Tree Composition and Diversity of a Hill Dipterocarp Forest after Logging

1Faculty of Forestry, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia

2Natural Resources and Agricultural Research Center of Bushehr Province, I.R.Iran *Corresponding Author: [email protected]

Malayan Nature Journal 2014, 66(4), 1-15

Tree Composition and Diversity of a Hill Dipterocarp Forest

after Logging

SEYED MOUSA SADEGHI

1,2, I. FARIDAH-HANUM

1*, WAN RAZALI,

W. M. 1, KAMZIAH ABD KUDUS

1 and KHALID REHMAN HAKEEM

1

Abstract: Logging operations have been known to highly influence the

environment of tropical rain forest. The present study investigated the effect

of supervised logging (SL) operations on tree composition and diversity of a

hill dipterocarp forest (HDF) in Ulu Muda Forest Reserve, Kedah,

Peninsular Malaysia. To describe the tree composition and diversity of the

secondary HDF after SL, the compositional factors and diversity were

analyzed. A plot of size 1-ha was established. All trees with diameter at

breast height ≥ 1cm in 10 sub plots (50m × 20 m) were enumerated,

measured and identified. In the study site, we recorded 891 individuals,

belonging to 56 families, 158 genera, 296 species and one variety. Ten

families provided 55.7% of the total species composition. Euphorbiaceae

has the highest number of species and was followed by Lauraceae,

Rubiaceae, Annonaceae and Meliaceae. With regards to relative dominance,

Diplospora malaccensis (Euphorbiaceae) gave the highest importance value

index for species and family, respectively. Shannon-Wiener’s index was

high with a value of 5.3. Ulu Muda Forest Reserve is high in endemism with

a total of 27 endemic species recorded. Two rare species which are

Symplocos calycodactylos and Alseodaphne garciniicarpa and one very

rare species, Cleistanthus major were found here. Diospyros argentea

was also found to be a new record for Kedah.

Keywords: Tree composition, diversity, hill dipterocarp forest, and logging.

INTRODUCTION

The environment of a tropical rain forest was known to be affected by

logging operations strongly (Burgess, 1971; Saiful, 2002; Okuda et al.,

2003; Akkharath, 2005). The reaction of tropical rain forest towards both

anthropogenic and natural disturbances is one of the most crucial aspects in

ecological studies (Lugo and Brown, 1986; Grace, 2004; Chave et al.,

2005).

2

The number of families, genera and species of Ulu Muda Forest

Reserve ( UMFR) was found to decrease after logging from 49 to 43

families, 136 to 124 genera, and 270 to 205 species, respectively (Saiful,

2002). The protection of primary forest is significant for biodiversity

conservation and climate change mitigation; the secondary forest must also

be considered for the same crucial roles (Berry et al., 2010). Countries

such as Indonesia and Malaysia have considered changing the logging

approaches from CL to supervised logging (SL) (Sist et al., 1998). In SL, all

activities were done under the supervision of “Supervisory Field Team” to

reduce the impact of logging on forest ecosystem during the logging period

(Sist et al., 1998). The benefit of SL compared to CL was to reduce damage

to the ecosystem of the forest to below 50% (Sist et al., 1998). In the year

2000, compartment 25A of UMFR was subjected to SL operations to

manage these forests under sustainable forest management approaches

(Saiful, 2002).

Forest composition of HDF was strongly affected by selective

logging operation immediately after logging (Saiful, 2002; Kamziah et al.,

2011). Conventional logging activities had declined the taxonomic

composition of the HDF of UMFR (Saiful, 2002). The family

Dipterocarpaceae was the most affected dominant family after logging in

UMFR (Saiful, 2002). The performance and demography of selectively

logged tropical forest were influenced by logging operations after 40-50

years (Yamada et al., 2013). Likewise, the fast growing species were

abundant in the secondary forest compared to the old growth forest (Okuda

et al., 2003). The intensity of logging operations affected the biodiversity of

the tropical rainforest (Imai et al., 2013; Saiful & Latiff, 2014). Biodiversity

of HDF was affected by land use management activities. Saiful (2002)

reported that Shannon Weiner’s index sharply decreased after CL in habitats

such as hillside, ridge and ridge top for all diameter at breast height (DBH)

size classes. Having a true understanding of floristic composition of the

successional secondary forest after disturbances would be crucial for

considering forest recovery procedures and planning forest management.

Forest succession is changes in plant community over the passage of time.

The process of succession could be progressive or regressive (Ellenberg and

Mueller-Dombois, 1974). The vegetation succession was classified into

three main groups: Phenological vegetation changes, Secondary succession,

and (3) Primary succession (Ellenberg and Mueller-Dombois, 1974).

Succession following logging is the secondary succession (Kimmins, 2004).

The presence or absence of residual vegetation and their propagules which

survive the disturbance is the most important factor in forest succession

(Turner et al., 1998). Likewise, size and intensity of disturbances can

strongly influence the succession potential of the regenerated forest (Van

Gemerden et al., 2003). Furthermore, severity of disturbances, matrix of

landscape, proximity of degraded forest to remnant forest areas, and soil

3

fertility can also influence forest succession (Chazdon, 2003). Additionally,

different species might be established in different regions (Ellenberg &

Mueller-Dombois, 1974).

The present research aimed to quantify the tree composition and

forest diversity value of Ulu Muda Forest Reserve in Kedah, 12- years after

supervised logging. It is part of an ongoing assessment on a 5-ha study plot

to be reported in another paper elsewhere.

MATERIALS AND METHODS

Study area

The research was carried out in the HDF of UMFR, Compartment 25 A

(Figure 1) at altitude of 419-555 m above sea level in the state of Kedah,

Peninsular Malaysia (5, 50’ N & 100, 55’ E). The average annual

precipitation and temperature of the site were 2869 mm and 26-29◦C (Lim,

1991; Saiful et al., 2008). In terms of geology, UMFR includes three

geologic formations, The Kulim granite, Bintang granite formation,

Semangol formation, and Baling formation as the basic levels of the ground

habitats (Lim, 1991). The main type of soil in the study site was ultisols

(Saiful 2002). The total area of compartment 25A was 232.09 ha. The

original vegetation type was dominated by dipterocarps (Faridah Hanum et

al., 1999; Saiful et al., 2008). Supervised logging operations began in

Compartment 25A in 2000 and ended in 2001 (Akkharath, 2005).

Methodology

Data were collected from 10 sampling plots totalling 1- ha was laid out

systematically in the supervised logging (SL) site (Fig. 1). All trees with

diameter at breast height ≥ 1cm in 10 subplots each of size 50m × 20 m

were enumerated, measured and identified. Taxa identification was based

on (Whitmore, 1972 ; Whitmore, 1973; Kochummen, 1978; Ng, 1989;

Turner, 1995; Symington et al., 2004).

The species composition and diversity of forest stand were analyzed. For

species richness, the rarefaction method and Jacknife approach were used.

The rarefraction method used followed Krebs (1999) as shown below:

Where E (Ŝn) = Expected number of species in random sample of n

individuals

4

S = Whole number of species in the entire collection

Ni = Quantity of trees of species i

N = Overall amount of trees in collection = ∑ Ni

N = Value of sample size (number of individuals) chosen for standardization

(n ≤ N)

( ) = Number of combination of n individuals that can be chosen from a set

of N individuals

= N!/n!(N-n)!

The Jackknife estimator approach (Krebs, 1999) was used to estimate the

maximum value of species richness as follows:

(

)

Where Ŝ = Jacknife estimate of species richness

s = Observed total number of species in the n plots

n = Total number of sampling units

k = Number of unique species

The species diversity and richness4 (SDR4) software was used for

calculating the diversity and richness of the forest stand (Seaby &

Henderson, 2006). The most common indices for diversity evaluation were

calculated as follows;

Simpson’s index is 1-D (Simpson, 1949; Krebs, 1999):

∑(

)

Where ni = Number of individuals of species i in the sample

N = Total number of individuals in the sample

s = Number of species in the sample

The Shannon-Wiener’s index (H) is (Pielou, 1966):

5

∑

Where s = Number of species and ρi= proportion of total sample belonging

to ith species

Margalef index could evaluate the richness index of stand (Clifford &

Stephenson, 1975):

DMG

Where S = Number of species,

N = Total recorded number of individuals

Alpha Fisher’s index (Fisher et al., 1943) of diversity (α):

S =

Where S = Total number of species in the sampling area

N = Total number of individuals in the sampling plot

α = Index of diversity

Additionally, Smith & Wilson (1996) evenness index was calculated as

follows (Krebs, 1999):

[

{

∑ ( ∑

⁄ )

⁄

}

]

Where E = EVar = Smith and Wilson’s index of evenness (Krebs, 1999)

ni= Number of individuals in species I in sample (i = 1, 2, 3, . . . s)

nj = Number of individuals in species j in sample (j = 1,2, 3, . . . s)

6

s = Number of species in entire sample

Furthermore, evenness index estimation was done by Pielou (1975) model:

Where H’ is the real value of evenness, and H max is the exactly maximum

potential evenness in the study area. The above mentioned models were

used to calculate the evenness value of the study site.

The importance value index (IVI) of each species was computed according

to Curtis & McIntosh (1951) as follows:

RF =

RD

RDo

The basal area (BA) of each individual was calculated as follows:

BA (m2) = [π × (DBH)

2]/40000

The family importance values (FIV) of forest stand were also computed

based on (Mori et al., 1983). The FIV was the summation of relative

diversity (RDi), relative density (RDe) and relative dominance (RDo):

RDi

RDe

RDo

The total tree numbers in all plots were used to generate an average of the

stand density ha-1

(Valappil and Swarupanandan, 1996).

RESULTS

Tree species composition analyzed for 1- ha of the supervised logged-over

HDF showed there were 891 individuals belonging to 296 species and one

variety in 158 genera and 56 families. Ten families in terms of species

composition provided 55.7 % of total species composition (Table 1). The

most diverse family was Euphorbiaceae with 44 species in 16 genera

7

followed by Lauraceae, Rubiaceae, Annonaceae and Meliaceae. Although

the family Dipterocarpaceae was not among the 10 top families (Table 1),

there were still 25 individuals from five species. The non-dipterocarp group

contributed 98.3% of tree composition; 62.6% of total species were

presented by ≤ 2 individuals in the study site.

Twenty seven endemic species comprising 9.1% of the total

number of species were found in the study site. These belong to 24 genera

from 20 families. In terms of species diversity, the most diverse family was

Euphorbiaceae (18.5%), followed by Lauraceae (11.1%), Anacardiaceae

(7.4.0%), Burseraceae (7.4.0%) and Annonaceae (3.7%). Results showed

there are 27 endemic species in the study site. Based on Ng et al. (1990),

two are rare species viz. Symplocos calycodactylos and Alseodaphne

garciniicarpa are considered rare while Cleistanthus major very rare.

Diospyros argentea is a new record for Kedah (Table 2).

Quantitative analysis of the most dominant species (20 species) is

presented in Table 3. In terms of relative dominance, 20 species contributed

22.8% and 44.1% of the total density and total basal area of the logged-over

stand. Moreover, in terms of basal area, the most dominant species was

Diplospora malaccensis (14.7%) followed by Shorea macroptera (13.7%),

Ochanostachys amentacea (11%), Shorea kunstleri (9.5%) and Sapium

baccatum (7.2%), respectively. The highest IVI was Diplospora

malaccensis followed by Shorea macroptera, Ochanostachys amentacea,

Mallotus kingii and Macaranga hosei (Table 3). A total of 121 species with

one individual were presented in the study site.

Likewise, in terms of FIV, ten families provided 6.2% of the total

relative density. Euphorbiaceae also contributed the highest value of FIV,

followed by Rubiaceae, Lauraceae, Annonaceae and Fagaceae. The

minimum value of FIV was contributed by Elaeocarpaceae (Table 4 and

Figure 3). In general, the species accumulation curve showed the increasing

trend; as the sampling area increased from 0.1 to one ha in the study site

(Figure 4). Additionally, it slightly increased from plot 2 (SL7/P1) to plot 3

(SL8/P3). The overall tendency of that curve did not achieve an asymptotic

condition.

Rarefaction method showed that an increase in the sample size led

to an increase in the number of species. When the number of individuals

was 89, the estimated number of species was 71.2. However, with 890

individuals the estimated (finite estimation) value of species richness was

296.9 (Figure 5). The jackknife estimation model demonstrated that an

increase in the number of samples led to an increase in the number of

estimated species (Table 5). Data showed that when this model was used

with one plot data, the predicted value of species richness was a minimum.

However, the maximum value of the estimated species richness was

predicted when the ten plot data were used in the model.

8

Our results showed that the biological diversity of the logged-over was high.

The overall Shannon-Weiner’s H index was 5.3 and the MacIntosh’s index

and evenness were 0.95 and 1.0, respectively. The lowest and highest value

of Shannon-Weiner’s Index was related to sampling plots SL7/P3 and

SL9/P2 which were 2.4 and 4.3 (Table 7). The number of individuals in

SL7/P3 and SL9/P2 was 18 and 130, respectively. Results of the Smith and

Wilson’s evenness method showed that the highest and lowest values of

evenness were related to SL7/P2 and SL6/P2 (Fig. 6) which were 0.9 and

0.8, respectively. However, the average value of evenness was 0.7 (Table 6).

DISCUSSION

In the sampling plots, there were no big trees because they were cut for

commercial purposes. However, many studies have indicated that the

primary HDF includes trees of all sizes ranging from DBH<1cm to ≥ 100

cm (super tree), (Whitmore and Burnham, 1984; Saiful, 2002). Therefore,

the findings of the study should be interpreted in light of this limitation.

Additionally, one of the most prevalent tree species in the HDF is Shorea

curtisii ssp. curtisii (Whitmore and Burnham, 1984), but a very small

number of this species was found in the logged-over forest due to logging.

According to Whitmore and Burnham (1984) and Symington et al. (2004),

the primary HDF was dominated by trees such as Shorea curtisii ssp.

curtisii, Shorea laevis and Shorea multiflora. Indeed, such trees were quite

scarce in the sampling plots. In terms of species richness, the supervised

logged-site (Compartment 25 A) was richer than unsupervised-logged

compartment (28 A), (Mardan et al., 2013) of UMFR. In the SL area, 891

individuals, including 296 species and one variety belonging to 157 genera

and 56 families, were found. Furthermore, Mardan et al. (2013) showed that

1- ha unsupervised logged HDF (= conventional logging or CL) of UMFR

consisted of 722 individuals belonging to 128 species, 81 genera and 42

families. Likewise, Euphorbiaceae contributed the most number of species

in both sites. In general, tropical rain forests of southeast Asia are rich in

species composition (Whitmore and Burnham, 1984). Our results were in

line with other available studies regarding the tree composition in tropical

rain forest (Table 8). Moreover, the high level of species diversity was also

observed in the logged-over HDF (Faridah -Hanum et al., 1999; Mardan et

al., 2013). Kimmins (2004) observed that in the secondary succession, the

establishment of pioneer species is the first stage of succession. Similarly, in

the study site pioneer species from the families Dilleniaceae,

Euphorbiaceae and Moraceae were recorded because past anthropogenic

disturbances created a new environment for light demanding species

including Macaranga hosei, M. gigantea, M. triloba, M. hypoleuca, M.

recurvata, M. setosa, Croton argyratus, Mallotus kingii, Artocarpus rigidus,

Buchanania sessifolia, Dillenia sumatrana, Epiprinus malayanus and

9

Helicia attenuata due to gap formation (SL7/P3 & SL8/P3) in the forest

(Figure 7). Moreover, changes in the physical, chemical, and biotic

environments, which had been produced by residual organisms, caused

replacement of community by new individuals (Kimmins, 2004). In the

study site, light demanding species were highly established. They accounted

for the high diversity in the disturbed area usually due to gaps caused by

logging activities. Ellenberg and Mueller-Dombois (1974) reported that a

small number of big size trees showed higher levels of dominant species

than young pioneer small sized species which were abundant in the

secondary succession. Similar results were recorded in our study site. At the

species level, big sized trees from Shorea with small number of individuals

presented higher value of IVI than pioneer species which had a larger

number of individuals with smaller sized DBH. However, at the family

level, data showed that combination of the early successional species from

Euphorbiaceae provided the highest value of FIV since in the gap area

resulting from logging operations the fast growing species maintained

themselves faster than shade-tolerant trees. There was no asymptote of the

accumulated species curve (Figure 4). The increasing curve indicated that

unsampled species were still in the population (Bacaro et al., 2012). In other

words, the sampling must increase to achieve the asymptotic situation of the

curve.

Diplospora malaccensis was the most dominant species in the study

area while Macaranga hosei was the most dominant species in

Compartment 28 A (CL area) (Mardan et al., 2013). Although, Shorea

kunstleri and Sapium baccatum were among the five top species with regard

to the basal area production, they were not among the five top species in

terms of IVI values because the number of those species was one and four

tree ha-1

, respectively. However, Mallotus kingii and Macaranga hosei were

included in the list of the five top species in terms of IVI contribution.

Results from UMFR and other study areas showed that the dominance of

species is different from site to site. The dominance of species has been

shown to depend on the quality of site and availability of the nutrient

resources for plant establishment and plant growth (Kunwar and Sharma,

2004).

Species importance value index and FIV computation of the study

site showed that Diplospora malaccensis and Euphorbiaceae provided the

highest level of those values (Table 8). However, Shorea curtisii ssp. curtisii

which gave the highest level of IVI in the other logged-over and primary

HDF was 42.9 and 32.6, respectively (Saiful, 2002; Kamziah et al., 2011).

The family Dipterocarpaceae provided the highest level of FIV

(Ghollasimood, 2011). Additionally, in the primary HDF in UMFR, the

dipterocarps also gave the highest value of FIV (Saiful, 2002) (Table 8).

However, in the logged-over HDF, Euphorbiaceae gave the highest FIV

among all families because logging operations had targeted the large trees of

10

HDF during the period of timber harvesting. Hence, most of the dipterocarp

trees were removed during that period. So, the pattern of primary HDF was

not found in the study area due to the forest being logged-over. The notable

point was that rich successional families such as Euphorbiaceae and

Rubiaceae ranked in the first and second levels of that value, respectively

(Okuda et al., 2003). Furthermore, among the 20 top species with regards to

IVI, Shorea macroptera provided the second place of that value (Table 3).

Our results showed that at the species level, in terms of dominant trees, the

pattern of the logged-over HDF was to some extent similar to the

undisturbed HDF while at the family level there was no similar pattern of

the primary HDF. In the study site, successional species from the family

Euphorbiaceae were found in all sampling plots. The positive signals of

recovery of species composition were considered from regenerated HDF.

However, long term research is required to confirm this. Also, the top niche

species in the forest stand were indicated by the dominance-diversity curve.

The top niche species were at the beginning of the curve while the other

species were arranged in the sequence of their niche level and with moderate

slope (Figure 2). The availability of appropriate niche and distribution of

nutrient resources affected the relative species dominant (Kunwar and

Sharma, 2004).

The study site was generally high in tree diversity. However,

changes were revealed when comparison of diversity index was made with

other forests (Table 8 & 9). The Shannon-Weiner’s index of the primary

HDF in UMFR was higher than that value of our study site which was 5.6

(Saiful et al., 2008) and 5.3, respectively. The Shannon-Weiner’s Index of

HDF, UMFR, was lower than that value of other study sites (Table 8); the

index of the study site was less than that value of Tekai Tembeling Forest

Reserve (TTFR) (Kamziah et al., 2011) which was 5.3 and 7.0, respectively.

However, Simpson and Smith-Wilson’s evenness indices of our area were

higher than those values of TTFR. Out of 296 species, 121 species were

classified under rare species (with ≤ two individuals). Additionally, data

revealed that SL7/P3 was strongly disturbed during the past logging period

(Fig. 6). However, overall diversity results showed that the secondary HDF

was rich (Table 6 & 8) because the logged-over forest was in the gap phase

of succession following logging operations. Van Gemerden et al. (2003)

demonstrated that 834 species including 23% endemic were identified

within Lower Guinea tropical rainforest of Cameroon. They concluded that

regenerating forest can provide biological conservation as a buffer region

around endangered zones. Our results showed high endemism in the study

site (11.4% of total species was endemic). Endemic species shows

biological uniqueness of an area (Peterson and Watson, 1998). The

sampled area, species abundance and gap sizes in the forest might affect the

biological diversity (Imai et al., 2013; Saiful & Latiff, 2014). Thus, we

considered the fluxes in the Shannon-Weiner’s index when we compared

11

our results with other available data (Table 9). Since species diversity of

UMFR was high, this secondary HDF can play a very crucial role in terms

of biological conservation. Although the study site was strongly disturbed

and with tracks of logging operations in the forest stand, the results showed

that the logged-over forest can also play a very important role in

environmental maintenance processes. The forest can provide multipurpose

objectives such as biodiversity conservation, carbon storage, climate

change mitigation, and soil and water resource preservation.

Late and early successional species were recorded in the secondary

HDF after logging (Davies et al., 2003; Lin et al., 2003). Late successional

species such as Shorea parvifolia ssp. parvifolia (Hiromi et al., 2012),

Hopea and some species including Intsia palembanica were recorded. The

above mentioned individuals were in different stages of life form (seedling,

sapling pole and mature tree). On the other hand, pioneer species were

recorded in the study site. Hence, the positive signals of forest stand towards

recovery were shown. The biological criteria are very useful tools to guide

the forest management in conservation planning. Conservation of biological

resources was presented by biological functions (Phua and Minowa, 2000).

Consequently, conservation of logged HDF occurred in a proper way that

can maintain the high value of biodiversity (Hamer et al., 2003; Cleary et

al., 2005; Yamada et al., 2013).

In the secondary HDF, it was observed that when the number of

species in 1- ha was extremely large, the number of individuals of most of

species was low. The numerous species were presented by small populations

(one individual) include Shorea kunstleri, Canarium pseudosumatranum,

Syzygium pustulatum, Serianthes grandiflora, Shorea pauciflora, Baccaurea

sumatrana, Timonius wallichianus, Mezzettia parviflora and Beilschmiedia

wallichiana. Similar results were reported by Fedorov (1966). Based on the

results obtained, it can be presumed that self-pollination was more common

than cross-pollination among the small population of trees. Thus, the

automatic genetic improvement process of such small population will

happen gradually (Fedorov, 1966). Furthermore, available published data

showed the greater incidence of sun energy near the equator along with a

resultant greater stability in biological productivity that might have been

implicated in tropical speciation (Connell and Orias, 1964; Wright, 1983;

Gentry, 1989). Thus, in the logged-over HDF, the gap formation resulting

from logging, promoted greater sun light in the new environment for high

level of diversity.

Species richness estimation by rarefaction method was smaller than

that value of Jacknife approach. According to rarefaction model, estimated

species richness was close to the observed value of species richness (Figure

5). Based on Jacknife method, the predicted rate of species richness was

higher than the observed rate of species richness (Table 5). Such results

presented some uncertainties regarding the above mentioned methods.

12

Hence, further studies are required to improve and clarify the species

richness estimation models (Figure 5 & Table 5). On the other hand Jacknife

estimating model allowed us to include the rare species data in the

calculation procedure and the majority of species (62.6%) was rare species

(species with 1 or 2 individuals), hence the number of expected species was

much higher (435.6) than observed species in the study site.

CONCLUSION

The supervised logged area of HDF at UMFR has high species diversity

and species richness. High endemism is another feature of this area. The

biological criteria are useful tools to guide the forest management in

conservation planning. Monitoring studies will be important and provide

future perspectives of responses of HDF towards supervised logging

operations and climate change. . This is important for policy makers to

consider the reduction process of biodiversity loss by forest degradation and

deforestation. Also, they may consider the value of carbon-based payments

for ecosystem services in tropical countries.

ACKNOWLEDGEMENTS

We would like to express our heartfelt appreciation to the late Pn. Latifah

Zainal Abidin for helping us during the fieldwork. We also thank the

Director of Kedah Forestry Department and Universiti Putra Malaysia

(Grant t No. 9199757) for supporting this research.

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