Diversity and distribution of birds in a Congo Basin wetland: the upstream part of the Nyong River valley in Cameroon along two regions (Centre and East)
Bibliographic record
Abstract
Several studies have recently been carried out on the avifauna of Cameroon and have made it possible to update the data for certain regions; however, no recent study has been carried out on the upper valley of the Nyong River, which is a wetland, and therefore the data remains quite old. We carried out a study on the avifauna of this valley and birds were sampled over a period of one year using the mist-netting method. The collected data were analyzed using PAST bio statistical software for the diversity and distribution of the avifauna. A total of 268 individuals belonging to 69 bird species were captured, with a high proportion of passerines (73%) compared with non-passerines. The high diversity of the avifauna is supported by estimated values of diversity indexes which show an absence of supremacy of one species (H’=3.64) and an equal distribution of individuals in their environment (J’=0.86). With the value of the Simpson diversity index of 0.96, our result confirms high diversity within the upper valley of the Nyong River avifauna but it also reveals the abundance of this avifauna. In addition, the Kruskal-Wallis test value of 0.04 showed a significant difference in the distribution of relative abundances of taxa at the areas investigated and that different could be justified by a difference in the physiognomy of their vegetation. This study confirms that the composition as well as the structure of the upper valley of the Nyong River as observed in the field play a main role in the diversity of bird species due to the presence of feeding, resting and nesting areas. Based on our distribution and diversity analysis, the pattern of variation in distribution of birds in this wetland appears to lean on environmental factors and particularly the vegetation, which played the main role with a mixture of poor and good dispersers, migratory and vagrant due to presence of lush vegetation all year round.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".