ArticleScientific data2026
A multi-source dissolved carbon dataset for China's inland waters over the past three decades: concentration, storage, and flux.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
A precise evaluation of carbon (C) concentration, storage, and flux dynamics in China's inland waters is essential for assessing the global C sink capacity of aquatic ecosystems and for understanding regional biogeochemical cycles. However, there is a lack of a comprehensive, spatially explicit, and long-term dataset that quantifies applicable parameters. To address this significant data gap, here we provide a comprehensive dataset that systematically records the concentration, storage, and flux dynamics of dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) across China's rivers, lakes, and reservoirs over a long timescale. This dataset is meant to consolidate and standardize historical measurements from published literature, field surveys, remote sensing inversion processes, and model simulations since the 1960s. The dataset includes dissolved carbon (DC) records from China's lakes (3,515), reservoirs (841), and rivers (32,735) that span decades, namely, from 1960 to 2022, as well as basin-scale C storage and flux data from the 1990s to the 2010s. The dataset is intended to serve as a fundamental resource for quantifying the role of China's inland waters within the global C cycle, for validating C assessment models, and for informing water quality and climate change policies.
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.