Sub-regional variation in atmospheric and land variables regulates tea yield in the Dooars region of West Bengal, India

© 2023. The Author(s) under exclusive licence to International Society of Biometeorology..

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:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:67

Enthalten in:

International journal of biometeorology - 67(2023), 10 vom: 21. Okt., Seite 1591-1605

Sprache:

Englisch

Beteiligte Personen:

Mallik, Piyashee [VerfasserIn]
Ghosh, Tuhin [VerfasserIn]

Links:

Volltext

Themen:

Atmospheric variable
Climate model projections
Journal Article
Panel regression
Soil
Soil temperature
Sub-regional variation
Tea
Tea yield

Anmerkungen:

Date Completed 15.09.2023

Date Revised 15.09.2023

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1007/s00484-023-02521-4

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM35980103X