
People use their local ecosystem and there are often signals about how this use affects ecosystem health. Capturing, interpreting, and responding to signals that indicate changes in ecosystems is key for their sustainable management. These signal-response chains are called “feedbacks”. Breaks in signal-response chains, “missing feedbacks”, will allow ecosystem health to degrade until a point when abrupt ecological surprises may occur.
In our study, we demonstrate how we can uncover missing feedbacks using the red loop-green loop (RL-GL) concept and how we may restore the feedbacks. The RL-GL concept classifies how people depend on their local ecosystems along a spectrum of two fundamentally different dynamics. One end of the spectrum is with weak local ecosystem ties and strong ties with external systems (red loop), the other with strong local ecosystem ties and weak ties with external systems (green loop). Both dynamics are theoretically sustainable – but when either end of the RL-GL spectrum follows unsustainable dynamics, for instance through over-consumption of resources, they are classified as red or green traps.
We classified the dynamics between Jamaican people and their coral reefs for eight different periods through Jamaican history from first human settlement (roughly the year 600) until now. The dynamics between Jamaican people and reefs have moved between all four RL-GL states: green loop, green trap, red loop, and red trap. Through this, we were able to pinpoint where feedbacks between Jamaican people and reefs were missing and which aspects were responsible for this.
One of the main aspects that masked the connection between Jamaican people and reefs appeared to be seafood exports. We therefore proposed that the Jamaican system could attempt to gradually move away from seafood exports and get Jamaica back to more sustainable green-loop dynamics between the people and reefs.
Our study is the first to apply the RL-GL concept to a coral reef system and we advocate for its practicality in uncovering missing feedbacks and in gaining an understanding of past, present, and future sustainability that can be of use in other systems.