MIDAS OUTCOMES

The general MIDAS includes visualizations for four different outcome. Three of these outcomes are index outcomes corresponding to the three CDF categories (governance, socioeconomic, and ecological). The final outcome, MMA Effectiveness, is a mixed applet outcome that allows the user to compare results of the three index outcomes.


MIDAS Index outcomes

All three MIDAS index outcomes include a time-series component that allows the user to visualize both the present state of the system and a prediction of how the state of the system will change in the near future, based on user observations of present conditions. The present value for each index has been determined through literature review, expert evaluation, and analysis of survey data. This provides an accurate baseline for change assessment. This model allows each CDF value (attribute) to be weighted to reflect its importance relative to the values of other CDFs. A specific subset of CDFs is used to calculate each of the three index outcomes, and weights have been assigned based on existing literature and consultation with experts. As the user changes CDF inputs, the index outcomes dynamically change. This allows the user to visualize how each CDF affects the near future state of the governance, livelihoods, and ecosystem health.

  • Governance Index: The Governance Index is used to evaluate the state of governance.
  • Livelihoods Index: The Livelihoods Index is used to evaluate the state of human wellbeing
  • Ecological Health and Resilience Index: The Ecological Health Index provides a measure of the health and resilience of natural ecosystems found in the coastal regions of the site country

MMA Effectiveness

The MMA effectiveness mixed outcome applet is visualized as a triangle whose three sides correspond to the three previously described index outcomes, scaled from poor to perfect. The near future value for each index outcome is plotted for each index, and adjacent points are connected to form an inner triangle. The size of this triangle will change depending on how close to the extremes (poor or perfect) the user-defined value for each index falls.