Implementing a 30 % area-based target could achieve near-complete biodiversity representation in the Hengduan Mountains, China

Despite their limitations, it is generally accepted that area-based conservation targets are essential. We explored the potential gains in biodiversity representation if the Kunming-Montreal 30% target was implemented to optimal benefit in the Hengduan Mountains (HDM) bioregion, China. Using high high-resolution (5×5 km²) seed plant species distribution and phylogeny, we created a composite index of biodiversity using six commonly used metrics. These priority biodiversity zones were then enhanced by inclusion of centers of paleo- and neo-endemism identified using the CANAPE method. High-value zones of biodiversity and endemism were then compared with existing nature reserve areas to identify priority conservation gaps. The existing nature reserves covering 12% of the HDM represent 57% of total bioregional taxonomic and 41% of phylogenetic diversity. If an additional 18% of total area were located to coincide with eight priority regions identified, we estimate representation of bioregional taxonomic and phylogenetic biodiversity would both exceed 96%. Explicitly incorporating priority biodiversity with centers of endemism showed these do not always coincide spatially and allowed more specific articulation of conservation aims and threatening processes. We conclude that even within this global biodiversity hotspot, with appropriate optimization a 30% area-based conservation target could provide near-complete representation of bioregional biodiversity.

Authors

Institutions

Publication Details

Journal
Global Ecology and Conservation
Published
2025-11-22
DOI
https://doi.org/10.1016/j.gecco.2025.e03988
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Implementing a 30 % area-based target could achieve near-complete biodiversity representation in the Hengduan Mountains, China

David C. Deane, Man Yang, Junjie Hu, Yanwei Guan et al.
Global Ecology and Conservation
Ecology and Vegetation Dynamics Studies
article

Implementing a 30 % area-based target could achieve near-complete biodiversity representation in the Hengduan Mountains, China

David C. Deane, Man Yang, Junjie Hu, Yanwei Guan, Bin Li, Jiaqi Wang, Yongqing Zhang, Xiaohui Lu, Fangyuan Yu, Haibin Yu, Zixin Lu
article en

Abstract

Despite their limitations, it is generally accepted that area-based conservation targets are essential. We explored the potential gains in biodiversity representation if the Kunming-Montreal 30% target was implemented to optimal benefit in the Hengduan Mountains (HDM) bioregion, China. Using high high-resolution (5×5 km²) seed plant species distribution and phylogeny, we created a composite index of biodiversity using six commonly used metrics. These priority biodiversity zones were then enhanced by inclusion of centers of paleo- and neo-endemism identified using the CANAPE method. High-value zones of biodiversity and endemism were then compared with existing nature reserve areas to identify priority conservation gaps. The existing nature reserves covering 12% of the HDM represent 57% of total bioregional taxonomic and 41% of phylogenetic diversity. If an additional 18% of total area were located to coincide with eight priority regions identified, we estimate representation of bioregional taxonomic and phylogenetic biodiversity would both exceed 96%. Explicitly incorporating priority biodiversity with centers of endemism showed these do not always coincide spatially and allowed more specific articulation of conservation aims and threatening processes. We conclude that even within this global biodiversity hotspot, with appropriate optimization a 30% area-based conservation target could provide near-complete representation of bioregional biodiversity.

Global Ecology and ConservationVol. 64
La Trobe University (AU), Guangzhou University (CN)
Openalex Percentile: Top 66%
Ecology and Vegetation Dynamics Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.