Effect of feedback loops on the sustainability and resilience of human-ecosystems

There is a great concern about the current growing and indiscriminate human activity over the environment that supports us. Many researchers and strategists have predicted human and natural disasters based on assumptions linked to economic, social and environmental trends. Most of these events have either not happened, the impact was far less than projected or they may have been delayed several years. Such situations might have not been due to erroneous assumptions or calculations, but rather to the ability of ecosystems to recover and adapt following a stressful situation or a disruptive event, so called resilience. The mechanisms of how resilience works generally imply intrinsic complex feedback loops of the systems; such loops absorb the external impacts and distribute them through the different elements that conform the system. This work analyzes a social feedback loop in the dynamics of a human-ecosystem and its consequences in the search for sustainable governmental targets. The loop is derived from the uncertainties in the demographic parameters and is incorporated into a mass-based compartmental model of a human ecosystem with social inequity. The methodology has been applied to three different types of societies with different development levels, using five different governmental targets. As expected, it is clear that feedback loops affect the behavior of the system. Results show that the same government target provides different results for different societies. Societies with a higher level of development present a better economic-social-environmental performance when an environmental target is used, such as GHG emissions; on the other hand, the society with less development presents a better performance when the used target is related to the economics of the system. In order to achieve a sufficiently resilient and sustainable society, the choice of an accurate governmental target is crucial since the objectives act differently for each type of society. Results also show that decision variables have more variation in the first periods of the analysis being practically stable in the final years. Then, the initial years of the simulation analysis are the most important to stabilize the system. Therefore, in real-world societies, not only the choice of the objective is important, but also the feedback mechanisms. Those mechanisms have to be implemented as quickly as possible, in order to identify or avoid probable future catastrophic scenarios.