Work

Recent trends and future directions in artificial intelligence (AI) applications for coastal ecosystems Conservation: Insights from a bibliometric analysis

Year: 2025

Type: article

Abstract: Coastal ecosystems, such as mangroves, seagrass beds, and coral reefs, provide essential ecological, economic, and social services. However, their capacity to deliver these services is diminishing due to increasing ecosystem disturbances, resource exploitation, and the impacts of climate change. In response, the integration of artificial intelligence (AI) tools into conservation efforts has led to a surge in scholarly publications, highlighting the need for a bibliometric analysis to systematically examine emerging trends and identify future directions in this rapidly evolving and interdisciplinary field. Bibliometric data were sourced from the Scopus database, covering a ten-year period from 2015 to June 2025. The analysis was conducted using Bibliometrix and VOSviewer, complemented by OpenRefine, Microsoft Excel, RStudio, and OriginPro for data cleaning and visualization. Results revealed an annual publication growth rate of 6.61% in the field. The institutions from China and the United States are at the forefront of research outputs and international collaborations, indicating their strong investment and leadership in the application of AI to coastal ecosystem conservation. Keyword co-occurrence analysis identified thematic clusters around AI tools such as remote sensing, machine learning, and deep learning, highlighting a transition from traditional environmental sensing toward real-time monitoring and predictive modeling. There is also a growing presence of multiple countries based on the keyword co-occurrence networks. It indicates increasing global participation, collaboration, and interest in applying AI to ecosystem conservation. Collectively, these findings point to a maturing research landscape with a promising trajectory toward the development of globally adaptive conservation strategies driven by artificial intelligence.

Source: Watershed Ecology and the Environment

DOI: 10.1016/j.wsee.2025.11.004

Author: Sylvester T. Cortes

Institution: Cebu Technological University

Language: English

Topic: Coastal wetland ecosystem dynamics

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDGs: Climate action, Life on land

Open Access status: gold

Estimated APC paid: $700