Research on wildlife conservation strategy based on gray prediction and entropy weight method

Weihan Wang; Jianshu Zheng; Jinqiu Zhang

doi:10.62051/knq5jn27

Authors

Weihan Wang
Jianshu Zheng
Jinqiu Zhang

DOI:

https://doi.org/10.62051/knq5jn27

Keywords:

Gray prediction; Entropy right method; Wildlife conservation strategy.

Abstract

This study provides an in-depth examination of nature reserve programs and their feasibility, focusing on the challenges posed by illegal wildlife trade. Through an extensive literature review of scientific databases such as SCI and EI, the thesis illuminates the frontiers of current conservation efforts and assesses the compatibility of nature reserve programs with stakeholders. The research includes a comprehensive case study of wetlands in Patagonia, Brazil, analyzing the correlation between illegal wildlife trade crime indicators and selected socio-economic factors. Using advanced modeling techniques, including the gray predictive model GM (1,1) and the information entropy weighting method (EWM), the paper predicts trends in endangered species such as the jaguar and assesses the effectiveness of conservation measures. In addition, an assessment improvement framework is proposed that integrates a perspective through vector autoregression (VAR) analysis to enhance the assessment of conservation strategies and stakeholder empowerment.

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References

[1] T. P. Mayor, A. Elías, P.E. Pérez, et al. Consumption of wildlife-origin products by residents at the largest wildlife market of Amazonian Peru: is there scope for demand reduction? [J]. Global Ecology and Conservation, 2023, 48: e02755.

[2] Xiong Xiaoqian, You Weixuan, Zhang Ling, et al. Analysis of the illegal utilization of wildlife resources in the Beijing area [J]. Chinese Journal of Wildlife, 2017, 38 (03): 376 - 385.

[3] Jiang Zhigang. Control of illegal trade in wild species and protect global biodiversity [J]. Biodiversity Science, 2013, 21 (02): 139 - 140.

[4] Song Z, Wang Q, Miao Z, et al. The dissemination of relevant information on wildlife utilization and its connection with the illegal trade in wildlife [J]. Journal of Forestry Research, 2022, 33 (01): 357 - 367.

[5] Yin Feng, Meng Meng, Xu Ling, et al. An investigation into the illegal trade of endangered wildlife and plant medicinal materials [J]. Forest Resources Management, 2015, (02): 24 - 30.

[6] Liang Zhijian, Hu Jiabei, Hu Sifan, et al. Research progress on wildlife consumption demand and behavior from a multidisciplinary perspective [J]. Biodiversity Science, 2020, 28 (05): 606 - 620.

[7] Cardoso P, Amponsah-Mensah K, Barreiros JP, et al. Scientists’ warning to humanity on illegal or unsustainable wildlife trade [J]. Biological Conservation, 2021, 263: 109341.

[8] Tlusty MF, Cawthorn D-M, Goodman OLB, et al. Real-time automated species-level detection of trade document systems to reduce illegal wildlife trade and improve data quality [J]. Biological Conservation, 2023, 281: 110022.

[9] Hou Senlin, Fei Yiling, Liu Dawei, et al. Analysis of the illegal utilization of wildlife resources in the Guangdong region from 2014 to 2018 [J]. Chinese Journal of Wildlife, 2021, 42 (04): 1219 - 1230.

[10] Wang Jing, Luo Lei, Sun Shanshan. Analysis and countermeasures of the illegal trade and poaching of wild birds in Shaanxi [J]. Chinese Journal of Wildlife, 2021, 42 (01): 266 - 270. DOI: 10.19711/j.cnki.issn2310 - 1490. 2021. 01. 037.

[11] Charity, S., & Ferreira, J. M. (2020). Wildlife Trafficking in Brazil. Retrieved from https://www.traffic.org/.