Ecological niche modeling predicting the potential distribution of Leishmania vectors in the Mediterranean basin: impact of climate change
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Bibliographic record
Abstract
BACKGROUND: N. Recent studies show that some phlebotomine sand flies were recorded in several parts of Germany and Belgium. In central Europe, some autochthone leishmaniasis cases are being recorded in regions traditionally regarded as leishmaniasis-free. An important challenge is to predict the geographical distribution of leishmaniasis vectors under new climatic conditions. In this study, we attempted to predict the current distribution of six leishmaniasis vectors in the Mediterranean basin and forecast species' geographical shift under future climate scenarios using an ensemble ecological niche modeling approach. Species records were obtained from scientific surveys published in the research literature between 2006 and 2016. A series of climate metrics describing temperature and precipitation in the study area under two climatic scenarios were obtained from WorldClim database. A consensus model was derived from six varieties of modeling approaches (regression, machine learning and classification techniques) in order to ensure valid prediction of distribution of vectors under different climate scenarios. RESULTS: Model performance was generally high for the included species with a specificity (true negative rate) ranging from 81.03 to 96.52% (mean = 86.94%) and a sensitivity (true positive rate) ranging from 87.93 to 100% (mean = 96.98%). Our work evidenced the hypothesis of the widespread of Leishmania vectors under climate change scenarios. All of the studied species are prospected to gain new areas that are actually not suitable for vectors' survival. Phlebotomine sand flies are prospected to invade extra-Mediterranean regions, especially western and central Europe. CONCLUSIONS: Our study confirmed the importance of environmental and climate factors on the distribution of leishmaniasis vectors and demonstrated the performance of ecological niche modeling in the prediction of the geographical spread of vector-borne diseases. Ecological niche modeling should be considered in the future as a valuable tool in addition to experimental laboratory studies for a better understanding of the biology of vector species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it