Keragaman Fitoplankton dan Potensi Harmfull Algal Blooms (HABs) di Perairan Sungai Musi Bagian Hilir Provinsi Sumatera Selatan
Bibliographic record
Abstract
Sungai Musi merupakan sungai terpanjang di Pulau Sumatera yang banyak dimanfaatkan masyarakat sebagai jalur transportasi dan berbagai aktivitas lainnya. Sungai Musi merupakan habitat fitoplankton yang dapat menjadi indikator kualitas perairan. Penelitian ini bertujuan mengetahui kelimpahan, keragaman, keseragaman, dominansi, dan menganalisis potensi HABs fitoplankton di Perairan Sungai Musi bagian hilir. Hasil pengamatan pada 10 stasiun, ditemukan 6 genus fitoplankton dari kelas Bacillariophyceae (Bacillaria, Coscinodiscus, Ghemponema, Navicula, Skeletonema, Strepthotecha), 6 genus dari kelas Chlorophyceae (Chlorella, Hydrodiction, Micrasterias, Pediastrum, Platydorina, Spirogyra), 1 genus dari kelas Cyanophyceae (Oscillatoria). Hasil analisis diperoleh kelimpahan sebesar 10-483 sel/L, indeks keanekaragaman (H’) 0,89-1,57, indeks keseragaman (E) 0,75-0,99, dan indeks dominansi (C) 0,25-0,46 dengan genus fitoplankton di kelimpahan tertinggi Spirogyra dan terendah Bacillaria. Hasil pengamatan menunjukkan parameter fisika-kimia termasuk kategori baik untuk pertumbuhan fitoplankton dan ditemukan beberapa jenis fitoplankton yang berpotensi HABs (Coscinodiscus, Skeletonema, Oscillatoria). The Musi River, the longest river on the island of Sumatra, is widely used by the community as a transportation route and for various other activities. Therefore, the Musi River is a habitat for phytoplankton and can be a bioindicator of water quality. This study aims to determine the success of analysing the abundance, diversity, uniformity, dominance and potential of HABs phytoplankton downstream of the Musi River. Observations of 10 sampling stations found six genera from the class Bacillariophyceae (Bacillaria, Coscinodiscus, Ghemponema, Navicula, Skeletonema, Streptotheca), six genera from the class Chlorophyceae (Chlorella, Hydrodiction, Micrasterias, Pediastrum, Platydorina, Spirogyra), one genus class Cyanophyceae (Oscillatoria). The results of the analysis obtained an abundance of 18-483 cells/L, the diversity index (H') 0.89-1.57, uniformity index (E) 0.75-0.99, and dominance index (C) 0.25-0.46 with the phytoplankton genus in the highest abundance of Spirogyra and the lowest Bacillariophyceae. Furthermore, the results of the observations show that the physicochemical parameters are in a suitable category for phytoplankton growth and found several types of phytoplankton that have the potential for HABs (Coscinodiscus, Skeletonema, Oscillatoria).
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".