Evaluating the relative influence of climate and human activities on recent vegetation dynamics in West Bengal, India

Abhishek Banerjee, Shichang Kang, Michael E. Meadows, Wasim Sajjad, Ali Bahadur, Muhammad Farhan Ul Moazzam, Zilong Xia, Joseph Mango, Bappa Das, Kelly L. Kirsten

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Assessing the relative importance of climate change and human activities is important in developing sustainable management policies for regional land use. In this study, multiple remote sensing datasets, i.e. CHIRPS (Climate Hazard Group InfraRed Precipitation with Station Data) precipitation, MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), Potential Evapotranspiration (PET), Soil Moisture (SM), WorldPop, and nighttime light have been analyzed to investigate the effect that climate change (CC) and regional human activities (HA) have on vegetation dynamics in eastern India for the period 2000 to 2022. The relative influence of climate and anthropogenic factors is evaluated on the basis of non-parametric statistics i.e., Mann-Kendall and Sen's slope estimator. Significant spatial and elevation-dependent variations in precipitation and LST are evident. Areas at higher elevations exhibit increased mean annual temperatures (0.22 °C/year, p < 0.05) and reduced winter precipitation over the last two decades, while the northern and southwest parts of West Bengal witnessed increased mean annual precipitation (17.3 mm/year, p < 0.05) and a slight cooling trend. Temperature and precipitation trends are shown to collectively impact EVI distribution. While there is a negative spatial correlation between LST and EVI, the relationship between precipitation and EVI is positive and stronger (R2 = 0.83, p < 0.05). Associated hydroclimatic parameters are potent drivers of EVI, whereby PET in the southwestern regions leads to markedly lower SM. The relative importance of CC and HA on EVI also varies spatially. Near the major conurbation of Kolkata, and confirmed by nighttime light and population density data, changes in vegetation cover are very clearly dominated by HA (87%). In contrast, CC emerges as the dominant driver of EVI (70–85%) in the higher elevation northern regions of the state but also in the southeast. Our findings inform policy regarding the future sustainability of vulnerable socio-hydroclimatic systems across the entire state.
Original languageEnglish
Article number118450
Number of pages12
JournalEnvironmental Research
Volume250
Early online date13 Feb 2024
DOIs
Publication statusPublished - 1 Jun 2024

Funder

This study was supported by the Second Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0605), Gansu Provincial Science and Technology Program (22ZD6FA005), and the Gansu Postdoctoral Science Foundation (E339880202). The authors would like to acknowledge all the remote sensing agencies to provide high-resolution long-term datasets.

Keywords

  • Anthropogenic activities
  • Climate variation
  • Google earth engine
  • Non-parametric trend test
  • Vegetation dynamics
  • West Bengal

ASJC Scopus subject areas

  • Environmental Science(all)
  • Biochemistry

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