Data Analysis and Prediction Study of Endangered Species Based on Ecological Environment

Chuan Zhao () and Chunyu Xing
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Chuan Zhao: Beijing Information Science, and Technology University
Chunyu Xing: Beijing Information Science, and Technology University

A chapter in LISS 2024, 2025, pp 157-169 from Springer

Abstract: Abstract Given the decreasing trend of global biodiversity year by year, preserving species diversity is significantly influenced by the ecological environment, making it a crucial factor of great importance. This study selected three categories of endangered animals: “vulnerable”, “endangered” and “critically endangered”, and analyzed the data in a clear and visually appealing manner from four different perspectives: Global Natural Disasters, Global Land Surface Temperature, Global Greenhouse Gas Emissions, and Worldwide Forest Cover Area, using relevant data from 2000 to 2022. By employing techniques such as correlation coefficient, linear regression equation, and heat map, the impact of various factors on endangered species was deeply discussed. The findings indicated that the quantity of three groups of endangered animals showed an overall upward trend. The order of the damage of the four ecological environments to endangered species is world forest coverage > global greenhouse gas emissions > global surface temperature > global natural disasters. By establishing the ARIMA prediction model, the number of endangered species of the three types was predicted and analyzed, and it was found that they all showed a significant increasing trend in five years. The results of this research can provide valuable guidance and solutions for reducing the threats caused to endangered animals in their ecological environment, to cope with the current challenges faced by biodiversity.

Keywords: biodiversity; endangered species; global ecological environment; ARIMA forecasting (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-981-96-9697-0_13

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