Remote Sensing Vegetation Indices to study migratory insect seasonal movements and population outbreaks.
Notice bibliographique
Résumé
Dispersal and migratory movements of phytophagous insects are strongly tight to vegetation phenology. The succeeding broods of seasonally migrating species connect distant regions that differ in the timing of plant growth. Also, the overall plant production and the extent of the growing season determine the breeding capacity of the insects, and thus influence their demographic trends. The use of photosynthetic activity proxies based on remote sensing observations, such as NDVI or EVI, opens new avenues to study migratory patterns of insects, a largely understudied field. Here, we present two applications of NDVI to study the migration of the Painted Lady butterfly, Vanessa cardui, an obligate migratory species with a large migratory range encompassing the Palaearctic and the Afrotropics.We develop a spatio-temporal Species Distribution Model (SDM) to determine monthly suitable areas for reproduction across its migratory range. We use a comprehensive dataset of V. cardui breeding occurrences and time-series of climatic and vegetation growth variables, including EVI and monthly difference (EVI change). Vegetation indexes proved to be relevant variables explaining V. cardui breeding suitability, having higher importance in the Afrotropical region. Moderate EVI values showed best conditions for breeding. EVI change had a better fit with slight increases of vegetation growth, discarding sharp changes in greening. These patterns agree with the phenology of V. cardui herbaceous hostplants in the growing season, distributed in open-areas such as meadows, weeds and bushland. In the temperate zone, vegetation growth was not a limiting factor and suitability was mostly explained by variables related to temperature.At a temporal scale, we assess the role that anomalies in photosynthetic activity might have in modulating demographic trends of V. cardui. We performed a pixel-based time-series analysis of monthly NDVI values from 2000 to 2022. We observe that four demographic outbreaks of the butterfly observed in Europe are immediately preceded by anomalous vegetation growth events in suitable breeding regions in Africa and/or the Middle East, suggesting a strong association between both events. We investigate in higher detail the largest of the outbreak episodes in 2019. The resulting maps of anomalies showed high signal in regions of the Middle East from December 2018 to May 2019. The highest anomalies were detected in rocky deserts and arid and semi-arid shrublands, while sand deserts were not affected. The large extent found with exceptional greening could have functioned as massive breeding grounds for V. cardui. This hypothesis strongly matches massive citizen science data of V. cardui observations that were first observed in the Arabian Peninsula in March, and that further spread all over Europe in unprecedented numbers.Taken together, we highlight the potential of remote-sensing vegetation indices to study seasonal migratory movements of phytophagous insects. We show how NDVI can inform models about the potential shifting distributions of migratory species, and how NDVI anomalies can be used to predict potential population outbreaks. In a world where insects represent the majority of terrestrial diversity, the use of vegetation indices may become standard in the fields of insect movement ecology and population dynamics.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».