higher number of adaptive combinations or PFTs. In the savanna plots within the first quadrat the ratio becomes stable and this may be an indication of the relative equilibrium of savanna dynamics compared with those of the more complex, disturbed forests and older fallows. The ecological meaning of these profiles requires further investigation.
The
'V' index (Fig. 3) illustrates the relative position of each plot in terms of
increasing structural complexity and richness in both species and PFTs. It is
of interest to note that in this instance, '
Discussion
The
sequences revealed very similar patterns in vascular plant species richness to
those found in Latin America (
All the forest types examined in this study were heavily used by the local people for hunting, fuel and medicinal resources. From this point of view they are highly regarded as a potentially rich source of extractable non-timber-forest-products. The inclusion of savanna LUTs has improved the ecological and environmental context needed to assess biodiversity overall and provided an additional, spatially-referenced framework for spatial modelling of actual and potential land use impact on plant-based biodiversity. Should there be a need to consider the likely effects of climate change then this extended gradient will be of potential use in modelling different climate change scenarios. A recent report of a biodiversity baseline study (Lawton et al., 1999) found little evidence to support the use of one taxon to predict the presence of another. That study was restricted to a localised, rain forest land use mosaic in Mbalmayo and did not use plant indicators. Because most or all animal taxa depend on plants for survival and because the distribution of many taxa extend beyond the immediate bounds of closed forest, it is likely that predictive performance could have been considerably improved had plants been included and had the samples been extended to a wider array of LUTs as in the present study.
Where estimates of above-ground carbon are logistically demanding evidence from this study and from the Sumatran benchmark study (Gillison and Liswanti, 1999) suggest that alternative, easy to measure surrogates may be available through the use of mean canopy height and basal area. Similarly a V index may be potentially useful but unlike simple estimates of structure this requires much more sophisticated computation and more variables.
The
training workshop held at Mbalmayo was considered successful by all who
attended. Feedback from participants also helped to refine the framework for
subsequent workshops that have been held in Latin America,
Conclusions
The
rapid survey method of recording site physical features and vegetation has
successfully identified a variety of land use impacts on plant-based
biodiversity. Results from more intensive multi-taxa and soil studies in
Acknowledgements
References
Gillison, A.N. and Brewer, K.R.W. (1985). The use of gradient directed transects or gradsects in natural resource surveys. Journal of Environmental Management20: 103-127.
Gillison, A.N. and Carpenter G. (1997). A generic plant functional attribute set and grammar for dynamic vegetation description and analysis. Functional Ecology11: 775-783.
Gillison, A.N. (1997). In 1997 ASB Annual Review Meeting report. Unpubl.
Gillison, A.N. and Liswanti, N. (compilers). An intensive
biodiversity baseline study in Jambi province, Central Sumatra, Indonesia. In:
A.N. Gillison (coordinator) Alternatives to Slasha nd Burn Project: Phase II.
Above-ground biodiversity assessment working group summary report 1996-99.
ICRAF,
Gillison, A.N., Liswanti, N. and Arief-Rachman,
Hairiah, K., and van Noordwijk, M. (1999). Soil properties
and carbon stocks. Section 10 in: Gillison, A.N. and Liswanti, N. (compilers).
An intensive biodiversity baseline study in Jambi province, Central Sumatra,
Indonesia. In: A.N. Gillison (coordinator) Alternatives to Slasha nd Burn
Project: Phase II. Above-ground biodiversity assessment working group summary
report 1996-99. ICRAF,
Vanclay, J.K.,
Gillison, A.N. and Keenan, R.J. (1997). Using Plant Functional Attributes to
quantify site productivity and growth patterns in mixed forests.
Wessels, K.J., Van Jaarsveld, A.S., Grimbeek, J.D. and Van der Linde, M.J. (1998). An evaluation of the gradsect biological survey method. Biodiversity and Conservation7: 1093-1121.
Table 1. Site
location and physical features for
|
Site |
Symbols |
Location |
Date |
Observers |
Lat. (N) |
Long. (E) |
Elev (m) |
Slope (%) |
Aspect (Deg) |
S_Dpt (cm) |
Ltr (cm) |
Terrain Unit |
Soil Type |
||||
|
+ + |
|
|
30-May-97 |
AG/MN/ZL/BS/Ka/NT |
03-36-05 |
11-36-15 |
657 |
0 |
0 |
>100 |
4 |
Plain |
Ultisol |
||||
|
CAM02 |
|
AWAE |
30-May-97 |
AG/MN/ZL/BS/Ka/NT |
03-36-05 |
11-36-15 |
657 |
0 |
0 |
>100 |
8 |
Plain |
Ultisol |
||||
|
CAM03 |
|
AWAE |
30-May-97 |
AG/MN/ZL/BS/Ka/NT |
03-36-05 |
11-36-15 |
657 |
0 |
0 |
>100 |
0 |
Plain |
Ultisol |
||||
|
CAM04 |
|
AWAE |
30-May-97 |
AG/MN/ZL/BS/Ka/NT |
03-36-05 |
11-36-15 |
657 |
0 |
0 |
>100 |
12 |
Plain |
Ultisol |
||||
|
CAM05 |
|
NKOL-FULU |
02-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
03-55-31 |
11-35-49 |
696 |
6 |
240 |
>100 |
2 |
Upper slope |
Ultisol |
||||
|
CAM06 |
|
NKOL-FULU MEFOU & AFAMBA Dept. |
02-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
03-55-31 |
11-35-49 |
696 |
6 |
240 |
>100 |
1 |
Upper slope |
Ultisol |
||||
|
CAM07 |
|
NKOL-FULU MEFOU & AFAMBA Dept. |
02-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
03-55-41 |
11-35-49 |
696 |
6 |
240 |
>100 |
0 |
Upper slope |
Ultisol |
||||
|
CAM08 |
|
MENGOMO (Ebolowa-Station) |
03-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
02-34-45 |
07-02-05 |
554 |
7 |
165 |
>100 |
6 |
Upper slope |
- |
||||
|
CAM09 |
|
MENGOMO (Ebolowa-station) |
03-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
02-34-37 |
11-01-29 |
576 |
4 |
340 |
>100 |
1 |
Upper slope |
- |
||||
|
CAM10 |
|
MENGOMO (Ebolowa-station) |
03-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
02-34-37 |
11-01-29 |
576 |
3 |
275 |
>100 |
3 |
Plain |
- |
||||
|
CAM11 |
|
AKOK (Ebolowa-Station) |
04-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
02-42-19 |
11-16-09 |
554 |
0 |
0 |
>100 |
2 |
Plain |
- |
||||
|
CAM12 |
|
AKOK (Ebolowa-Station) |
04-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
02-42-27 |
11-16-30 |
554 |
5 |
170 |
>100 |
0 |
Upper slope |
- |
||||
|
CAM13 |
|
AKOK (Ebolowa-station) |
04-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
02-43-08 |
11-17-05 |
585 |
5 |
130 |
>100 |
2 |
Upper slope |
- |
||||
|
CAM14 |
|
AKOK (Ebolowa-Station) |
04-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
02-43-12 |
11-16-58 |
585 |
5 |
130 |
>100 |
2 |
Upper slope |
- |
||||
|
CAM15 |
|
AKOK (Ebolowa-station) |
04-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
02-42-45 |
11-16-42 |
559 |
0 |
0 |
>100 |
4 |
Plain |
- |
||||
|
CAM16 |
|
BAFIA (20 km after Bafia) |
05-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
04-48-58 |
11-10-27 |
560 |
12 |
50 |
> 50 |
0 |
Upper slope |
- |
||||
|
CAM17 |
|
MAKAM III - BATOUM II |
05-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
05-02-40 |
10-42-04 |
977 |
35 |
205 |
>100 |
0 |
Upper slope |
- |
||||
|
CAM18 |
|
NKOMETOU II |
06-Jun-97 |
AG/MN/ZL/BS/Ka/NT |
04-04-51 |
11-33-17 |
596 |
8 |
195 |
>100 |
0 |
Upper slope |
- |
||||
|
CAM19 |
|
Near BAFIA |
27-Aug-96 |
AG/MN/ZL/BS/Ka/NT |
04-48-56 |
11-10-25 |
640 |
25 |
45 |
>100 |
0 |
Upper slope |
- |
||||
|
CAM20 |
|
NKOLITAM |
28-Aug-96 |
AG/MN/ZL/BS/Ka/NT |
03-28-21 |
11-29-25 |
0 |
0 |
0 |
>100 |
0 |
Swamp |
|
||||
|
CAM21 |
|
AKOK 'Enuzam' |
28-Aug-96 |
AG/ZL/ Nico-TCHA |
02-42-45 |
11-16-45 |
550 |
7 |
0 |
>100 |
3 |
Upper slope |
Sandy clay loam |
AG: Andy Gillison; MN: Martine Ndogo; ZL: Zapfack Louis; BS: Bonaventura Sonke; Ka: Kanfiani; Lat: Latitude; Long: Longitude; Elev: Elevation; S_Dpt: Soil Depth; Ltr: Litter
Table 2. Summary data for vascular plant species, PFTs
or modi and species/PFT ratio, S/W
PFT index, Simpson PFT index*
|
No. |
Site |
Symbols |
Total Records |
Unique PFTs |
Unique Species |
Unique Species/PFTs |
|
Simpson PFT Index |
||||
|
2 |
CAM01 |
|
103 |
43 |
103 |
2.40 |
0.0789 |
3.15 |
||||
|
+ |
CAM02 |
|
61 |
37 |
61 |
1.65 |
0.0422 |
3.41 |
||||
|
12 |
CAM03 |
|
20 |
19 |
20 |
1.05 |
0.0550 |
2.93 |
||||
|
5 |
CAM04 |
|
54 |
35 |
54 |
1.54 |
0.0418 |
3.38 |
||||
|
4 |
CAM05 |
|
50 |
33 |
50 |
1.52 |
0.0432 |
3.34 |
||||
|
15 + |
CAM06 |
|
30 |
22 |
30 |
1.36 |
0.0556 |
3.00 |
||||
|
12 |
CAM07 |
|
14 |
12 |
14 |
1.17 |
0.0918 |
2.44 |
||||
|
2 |
CAM08 |
|
93 |
42 |
93 |
2.21 |
0.0517 |
3.36 |
||||
|
J |
CAM09 |
|
76 |
47 |
76 |
1.62 |
0.0461 |
3.55 |
||||
|
2 |
CAM10 |
|
80 |
47 |
80 |
1.70 |
0.0372 |
3.59 |
||||
|
1 |
CAM11 |
|
71 |
50 |
71 |
1.42 |
0.0395 |
3.65 |
||||
|
4 |
CAM12 |
|
78 |
55 |
78 |
1.42 |
0.0256 |
3.85 |
||||
|
2-8 |
CAM13 |
|
100 |
66 |
100 |
1.52 |
0.0228 |
4.01 |
||||
|
|
CAM14 |
|
61 |
44 |
61 |
1.39 |
0.0309 |
3.65 |
||||
|
1S P |
CAM15 |
|
63 |
43 |
63 |
1.47 |
0.0426 |
3.52 |
||||
|
D |
CAM16 |
|
51 |
37 |
51 |
1.38 |
0.0358 |
3.49 |
||||
|
1-25 |
CAM17 |
|
47 |
41 |
47 |
1.15 |
0.0267 |
3.67 |
||||
|
H |
CAM18 |
|
45 |
29 |
45 |
1.55 |
0.0528 |
3.17 |
||||
|
|
CAM19 |
|
25 |
18 |
25 |
1.39 |
0.0656 |
2.81 |
||||
|
45 |
CAM20 |
|
57 |
29 |
57 |
1.97 |
0.0612 |
3.08 |
||||
|
|
CAM21 |
|
57 |
41 |
57 |
1.39 |
0.0360 |
3.55 |
* S/W = Shannon-Wiener diversity index for PFTs; Simpson’s diversity index for PFTs (Gillison and Carpenter, unpubl.)
Table 3. Vegetation structural data
|
Site |
Vegetation |
M_Can |
CC |
CW |
CNW |
Wdy |
Bry |
Litter |
M_BA |
M_FI |
FI CV% |
|
CAM01 |
Not previously gardened; very disturbed;
secondary forest. Logged 15 yrs |
20.00 |
70 |
0 |
0 |
7 |
3 |
4 |
18.00 |
26.25 |
88.24 |
|
CAM02 |
2 year Chromolaena fallow |
2.50 |
95 |
0 |
0 |
9 |
2 |
8 |
2.00 |
100.00 |
0.00 |
|
CAM03 |
New garden
with groundnut, Cassava |
0.40 |
5 |
0 |
0 |
2 |
1 |
0 |
0.50 |
90.50 |
32.31 |
|
CAM04 |
8-10 year Chromolaena fallow ex forest. |
3.50 |
95 |
0 |
0 |
9 |
2 |
12 |
4.67 |
65.50 |
64.48 |
|
CAM05 |
Secondary
forest heavily disturbed |
12.00 |
95 |
0 |
0 |
8 |
3 |
2 |
7.33 |
45.00 |
64.89 |
|
CAM06 |
4 year Chromolaena fallow with Oil Palm |
2.60 |
95 |
0 |
0 |
9 |
2 |
1 |
2.17 |
100.00 |
0.00 |
|
CAM07 |
New garden
(Egusi melon); slashed and burned 8 months prev. |
0.40 |
30 |
0 |
0 |
1 |
1 |
0 |
4.67 |
17.25 |
147.94 |
|
CAM08 |
Secondary
forest - logged. |
18.00 |
70 |
0 |
0 |
7 |
5 |
6 |
20.67 |
37.50 |
78.64 |
|
CAM09 |
2 year Chromolaena fallow - from secondary
forest |
2.50 |
95 |
0 |
0 |
9 |
1 |
1 |
0.50 |
100.00 |
0.00 |
|
CAM10 |
Cocoa
plantation non maintained (Jungle cocoa (T.
cacao) > 45 years) |
12.00 |
75 |
0 |
0 |
6 |
3 |
3 |
17.33 |
15.75 |
172.74 |
|
CAM11 |
2 year Chromolaena fallow from secondary
forest. |
2.30 |
95 |
0 |
0 |
9 |
1 |
2 |
1.50 |
80.00 |
51.30 |
|
CAM12 |
One year
old garden fallow slash-burn ex forest |
2.00 |
90 |
0 |
0 |
8 |
1 |
0 |
1.00 |
75.00 |
59.23 |
|
CAM13 |
4 year Chromolaena fallow ex forest |
3.50 |
95 |
0 |
0 |
8 |
2 |
2 |
1.00 |
58.60 |
76.88 |
|
CAM14 |
2 year Chromolaena fallow (from an 8 years
fallow) |
2.50 |
95 |
0 |
0 |
9 |
2 |
2 |
1.00 |
79.25 |
51.35 |
|
CAM15 |
Cocoa
plantation maintained < 30 years |
18.00 |
75 |
0 |
0 |
3 |
5 |
4 |
20.00 |
51.00 |
44.49 |
|
CAM16 |
1 year
Cassava (only) crop after major planting. Last year sedentary. |
2.50 |
50 |
0 |
0 |
6 |
1 |
0 |
2.00 |
85.00 |
24.66 |
|
CAM17 |
Humid
savanna (Shrub savanna dominated by Lophira
/ Butyrosperma) |
3.00 |
70 |
0 |
0 |
3 |
1 |
0 |
2.00 |
86.25 |
26.46 |
|
CAM18 |
1 year Chromolaena fallow following 25 years
mult. Chromolaena fallows. |
1.80 |
98 |
0 |
0 |
10 |
1 |
0 |
0.20 |
95.25 |
22.30 |
|
CAM19 |
Annually
fired savanna, tall grass (Hyparrhenia) |
4.00 |
8 |
0 |
0 |
2 |
1 |
0 |
0.67 |
76.75 |
29.84 |
|
CAM20 |
Slightly
disturbed, Raffia palm swamp. |
18.00 |
90 |
0 |
0 |
8 |
2 |
0 |
14.00 |
17.00 |
103.83 |
|
CAM21 |
Old
secondary forest (Old coppice slumps, upper storey & dense Tabernaemontana under storey ca. 1-2 m. Many
ground Marantaceae.) |
20.00 |
85 |
0 |
0 |
8 |
5 |
3 |
26.00 |
31.75 |
79.36 |
M_Can: Mean Canopy Height ; CC: Crown Cove%r; CW: Crown Cover% Woody plants; CNW: Crown Cover% Non Woody plants; M_BA: Mean Basal Area m2 ha-1; Bry: Bryophyte cover-abundance; Wdy: Woody Plants<1.5m tall, cover-abundance; M_FI: Mean Furcation Index; FI CV%: Coefficient Variation % of FI.
|
Box 2 Matrix values for Cameroon plots The following attributes are considered to be the
minimum set need to effectively describe above-ground biodiversity. All data
are recorded from within a 40 x 5m plot. These are:
Vegetation structure Mean canopy height (m) Basal area (m2
ha-1) (Bitterlich estimate)
Plant species All vascular plant species
Plant Functional Types (Modi)
Species : PFTs, ratio (a measure of taxonomic and
functional heterogeneity)
Vegetation (‘V’) Index An index derived by seeking the single best
eigenvector solution from a multi-dimensional scaling analysis using the
above attributes. The index is standardised from 0.1 – 1.00, the highest
values indicating lowest vegetation complexity and, by implication, plant
biological diversity. This index corresponds generally with increasing land
use intensity expressed as an ‘R’ (Ruthenberg) value. All values are listed
in Tables 4 & 5. Plot numbers refer to those listed in the 1997 ASB Annual Review Meeting report for Above-ground biodiversity for Cameroon and Tables 1,2,3 in this report. |
Table 4. Matrix values for above-ground plant biodiversity
arranged according to site
|
Plot No |
Mean_ht |
Basal_A |
PFTs |
Species |
Spp:PFT |
V-Index |
|
Camasb01 |
20 |
18 |
43 |
103 |
2.40 |
0.10 |
|
Camasb02 |
2.5 |
2 |
37 |
61 |
1.65 |
0.67 |
|
Camasb03 |
0.4 |
0.8 |
19 |
20 |
1.05 |
0.94 |
|
Camasb04 |
3.5 |
4.7 |
35 |
53 |
1.51 |
0.71 |
|
Camasb05 |
12 |
7.3 |
32 |
50 |
1.56 |
0.54 |
|
Camasb06 |
26 |
2.2 |
24 |
29 |
1.21 |
1.00 |
|
Camasb07 |
0.4 |
4.7 |
12 |
14 |
1.17 |
0.96 |
|
Camasb08 |
18 |
20.7 |
41 |
93 |
2.27 |
0.15 |
|
Camasb09 |
2.5 |
0.5 |
45 |
76 |
1.69 |
0.63 |
|
Camasb10 |
12 |
17.3 |
47 |
80 |
1.70 |
0.38 |
|
Camasb11 |
2.3 |
2 |
49 |
71 |
1.45 |
0.67 |
|
Camasb12 |
2 |
1.3 |
55 |
78 |
1.42 |
0.65 |
|
Camasb13 |
3.5 |
1 |
66 |
100 |
1.52 |
0.53 |
|
Camasb14 |
2.5 |
1 |
44 |
61 |
1.39 |
0.69 |
|
Camasb15 |
18 |
20 |
29 |
45 |
1.55 |
0.35 |
|
Camasb16 |
2.5 |
2 |
44 |
63 |
1.43 |
0.69 |
|
Camasb17 |
3 |
2 |
40 |
51 |
1.28 |
0.72 |
|
Camasb18 |
1.8 |
0.2 |
41 |
47 |
1.15 |
0.78 |
|
Camasb19 |
4 |
0.7 |
18 |
25 |
1.39 |
0.87 |
|
Camasb20 |
18 |
14 |
29 |
57 |
1.97 |
0.32 |
|
Camasb21 |
20 |
26 |
41 |
57 |
1.39 |
0.27 |
Table
5. Matrix values for above-ground plant
biodiversity
arranged according to Vegetation
(‘V’) index.
|
Plot No |
Mean_ht |
Basal_A |
PFT |
Species |
Spp:PFT |
V-Index |
|
Camasb01 |
20 |
18 |
43 |
103 |
2.40 |
0.10 |
|
Camasb08 |
18 |
20.7 |
41 |
93 |
2.27 |
0.15 |
|
Camasb21 |
20 |
26 |
41 |
57 |
1.39 |
0.27 |
|
Camasb20 |
18 |
14 |
29 |
57 |
1.97 |
0.32 |
|
Camasb15 |
18 |
20 |
29 |
45 |
1.55 |
0.35 |
|
Camasb10 |
12 |
17.3 |
47 |
80 |
1.70 |
0.38 |
|
Camasb13 |
3.5 |
1 |
66 |
100 |
1.52 |
0.53 |
|
Camasb05 |
12 |
7.3 |
32 |
50 |
1.56 |
0.54 |
|
Camasb09 |
2.5 |
0.5 |
45 |
76 |
1.69 |
0.63 |
|
Camasb12 |
2.0 |
1.3 |
55 |
78 |
1.42 |
0.65 |
|
Camasb02 |
2.5 |
2 |
37 |
61 |
1.65 |
0.67 |
|
Camasb11 |
2.3 |
2 |
49 |
71 |
1.45 |
0.67 |
|
Camasb16 |
2.5 |
2 |
44 |
63 |
1.43 |
0.69 |
|
Camasb14 |
2.5 |
1 |
44 |
61 |
1.39 |
0.69 |
|
Camasb04 |
3.5 |
4.7 |
35 |
53 |
1.51 |
0.71 |
|
Camasb17 |
3.0 |
2 |
40 |
51 |
1.28 |
0.72 |
|
Camasb18 |
1.8 |
0.2 |
41 |
47 |
1.15 |
0.78 |
|
Camasb19 |
4.0 |
0.7 |
18 |
25 |
1.39 |
0.87 |
|
Camasb03 |
0.4 |
0.8 |
19 |
20 |
1.05 |
0.94 |
|
Camasb07 |
0.4 |
4.7 |
12 |
14 |
1.17 |
0.96 |
|
Camasb06 |
26 |
2.2 |
24 |
29 |
1.21 |
1.00 |


Fig 1a Classification
of all sites according to species and PFT richness and vegetation structure (see Table1 for symbols)
Figure 1b Multidimensional
Scaling of species and PFT richness and vegetation structure
Fig. 2 Relationship between vascular plant species
and PFTs along gradient
of land use types in
Cameroon (arrow indicates Jungle Cacao)
![]()

Fig. 3 Land Use Types ranked against “V” index
(from: vegetation structure, species and functional types), Mbalmayo, Cameroon

Fig. 4 Correlation between “V” Index and total
average above-ground carbon
Annex I List of participants in
Above-Ground Biodiversity Workshop 27-29 May, 1997, Mbalmayo, Cameroon
|
No. |
Names |
Address |
|
1. |
Bonaventure Sonke |
University de Yaounde I B.P. 8225, or B.P. 047 Yaounde Tel.: (237) 21-42-73 Fax.: (237) 20-94-72 |
|
2. |
Ghogue Jean-Paul |
Cameroon national Herbarium GEF - Biodiversity P.O. Box 1601 Yaounde Tel. 31-44-16 |
|
3. |
Kenfack David |
Korup Forest dynamics Project c/o Korup Project P.O. Box 2417 Douala Tel.: 43-06-64 |
|
4. |
Kengue Joseph |
IRA/CRA Nkolbisson P.O. Box 2067 Yaounde - Cameroon Tel.: c/o (237) 23-75-60 |