Wireless Sensor Networks (WSNs) have emerged as a powerful technology for environmental monitoring in various domains, including forest ecosystems. This paper presents a comprehensive review of the application of WSNs in environmental monitoring specifically focused on forest ecosystems. The unique characteristics and challenges of forest environments necessitate the development of tailored solutions for effective data collection and analysis. The paper discusses the key components of WSNs, including sensor nodes, communication protocols, and data processing techniques, and highlights their relevance in the context of forest ecosystem monitoring. Various environmental parameters, such as temperature, humidity, light intensity, air quality, and soil moisture, are monitored using WSNs to provide valuable insights into the health and dynamics of forest ecosystems. The paper also discusses the deployment strategies for WSNs in forests, considering factors such as node placement, energy management, and network topology. Furthermore, it explores the existing research trends and highlights the challenges associated with WSNs in forest ecosystems, such as limited network lifetime, data accuracy, and scalability. To overcome these challenges, recent advancements and potential future directions in the field are presented, including energy-efficient protocols, data fusion techniques, and machine learning approaches for improved data analysis. The research paper contributes to the existing body of knowledge by providing a comprehensive overview of WSNs for environmental monitoring in forest ecosystems, outlining their applications, challenges, and future prospects. The findings presented in this paper will be beneficial for researchers, practitioners, and policymakers working in the field of environmental monitoring and conservation in forest ecosystems