ArticleData in brief2026
A 2000-2023 dataset for measuring China's biodiversity risk.
Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing frequency of extinctions of biological populations has important implications for related sectors. Consequently, the risks associated with biodiversity are receiving increasing attention and are being recognized as entirely new risk factors. To understand the drivers of biodiversity risk, it is crucial to measure biodiversity risk at multiple levels, especially in developing countries. Using machine learning and text mining methods, we measure the biodiversity risk of the Chinese market from 2000 to 2023 from the perspectives of macro-government, meso‑industry, and micro-firms, by analysing official news media texts, related fund-holding data, and listed firms' annual reports. We construct a macro-level index derived from the sentiment and frequency of biodiversity-related discourse in official media, including the China Environment News and the CCTV News, from 2013 to 2023. We also construct a meso-level industry risk exposure indicator, calculated as the deviation of biodiversity-themed public funds' holdings from market portfolio weights across 58 sectors. In addition, we develop micro-level firm-specific metrics, based on the frequency and sentiment analysis of biodiversity sentences in the annual reports of 5606 A-share listed firms, 2000-2023, using an improved BERT model for Chinese text. These indicators provide researchers, policymakers, and financial practitioners with a foundational resource for empirically investigating the economic and financial implications of biodiversity risk in China.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.