CUBE ChatShaala Summary – 09/11/2025
Topic: Mango Flowering in Bangalore – Shama’s Place and mapping across country
The discussion centered around the ongoing Mango Flowering Mapping Project, where data were collected from different regions across India to track seasonal patterns in mango flowering and fruiting.
Key Observations
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Mumbai (Sneha’s observation):
- Sample size: 30
- Flowering: 6 trees (20%)
- Fruiting: 7 trees (23.33%)
- Expected flowering rate: Initially 50%, now adjusted to 30%.
- October vs. November: No significant change—indicating a stable pattern.
- Sneha’s Hypothesis: Mango trees are following the same reproductive cycle.
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Thrissur (Seethalakshmi’s observation):
- Sample size: 10
- Flowering: 6 trees (60%)
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Trivandrum (Sailekshmi’s observation):
- Sample size: 10
- Flowering: 7 trees (70%)
This data visualized across a map of India shows regional variation, with higher flowering percentages in southern regions (Kerala) compared to Bangalore.
Learning Highlights
- Environmental and climatic variations influence the flowering pattern of mangoes across regions.
- The hypothesis of a synchronized flowering cycle raises new questions about whether mango trees across latitudes experience common triggers such as temperature, rainfall, or daylight hours.
- The comparison between October and November indicates a possible plateau phase rather than a rise in flowering activity.
Tinke Moments (This I Never Knew Earlier)
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Linking local to global: Cubists realized that a local observation can become part of a larger citizen-science dataset.
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Critical observation: Adjusting expectations (from 50% to 30%) reflects real-time scientific thinking.
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Pattern recognition: Seeing the same flowering percentage across months led to rethinking assumptions about progression in flowering cycles.
Gaps & Misconceptions
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Some Cubists assumed flowering should always increase monthly, which the data contradicted.
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The relationship between temperature, rainfall, and flowering was discussed but remains unclear—needing systematic environmental data.
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The assumption that flowering equals fruiting was challenged by the differing percentages.
Provocative Questions to Inspire the Community
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Why are flowering percentages higher in Kerala compared to Bangalore?
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Could latitude and local climate conditions be synchronizing or desynchronizing mango flowering?
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What other factors—such as age of the tree, pruning, or soil type—might affect flowering rate?
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How can we correlate flowering data with temperature and rainfall patterns over time?
Reflection: What I Learned
Today’s ChatShaala deepened my understanding of how collaborative data collection reveals patterns invisible at the local level. It showed how real scientific thinking involves questioning expectations, re-evaluating data, and identifying unknowns. Every small observation contributes to a larger ecological understanding of seasonal rhythms in plants.
photographs during Chatshaala