A Bibliometric and Visualized Analysis of Research Progress and Trends on Decay and Cavity Trees in Forest Ecosystem over 20 Years: An Application of the CiteSpace Software
Bibliographic record
Abstract
As one of the most serious health issues facing trees, the occurrence of decay and hollowing not only reduces the stability and quality of living trees but also leads to the deterioration of their eco-physiological functions, which creates great challenges to the conservation and sustainable management of forest resources. In recent years, the study of tree decay and hollow rot have attracted more and more attention from scholars at home and abroad. The relevant research results have a great significance for the prevention and control of affected living trees and the conservation and sustainable management of endangered species. However, there is a lack of systematic literature review and an insufficient understanding of research hotspots and trends in this field. This paper selects literature retrieved from the CNKI and Web of Science core databases as data sources, the number of publications, research topics, research status, hot spots, and trends, as well as the main research countries, institutions, and co-cited authors in the field of tree decay are visualized by using bibliometrics software CiteSpace (V.5.8.R3), and the current international research hotspots and development trends in this field were systematically summarized. The results showed that the number of papers in this field at home and abroad showed rapid growth in general, and the number of Chinese papers showed a slow growth after 2009. The number of papers published in English by Chinese authors was more than the number of papers published in Chinese in the field. From 2002 to 2021, the research hotspots in this field are constantly changing. Cluster analysis shows that the main themes of the relevant research are as follows: “Eastern Canada” tree species, “hydraulic vulnerability segmentation”, “dead wood management”, and “hydraulic safety”. The advantages and disadvantages of hollow/dead wood on forest ecosystems were explored from different perspectives, providing a theoretical basis and scientific support for the forest health and sustainable management. The United States dominates the research in this field, while China is a relatively late comer but is catching up fast, and the Chinese Academy of Sciences is the most prolific publisher on this topic in China. The influence of Chinese research in this field on relevant international publications is gradually increasing. In short, the research in this field is still in the phase of rapid development, and both the breadth and depth of quantitative research are increasing. How to accurately diagnose and quantify the internal decay of tree trunks and its relationship with tree death and forest decline under the interference and pressure of climate change and human activities is still a hot and difficult issue in this field.
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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 | 0.002 | 0.021 |
| 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) | 0.000 | 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; a candidate call from one teacher head, not a consensus.
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".