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Who reads the Earth's archives? Geography, Income, and the Uneven Evidence Base for a Shared Planet
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Abstract
Global environmental assessments depend on natural-archive evidence, yet where this evidence is produced and how its geography maps onto the Sustainable Development Goals (SDGs) remains unclear. Here we map the sampling and publication geography of 33,145 studies of past environments, tracing each to the SDG it addresses. The geography is highly unequal. A group of 25 countries is home to 55% of world population but accounts for 81% of sampling and 89% of publication credit, with per capita evidence output about seven times higher and all eleven goals drawing 82–90% of their evidence from them. Income acts as a threshold rather than a gradient: the elasticity of output to income is flat below about 41,000 PPP dollars per capita, where its slope with respect to income is close to zero, and steps up above it. Sampling and publication are concentrated in the same countries, so sample accessibility is unlikely to be the main constraint; the deficit is more consistent with limited analytical capacity. The evidence base for the SDGs therefore reflects a minority's research geography, not the distribution of the processes measured. Our findings provide a baseline for measuring commitments to widen participation and identify analytical capacity, not sample access, as the binding constraint on whose evidence is used in global assessments.
DOI
https://doi.org/10.32942/X26X2J
Subjects
Communication, International and Intercultural Communication, Publishing
Keywords
Bibliometrics; Palaeoclimatology; Research inequality; Geographic bias; Open science, Bibliometrics, Palaeoclimatology, Research inequality, Geographic bias, Open science
Dates
Published: 2026-10-13 13:54
Last Updated: 2026-10-28 16:48
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License
CC-By Attribution-NonCommercial-NoDerivatives 4.0 International
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Conflict of interest statement:
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data and Code Availability Statement:
The bibliographic corpus itself cannot be redistributed because of the Web of Science licence. The derived record-level annotation table, the complete search string, the extraction prompt and the manual validation sample are archived on Zenodo at https://doi.org/10.5281/zenodo.23294431 under a CC BY-NC-SA 4.0 licence. The analysis code is available at https://github.com/honghlaries/natural-archive-bibliometrics under an MIT licence.
Language:
English
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