Monitoring pattern change of forest patches in tropical ...

Landscape Ecology and Managemont 9(1)26 -40 .2004 Original

article

Monitoring

pattern

change

of forest patches

two different

Saiful

1

Graduate

School for International

and

and Cooperation, 739-8529,

2

landscape

using

levels of forest classification

ArifAbdullah1,2

Development

in tropical

Nobukazu

Hiroshima

Nakagoshi1

University

1-5-1 Kagamiyama,

Higashi-Hiroshima

City,

Japan

Institute for Environmentand Development (LESTARI), UniversitiKebangsaan Malaysia 43600 Bangi Selangor Darul Ehsan, Malaysia

Abstract The objective of this study was to quantify temporal changes in the spatial structure and pattern of forest patches in the Langat Basin, Peninsular Malaysia in three different periods (1971/1972, 1981/1982and 1991/1992) from two perspectives; firstly the changes that might impact the environment of the Basin, and secondly its implication for the forest management system. Based on these perspectives, forest patches defined in this study were classified into two groups: Group 1: based on types of natural forest, and Group 2: only fou based on status under the PeninsularMalaysian Forest Management Systems. For both groups landscape metrics were used to quantify landscape structure. Factor analysis was used to select the final metrics for describing landscape structure change of forest patches throughout the study period. A total of eight metrics were finally selected for Group 1 and r metrics for Group 2. This result suggests that metrics that have to be considered to give information about landscape structure change depending on how forest patches are defined. Landscape structure analysis in Group I showed that all types of forest in the Langat Basin had experienced fragmentation and deforestation particularly between the period of 1981/1982 and 1991/1992, and it occurred intensely particularly in peat swamp forests. This indicates that peat swamp forests are the most threatened forest ecosystem in the Langat Basin. At the forest management level (Group 2), most of the primary forests had changed to secondary forests between the periods of 1971/1972 and 1981/1982. The secondary forests were intensely analyses explained that human activities in the Langat Basin, including forest management systems, affect the spatial structure of the forest patches. This information is vital to influence future land use planning and forest management systems to ensure the sustainability not only of the forest ecosystems but also of the environment of the Langat Basin. Key words: ecosystem health, fragmentation, landscape metric, Langat Basin, patch analyst, tropical rain forest

Introduction In tropical landscapes, forests are a key element to ensure

been

environmental sustainability and maintenance of various

degradation

ecological

However, forest area in most

through logging activities (Slik et al. 2002) and forest

tropical countries is becoming increasingly devastated

fires (Gerwing 2002; Davies and Unam 1999). Tropical

and

and

rainforests, for example, the Amazonian rainforest, has

socio-economic background; the most critical reason for

been known to store a large quantity of terrestrial carbon

decades has been rapid development

(Koop and Tole

biomass (e.g., Nascimento and Laurance 2002; Laurance

2001; Laurance 1999; Tole 1998). Massive clearance of

et al. 1998). Destruction of tropical rainforests by human

forest areas, or deforestation,

activities may increase the concentration of gases such as

this

processes.

is

usually

attributed

to

cultural

in tropical countries has

Received:October17,2003/Accepted:April 18,2004

26

the

leading

cause

of

severe

environmental

and loss of forest resources, particularly

Monitoring

pattern

change

of forest

patches

carbon dioxide, nitrous oxide and methane, in the

forest management and conservation, both in temperate

atmosphere, which are the principle contributors to the alteration of world climatic conditions. The major result

(e.g., Zipperer 1993; Reed et al. 1996) and tropical (e.g Skole and Tucker 1993) regions. Assessment of spatial

of this is an increase in the world ambient temperature,

structures and patterns of forest patches provides

or global warming (Hashimotio et al 2000).

knowledge that allows some assumption about its impact

Apart from log extraction and burning, deforestation

on the environment, even without extensive information

in developing tropical countries is catalysed by the

or facts about ecological processes that might be affected

ongoing spatial and temporal land use or land cover change (Laurance 1999). Temporal change of land

(O'Neill et al. 1997). Asian tropical rainforests have seen relatively high

mosaics ultimately impacts the spatial structure and

rates

pattern of a particular landscape (Forman 1995; Farina 2002). Patches of forests are part of various components

degradation in Malaysian rainforests has gradually

that characterize the structure, pattern, heterogeneity and

undisturbed forest areas have been considered to be

complexityof an ecosystem mosaic (Forman and Godron

severely threatened (Bryant et al. 1997).According to the

1986). Conversion of forest areas to other land use,

United Nations Food and Agriculture Organization

especially in highly human dominated landscapes, changes the pattern and spatial configurationof the forest

(FAO) (1997), between 1990 and 1995 the rate of deforestation in Malaysia was among the highest in the

patches (e.g., Reed et al. 1996). Continuation of this

tropical Asian region. One of the areas in Malaysia that

process has possibly left some forest patches in fragmented form that is to say the forest is an isolated

has been identified as experiencing extensive loss of

patch or is disconnected from a contiguous forest

activities is the Langat Basin. In twenty years (between

(Zipperer 1993).Landscape modification that contributes to forest depletion and fragmentation has important

1971 and 1991) the Basin lost approximately 27% of its

of

deforestation (Laurance

increased, particularly since the

1999).

Forest

1990s, and its

forest cover due to various human and development

forest cover (Abdullah 2003).

implications for various ecological processes (Hunsaker

Increasing pressure on its natural areas by human

et al. 1994). Empirical studies have shown that changes

activities has led to diverse environmental problems in

in spatial structure and patterns of forest patches within

the Basin, including among others flash floods,

landscapes alter the physical characteristics of the

land-slides and river sedimentation, which are naturally

interior forest environment and increase the 'edge effect'

related to degradation of forest areas. The Basin is now a

of the forest periphery (Kapos et al. 1997). This

focal area in the application of the concept of ecosystem

alteration can have an impact on ecological and

health in environmental management in Malaysia

biological entities of the forest, which include flora and fauna (Pires 2002; Stevens and Husband 1998; McIntyre

(Nordin et al. 2003; Nordin and Azrina 1998). Therefore, some quantitative understanding is needed on how

1995;Harris 1988;van Dorp and Opdam 1987).

human activities will affect the spatial and temporal

The landscape-scale monitoring approach provides

change of structure and patterns of the Basin's forest

outstanding potential for assessing dynamic change of

patches in the future. Landscape metrics or indices

spatial structure and pattern of a particular landscape

provide necessarytools for quantifying such changes and describing the characteristic of patches in heterogeneous

(Turner and Gardner 1991; Gustafson 1998). This approach has been applied widely in monitoring land-use

landscapes (Farina 2002; O'Neill et al. 1999; Riitters et

or land-coverchange over time for land management and

al. 1995; Turner and Gardner 1991; O'Neill 1988). The

planning purposes (e.g., Lausch and Herzog 2002; Coppedge et al. 2001; Luque et al. 1994; Simpson et al.

objective of this study was to quantify dynamic changes

1994). Realizing that human activities have caused the

Langat Basin, spatially and temporally, from two

alteration of land

perspectives; i) the changes in the forest that might impact the environment of the Basin, and ii) its

in

in spatial structure and pattern of forest patches in the

landscape-scale, landscape

perspective has also been recognised as applicable in 27

Saiful

implication study

for

will

increasing and

the

provide

forest

a data

set

effectiveness

monitoring

management and

and

and

improving

forest

Ecological Zone 2 is undulating with hills and knolls

for

use

planning,

areas

in

Nakagoshi

Ecological Zone 1 is hilly and forested, whereas

This

essential

land

of

Abdullah•ENobukazu

system.

information

managing

Arif

interspersed with relatively flat land, and Ecological Zone 3 is almost entirely flat (Nordin et al. 2003).

the

The Basin has experienced extensive loss of forest

Basin.

cover, because in the 1960s and 1970s, much of its forested areas were converted primarily into large-scale

Methods Study The

Langat

Malaysia, part

state

a

between

area

being

of Negeri

state

between

2930

its

km2 is

of

divided

geomorphology

a

1). The

Basin

is

rapidly and large areas of forested land were cleared for

2•K 36'

E 102•K 2',

into

covers

Selangor (Fig.

N

(Nordin

and

plantations, mining areas and human settlements (Wong 1974). In the 1980s and 1990s the Basin changed more

developing

Sembilan

E 100•K 10' and

Basin on

premier

in the

approximately

and

based

Basin,

is situated

of the

located

Langat

agriculture schemes, particularly oil palm and rubber

area

and

with Azrina

three and

area

and

N

the

ecological

urbanization, industrialization, building highways and

3•K 17',

total

1998).

in

land

other infrastructure (Abdullah and Nordin 2001).

The

Presently, the Basin is predominantly covered by agricultural land (64%), whereas the forest areas cover

zones

only 25% and the remaining land type (bareland, built-up

physiognomy.

areas and water bodies) range between 1% and 7% of the total land area (Nordin et al. 2003). There are three major forest types in the Langat Basin; dipterocarp (lowland and hill dipterocarp), peat-swamp, and mangrove forests (Abdullah 2003). Data acquisition This study used the existing three digital forest maps of the Langat Basin from different temporal periods (1971/1972, 1981/1982 and 1991/1992) in the form of vector orpolygon. The digital maps were based on maps of theNational Forest Inventory 1 (NFI 1) 1971/1972,NFI 2(1981/1982) and NFI 3 (1991/1992) produced by the Department of Forestry, Peninsular Malaysia. These data were compiled by the Department through rectifyingaerial photos, large-scaleresource maps and extensive fieldwork. The maps were digitised and transform intothe same geographic co-ordinates using geographic information system (GIS) application software ArcInfo 8.0.1 . Landscap e analysis In landscape analysis, calculation and interpretation of landscape metrics depends critically on how we initially define or describe the landscape (McGarigal and Marks 1995). In the Langat Basin we hypothesized that land modification and forest management systems have affect the spatial structure and pattern of its forest patches. Therefore, forest patches defined in this study were Fig.1: The geographical

classified into two groups; Group 1: forest patches

location of the Langat Basin.

classified based on types of forests, i.e. i) dipterocarp,ii)

28

Monitoring

Table1. Forest classification

pattern

under Peninsular

change

of forest

Malaysian

patchc.

Forest Management

Systems.

Source: Forest Inventory Maps (1971/1972, 1981/1982 and 1991/1992), Department of Forestry Peninsular Malaysia

This

requiring ArcView 3.0 or higher to operate (Elkie et al.

and

1999). In this study Arc View 3.2 was used. For each

temporal change of forest patches and also assumptions

period, landscape metrics were calculated with the vector

about the impact of this on the environment of the Basin,

version of Patch Analyst at class-levels, which integrates

and Group 2: forest patches classified based on status of

all the patches of a given type or class (McGarigal and

forest as categorised under Peninsular Malaysian Forest

Marks 1995).

peat

swamp

classification

and

iii)

provides

mangroves

an

insight

forests.

into spatial

Management Systems, i.e., i) Good dipterocarp (Gd) ii)

Patch Analyst 1.1 (Elkie et al., 1999) provides various

Poor dipterocarp (Pd) iii) Superior dipterocarp (Sd) iv)

metrics that can be used to calculate landscape structure

Upperhill dipterocarp

dipterocarp

and pattern at class-level and clustered into 4 groups, i.e.

(Sdip) vi) Secondary peat swamp (Sps) vii) Primary

Area metrics, Size metrics, Edge metrics and Shape

mangrove (Pm) vii) Plantation forest (Pt) ix) Primary

metrics. Although numerous metrics can be used to

peat swamp (Pps) and x) Secondary mangrove (Sm). The

quantify landscape structure, some of them are redundant

description

for analysing a particular landscape (Forman and Godron

(Ud) v) Secondary

for each class is given in Table 1.

This

on spatial and

1986; O'Neill et al. 1988; Turner and Gardner 1991). In

temporal changes that are useful for forest management

this study, factor analysis (O'Neill et al. 1988; Lausch

purposes. For each group, at the three temporal periods

and Herzog 2001) was used to select the final metrics for

(1971/1972

classification

provides

understanding

quantifying

quantifying landscape structure and patterns of forest

spatial structure and patterns of forest patches involved

patches in the Basin. The metrics of each class used in

the calculation of landscape metrics or indices that

factor analysis is listed in Table 2. For each class, only

described

metrics showing the highest correlation or greatest sum

1981/1982

landscape

and

1991/1992)

composition

and

configuration

(Riitters et al. 1995; Gustafson 1998; O'Neill 1999). The

of factor loading

calculation of the landscape metrics was performed using

component or factor in the three maps were chosen to

Patch Analyst 1.1, that available in two versions, i.)

quantify landscape structure and patterns for Group 1

vector only version and ii) vector and grid version,

and Group 2.

29

and uniquely correspond

to each

Saiful

Table 2. List of landscape

Arif

Abdullah •E

metrics

Nobukazu

Nakagoshi

(Elkie et al., 1999)

used for factor analysis

Table 3. Results of factor analysis, vorimax rotation and factor loading for each metric over the three periods based on natural forest classification. Bold: final metrics chosen to quantify landscape structure and pattern at class-level based on natural forest classification.

to quantify landscape structure and patterns. All the

Results Factor analysis resulted in 8 metrics for Group (Table 3) and 4 metrics for Group 2

I

selected metrics showed the highest correlation (between 0.8 to 1.0 correlation coefficient, either positive or

(Table 4), selected

30

Monitoring

pattern

change

of forest

patches

Table 4. Results of factor analysis, vorimax rotation and factor loading for each metric over the three periods based on forest management classification. Bold: final metrics chosen to quantify landscape structure and pattern at class-level based on forest management classification.

negative with uniquely corresponds to each underlying

the total area of peat swamp (Table 5) compared with the

component or factor. The principle component analysis

other two types of forest. The Number of Patch (NumP)

(PCA) with three underlying

factors explained about

for each type of forest increased between 1971/1972 and

91% and 84% of the total variation of the 13 metrics for

1981/1982, and the trend was continuous for dipterocarp

Group 1 and Group 2, respectively.

in the following period, but declined for the other two

Landscape analysis: Group 1

types of forest, most apparently in peat swamp forest

The evolution of landscape structure and pattern for

(Fig. 2a-c) The PSSD of dipterocarp forest in 1971/1972 and

each type of forest (dipterocarp, peat swamp and mangrove

forests)

in

1971/1972,

1981/1982

1981/1982 was similar (Fig. 4a), however, the MedPS in

and

1991/1992 is illustrated in Fig. 2a, b and c. A gradual

1971/1972 was much

decrease

revealed that the former period had more uniformly sized

in class area (CA) over the decades was

larger than 19F1/1982. These

primarily observed for peat swamp forests (Figure 2c),

and larger patches compared to the latter period that had

whereas most dipterocarp forest areas were eliminated

greatly differing and small patch sizes. In 1991/1992

between 1981/1982 and 1991/1992 (Fig. 2a), and the

both PSSD and MedPS had reduced from the previous

changes in mangrove forest fluctuated (Fig. 2b). The

period (1981/1982). This indicates that, larger patches in

trend or pattern of change of peat swamp forest was

1981/1982 were reduced in size. At the same time

similar to the trend changes of the whole forested area in

several patches may have been eliminated

the Basin between the three periods (Fig. 3). Regression

Basin's

analysis revealed that the trend of declination throughout

MedPS.

landscape,

which consequently

from the

reduced

the

In mangrove forest, the PSSD and MedPS in 1971/1972

the decades was mainly influenced by the reduction in

31

Saiful

Arif

Abdullah •E

Nobukazu

Nakaaoshi

(a)Dipterocarp

Fig. 3. Total area (ha) for each type of forest relative to the total forested areas in the Langat Basin in the three periods.

1971/1972 and 1981/1982, but the PSSD values were (b)Mangrove

similar (Fig. 4c). This result showed that in 1971/1972, the patch sizes were uniform and large and in 1981/1982 the patches had much variation and were smaller in size. In 1991/1992 the PSSD had decreased

but MedPS

increased. This indicates the reduction in size of larger patches in the previous periods (1981/1982) and small patches were eliminated from the Basin's landscape. Generally, the three types of forests showed different patterns for Total Edge (TE) throughout the decades. The TE for dipterocarp

(c)Peat swup

1981/1982

but

increased between 1971/1972 and

showed

a

remarkable

decrease

in

1991/1992 (Fig. 5a). In contrast, the TE of mangrove forest was almost the same in 1971/1972 and 1981/1982 but increased steadily in 1991/1992 whereas in peat swamp forests TE was declined throughout the temporal scale (Fig. 5b and 5c, respectively).

The mean edge

length of patches of each type of forests was reduced between 1971/1972 and 1981/1982 as shown by Mean Patch Edge (MPE) and it was perceptible for mangrove and peat swamp forests (Fig. 5a-c). Except for mangrove Fig. 2a-c. Area (ha) and Number of Patch (NumP) for each type

forest, this trend was continuous in dipterocarp and peat

of forest in 1971/1972, 1981/1982 and 1991/1992. Bar: Area;

swamp forests after ten years (1991/1992). Figures 6a-c show the complexity of patches for each

Line: NumP

type of forest over the periods. All type of forests had were higher than in 1981/1982 and 1991/1992 (Fig. 4b).

simple shape complexity and remained constant in this

The value of PSSD and MedPS in 1981/1982 and

respect throughout the years, as shown by the Mean

1991/1992 was similar

the

Patch Fractal Dimension (MPFD). However, the Area

presence of uniform and small patches. There was a clear

Weighted Mean Shape Index (AWMSI) indicates that the

difference between the MedPS of peat swamp forest of

larger patches were the more complex and elongated

and generally

reflected

32

Monitoring

pattern

change

of forest

patches

Table 5. Regression matrix between total area (dependent variable) and three types of forest (independent variables).

Dependent

variable:

total forest

area

(a)Dipterocarp (a)Dipterocarp

(b)Mangrove

(b)Mangrove

(c)Peatswamp

(c)Peatswamp

Fig. 5 Total Edge-TE (m) and Mean Patch Edge-MPE (m/patch) for each type of forest in 1971/1972, 1981/1982 and 1991/1992. Bar: TE; Line: MPE

boundary shapes they had. Over the periods, the larger Fig.4 Patch Size Standard Deviation (PSSD) and Median Patch Size (MedPS) for each type of forest in the three periods .

patches of dipterocarp forest shape complexity did not change much (Fig. 6a) but the complexity was gradually

33

Saiful

Arif Abdullah¥Nobukazu

Nakagoshi

(a) Dipterocarp (a)

(b) Mangrove

(b)

(c) Peat swamp

Fig. 7 (a) Total area of each type of primary forest relative to the overall area of primary forest in the three periods and (b) total area of secondary forest in the three periods.

of

primary

dipterocarp

forest

increased

between

Fig. 6 Area Weighted Mean Shape Index (AWMSI) and Mean

1971/1972 and 1981/1982 but by 1991/1992 much of the

Patch Fractal Dimension (MPFD) for each type of forest in the

areas were reduced in size. In contrast to this, the

three periods.

secondary

dipterocarp

forest was shown to have lost

most of its area by 1981/1982, but in 1991/1992 it had increased to a size similar to that of 1971/1972 (Fig. 7b).

reduced for mangrove and peat swamp forests (Fig. 6b

The overall total area differences between the years

and 6c, respectively).

both for primary and secondary dipterocarp were not

Landscape analysis: Group 2 The trend of changes of primary dipterocarp (Gd: good dipterocarp; Pd: poor dipterocarp; dipterocarp; Up: upperhill dipterocarp)

Sd: superior

significant

(Mann-Whitney

U-test, p>0.05).

the total

area of secondary

dipterocarp

However, forests

in

1971/1972 and 1981/1982 was significantly larger than

in 1971/1972,

1981/1982 and 1991/1992 is shown in Fig. 7a. Gd, Pd

the total area of primary dipterocarp

and Sd had similar patterns, the total area increasing

U-test: U=59.0 p