Predictive Model for Gross Community Production Rate of Coral Reefs using Ensemble Learning Methodologies

TL;DR

This paper proposes an ensemble machine learning model to analyze key physical and chemical parameters affecting coral reef health, aiming to predict and improve the gross community production rate for better ecosystem sustainability.

Contribution

It introduces a novel ensemble learning approach to model coral reef productivity based on critical environmental parameters, enhancing predictive accuracy over existing methods.

Findings

Identified key parameters influencing coral reef health.

Developed an ensemble model for predicting community production rate.

Potential to inform conservation strategies.

Abstract

Coral reefs play a vital role in maintaining the ecological balance of the marine ecosystem. Various marine organisms depend on coral reefs for their existence and their natural processes. Coral reefs provide the necessary habitat for reproduction and growth for various exotic species of the marine ecosystem. In this article, we discuss the most important parameters which influence the lifecycle of coral and coral reefs such as ocean acidification, deoxygenation and other physical parameters such as flow rate and surface area. Ocean acidification depends on the amount of dissolved Carbon dioxide (CO2). This is due to the release of H+ ions upon the reaction of the dissolved CO2 gases with the calcium carbonate compounds in the ocean. Deoxygenation is another problem that leads to hypoxia which is characterized by a lesser amount of dissolved oxygen in water than the required amount for the existence of marine organisms. In this article, we highlight the importance of physical parameters such as flow rate which influence gas exchange, heat dissipation, bleaching sensitivity, nutrient supply, feeding, waste and sediment removal, growth and reproduction. In this paper, we also bring out these important parameters and propose an ensemble machine learning-based model for analyzing these parameters and provide better rates that can help us to understand and suitably improve the ocean composition which in turn can eminently improve the sustainability of the marine ecosystem, mainly the coral reefs