During the last thirty or forty years there has been a paradigm shift due to the postmodern scientific revolution, mainly with the emergence of so called complex sciences, which change the object of study from the parts to the whole [30]. This has meant no longer centering the study in linear and determinant processes, but in non-linear processes organized in hierarchical interrelated networks, in order to identify the main interactions among variables and the processes involved in the study’s objective; this way the processes and tendencies that emerge from these interactions, turn the concepts of complexity, network and hierarchy into fundamental issues [57].
This means changing the fragmentation for integration and complementation of the parts. The intention is to trespass the limits of the traditional scientific knowledge which proposes the objectivity and certainty of scientific truths, recognizing the need for an integral and contextual vision, as well as, and the need to deal with uncertainties [13, 30, 63, 64]. The key of the epistemological property of this paradigm shift is the development of an inter – and trans-disciplinary approach that requires variation in the current scientific reasoning. Roling [13] proposes the evolution of the science paradigm, starting with the simple dynamic structures and mechanical models, passing by the self-regulated models and homeostatic feedback models, towards the complex adapting auto-organizing systems, as well as, the autopoietic cognitive models (Figure 3).
Fig. 3. New scientific paradigm evolution [adapted from 13]. |
The main difference between positivism and constructivism lies in how you consider epistemologically, the relationship between the observer and the object and phenomena observed. Positivism considers the independent phenomena of the particular observer. Constructivism, on the other hand, incorporates an interaction between the observer and the phenomenon observed, and recognizes that our perception of the world is only an individual and partial one [63]. From the perspective of constructivism, there should be a permanent dialog between the various observers, in order to piece together a group vision of reality, turning this into a collective cognition process. This effective dialogue, resulting from the collective construction is the foundation for the study of the phenomenon from the constructivism perspective.
In the XVII century, the French mathematician Rene Descartes formalized the reductionism perception. According to him, it is necessary to dissect and analyze separately and make precise measurements of the complex phenomena to fully understand it. This approach is synthetized in Discours de la methode (1637). As a consequence, it has created a utilitarian criteria of the truth and a reduction of the phenomenon studied to an instrumental notion [30]. During the same century, the English physicist, Isaac Newton, complemented this approach with mechanical vision of the universe. In this approach the wish to set rules and laws, and even some regularities could be sensed [65].
The holistic approach is based on the system theory, and thus, on the approach which established that the universe is an interrelated system, originating in the aristotelic consideration that the whole is greater than the sum of its parts. All the data is more than the sum of the fragments of information, having to know it all to understand the collective behavior of the parts [30], namely, its combinations, and functional interactions in the construction of the systemic totality. The holistic approach considers that the problems must be tackled from the totalities and considering the contexts, as well as from the qualitative approach which gives meaning and sense to the quantitative.
The first quadrant of Figure 3, shows the reductionist – positivist approach, where each phenomena is perceived and treated independently from every discipline; the second quadrant is still based on positivism, but has evolved from a reductionist to a holistic perspective. There is a partial integration of the positivist – reductionist disciplines, but not enough to develop an integral and operational approach toward transdisciplinary and multidimensional problems.
The third quadrant presents an holistic and constructivist approach. Here the Adaptative Complex System (ACS) is located [sensu 64], the cognitive theory [39, 40, 8], the social knowledge based on and intentional and adaptive collective cognition in the design and management of our own destiny [1, 2, 13].
One of the outstanding values of the systemic approach, which is based on second order cybernetics, is that it may overcame epistemological barriers between science and humanity, as well as, between the techno-economical-political areas, where the decision process regarding the management of territories and natural resources take place [13, 30].
The homeostatic systems are related to the model equilibrium paradigm [35, 63], that is to say, they are connected to nature and to the perception of ecosystem as a balanced system. A central issue of this paradigm is the system’s tendency to reach a unique state of stability. In the evolving complex system study emerges a non-equilibrium paradigm [66]. Key aspects of the non-equilibrium paradigm are: the system can reach numerous constant states and keep the organizational pattern; the system has an open relation with its surroundings; it is capable of focusing on the continuous process co-evolutionary coupling [66].
The Adaptive Complex System (ACS) is a concept and model that correspondence a turning point for the study systems of traditional sciences. The main feature of ACS, according to Gell-Mann [64], could be its use for landscape study. Each landscape is an iterative information processing system interacting with its environment; it continuously processes new information from its surrounding environment, generating new adaptive tendencies, coupling and stability. Since, the historical evolving process doesn’t couple under the new circumstances and information, it can’t adapt to the system not connect with its surrounding environment, and thus, collapses.
In systems far from equilibrium, such as the ACS’s, order and disorder (chaos) are continuously interacting. In the chaotic stage, these systems tend to dissipate energy and generate entropy, creating conditions with new, continuous and iterative, order patterns, and occasionally developing a new organizational pattern and type of system [8, 13, 30]. This perspective is necessary to understand the adaptive evolution of cultural landscapes [13, 30, 67, 68].
The goal of the ACS’s is to adapt to variable and changing environments, through different schemes stored in the historic system memory. The self-oriented capacity to adjust is explained by the ACS model. Highlighting human behavior as the main determining factor in the cultural landscapes dynamic and evolution.