Building walls around open wells prevent Asiatic Lion Panthera leo persica (Mammalia: Carnivora: Felidae) mortality in the Gir Lion Landscape, Gujarat, India
Bibliographic record
Abstract
The Asiatic Lion population has increased in the last three decades, which now occupies a large regional spread with six or more identified satellite populations in eight districts of Gujarat. An overlap of lion habitat with human-dominated landscape elements leads to an increase in lion-human interactions in these growing satellite populations. A high rate of lion mortality has been observed in the periphery of Gir in the last decade due to falls into open dug wells. These wells have been excavated for irrigation in the agricultural landscape of Gir. About 145 wild animals including lions have died due to accidental falls into open wells in past 10 years. It has been observed that construction of parapet walls around wells in some of the peripheral areas of Gir Sanctuary have prevented this accidental mortality at very low cost. To assess the efficiency of these measures we did a survey of 20 random villages in the Gir Lion Landscape to collect data on the types of wells that cause this uncalled-for mortality. The paper explores the reasons for the lions falling into wells in the agricultural areas outside the Gir Sanctuary. The survey has shown that the corridors used by lions and in the satellite population areas are high risk sites where more parapet walls should be built on a priority basis. From the year 2007 to 2018 more than 48,000 parapet walls have already been randomly built in the periphery of the Gir Sanctuary. Out of 130 identified wells, 90 were protected with parapet wall or iron net while, 32 were without parapet wall and rest eight were with unfinished parapet wall. Providing a scheme for building more parapet walls around prioritized open wells would be an effective step towards Asiatic Lion conservation in the Gir Lion Landscape. Our survey indicates that there has been no mortality of lions in those wells where parapet walls have been built.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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".