Bibliometric Analysis of Top Papers in Ecology Based on Essential Science Indicators during 2011–2021
Bibliographic record
Abstract
Based on the Essential Science Indicators database, this study analyzed 1,777 top papers in the Ecology subject category of Web of Science, for eleven years from 2011 to 2021, which included 1,770 highly cited papers and 15 hot papers in the field and belonged to 33 categories and 29 research areas. All top papers written in English came from 12,677 authors, 3,246 organizations and 123 countries or territories, and were published in 104 journals and 5 book series in the field. The top five journals publishing the highest number of top papers are Proceedings of the Royal Society B Biological Sciences (9.96% of papers), Global Change Biology (7.88%), ISME Journal (7.71%), Landscape and Urban Planning (7.54%) and Trends in Ecology and Evolution (5.01%), each published more than 89 papers. Top five countries were USA, England, Australia, Germany and Canada. Furthermore, top six organizations publishing the highest number of top papers are University of California, Berkeley, University of Oxford, Chinese Academy of Sciences, University of Queensland, University of British Columbia, and University of California, Davis (more than 62 papers each). VOSviewer software supported the bibliometric analysis. Co-occurrence analysis of top papers' keywords identified eight clusters that correspond to eight major research topics representing different viewpoints on Ecology. Those main topics are: ecosystem services and conservation management, climate-change impacts, evolution and selection, biodiversity, diversity and abundance, ecology patterns and community structure, ecology prediction, impacts of biological invasions. The subject of ecosystem services and conservation management is a front or recent interest topics in Ecology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.066 | 0.101 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".