Forest Biodiversity Index of the Western Himalayas – an aggregate index based on the National Forest Inventory of India

Assessing biodiversity through criteria and indicators has been suggested but rarely put into practice. Documenting and monitoring global biodiversity change is challenging due to limited or biased data and a lack of agreed obligations, but indicators play a key role in studying this problem. For the Western Himalayas we have developed the Forest Biodiversity Index (FBI), based on national forest inventory data. The FBI combines various indicators weighted by experts to assess overall forest biodiversity, including factors reflecting naturalness, vegetation structure, soil (erosion and depth), disturbance, and response. The weight of factors was determined using the group conversion method, considering experts’ opinions while giving justification for assigning a particular value. The sum of all weighted indicator values for 3549 forest inventory points gives us a map illustrating variation in biodiversity: from low to very high. Thus, the FBI is a comprehensive index, which can be used to communicate and provide a workable platform to detect and monitor any biodiversity change over a given period. The FBI in the Western Himalayas shows that more than 89% of the area is in high and very high biodiversity zones, with an accuracy of about 74.8% via validation.

Authors

Institutions

Publication Details

Journal
Biodiversity Research and Conservation
Published
2024-12-30
DOI
https://doi.org/10.14746/biorc.2024.76.2
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

Forest Biodiversity Index of the Western Himalayas – an aggregate index based on the National Forest Inventory of India

Arun Kumar Thakur, Ranjeet Kumar, R. K. Verma, Rajesh Kumar
Biodiversity Research and Conservation
Ecology and Vegetation Dynamics Studies
article

Forest Biodiversity Index of the Western Himalayas – an aggregate index based on the National Forest Inventory of India

Arun Kumar Thakur, Ranjeet Kumar, R. K. Verma, Rajesh Kumar
article en

Abstract

Assessing biodiversity through criteria and indicators has been suggested but rarely put into practice. Documenting and monitoring global biodiversity change is challenging due to limited or biased data and a lack of agreed obligations, but indicators play a key role in studying this problem. For the Western Himalayas we have developed the Forest Biodiversity Index (FBI), based on national forest inventory data. The FBI combines various indicators weighted by experts to assess overall forest biodiversity, including factors reflecting naturalness, vegetation structure, soil (erosion and depth), disturbance, and response. The weight of factors was determined using the group conversion method, considering experts’ opinions while giving justification for assigning a particular value. The sum of all weighted indicator values for 3549 forest inventory points gives us a map illustrating variation in biodiversity: from low to very high. Thus, the FBI is a comprehensive index, which can be used to communicate and provide a workable platform to detect and monitor any biodiversity change over a given period. The FBI in the Western Himalayas shows that more than 89% of the area is in high and very high biodiversity zones, with an accuracy of about 74.8% via validation.

Biodiversity Research and ConservationVol. 76
Indian Council of Forestry Research and Education (IN)
Openalex Percentile: Top 75%
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.