Conservation strategies: Emerging trends and ongoing challenges in species ecological niche modeling
Abstract
Ecological Niche Modeling (ENM) has emerged as a powerful tool for understanding species distributions and informing conservation strategies. The ability to predict where species can live based on environmental conditions is central to developing effective conservation plans, especially in the face of climate change and habitat destruction. This article reviews the emerging trends in species ecological niche modeling, highlighting the latest advancements, including machine learning techniques, incorporation of spatial and temporal dynamics and the integration of genetic data. Additionally, it addresses the ongoing challenges of ENM, such as model uncertainty, scale mismatch and the complexity of ecological interactions. The article concludes by discussing future directions for improving ENM methodologies and their application in real-world conservation efforts.