Advancements of ”CAPTAIN” in Plants Conservation Compared to Traditional Techniques

Authors

  • Chuyu Deng School of Horticulture, South China Agricultural University
  • Pui Lam Lau School of Life Sciences, Chongqing University
  • Xianhua Liang School of Environmental Engineering, Guangzhou University
  • Meifu Lin School of Horticulture, South China Agricultural University
  • Qiwen Zhu School of Chemistry and Chemical Engineering, Guangzhou University

DOI:

https://doi.org/10.61603/ceas.v1i2.25

Keywords:

plant diversity, PACA, Marxan, conservation management, CAPTAIN, artificial intelligence

Abstract

The rapid decline in plant diversity has become a pressing issue with significant implications for humanity. Numerous methods and technologies are being developed to address this problem. Traditional methods, primarily based on statistical analysis, are being used alongside modern conservation methods that leverage AI (Artificial Intelligence) technology. Among many conservation approaches, we compare the traditional and modern methods to find out how AI has been involved. Based on our research, two traditional models have been chosen for this report. Marxan has been widely used since it was developed. Based on the IUCN Red List database, PACA accelerates plant extinction risk assessments. However, these models have some limitations, including unsuitability for rapid and urgent conservation management, poor adaptability, etc. In contrast, CAPTAIN, based on artificial intelligence technology, not only overcomes the limitations of traditional models but also offers advantages such as non-locality and upgradability. By analysing the differences and correlations between statistical technology and AI technology, we aim to enhance our understanding of the advancements of AI in plant conservation and summarize their development status and prospects.

Downloads

Published

2023-12-22

Issue

Section

Articles

How to Cite

Advancements of ”CAPTAIN” in Plants Conservation Compared to Traditional Techniques. (2023). Cambridge Explorations in Arts and Sciences, 1(2). https://doi.org/10.61603/ceas.v1i2.25