Global Research on Riparian Zones in the XXI Century: A Bibliometric Analysis
Bibliographic record
Abstract
Riparian zones (RZs) are transitional environments at the interface between land and freshwater ecosystems, which are important in terms of socioecological services. In this work, we report a bibliometric-based analysis to unveil the knowledge structure and actors of scientific production on riparian zones for the first 20 years of the 21st century. We performed a literature search, querying for riparian zones publications for the period 2001–2020. The selected 1171 bibliographic records were analyzed by extracting several bibliometric indices of reporting tendencies, location, collaboration dynamics, and top topics. Results show that RZs publications increased considerably from 2001 to 2020, and top journals publishing on the subject are from the water, environmental management, and ecology areas. The US, China, Brazil, and Canada were the most productive countries, while the institutions with higher productivity were the Chinese Academy of Sciences and Oregon University. In terms of impact, the US, Canada, and Australia led in citation number, while the country collaboration network showed that the strongest links occur between China and the US. Our results also show that few studies were produced in low-middle income countries, which suggests a need to funnel international funding to study riparian environments in these geographical contexts. According to analysis of frequency, top topics are related to water quality and focused on lotic environments. We here present the main knowledge structure of RZs studies globally for the first 20 years of the XXI century.
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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 | 0.003 | 0.075 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".