Spatio-temporal Variations of Macrobenthic Annelid Community of the Karnafuli River Estuary, Chittagong, Bangladesh
Bibliographic record
Abstract
The spatial and temporal variation in species composition, distribution, abundance, biodiversity and succession of the macrobenthic annelid assemblages in the intertidal zone of the Karnafuli Estuary are analyzed in this paper. Samples were collected from nine stations placed in different tide marks from three sites of the study area. From the total of 180 samples collected during one year sampling period, a total of 4,46,516 individuals of macrobenthic annelids belonging to polychaete, oligochaete and clitellata classes and represented by 12 species/taxon were identified. The most abundant species recorded in this study were Capitella sp., Lycastonereis indica, Namalycastis fauveli , Nephthys oligobranchia within polychaetes; Tubifex sp. within oligochaete and Tubificoides insularis within clitellata. Capitellidae was the most abundant family represented by Capitella sp. which was distributed in the study area in all seasons of the year and it was ranged from a minimum value (Site1 (S 1 ): 23 individual/m²) during pre monsoon to a maximum value (Site2 (S 2 ): 243687 individual/m²) during post monsoon. This species supported the highest contribution (98.67%) to the average abundance recorded in post monsoon. The abundance of some species fluctuated in different seasons with a marked seasonal and spatial succession. Higher values of species diversity and evenness were recorded during monsoon and maximum numbers of individuals were counted during post monsoon. The macrobenthic annelid assemblages showed distinct seasonal differences (Analysis of similarities (ANOSIM test) by using PRIMER (v.6) software). All the seasons were distinguished at different significant level (global r = -0.083 and p = 63.8%). Average similarities within the macrobenthic annelid community compositions recorded during monsoon, post monsoon, winter and pre monsoon were 95.74%, 39.87%, 32.25% and 34.21% respectively. Similarly, average similarities recorded in site 1, site 2 and site 3 were 29.18%, 99.00% and 57.53% respectively. Average dissimilarity was highest (55.20%) between the species composition of post monsoon and winter and the lowest value (39.30%) of average dissimilarity was found between monsoon and post monsoon. Again average dissimilarity presented the highest value between site 1 & site 3 (55.93%) and the lowest value between the site 2 & site 3 (38.87%).
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".