Vol. 9(3), pp. 128-146, March 2015
DOI: 10.5897/AJPS2015.1265
Article Number: 32ECE3D51741
ISSN 1996-0824
Copyright © 2015
Author(s) retain the copyright of this article
http://www.academicjournals.org/AJPS
African Journal of Plant Science
Full Length Research Paper
Floristic diversity under anthropogenic activities in the
protected forests of Duekoué and Scio in southwestern
Côte d’Ivoire
François N’guessan KOUAMÉ
1
*, Olivier Adjé AHIMIN
2
, Maxime N’takpé Kama BORAUD
1
and
Edouard Kouakou N’GUESSAN
1
1
Laboratoire de Botanique, Université Félix Houphouët-Boigny, Abidjan, Cote d'Ivoire.
2
Société de Développement des forêts (SODEFOR), Abidjan, Cote d'Ivoire.
Received 7 January, 2015; Accepted 18 February, 2015
This study analyses the effects of anthropogenic disturbance on trees and shrubs floristic α-diversity in
two protected rain forests in southwestern Côte d’Ivoire. These forests have been under timber
harvesting since their protection in 1929. The forestry service had developed plantations of indigenous
timber species and teak since 1996 to increase their productivities for timbers. Additionally, they host
many plantations of cash crop among which coffee, cocoa and rubber are the most important. To
understand how these plantations affect the local flora, the diversity of shrubs and trees with DBH ≥ 10
cm was analyzed through the species number and diversity indices. Plots were of 20 m x 50 m size and
a total of 10 per vegetation type. Highest species numbers, Shannon-Wiener’s index, Hill’s index and
Pielou’s index, in both plots and vegetation types were found in natural forest and undergrowth cleared
forest which had similar values of these parameters. Plot richness was ranked between 1 and 7 species
whilst vegetation type richness varied from 4 to 12 species for all plantations. Yet Simpson’s diversity
index showed highest values in plantations. Richness in plantation was influenced by the location of
plantation site and the nature of crop but no influence was found with the combination site and crop
nature.
Key words: Forest protection, cash crops, agroforestry, flora and diversity, South-West Côte d’Ivoire.
INTRODUCTION
The tropical humid forests host higher vascular plant
richness and diversity compared to European and North
American forests (Richards, 1996; Myers et al., 2000;
Blanc, 2002; Parmentier et al., 2007; Parmentier et al.,
2011). Mixed mesophytic forests of China and Southeast
America that are the richest among the non-tropical
forests (Richards, 1996) harbor 20 to 30 species. These
numbers are smaller than the richness of trees bigger
than 10 cm DBH in a hectare of primary Tropical humid
forest plot that is often estimated between 40 and 100
*Corresponding author. E-mail: fnkouame3@gmail.com. Tel: (+225) 07009566, 03007139, 44263046.
Author(s) agree that this article remain permanently open access under the terms of the Creative Commons Attribution License
4.0 International License
species (ORSTOM and UNESCO, 1983; Kouamé, 1998)
and can reach 251 species (Ghazoul and Sheil, 2010).
These forests also harbor high abundance and diversity
of lianas which constitute other fundamental characteristics
of this vegetation type (Richards, 1996; Kouamé et al.,
2007).
Agriculture has played an important role in the trans-
formation of lowland tropical forest landscapes worldwide
over the past centuries and continues to do so today
(Lass, 2004; Schroth and Harvey, 2007). In many regions,
cash crops have been a driver of deforestation, with
plantations or agroforestry systems replacing the original
forest ecosystems (Ruf and Schroth, 2004). In comparison
to other land uses that replace intact forest, traditional
Cocoa (Theobroma cacao L., Sterculiaceae) and Coffee
(Coffea canephora Froenh., Rubiaceae) agroforests, with
diverse and structurally complex shade canopies, are
among the agricultural land uses that are most likely to
conserve a significant portion of the original forest
biodiversity (Perfecto et al., 1996; Moguel and Toledo,
1999; Rice and Greenberg, 2000; Schroth et al., 2004;
Faria et al., 2006; Harvey et al., 2006). Although cocoa
and coffee cultivation may represent a serious threat to
biodiversity in certain countries such as Côte d’Ivoire,
Ghana, and the Dominican Republic, where their agro-
forests make up a significant proportion of all woodland
(Donald, 2004), there are a number of reasons for
regarding their shaded cultivation as environmentally
preferable to many other forms of agriculture in Tropical
forest regions (Greenberg, 1998; Power and Flecker,
1998). Since economic prospects for Rubber (Hevea
brasiliensis Müll.Arg., Euphorbiaceae) on the world
market are positive (Smit and Vogelvang, 1997; Burger
and Smit, 1998, 2000) and the production by smallholders
is still profitable (Levang et al., 1999; Suyanto et al.,
2001), large tropical forest areas have been converted
into Rubber plantations responsible for drastic erosion of
local trees richness (Beukema et al., 2007). For rubber
cultivation, forest is fully cleared and crops are established
as monoculture plantations on average replanted after
about 40 years, but some plantations are maintained to
an age of 70-80 years (Gouyon et al., 1993). In many
Tropical countries, this loss of the natural forests has
been counteracted by the rapid increase in degraded
forestland allocated to plantation establishment and other
policies (CTFT, 1989). Like many other tropical countries,
the loss of Ivoirian’s natural forests has been counteracted
by comprehensive reform programmes in the forestry
sector among which a key reform was the Government’s
initiative in plantation establishment in the country, not
only to halt forest degradation but also to catalyze
important native forest flora restoration after long period
of anthropogenic and non-anthropogenic disturbances
(Lemenih and Teketay, 2004; Baatuuwie et al., 2011).
These programmes have increased plantations since
1992 of both native and exotic timber tree species
amongst which Teak (Tectona grandis L.f., Verbenaceae)
Kouame et al. 129
is predominant. Teak cultivation involves full local vegeta-
tion removal sometimes with mechanics.
In Côte d’Ivoire, there are two main categories of protected
areas; the national parks exclude any human activities
except management and research, and the classified
(protected) forests whose purpose is management for
sustainable logging (Kouamé, 1998). The definition and
delimitation of these protected areas began in 1924 by
their static conservation (de Koning, 1983; Ahimin, 2006).
After the Ivorian independence in 1960, their legal status
was created together with a national forest research institute
(IDEFOR) and a national society for forest development
(SODEFOR). Forty years later, anthropogenic activities in
national parks, protected forests and biological reserves
result in their degradation despite the promulgation of
legal instruments/laws (Dao, 1999; Chatelain et al., 2004;
Ahimin, 2006). Due to rarefaction of wastelands in the
rainforest area, the farmers crossed the limits of protected
forests within which they establish their crops. The
politico-military crisis in Côte d’Ivoire since 2002 led to
increase in the illegal occupation of its South-western
protected areas, especially Duekoué and Scio forests. In
areas undergoing rapid land use change such as the
rainforest of Côte d’Ivoire, where undisturbed lowland
forest has almost completely disappeared (Chatelain et
al., 2004; BNETD, 2010), the question whether at least
some of the native rainforest species can survive in
disturbed forest types has become important. The
potential significance of such agroforestry systems for
biodiversity conservation is stressed by nature conservation
agencies and the international research community
(Siebert, 2002; Garrity, 2004; Schroth et al., 2004).
To understand the effects of Teak plantations created
by the Forestry Service and the cash crops production by
small farmers in the protected forests of Duekoué and
Scio on the diversity of trees, shrubs and lianas, eighty
20 m x 50 m plots were investigated for their woody plant
richness. We sampled woody plant individuals that had
10 cm DBH and above at the species level, with the aim
of analyzing woody plant species composition and diversity
in relation with the anthropogenic activities. Given that
both the agroforestry systems of creating forestry plan-
tations and farming cash crops aim to promote few
targeted species at the expense of the local flora, we
hypothesized to find higher plant species richness and
diversity in natural vegetation than in plantations.
MATERIALS AND METHODS
Research site and data collection
Research was carried out in the classified forests of Duekoué (6°
30’- 6° 45’ N, 7° 00’- 7° 15’ W) and Scio ( 6° 30’-7° 00’ N, 7° 30’- 8°
05’W) South-west of Côte d’Ivoire (Figure 1). Climate in both areas
is sub-equatorial with a long wet season from February to
November and a short dry season from November to January.
Annual rainfall varies from 1600-1700 mm in Duekoué forest to
1700-1800 mm in Scio forest. The average monthly temperature is
130 Afr. J. Plant Sci.
Figure 1. Localization with MapInfo 7.8 software of research sites on the map of protected areas and main floristic features
distribution in Western Côte d’Ivoire rainforest zone (From Kouamé and Zoro Bi, 2010). A: General vegetation and
protected areas map of Côte d’Ivoire, B: South-west region, C: research sites location.
25ºC while monthly and annual potential evapotranspiration of
Duekoué and Scio are 123.5 and 1482 mm, respectively (Eldin,
1971). The soils of both forests belong to the remould ferrallitic
group (Perraud and De La Souchère, 1970). The Duekoué forest,
with an area of 53,600 ha (SODEFOR, 1994), consists of a moist
semi-deciduous forest defined as a Tropical rainforest type in which
part of the higher trees shed their leaves during the 3-4 months dry
season in a region of 1350-1600 mm annual rainfall (ORSTOM and
UNESCO, 1983) and interrupted by savannas areas and inselbergs
(Monnier, 1983). The original vegetation of Scio forest, covering
88,200 ha (SODEFOR, 1996), belongs to South-western evergreen
forest type of Côte d’Ivoire that spreads in the wettest forest area.
(Kouamé, 2010; Kouamé and Zoro Bi, 2010)
Field data collection was carried out in eighty 1000 m² (20 m x 50
m) plots, as suggested by Thiombiano et al. (2010), established per
10 in four different vegetation types (biotopes) for each forest
(Table 1). Homogeneity, local area, repetition, presence of plant
individuals with DBH≥10 cm and availability were the criteria of
these biotopes’ selection. Thus, the biotopes plotted were the natural
forest patches, the undergrowth cleared forests, the coffee plan-
tations, the cocoa plantations, the rubber plantations and the teak
plantations (Table 1). Each plot was sub-divided into ten 100 m²
sub-plots where all plants with DBH≥10 cm were assessed for their
scientific names and DBH.
Data analysis
Taxa identification followed Aubréville (1936), Lebrun and Stork
(1991-1997), Aké Assi (2001, 2002) and Hawthorne and Jongkind
(2006). Family and authors names have been updated with Mabberley
(1997).
Floristic diversity was analyzed using the species number
considered as the first diversity parameter (Gaston, 1996; Tuomisto,
2011) and the three commonest diversity indices (Shannon-Wiener,
1949; Simpson, 1949; Pielou, 1966). Simpson’s diversity index (D’)
checks the probability for 2 random individuals in a community to
belong to the same species (Simpson, 1949).
Where, Pi = ni/∑ni with ni as average cover of a species i and ∑ni
the total cover of all species. D’ varies from 0 (maximum diversity)
to 1 (minimum diversity). This index is sensitive to the variation of
importance for most abundant species (Peet, 1974; Grall and Coïc,
2006).
Shannon-Wiener’s index (H’) which is the most recommended
index to check richness diversity (Grall and Coïc, 2006) is below
formulated:
with Pi as relative average cover of species I in a community
(Shannon and Wiener, 1949). H’ varies from 0 (monospecific
settlement) to LnS (maximum diversity). This index is sensitive to
the variation of importance for most rare species (Peet, 1974; Grall
and Coïc, 2006).
Pielou’s index (J’) measures the degree of a settlement diversity
and corresponds to the average between the affective diversity
A
B
C
D’ = 1 - ∑Pi
2
H’ = -
∑ PiLnPi
i=1
s
Kouame et al. 131
Table 1. Description and localization of plots.
Biotopes
Duekoué
forest
Latitude N
Longitude W
Biotopes
Scio forest
Latitude N
Longitude W
Coffee plantations
PCAFD1
6° 42
7° 06
Coffee plantations
PCAFS1
6° 38
7° 52
PCAFD2
6° 40
7° 06
PCAFS2
6° 38
7° 51
PCAFD3
6° 41
7° 14
PCAFS3
6° 31
7° 48
PCAFD4
6° 43
7° 12
PCAFS4
6° 39
7° 50
PCAFD5
6° 41
7° 14
PCAFS5
6° 38
7° 52
PCAFD6
6° 40
7° 06
PCAFS6
6° 38
7° 51
PCAFD7
6° 42
7° 06
PCAFS7
6° 38
7° 53
PCAFD8
6° 43
7° 02
PCAFS8
6° 38
7° 53
PCAFD9
6° 40
7° 06
PCAFS9
6° 31
7° 48
PCAFD10
6° 43
7° 12
PCAFS10
6° 39
7° 47
Cocoa plantations
PCAOD1
6° 42
7° 06
Cocoa plantations
PCAOS1
6° 31
7° 48
PCAOD2
6° 42
7° 06
PCAOS2
6° 38
7° 51
PCAOD3
6° 42
7° 12
PCAOS3
6° 39
7° 46
PCAOD4
6° 41
7° 14
PCAOS4
6° 38
7° 51
PCAOD5
6° 42
7° 12
PCAOS5
6° 38
7° 52
PCAOD6
6° 43
7° 12
PCAOS6
6° 39
7° 46
PCAOD7
6° 42
7° 12
PCAOS7
6° 38
7° 51
PCAOD8
6° 42
7° 12
PCAOS8
6° 38
7° 51
PCAOD9
6° 43
7° 12
PCAOS9
6° 39
7° 47
PCAOD10
6° 42
7° 12
PCAOS10
6° 39
7° 47
Rubber plantations
PHEVD1
6° 42
7° 06
Undergrowth cleared
forests
FDEFS1
6° 39
7° 46
PHEVD2
6° 42
7° 06
FDEFS2
6° 38
7° 51
PHEVD3
6° 42
7° 06
FDEFS3
6° 38
7° 51
PHEVD4
6° 43
7° 06
FDEFS4
6° 39
7° 46
PHEVD5
6° 43
7° 06
FDEFS5
6° 39
7° 51
PHEVD6
6° 42
7° 14
FDEFS6
6° 39
7° 50
PHEVD7
6° 42
7° 14
FDEFS7
6° 39
7° 50
PHEVD8
6° 42
7° 12
FDEFS8
6° 38
7° 48
PHEVD9
6° 43
7° 06
FDEFS9
6° 38
7° 52
PHEVD10
6° 42
7° 06
FDEFS10
6° 38
7° 53
Teak plantations
PTECD1
6° 42
7° 12
Natural forests
FNBAS1
6° 39
7° 46
PTECD2
6° 42
7° 12
FNBAS2
6° 38
7° 51
PTECD3
6° 42
7° 12
FNBAS3
6° 39
7° 48
PTECD4
6° 42
7° 13
FNBAS4
6° 38
7° 53
PTECD5
6° 42
7° 01
FNBAS5
6° 39
7° 49
PTECD6
6° 41
7° 14
FNBAS6
6° 31
7° 48
PTECD7
6° 41
7° 14
FNBAS7
6° 34
7° 51
PTECD8
6° 42
7° 12
FNBAS8
6° 39
7° 49
PTECD9
6° 42
7° 13
FNBAS9
6° 30
7° 51
PTECD10
6° 42
7° 12
FNBAS10
6° 39
7° 50
H’ and the maximum theoretical diversity H’max (Pielou, 1966).
with H’ as Shannon-Wiener index. J’ varies from 0 (monospecific
settlement) to 1 (similar distribution of all species).
Additionally to these commonest indices, Hill’s index which is a
combination of Simpson’s diversity index and Shannon-Wiener’s
index (Hill, 1973; Grall and Coïc, 2006) was used to analyze the
diversity in biotopes as recommended by Peet (1974) and
J’ = H’/H’max
132 Afr. J. Plant Sci.
Figure 2. Richness and diversity indices in plots.
Routledge (1979).
Hill varies from 1 (monospecific settlement) to α (similar distribution
of all species).
Such as data in plots showed normal distribution (Mead et al.,
1993; Bar-Hen, 1998; Young and Young, 1998; Fowler et al., 1999),
their statistical analyses were performed with parametric tests as
recommended by Mead et al. (1993) and Fowler et al. (1999). Plot
richness and diversity indices were compared using paired samples
t test of Student (Student, 1908; Greig-Smith, 1983) with SPSS
18.0 software. Richness of coffee plantations and cocoa plantations
that was assessed in both research sites (Table 1) was analyzed
with ANOVA (Scherrer, 1984; Mead et al., 1993; Fowler et al.,
1999) using Statistica 7.1 software for checking prospective impacts
of site and/or crop nature on plot richness. Bonferroni’s Post-Hoc
test with Statistica 7.1 software led to segregate impacts of site and
crop nature as the ANOVA showed their effects on plot richness.
RESULTS
The natural forest patches (FNBAS) in Scio site showed
the highest α-diversity in plots and biotopes whereas the
undergrowth cleared forests (FDEFS) in Scio showed the
second highest α-diversity (Figure 2, Table 2). Both
0
9
18
27
36
45
0 5 10
Richness (species number)
Plot number
Richness
FNBAS
FDEFS
PCAFD
PCAFS
PCAOD
PCAOS
PHEVD
PTECD
0
1
2
3
4
0 5 10
Shannon-Wiener index
Plot number
Shannon-Wiener
FNBA
FDEFS
PCAFD
PCAFS
PCAOD
PCAOS
PHEVD
PTECD
0.0
0.3
0.6
0.9
1.2
0 5 10
Simpson diversity index
Plot number
Simpson diversity
FNBA
FDEFS
PCAFD
PCAFS
PCAOD
PCAOS
PHEVD
PTECD
0
300
600
900
1200
0 5 10
Hill index
Plot number
Hill
FNBA
FDEFS
PCAFD
PCAFS
PCAOD
PCAOS
PHEVD
PTECD
0.0
0.3
0.6
0.9
1.2
0 5 10
Pielou index
Plot number
Pielou
FNBA
FDEFS
PCAFD
PCAFS
PCAOD
PCAOS
PHEVD
PTECD
Hill = (∑Pi
2
)
-1
1/exp[H’]