A new study, led by researchers from the National Centre for Biological Sciences (NCBS), has compiled ‘InvenTree-meta’, the largest meta-dataset of tree inventory studies from India, and concluded that Indian forests could make for a valuable addition to global ecological analyses and climate studies.
The rationale behind the project was that while scientists around the world use vast forest datasets to understand how trees store carbon and respond to climate change, South Asia, especially India, contributes little to global forest databases, limiting the understanding of tropical ecosystems.
By mapping where tree inventories have been conducted, the researchers also identified important knowledge gaps such as the fact that biodiversity-rich landscapes like the northern Western Ghats, northeastern India, the Western Himalayas and the Nicobar Islands remain relatively under-sampled. Several regions undergoing rapid forest loss—including parts of northeast and eastern India—also lack sufficient ecological data, making it harder to monitor changes in biodiversity and guide conservation efforts.
The database brings together information from 465 published studies conducted between 1991 and 2023, spanning more than 4,650 hectares of forests across all of India’s biomes. “We wanted to see whether data availability (limited sampling) or data accessibility might be a larger contributor to the India-gap in global studies. What we found indicates that there has been extensive sampling, but accessibility might be the bottleneck,” said Krishna Anujan, postdoctoral fellow, Smithsonian Tropical Research Institute, and Lead, Network Building, India Tree Inventory Network.
Most tree inventory studies in India are relatively small, with a median sampled area of just two hectares, and over 80% of the underlying datasets are not publicly accessible. This makes it difficult to combine them into larger regional or global analyses, even though collectively they represent an enormous scientific resource.
“Although we didn’t explicitly test these, there are practical and structural barriers to making the data reusable; there are high costs (effort required to meet reusability standards) and no clear incentives, and maybe even disincentives (publishing power is often in the Global North) for Indian researchers to make hard-collected forest data openly available and reusable,” said Anujan.
