The research highlights significant financial and conservation benefits that result when using computer simulation models to perform scientific due diligence prior to trading habitat. The computer simulation model was able to incorporate interactions between land use change and how a species survives to provide a more complete understand how species are affected by markets.
The paper’s author Dr. Bruggeman highlights, “As we invest in environmental sustainability it is important to incorporate scientific due diligence into decisions. This is particularly true when investing in regulatory-based markets in which the goal is to minimize risks of extinction for threatened and endangered species due to real estate development”.
Dr. Bruggeman developed a set of trading metrics along with the simulation model to account for negative effects of these markets that are often ignored, providing a tool to determine the probability of achieving no net loss of biodiversity at a landscape scale.
“Looking at the effects across a landscape is critical, as the species we are working to protect often can not survive on isolated islands of habitat. Further, when decisions are made regarding whether to remove a species from protections under the Endangered Species Act, those decisions are made at the landscape-scale. So markets that ignore landscape impacts could actually be slowing our ability to delist and remove regulatory restrictions. If we want to protect what millions of years of evolution have provided, we must apply a landscape perspective to these markets. Excluding critical uncertainties about how species survive in complex landscapes does not make sense from either an economic or ecological perspective”, Dr. Bruggeman added.
By using a landscape simulation model, the research included uncertainty regarding how species disperse across a landscape into trading decisions. Given the cost of trading habitat, the research indicated that conservation bankers could save as much as $987,086 by learning the true dispersal behaviors. Thus, the cost-effectiveness of the market would increase while enhancing the persistence of the species – a win-win. However, the cost savings varied by the type of landscape change that occurred. When just a few parcels changed the simulation model was able to identify the most cost-effective trade in spite of the uncertainty regarding dispersal. In the U.S., the absence of scientific certainty can not be used to prevent a habitat trade under the Endangered Species Act. Therefore, the research highlights the financial benefits to the banker of reducing uncertainty, and a method for determining when uncertainty matters.The work is timely given President Obama’s recent call for revised Federal guidance to stress the importance of landscape-scale mitigation markets and include innovative solutions from the private sector. Dr. Bruggeman is optimistic as the techniques have been applied to evaluate the development of a few of markets on the ground already.