Influence of Multiple Linear Infrastructure on Diversity of Small Mammals in Mikumi National Park, Tanzania
Bibliographic record
Abstract
The need for rapid development in developing countries has led to establishment of major public infrastructure even in biodiversity rich protected areas. Mikumi National Park in central Tanzania is traversed by five such major infrastructures namely an optic fibre, a busy public road, an oil pipeline, power lines and railways. We assessed diversity and abundance of small terrestrial mammals of the order Eulipotyphla and Rodentia as indicator groups in relation to impacts of such infrastructure. Animals were live trapped during wet (February-April) and dry (July- September) seasons in 2018 from three established plots along the three transects set perpendicular to each of the four infrastructures. In 10102 trap nights, we captured 453 small mammals of nine species of which Mastomys natalensis constituted 75.4 % of total catch. Diversity and abundance varied between seasons, infrastructure and plots location. Dry season had significantly higher diversity than wet season and the railway site had higher diversity than the other infrastructure. The intermediate plots (500 m from infrastructure) had significantly higher abundance of animals than immediate (0-50 m) and distant (1000 m) plots. The differences in these results can be attributed by seasonal fluctuations of animal populations, and intensity of disturbance in each infrastructure and plot. It is important to examine impacts of future infrastructure developments using small mammals.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".