Models of natural systems are rarely precise and reliable. Their usefulness comes from their ability to pursue assumptions made by humans.
It is not always necessary to “prove” that projected outcomes will actually take place, but they do need to be plausible, possible, credible and relevant
Fahey Randall 1998. To be possible and credible they must pass the logic test. The logic test was similar to the first criterion of the evaluation, which the
model passed. The model has been found to be useful, particularly for developing scenarios and observing the likely impacts of each scenario on forest
sustainability and stakeholders’ well-being.
4.6. Collaboration Scenarios and Testing the Second Hypothesis
Comparing the current forest management system and scenarios of collaborative forest management tested the research’s second hypothesis, which
is: to get better outcomes of collaborative forest management, all relevant stakeholders must be performed. The testing required two steps: firstly, a
scenario of collaborative management was developed using the model; secondly, it was necessary to compare the simulation outputs of current and developed
forest management scenarios.
4.6.1. Collaborative Forest Management
Collaborative forest management CFM is defined simply, in this case, as a shared production of timber. Shared production can only occur if there is an
agreement between Inhutani II and local communities that is approved by the relevant levels of government. Collaborative management is considered
successful if the costs of collaboration are lower than the benefits gained from it. A collaboration is a social phenomenon that might occur because the agents, in
this case, the stakeholders, want to achieve their goals. In order to achieve their
goals, they might work alone or work together with other agents. Figure 4.30 shows agents under relevant social institutions, communicating with each other to
satisfy their goals. A bounded rational economic behavior was observed in the field as the
prime characteristic behind agents collaboration. This means agents are likely to collaborate if it is economically profitable and supported by, or at least not
prohibited by, their belief systems. In the simulation, each agent does two primary things: firstly, agents execute what they usually do or plan to do, in order
to achieve their goal; secondly, they communicate with other agents to seek a way to improve their opportunities in relation to their goal. . Figure 4.31 illustrates
how the simulation developed scenarios of collaborative management.
Figure 4.30. A social phenomenon of collaboration Table 4.40 lists criteria for selecting an area of collaboration according to the
perspectives of each agent. Agents implement these criteria in selecting areas of collaboration.
goals goals
goals
Social institution Collaboration in the management of the
forest
Communication Govts.
Inh2 Comns.
Figure 4.31. Development of collaboration scenarios
Table 4.40. Criteria for collaborative timber harvesting from the perspective of two parties
Communities’ criteria Inhutani II’s criteria
Close to the river network Far from the built road network
Commercially feasible Communities pay Inhutani II
Close to their villages Traditional, not mechanized harvesting
- Medium-sized trees only
Source: Field interview
Below illustrates the logic of representing characteristics of collaboration between agents
Inhutani II Local
communities Govts
20 years simulation
Forest cover Standing stock
Communities’ incomes Inhutani II net revenue
Govts’ incomes Indicators observed
Scenario of collaboration
Giving local communities rights to
log in certain areas and in a traditional
way Fee to Inhutani II
Scenarios’ design loop
The following describes the logic of Inhutani II’s evaluation of the communities proposal:
Function: Creating social phenomena of collaborative forest management.
Algorithm: According to their plan Inhutani II is encouraged, with government
enforcement, to collaborate with the communities. Inhutani II continues seeking for collaboration with communities
inh2 send: lorehComn. inh2 send: seturanComn.
inh2 send: langapComn. The communities seek collaborations to improve their well being. They
respond to Inhutani II’s desire, by sending proposals for collaboration communities sendProposal:inh2.
Inhutani II evaluate and replay the proposal sent by communities inh2 replay:CommProposal of:fmu.
The proposal approval or disapproval becomes an event and is analyzed by beliefRevision:eventQ, a part of BDI belief-Desire-Intention function
of communities beliefRevision:eventQ
Collaborative logging is a possible output of BDI function If there are agreements between Inhutani II and the communities then
the agreement will be internalized into Inhutani II activities
Function: Communities proposal evaluation Input: communities’ proposal
Output: dis approval messages of Inhutani II replay:CommProposal of:fmu.
areaComanaged := evaluateComnProposal:m of:fmu. if areaComanaged 0 then sendMessage:approval
to:communities. else sendMessage:disapproval to:communities.
evaluateComnProposal:m of:fmu. selectComanageArea:fmu.
selectComanageArea:fmu. areaOffered
← Area meet Inhutani II’s criteria for collaboration
The following describes the logic of collaborative logging and its effects:
4.6.2. Simulation Outputs of Collaborative Forest Management
