Climate adaptation turning points in cacao production in the Peruvian Amazon
Notice bibliographique
Résumé
Cacao farmers in Peru aim to have an economic activity that delivers sustained income and allows them to achieve an acceptable quality of life. Their main challenges comprise drought, pests and diseases. For farmers, droughts of two weeks during the harvest season are critical, because they reduce the yield that could be harvested and commercialized. Drought stress also turns cacao trees more vulnerable to attacks of pests and diseases. \nThe climate conditions where farmers perceive undesirable conditions were identified at a precipitation 32°C in the study area located in San Martin. Further critical climatic variables are: precipitation of the driest month, maximum temperature of the warmest month, as well as precipitation of the driest quarter and mean temperature of the driest quarter. \nIn San Martin cacao already faces current maximum temperatures that exceed its optimum range and reach an average maximum of 32°C during the warmest month of the year. Climate projections show a clear increasing trend in temperature for the future. Models project an average of 34.8°C for 2050 under RCP 4.5 and up to 37.9°C by 2070 under RCP 8.5. Some localities in the study area also receive precipitation lower than 100 mm/ month during the driest month and the driest quarter under current conditions. Although there is variability among projections and RCP, models project a decrease in precipitation for the driest month and driest quarter under RCP 8.5. \nThe suitability models show that the distribution range of cacao is mostly projected to remain suitable. Areas that may gain in suitability are located along a narrow NNW - SSE stripe along the Andes at higher elevations. In contrast, losses are projected along the Andean foothills and lower Amazon basin, especially towards 2070. Diseases follow a similar geographic trend. However, for some diseases the loss of suitable areas is prominent along large areas at the eastern Andean slopes and towards the lower Amazon. Insects’ responses vary under future scenarios. Carmenta sp. maintains large suitable areas in San Martin and Monalonion sp. gains in suitable areas under RCP 8.5. \nThis work shows the added value of integrated approaches, especially by adding performance thresholds and incorporating stakeholders’ perceptions into ecological modelling. In addition, to the author’s knowledge, this work is the first to model cacao together with varied cacao pests and diseases in a single modelling exercise. \nThere is a diversity of stakeholders in the Peruvian cacao sector, who require practical information on climate change impacts on cacao, its pests and diseases, as well as adaptation possibilities. Thanks to scientific platforms as well as stakeholder networks, there is an opportunity and momentum to share the results of this work.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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 ».