Consideraciones adicionales para el cálculo del VNR

To the author’s knowledge, the application of MAS/AB modeling to explore the possible impact of land-use policies, i.e., PES and ES trade-offs, is novel. However, it is also interesting to compare this model with models other than MAS/AB models that also quantify ES trade-offs. For example, the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) as a spatially explicit modeling tool (Tallis et al. 2011) predicts changes in ecosystem services, biodiversity conservation, and commodity production levels (Nelson et al. 2009). From the model application in the Willamette Basin, Oregon, little evidence was found of trade-offs under scenarios where scores for ES (i.e., carbon sequestration, storm peak mitigation, water quality, and soil conservation) and biodiversity were high. In contrast, in scenarios that involved more development and had higher commodity production values but lower levels of ES and biodiversity, the high trade-offs could be alleviated through payments for carbon sequestration.

Though a similar trend/pattern was also observed in the LB-LUDAS application, I wasn’t able to run the INVEST model. Thus, it is not possible to comprehensively compare the two models.

140 7.5 Conclusions

The improved version of LB-LUDAS model was applied for understanding the SESs of a rubber agroforest landscape in Jambi province. Three scenarios namely, PES (for conservation pathway), SUB (development pathway) and baseline (current trend) scenarios were simulated. Findings show that under the PES scenario, LUCC was very minimal (mostly due to natural transition processes). On the other hand, LUCC under the SUB scenario was very evident, particularly in the rice paddies and rubber agroforests.

Regarding socio-economic and environmental impacts, under the PES scenario household livelihoods would be better off, and ecosystem services (i.e., carbon emission reduction) and biodiversity would be enhanced, suggesting synergies among them. While under the SUB scenario, synergies are also evident between income and ES when compared to baseline scenario, improvements in terms of wealth inequality and livelihood welfare could not be achieved.

Furthermore, the third hypothesis is found to be acceptable, i.e., dramatic and

unexplained oscillations (specifically in crop yields) were results of a misspecification in modeling the agent's behavior when relevant confounders were not incorporated in the agent’s model (section 6.1.3). Incorporating the decision processes as the

confounders (i.e., PES adoption and with financial investment provision) not only reduced the oscillations but also provided relevant factors that could explain the outcome. Moreover, new emergent behavior was also observed (section 7.4.1).

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8 CONCLUSIONS AND RECOMMENDATIONS

The aim of this study is to contribute to the research on the understanding and management of the dynamics of the relationships between humans and ecosystems that consider various processes and feedbacks of socio-ecological systems. It also assessed the potential spatial and temporal impacts of payments for ecosystem services schemes (PES) as a widely recognized management or policy instrument for land use. Four key aspects of these relationships are provided.

First, the gap between agricultural production and agro-biodiversity protection can be bridged. The rubber agroforest is an example of a man-made ecosystem, which is considered a multi-functional landscape system that could serve agricultural production and agro-biodiversity conservation. However, it requires a management regime or policy interventions to survive in a continually changing social environment.

Second, PES schemes (i.e., eco-certification and 70% protection zoning for reduced emission from deforestation and degradation (REDD) strategy) as land-use policy interventions offer synergies among ES (i.e., carbon emission reduction), biodiversity and household livelihoods. Management schemes such as these reduced the trade-offs by enhancing ES as a result of the interactions between household agents’ livelihood dynamics and their land-use decisions.

Third, the use of MAS/AB models is a highly valuable framework to tackle the complexity of social-ecological systems (SESs). However, essential patterns and processes of the systems should be incorporated to provide sound outputs while reflecting the real-world systems.

Fourth, the LB-LUDAS model (with process-based decision-making sub- models) as an integrated and multi-agent system (MAS) model was able to represent the dynamics and interactions as well as the processes between the human and landscape systems of a rubber agroforest landscape. It is a tool that quantifies and estimates possible impacts of land-use change policies, e.g., species loss, carbon emissions, opportunity costs, etc. Also, it has the basic functionalities of a negotiation-support system (NSS) tool to support the design of the land-use policies, as it can predict landscape level through the likely response of agents in externally set rules and incentives.

142 8.1 Where from here?

In the following, the background of the above conclusions is summarized. Chapter 1 describes the fundamental concepts of SESs and inherent challenges of understanding the coupled systems. In Chapter 2, the details of one of the frameworks for studying the SESs of a rubber-agroforest-dominated landscape are presented. The multi-agent system model, i.e., LB-LUDAS (Lubuk Beringin – Land Use DynAmic Simulator) model as the framework of this study, is described using the standard ODD (Overview, Design and Details) protocol.

Chapter 3 characterizes the human system of the rubber agroforest landscape in Jambi province and addresses its heterogeneity. It also identifies the factors affecting the decision making of the human agents, including the decision process under specific conditions. Having set up the human system, Chapter 4 explores and describes the land- use policy interventions, i.e., PES schemes such as REDD and eco-certification or eco- labeling. The factors affecting the participation or adoption in PES schemes of the human agents are identified and a sub-model for decision making developed.

Chapter 5 has a strong focus on building ecological sub-models for the bio- physical system of the model. In this way, the criticism about the weak incorporation of ecological processes in most MAS/AB models is addressed. Data generated from empirical studies were calibrated and parameterized, and incorporated the important patterns and processes of the biophysical system reflecting the real rubber-agroforestry landscape as far as possible, i.e., species richness, forest and agronomic yields, natural succession and carbon sequestration.

Chapter 6 presents the operationalization of the LB-LUDAS model. During this process, challenges were encountered regarding the calibration and validation of the empirically based MAS/AB model as manifested in the model outputs. Two assumptions were identified as explanations of the observed phenomenon: 1) the recursive use of a non-contracting function that mimics the natural oscillation, and 2) mis-specification of agents’ behavior when relevant confounders are not incorporated in the agent’s modeling. To resolve the latter hypothesis, process-based decision making sub-models were proposed and integrated in the LB-LUDAS’ decision-making mechanism.

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Chapter 7 is the final empirically based chapter where the LB-LUDAS model with improved decision-making mechanisms was applied. Three scenarios were simulated: 1) PES (conservation pathway), 2) SUB (economic development pathway), and 3) baseline or current trend. As an overall result of the three scenarios, PES was found to be a highly desirable scenario, as it could not only reduce the trade-offs between ES and biodiversity but also bridge the gap between conservation of rubber- agroforest and the livelihoods of human agents.