For this study a thorough survey approach was adopted to prepare a database on
private sector forest plantations. In Peninsular Malaysia, such a study is
possible within a few months because the nation is small compared to countries
such as India or China. The total land area in Peninsular Malaysia is 13 million
ha. About six million ha constitute natural forests with protection and production
functions. Forest plantations are located in the non-forest areas. As Peninsular
Malaysia is divided into 11 states, a state-wise survey approach therefore
seemed logical. Using this approach, the survey was carried out via visits
to each state where data were recorded in the field. This ensured that the
extent of forest plantations could be documented accurately.
Initially, the relevant data to be collected were identified. A uniform data
collection sheet was developed (Appendix 1) that detailed data on location,
species planted, spatial extent, planting system employed and ownership, cultural
practices, reason for planting timber species and plantation terrain. Each
state was combed systematically and all the existing forest plantations, established
by small- and large-scale investors, were documented. Most of the information
was obtained through interviews with representatives of relevant companies,
farmers and state authorities.
To facilitate and accelerate data collection, individual state forest departments
and agricultural departments and the various agencies involved were informed
in writing of the study objectives and asked to assist the data collecting
team during the field work. Before visiting the field, several meetings were
held with these departments and other agencies such as the Federal Land Development
Authority (FELDA) and the Rubber Industry Smallholders Development Authority
(RISDA) to refine the survey design. Where possible, the departments were
asked to appoint one officer to assist the team. Time permitting, the field
officers were also asked to start data collection before the team arrived.
Similar requests were also sent to FELDA and RISDA who have land banks with
the potential for forest plantation development.
Following this notification, the data collection team – consisting of seven members – was briefed on the survey procedures. A survey plan was prepared and the team was divided into three groups, each comprising one assistant research officer and one research assistant. Several states were allotted to each of the groups. To ensure the team had understood the nature of the task, the survey was tested in the state of Selangor. After adjusting the survey forms (see Appendix 1), the three groups visited the respective states, and the survey was completed in four months (Table 1). Teams had approximately one month for each state. In each state they met with the state forestry officer assigned to the study. The team visited various state agencies and district offices to locate areas assigned or planted with forest plantations before interviewing plantation owners during the field visits.
Table 1. Survey schedule
State |
Survey schedule (month) |
|||||||||||
Team 1 |
Team 2 |
Team 3 |
||||||||||
1 |
2 |
3 |
4 |
1 |
2 |
3 |
4 |
1 |
2 |
3 |
4 |
|
Selangor |
x |
x |
x |
|||||||||
Perlis |
x |
x |
||||||||||
Kedah |
x |
x |
||||||||||
Penang |
x |
x |
||||||||||
N. Sembilan |
x |
x |
||||||||||
Malacca |
x |
x |
||||||||||
Perak |
x |
|||||||||||
Pahang |
x |
|||||||||||
Kelantan |
x |
|||||||||||
Trengganu |
x |
|||||||||||
Johore |
x |
The data were analysed at the Forest Research Institute Malaysia (FRIM). Some
background information on current plantation status was first collated from
the records available at FRIM and Forest Department, Peninsular Malaysia.
This included:
Next, the data collected during the survey were keyed into Excel spreadsheets
for each state. Summaries were then generated for the whole of Peninsular
Malaysia. All information presented in this report was derived from the data
analysis.
Costs included the wages of the field officers and the assistant research officers
(AROs) for a period of four months. The monthly wages of each accompanying
state officer were also taken into account for a period of one month per officer.
Lodging and food expenses for each ARO amounted to RM100 per day. For the
assistants the rate was RM60 per day. Vehicle rental came to RM150 per day,
which included fuel costs and the daily wage of the driver.
As this was the first survey of its kind the costs for each hectare of plantation
surveyed were quite high. However, if the total non-forest area is considered,
the costs are fairly low (Table 2).
Note: Exchange rate US$1 = RM3.8
If the land area of a particular country is small, it may be possible to carry
out the initial ground survey to develop the first database with few errors
and relatively quickly. Once the database is established, data sheets of the
existing plantations can be distributed to the respective state forestry office.
Providing additional data sheets allows for regular updates in each state.
In this way, the state forestry offices can then be charged to furnish updated
information on private plantations at the end of each year to the central
agency, which is responsible for updating the main database.
In large countries such as India and China and when funds are limited, it may
not be feasible for a single agency to conduct a ground survey as this would
be time consuming and costly. In such cases, a standard format for data collection
has to be developed. This facilitates the consolidation of data collected
by different agencies in an effective and accurate way. In each state, province
or district an officer – probably from the forestry department – should be
appointed to carry out the survey and to manage the collected data. The data
can then be transmitted to a single agency that can then build up a database.
Following the survey carried out in Peninsular Malaysia during this study, it
is proposed that the state forestry departments take the responsibility to
update the database on an annual basis. Related activities will become part
of their daily duties, which would reduce costs substantially.