Study on species composition and species diversity of Castanopsis secondary forest in Jiangle Forest Farm
Bibliographic record
Abstract
By using the survey data of permanent plots in Fujian Jiangle Farm,the species composition and species diversity were investigated,so as to provide certain reference basis for the study of Castanopsis secondary forests.The sample plots' species diversity values for tree layer,shrub layer and herb layers were studied by selecting Shannon-Wiener index,Simpson's diversity index,Dominance index,Species richness and Evenness index as the diversity measure indexes,and according to the tree layer species diversity indexes of the sample plots,the Castanopsis secondary forests were clustered and analyzed,thus the sample plot types were divided.The results show as follows:(1) Species composition was rich,there were 76 kinds of species in tree layer,77 kinds in shrub layer,22 kinds in herb layer;(2) All diversity index differences about tree layer,shrub layer and herb layer of the sample plots were big,while the evenness and dominance indexes' differences were not very big,the species distributions were relatively uniform;(3) Shannon-Wiener index,Simpson's diversity index,Species richness and Evenness index all ranked from bi g to small as follows:tree layer shrub layer herb layer,and the order of the Dominance index was opposite;(4) Castanopsis secondary forests were divided into three types,of them type-I included plot-1,plot-2,and plot-11,type-Ⅱ included plot-5,plot-6,plot-10,plot-12,plot-13 and plot-14,and type-Ⅲ included plot-9,plot-17 and plot-18.Shannon-Wiener index,Simpson's diversity index,Species richness and Evenness index sequenced from big to small as follows:type Ⅲ type Ⅱ type Ⅰ,the order of the Dominance index was opposite.Species composition of Castanopsis secondary forests in this area were rich,There was a big difference about species diversity in each layer,and there was similar species diversity in the same type,it shows that the degree of interference was similar.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".