Evidence map›Paper›PMID 42386729›Full record

ArticleNature communications2026

Global inequality in roadkill burden concentrates collision risk on threatened species in low- and middle-income countries.

Yuhang Li, Zixi Zhao, Xinmiao Chen, Kai Wang, Haozhong Si, Linyou Gu, Zhenqi Wang, Jiahua Xing, Feng Xu, Yang Liu and 1 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yuhang Li *Lab of Animal Behavior & Conservation, The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.ORCID http://orcid.org/0000-0002-3090-804X
Zixi Zhao *Lab of Animal Behavior & Conservation, The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.
Xinmiao ChenLab of Animal Behavior & Conservation, The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.
Kai WangYunnan Key Laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
Haozhong SiLab of Animal Behavior & Conservation, The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.ORCID http://orcid.org/0000-0002-2179-6621
Linyou GuNanjing Forestry University, Nanjing, China.
Zhenqi WangNanjing Forestry University, Nanjing, China.
Jiahua XingLab of Animal Behavior & Conservation, The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.
Feng XuChina-Tajikistan Belt and Road Joint Laboratory on Biodiversity Conservation and Sustainable Use, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China.ORCID http://orcid.org/0000-0001-8925-977X
Yang LiuSchool of Ecology, Sun Yat-sen University, Shenzhen, China.ORCID http://orcid.org/0000-0003-4580-5518
Zhongqiu LiLab of Animal Behavior & Conservation, The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China. lizq@nju.edu.cn.

Funding

National Science Foundation of China | National Natural Science Foundation of China-Yunnan Joint Fund (NSFC-Yunnan Joint Fund) 32471564
6 · The paper itself

Abstract

Global development relies on vast and expanding road networks, yet the global distribution of the wildlife mortality they cause remains poorly quantified. Here we show, using researcher-led surveys, global citizen-science records and a high-resolution national dataset for China, that wildlife-vehicle collisions disproportionately burden biodiversity in low- and middle-income countries. After standardising for species pools and sampling effort, low- and middle-income countries bear a heavier roadkill burden than high-income countries, with the strongest disparities reaching 2-4-fold for threatened vertebrates but much weaker contrasts for non-threatened species. This reflects elevated collision rates among threatened fauna rather than a broader list of affected species. In China, the same pattern unfolds along a land-use intensity gradient: transformed landscapes elevate risk for common generalists while progressively filtering threatened taxa from the roadscape. Overall, expanding transport networks concentrate contemporary collision burden on threatened biodiversity in low- and middle-income countries.

Indexed as

Accidents, TrafficDeveloping CountriesEndangered SpeciesAnimalsAnimals, WildBiodiversityChinaConservation of Natural Resources

Identifiers

PMID42386729
PMCPMC13473495

What OpenQuestion holds

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Registered trials

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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.