9 Conclusion
From our empirical study we have found that the real world is a complex system
concerning landscape management. The key for understanding the changes in land
management is the knowledge of farmers’ decisions. With these decisions farmers
decide not only for their economic perspective but also determine the ecological
performance of the resulting land management system. Farmers are influenced by
several drivers and follow different goals that are economic, cultural, religious, or
ecological or region-specific based. Farmers have many options for action of which
some are already implementing and about many other options the farmers are
currently unaware. Science has to deal with both options/activities—those that are
already established in the landscape and those are in the process of the development
by scientists to become visible for the real world. To understand the effects of
alternatives options they must be evaluated from a socioeconomic as well as ecological viewpoint. Until now much scientific work is done on investigating parts of
this complex system, but few models are available to integrate all of the components of this complex system. Our work is concentrating on understanding this
complexity for sustainable Himalayan landscape management and delivering a
modeling system that integrates all relevant components. After literature survey we
decided for linear programming (LP) approach to integrate all the aspects of
multifunctional landscape management. Therefore, our research approach has
illustrated in detail the theory and development of the theoretical model and consequently the conversion of theoretical model into a conceptual model. The analysis
and the procedure up to the development of the conceptual model was based on
detailed field-scale data collected from the study region in the Himalayas of India
over a period of several years. This noteworthy as excluding this approach in
designing and developing the theory and concepts has been identified a main reason
to be unsuccessful of the models. Yet, to be useful to understand the real-world
complexities, we followed the integrated interdisciplinary approach. The conceptual
model system MODAM which we developed for the Himalayas is more a philosophy rather than a pure software solution. In complex landscape research, as in
the landscape of the Himalayan region, it might be difficult to make an integrated
approach from the segregated datasets. Therefore, the outlook of MODAM has
enough potential to make multidisciplinary research into integrated interdisciplinary
nature. Figure 9 shows the structure of model system MODAM for the Himalayan
landscape which is intended to handle the theoretical model (Fig. 7) and which we
developed for the landscape fits extremely well in view of the landscape complexities (please see Table 2). Our research experience in this endeavor indicates
that the modeling is not synonymous with the formulation of a software solution.
This is because that the modeling starts much earlier when thinking process about
the model starts and comprehends a complex process of preceding research coordination. Hence, from a scientific point of view, the challenge is to link the natural
as well as social and economic disciplines together to make the research integrated
and interdisciplinary. Developing a software solution is the end of a long modeling
622
S. Nautiyal et al.
From our empirical study we have found that the real world is a complex system
concerning landscape management. The key for understanding the changes in land
management is the knowledge of farmers’ decisions. With these decisions farmers
decide not only for their economic perspective but also determine the ecological
performance of the resulting land management system. Farmers are influenced by
several drivers and follow different goals that are economic, cultural, religious, or
ecological or region-specific based. Farmers have many options for action of which
some are already implementing and about many other options the farmers are
currently unaware. Science has to deal with both options/activities—those that are
already established in the landscape and those are in the process of the development
by scientists to become visible for the real world. To understand the effects of
alternatives options they must be evaluated from a socioeconomic as well as ecological viewpoint. Until now much scientific work is done on investigating parts of
this complex system, but few models are available to integrate all of the components of this complex system. Our work is concentrating on understanding this
complexity for sustainable Himalayan landscape management and delivering a
modeling system that integrates all relevant components. After literature survey we
decided for linear programming (LP) approach to integrate all the aspects of
multifunctional landscape management. Therefore, our research approach has
illustrated in detail the theory and development of the theoretical model and consequently the conversion of theoretical model into a conceptual model. The analysis
and the procedure up to the development of the conceptual model was based on
detailed field-scale data collected from the study region in the Himalayas of India
over a period of several years. This noteworthy as excluding this approach in
designing and developing the theory and concepts has been identified a main reason
to be unsuccessful of the models. Yet, to be useful to understand the real-world
complexities, we followed the integrated interdisciplinary approach. The conceptual
model system MODAM which we developed for the Himalayas is more a philosophy rather than a pure software solution. In complex landscape research, as in
the landscape of the Himalayan region, it might be difficult to make an integrated
approach from the segregated datasets. Therefore, the outlook of MODAM has
enough potential to make multidisciplinary research into integrated interdisciplinary
nature. Figure 9 shows the structure of model system MODAM for the Himalayan
landscape which is intended to handle the theoretical model (Fig. 7) and which we
developed for the landscape fits extremely well in view of the landscape complexities (please see Table 2). Our research experience in this endeavor indicates
that the modeling is not synonymous with the formulation of a software solution.
This is because that the modeling starts much earlier when thinking process about
the model starts and comprehends a complex process of preceding research coordination. Hence, from a scientific point of view, the challenge is to link the natural
as well as social and economic disciplines together to make the research integrated
and interdisciplinary. Developing a software solution is the end of a long modeling
622
S. Nautiyal et al.