Multi-Decadal Mapping and Climate Modelling Indicates Eastward Rubber Plantation Expansion in India

Pulakesh Das, Rajendra Mohan Panda, Padmanava Dash, Anustup Jana, Avijit Jana, Debabrata Ray, Poonam Tripathi and Venkatesh Kolluru
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Pulakesh Das: Sustainable Landscapes and Restoration, World Resources Institute India, New Delhi 110016, India
Rajendra Mohan Panda: Geosystems Research Institute, Mississippi State University, Mississippi State, MS 39759, USA
Padmanava Dash: Department of Geosciences, Mississippi State University, Mississippi State, MS 39762, USA
Anustup Jana: Department of Remote Sensing & GIS, Vidyasagar University, Midnapore 721102, India
Avijit Jana: Department of Remote Sensing & GIS, Vidyasagar University, Midnapore 721102, India
Debabrata Ray: Regional Research Station, Rubber Research Institute of India, Agartala 799006, India
Poonam Tripathi: International Centre for Integrated Mountain Development, Kathmandu 44700, Nepal
Venkatesh Kolluru: Department of Sustainability and Environment, University of South Dakota, Vermillion, SD 57069, USA

Sustainability, 2022, vol. 14, issue 13, 1-16

Abstract: Automated long-term mapping and climate niche modeling are important for developing adaptation and management strategies for rubber plantations (RP). Landsat imageries at the defoliation and refoliation stages were employed for RP mapping in the Indian state of Tripura. A decision tree classifier was applied to Landsat image-derived vegetation indices (Normalized Difference Vegetation Index and Difference Vegetation Index) for mapping RPs at two-three years intervals from 1990 to 2017. A comparison with actual plantation data indicated more than 91% mapping accuracy, with most RPs able to be identified within six years of plantation, while several patches were detected after six years of plantations. The RP patches identified in 1990 and before 2000 were used for training the Maxent species distribution model, wherein bioclimatic variables for 1960–1990 and 1970–2000 were used as predictor variables, respectively. The model-estimated suitability maps were validated using the successive plantation sites. Moreover, the RPs identified before 2017 and the Shared Socioeconomic Pathways (SSP) climate projections (SSP126 and SSP245) were used to predict the habitat suitability for 2041–2060. The past climatic changes (decrease in temperature and a minor reduction in precipitation) and identified RP patches indicated an eastward expansion in the Indian state of Tripura. The projected increase in temperature and a minor reduction in the driest quarter precipitation will contribute to more energy and sufficient water availability, which may facilitate the further eastward expansion of RPs. Systematic multi-temporal stand age mapping would help to identify less productive RP patches, and accurate monitoring could help to develop improved management practices. In addition, the existing RP patches, their expansion, and the projected habitat suitability maps could benefit resource managers in adapting climate change measures and better landscape management.

Keywords: defoliation; refoliation; landsat; NDVI; DVI; CART; shared socioeconomic pathways (SSP); maxent (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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