15
3.2. Javan Gibbon Habitat Suitability Model
The formulation of javan gibbon habitat suitability model is described even the aim is to test SUITSTAT performance. Additionally, the required data, field
data collection, and the preparation of the data before processed by the system are informed in the following subsection.
3.2.1. Model Formulation
In the geographic scale, the habitat can be analyzed simply based on its major
shaping-factor
, which are physical and biological factors, and also human factors due to their activities which are often causing the rapid changing on the
environment. Those factors almost can be represented into spatial data. By means of spatial and statistical numerical analysis, the pattern of driving factors
of habitat selection can be identified. This theoretical framework is drawn in the Figure 2.
Suitability model is estimated using GIS-based decision rules, i.e.: Simple Additive Weighting
SAW method. It considers habitat factors, such as biotic, abiotic and human factor as decision criteria. Habitat factors are represented by
available spatial data, such as land cover, riverwater body, roads, slopes, elevation-based forest ecosystem. The model outcome decision is represented
by the score of correspond feature which reflects the suitability level the higher score, the higher suitability level.
`
Figure 2. Theoretical Framework
Human Interaction
Biological factor
Wildlife Response
Physical factors
Spatial statistical analysis,
decision rules Wildlife
habitat suitability
Selected Habitat
16 Almost of all variable are related to gibbon behavior and hence its survival.
These factors were selected through rationalizing knowledge specifically on javan gibbon and generally on wildlife. Javan gibbon is a brachiated monkey which
primarily depends on the forest structure Napier and Napier, 1985; Kappeler, 1984a. In Mt Salak, such forest structure that enabling gibbons to perform their
daily activity ranging, feeding, and resting or sleeping is satisfied by primary lowland and submontane forest. Therefore, forest succession stage or maturity
primary and secondary forest and forest elevation based ecosystem are considered as a cue to habitat suitability.
The existing of non-habitat nonforested area such as settlement, paddy field, crops, bushes, and roadtracks gives influence to the health of habitat
which related with the concept of edge effect and fragmentation Morrison et. al., 1992; Primack et al., 1998. The influence to the species habitat correlates with
habitat distance to non-habitat area. These factors are also related with detectability of javan gibbon to the intruders of their homerange or territory, as
observed by Tobing 1999. As a territorial species, every group of javan gibbon moves inside a
relatively fixed area homerange to find resources. The movement is highly relied on the continuance of the canopy. The canopy surface usually follows the
terrain. Even there has been no evidence revealing the difference of ranging distance on the canopy above slopy and plain topography, topographic condition
commonly affects the movement of wildlife and probably javan gibbon. Generally, the effort for accomplishing a route in steeper area is bigger than plain
area. Hence, slope factor is included in the model, which arbitrarily divided into three slope classes, 0 – 15 representing plain topography, 15 – 45
representing plain to steep terrain and more than 45 representing steep terrain.
The existence of rivers or water body is vital for wildlife survival. Seeing that javan gibbon rarely came down from top forest canopy, this factor seems
unimportant. However, this factor was included into the model consider to the possible relationship of this factor to community structures in javan gibbon habitat
as noted by Hadi 2002.
17 The decision constraints are also considered in the model. The constraints
are considered due to the existence of a factor in the land entity that is not livable for gibbon. Non-forested area such as tea plantation, bushes, open land, and
settlement and area on which trespassed by the road are considered as model constraints. Since there is no information on edge-effect to javan gibbon habitat
structure, this factor is approximated from javan gibbon alert behavior. As observed by Tobing 1999, javan gibbon could detect human existence in 20 m
flash distance. Therefore, the area within the distance of 20 m from roads and non-forested land are considered also as model constraints.
The occurrence of gibbon group is meant as proxy indication of suitable habitat. The concerned habitat variable are measured according those gibbon
distribution over 29 distinct groups and analyze with Principal Component Analysis
PCA. Considers that principal component loading value indicates the contribution of a variable to variance explained by correspond principal
component eigenvalues; Hence, the maximum of principal component loading of the interpretable component suggest level of importance of variable in
determining suitable habitat. Subsequently, it is used to calculate weight of each variable weight. Broken Stick Distribution is used to determine how many
components were interpretable
McGarigal et al., 2000
. The process of GIS-Based SAW Method was performed by SUITSTAT
system which adopts Malczewski’s 1999 procedure.
3.2.2. Required Data
Kategori