In Myanmar’s Ayeyarwady Delta, mangroves play a vital role for coastal communities, which depend on the forests as a source for fuel, food and protection from extreme weather events. But over the years, the mangroves have been exposed to overexploitation, land conversion and illegal logging activities that have exacerbated the challenges for the communities in securing a stable income. They also have increased their vulnerability to natural disasters as declines in mangroves results in reduced coastal protection.
To reverse this trend, landscape conservation and restoration require substantial investment, which can often only be justified if the financial returns are clearly known. To address this issue, the Global Green Growth Institute (GGGI), in partnership with the Green Growth Knowledge Partnership (GGKP) and the University of Queensland (UQ), conducted an Economic Appraisal of Ayeyarwady Mangrove Forests, aimed at integrating natural capital into investment decisions by improving the management of the mangrove forests. To estimate the return on investment for the restoration and improved management of mangroves, the 3Returns Framework was developed.
The 3Returns Framework
The 3Returns Framework was designed to be a practical method for decision-makers to perform landscape assessments that reveal which interventions have the greatest potential for sustainability. This is done through an innovative approach that considers landscape interventions as business cases and includes the valuation of monetary and non-monetary benefits or “returns” through the lens of natural capital, social & human capital, and financial capital.
The framework can easily be broken down into four key phases in order to be used by any decision-maker – identification and scoping, valuation, return on investment analysis and result interpretation.
Identification and scoping
The goal of the first phase is to define the scope of the assessment based on the spatial area of interest and the relevant stakeholders, including government officials, the private sector and local communities, within that area. Once this is done, the main land use types and their boundaries will need to be determined, and then the scale that will be used for the landscape assessment can be considered. The scale could take place at the project or landscape level, or within a specific political boundary.
The 3Returns Framework is not meant to be used at the national level, but instead works best at the regional or local level. For example, in Myanmar, the framework examined and identified green growth options to enhance the well-being of the local communities of the densely populated Ayeyarwady Delta, with a total study area of 85,432 hectares of mangrove habitat.
Valuation
The valuation phase can be broken down into two components – baseline valuation and scenario modeling. The minimum requirement for the baseline valuation requires quantifying both monetary and non-monetary benefits, as well as capital status’ outputs from which benefits arise. If available, secondary sources of information can be used; otherwise, primary data (for monetary and non-monetary benefits and capital status outputs) must be collected. At a minimum, quantitative variables related to ecosystem services, jobs, green jobs and capitals should be quantified. Monetary benefits, including economic activities and ecosystem services, as well as operational expenditures, should be quantified and monetized, to the extent possible.
The second part of the valuation phase is scenario modeling. The 3Returns Framework contrasts a business-as-usual scenario against green growth scenarios to understand changes in capitals (natural, social & human, and financial capital) and the benefits derived from them.
The business-as-usual scenario assumes a continuation in operations as observed in the area of interest. Green growth scenarios aim to reflect changes in capitals derived from interventions, or investments, which affect the overall benefits derived from them. For each scenario, capital expenditures, changes in capital status outputs and changes in benefits, which are derived from the changes in capitals, need to be modeled.
In the case of Myanmar, the business-as-usual scenario assumed continued mangrove degradation with limited mangrove restoration projects. The green growth scenarios were based on a range of investments in restoration and improved management approaches with varying intensity and altering management arrangements of government and private-managed mangroves.
Return on investment analysis
The return on investment (ROI) analysis phase allows for the information that has been measured, estimated and modeled in the previous phase to be organized in a way that distinguishes monetary and non-monetary values, while allowing for the analysis of financial indicators that support decision making.
The table below presents the ROI analysis structure that should be used.
Result interpretation
Interpreting the results is the final phase of the 3Returns Framework methodological process. Considering the investment approach in capitals, the interpretation of the ROI is crucial in understanding the efficiency of the different potential scenarios under investigation. When analysing socio-economic systems in a landscape, it is expected that the business-as-usual scenario reflects a positive net present value (NPV), although this is not always true. It is also expected that, depending on the nature of the actions, a potential intervention reflects a positive and greater NPV than the business-as-usual scenario. Based on this, a range of potential interventions can be analysed, with the most favourable ones displaying the greatest NPV. However, higher NPVs can typically be expected to be backed by greater investments, which can represent a risk, as the return on investments from landscapes will be on an extended time horizon.
Additionally, even though the profitability from sustainable practices can be greater than the one from business-as-usual practices as observed in the Myanmar case, the fact that the profitability from this scenario can be positive without investing in natural and social & human capital hinders the motivation to move to a more sustainable model.
Regarding the ROI, the pilot case in Myanmar showed that the return on investment in the business-as-usual scenario was initially higher, reflecting the exploitation of resources without replenishment. Conversely, green growth scenarios initially showed lower ROI due to the allocation of resources into sustainable interventions. Expanding the analysis until 2079, the ROI for green scenarios then provided evidence of greater level of benefits in the long run reflected in growing ROIs. On the other side, ROI for business as usual declined over time, reflecting the decrease in benefits due to limited reinvestment or replenishment of key capitals and continued overexploitation.
Through the combination of analysing financial indicators, non-monetary benefits, and capitals’ status, a decision-maker can effectively reveal which landscape intervention has the greatest potential for sustainability through the consideration of natural, social & human, and financial capital. This was effective in the case of the Ayeyarwady Delta in Myanmar and can be replicated elsewhere in the world to achieve similar results.