Biodiversity early warning for the objectives of Kunming-Montreal Global Biodiversity Framework

doi:10.17520/biods.2025329

Abstract

Abstract:

Background: Biodiversity conservation remains one of the most urgent priorities on the global environmental agenda. Effectively halting and reversing the ongoing loss of biodiversity constitutes a fundamental challenge for contemporary ecological governance. In order to fulfill the objectives of global sustainable development, it is essential to establish a robust and responsive global biodiversity early warning system capable of real-time monitoring and dynamic assessment of biodiversity trends. The Kunming-Montreal Global Biodiversity Framework (KMGBF), adopted at the fifteenth meeting of the Conference of the Parties to the Convention on Biological Diversity (COP15), outlines a strategic roadmap for the future of global biodiversity governance.

Aims: Based on the objectives articulated by the KMGBF, this study investigates the current status, principal challenges, emerging opportunities, and strategic pathways for advancing the development of a global biodiversity early warning system. Through enhanced international policy coordination and collaborative efforts, the envisioned system aspires to promote the scientific and intelligent governance of global biodiversity. It is expected to provide a rigorous scientific foundation for the formulation and execution of biodiversity conservation policies across nations, thereby making a substantive contribution to global biodiversity protection and the broader pursuit of sustainable development.

Challenges & Prospects: This study begins by underscoring the pivotal role of the KMGBF in guiding the development of a global biodiversity early warning system. Despite notable advancements in recent years, significant challenges persist, including incomplete data coverage, reliance on outdated technologies, and insufficient international cooperation. Building on the vision articulated in the KMGBF, this paper systematically outlines the foundational architecture and key components of a global biodiversity early warning system, and proposes a suite of global indicators to facilitate its implementation. Furthermore, this paper advocates the integration of multi-source data, including satellite remote sensing and ground-based camera observations, along with advanced technologies such as cloud computing and artificial intelligence. This integrated approach aims to establish a scalable and resilient global biodiversity early warning system that can support multidimensional, multilevel, and multiscale biodiversity assessments.

Key words: biodiversity, Kunming-Montreal Global Biodiversity Framework, remote sensing technique, early monitoring and warning

Le Yu, Jiatong Gu, Hui Wu, Zhenrong Du, Xiyu Li, Xiaoli Shen, Li Zhu, Keping Ma. Biodiversity early warning for the objectives of Kunming-Montreal Global Biodiversity Framework[J]. Biodiv Sci, 2025, 33(12): 25329.

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URL: https://www.biodiversity-science.net/EN/10.17520/biods.2025329

https://www.biodiversity-science.net/EN/Y2025/V33/I12/25329

Figures/Tables 6

References 49

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序号 Number	类别 Category	指标参数 Indicator parameter
1	生境条件 Habitat condition	大气降水 Atmospheric precipitation
2		地表温度 Surface temperature
3		高程 Elevation
4		土壤含水量 Soil moisture
5	生境结构 Habitat structure	冰盖栖息地 Ice cover habitat
6		城市栖息地 Urban habitat
7		土地覆盖 Land cover
8		地上生物量 Above-ground biomass
9		植被覆盖度 Fraction of vegetation cover
10		植被密度 Vegetation density
11		植被高度 Vegetation height
12	生境质量 Habitat quality	生态系统破碎化 Ecosystem fragmentation
13		生态系统结构差异 Ecosystem structural variance
14		碳循环 Carbon cycle
15		光合有效辐射吸收比率 Fraction of absorbed photosynthetically active radiation
16		总初级生产力 Gross primary productivity
17		净初级生产力 Net primary productivity
18		叶面积指数 Leaf area index
19		叶绿素含量与通量 Chlorophyll content and flux
20		蒸散发 Evapotranspiration
21	生态系统物候学 Ecosystem phenology	返青期(季节开始) Green-up (start of season)
22		峰值(季节最大值) Peak (maximum of season)
23		衰老期(季节结束) Senescence (end of season)
24	物种种群 Species population	物种丰度 Species abundance
25		相对物种丰度 Relative species abundance
26		种群密度 Population density
27	干扰影响 Interference impact	极端天气频度及强度 The frequency and intensity of extreme weather events
28		野火扰动的生物学影响 Biological effects of fire disturbance
29		生物干扰类型及影响程度 Types and severity of biological interference
30		非法活动类型及规模 Types and scale of illegal activities
31		背景完整度 Contextual intactness

序号 Number	类别 Category	指标参数 Indicator parameter
1	生境条件 Habitat condition	大气降水 Atmospheric precipitation
2		地表温度 Surface temperature
3		高程 Elevation
4		土壤含水量 Soil moisture
5	生境结构 Habitat structure	冰盖栖息地 Ice cover habitat
6		城市栖息地 Urban habitat
7		土地覆盖 Land cover
8		地上生物量 Above-ground biomass
9		植被覆盖度 Fraction of vegetation cover
10		植被密度 Vegetation density
11		植被高度 Vegetation height
12	生境质量 Habitat quality	生态系统破碎化 Ecosystem fragmentation
13		生态系统结构差异 Ecosystem structural variance
14		碳循环 Carbon cycle
15		光合有效辐射吸收比率 Fraction of absorbed photosynthetically active radiation
16		总初级生产力 Gross primary productivity
17		净初级生产力 Net primary productivity
18		叶面积指数 Leaf area index
19		叶绿素含量与通量 Chlorophyll content and flux
20		蒸散发 Evapotranspiration
21	生态系统物候学 Ecosystem phenology	返青期(季节开始) Green-up (start of season)
22		峰值(季节最大值) Peak (maximum of season)
23		衰老期(季节结束) Senescence (end of season)
24	物种种群 Species population	物种丰度 Species abundance
25		相对物种丰度 Relative species abundance
26		种群密度 Population density
27	干扰影响 Interference impact	极端天气频度及强度 The frequency and intensity of extreme weather events
28		野火扰动的生物学影响 Biological effects of fire disturbance
29		生物干扰类型及影响程度 Types and severity of biological interference
30		非法活动类型及规模 Types and scale of illegal activities
31		背景完整度 Contextual intactness