Environmental <scp>DNA</scp> biomonitoring in biodiversity hotspots: A case study of fishes of the Okavango Delta
Bibliographic record
Abstract
Abstract The Okavango Delta is the largest freshwater wetland in southern Africa and a recognized biodiversity hotspot and UNESCO World Heritage Site. The region is extremely rich in floral and faunal diversity, including a fish fauna of ~90 species in 15 families, that also support recreational and subsistence fishing. Anthropogenic pressures and invasive species threaten the unique biodiversity and ecosystem services that the Delta provides, necessitating biomonitoring tools that can provide broad community‐level diversity insights. Here, we utilize environmental DNA metabarcoding of aquatic eDNA using the MiFish 12S rRNA primers, to investigate fish communities and also sequenced 211 mtDNA 12S barcodes for 74 species across 36 genera of fishes from the region. Metabarcoding recovered 11 of 15 families, with 40 species detected across 23 genera, representing ~50% of known diversity, with the mtDNA 12S fragment able to delineate all genera (except for the cichlid genera Serranochromis and Pharyngochromis that comprised a single clade) and most species, except for some in the Clarias , Enteromius , Labeo , Lacustricola , and Petrocephalus genera. Generally, abundant and wide‐spread taxa such as Clarias spp. and Marcusenius altisambesi , amongst others, were often detected in the surveys, with other species, including Zaireichthys kavangoensis , Schilbe intermedius , and Labeo sp. detected less frequently. Dissolved oxygen, temperature, and dissolved organic solids were positively correlated with community diversity, highlighting the influence of environmental factors in shaping fish communities in the region. Further, there was strong variability in the eDNA signal across only 1000 m, suggesting that future surveys need to consider spatio‐temporal aspects of sample collection. Our study highlights the potential of eDNA metabarcoding for surveying aquatic biodiversity in the Okavango Delta, particularly within the context of baseline biodiversity inventories, that underpin conservation and management initiatives. As such, we provide a number of recommendations that can help structure future sampling efforts in the region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".