Vietnamese Odonata: bridging global biodiversity, ecological, and conservation gaps in a changing world.

Quoc Toan Phan, Huy Ngoc Nguyen, Khuong V Dinh
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Abstract

Vietnam is a global hotspot, hosting 493 Odonata species, with ~95% evaluated by the IUCN. Odonata species play vital ecological roles in aquatic and terrestrial ecosystems; yet, they face escalating threats from climate change, habitat loss, and pollution. Adult taxonomy has dominated research; yet, critical eco-evolutionary, ecotoxicological, and conservation studies are lacking. This synthesis of 200 years of Vietnamese Odonata research bridges knowledge gaps, offering insights into tropical ecosystem vulnerability in a changing world. We propose an integrative framework scalable to all aquatic invertebrates and understudied tropical regions to advance research and conservation: (1) enhance larval and adult taxonomy and phylogeny using morphology, DNA barcoding (COI gene), and whole genome sequencing for ecologically important, critically endangered or rare species; (2) implement monitoring programmes with eDNA metabarcoding, remote sensing, automated imaging, and citizen science to track distributions, phenology, and traits; (3) conduct eco-evolutionary and ecotoxicological studies with multi-omics to elucidate mechanisms underlying ecophysiology and evolutionary responses; and (4) apply machine learning to project distributions and responses to environmental changes. This framework aligns with global biodiversity and sustainability policy agendas, including the Convention on Biological Diversity and SDGs 14: Life Below Water, and 15: Life on Land, and offers actionable solutions for protecting vulnerable ecosystems.

越南河豚:在不断变化的世界中弥合全球生物多样性、生态和保护差距。
越南是全球的热点地区,拥有493种蜥目动物,其中约95%被IUCN评估。齿形动物在水生和陆地生态系统中起着重要的生态作用;然而,它们面临着气候变化、栖息地丧失和污染日益加剧的威胁。成人分类学在研究中占主导地位;然而,缺乏关键的生态进化、生态毒理学和保护研究。这篇综合了越南200年河豚研究的文章弥合了知识鸿沟,为不断变化的世界中热带生态系统的脆弱性提供了见解。我们提出了一个可扩展到所有水生无脊椎动物和未被充分研究的热带地区的综合框架,以促进研究和保护:(1)利用形态学、DNA条形码(COI基因)和全基因组测序加强对生态重要、极度濒危或稀有物种的幼虫和成虫分类和系统发育;(2)利用eDNA元条形码、遥感、自动成像和公民科学实施监测计划,以跟踪分布、物候和特征;(3)利用多组学技术开展生态进化和生态毒理学研究,阐明生态生理和进化反应机制;(4)将机器学习应用于项目分布和对环境变化的响应。该框架符合全球生物多样性和可持续性政策议程,包括《生物多样性公约》和可持续发展目标14:水下生命和15:陆地生命,并为保护脆弱的生态系统提供了可行的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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