Sub-regional variation in atmospheric and land variables regulates tea yield in the Dooars region of West Bengal, India
Abstract Climatic variables can have localized variations within a region and these localized climate patterns can have significant effect on production of climate-sensitive crops such as tea. Even though tea cultivation and industries significantly contribute to employment generation and foreign earnings of several South Asian nations including India, sub-regional differences in the effects of climatic and soil variables on tea yield have remained unexplored since past studies focused on a tea-producing region as a whole and did not account for local agro-climatic conditions. Here, using a garden-level panel dataset based on tea gardens of Dooars region, a prominent tea-producing region in India, we explored how sub-regional variations in climatic and land variables might differently affect tea yield within a tea-producing region. Our analysis showed that the Dooars region harboured significant spatial variability for different climatic (temperature, precipitation, surface solar radiation) and soil temperature variables. Using graph-based Louvain clustering of tea gardens, we identified four spatial sub-regions which varied in terms of topography, annual and seasonal distribution of climatic and land variables and tea yield. Our sub-region-specific panel regression analyses revealed differential effects of climatic and land variables on tea yield of different sub-regions. Finally, for different emission scenario, we also projected future (2025–2100) tea yield in each sub-region based on predictions of climatic variables from three GCMs (MIROC5, CCSM4 and CESM1(CAM5)). A large variation in future seasonal production changes was projected across sub-regions (−23.4–35.7% changes in premonsoon, −4.2–3.1% changes in monsoon and −10.9–10.7% changes in postmonsoon tea production, respectively)..
| Medienart: |
Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:67 |
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| Enthalten in: |
International journal of biometeorology - 67(2023), 10 vom: 21. Juli, Seite 1591-1605 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Mallik, Piyashee [VerfasserIn] |
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| Links: |
Volltext [lizenzpflichtig] |
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| Themen: |
Atmospheric variable |
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| Anmerkungen: |
© The Author(s) under exclusive licence to International Society of Biometeorology 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| doi: |
10.1007/s00484-023-02521-4 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
OLC2145219560 |
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| 520 | |a Abstract Climatic variables can have localized variations within a region and these localized climate patterns can have significant effect on production of climate-sensitive crops such as tea. Even though tea cultivation and industries significantly contribute to employment generation and foreign earnings of several South Asian nations including India, sub-regional differences in the effects of climatic and soil variables on tea yield have remained unexplored since past studies focused on a tea-producing region as a whole and did not account for local agro-climatic conditions. Here, using a garden-level panel dataset based on tea gardens of Dooars region, a prominent tea-producing region in India, we explored how sub-regional variations in climatic and land variables might differently affect tea yield within a tea-producing region. Our analysis showed that the Dooars region harboured significant spatial variability for different climatic (temperature, precipitation, surface solar radiation) and soil temperature variables. Using graph-based Louvain clustering of tea gardens, we identified four spatial sub-regions which varied in terms of topography, annual and seasonal distribution of climatic and land variables and tea yield. Our sub-region-specific panel regression analyses revealed differential effects of climatic and land variables on tea yield of different sub-regions. Finally, for different emission scenario, we also projected future (2025–2100) tea yield in each sub-region based on predictions of climatic variables from three GCMs (MIROC5, CCSM4 and CESM1(CAM5)). A large variation in future seasonal production changes was projected across sub-regions (−23.4–35.7% changes in premonsoon, −4.2–3.1% changes in monsoon and −10.9–10.7% changes in postmonsoon tea production, respectively). | ||
| 650 | 4 | |a Tea yield | |
| 650 | 4 | |a Atmospheric variable | |
| 650 | 4 | |a Soil temperature | |
| 650 | 4 | |a Sub-regional variation | |
| 650 | 4 | |a Panel regression | |
| 650 | 4 | |a Climate model projections | |
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