I’ve been studying Environmental sciences for almost a decade now and other than in EIA, this is the first time I tackle the notion of Environmental Decision Making. In researching past issues regarding environmental management, the challenge has always been in the decision-making process. How do you satisfy everyone’s wishes? Because the science, economics, and social values often conclude in conflicting ideologies, consensus decision-making is usually best applied. While theoretically adhering to the highest number of stakeholders, this type of decision-making is not the best.
The problem with environmental management today is that data tells us exactly what is best for the economy, and values dictate what is better for society. Uncertainties often exist in the environmental aspects of decision-making. While certain stakeholders do fight for the environment, trade-offs are often made that disadvantage resource and biodiversity protection. Add to that the fact that the economy is what finds environmental science, and the earth is never the victor.
The notion of adaptive management is one of the most important themes of SDM. Through my studies, I’ve often pondered over the clash of economics and environment. When learning about adaptive management, I quickly understood that environmental protection had to be done at an ecosystem level, and because this is a new and evolving science, it needed to be often rewritten, and treated on a case-by-case basis.
My interests in these readings lie in the ‘informed, defensible, and transparent’ nature of SDM. As an environmental scientist, it’s emphasis on uncertainty is the driver of what makes this decision making technique best, in my opinion. Just like in adaptive management, it’s important to have a prescriptive approach, and utilise different alternatives.
Environments are fragile, and the notion of tradeoffs is dangerous. The problem with environmental issues is that they are not black and white, tangible, and often enough not even measurable. This is where SDM will make a difference.