Harnessing AI for Predictive Ecosystem Management: Transforming Conservation Through Data-Driven Insights

Abstract

In this chapter, we explore the transformative power of artificial intelligence (AI) in preserving global biodiversity. With ecosystems facing unprecedented pressures from habitat destruction, unsustainable land use, and climate change, Machine Learning has emerged as an admirably suitable approach for data-driven conservation efforts. Using AI-powered machine learning, deep learning, and computer vision allows for monitoring huge areas remotely as well as analyzing complex data sets which help in forecasting future trends. This predictive ability allows our efforts to transition from reactive conservation to a proactive one. Species distribution modeling, wildlife population monitoring, anti-poaching efforts, disease prediction, and human-wildlife conflict mitigation are some of the many applications. Despite the opportunity that AI presents, we still have a long way to go in addressing ethical concerns related to data privacy and bias. By utilizing AI, we will create coordinated plans to save animals and habitats from destruction, which would otherwise lead us into a future unsupportive of life for both humans and non-humans.