Assessing the Impact of Wildlife on Vegetation Cover Change, Northeast Namibia, Based on MODIS Satellite Imagery (2002-2021)

Sensors (Basel). 2022 May 25;22(11):4006. doi: 10.3390/s22114006.

Abstract

Human-wildlife conflict in the Zambezi region of northeast Namibia is well documented, but the impact of wildlife (e.g., elephants) on vegetation cover change has not been adequately addressed. Here, we assessed human-wildlife interaction and impact on vegetation cover change. We analyzed the 250 m MODIS and ERA5 0.25° × 0.25° drone and GPS-collar datasets. We used Time Series Segmented Residual Trends (TSS-RESTREND), Mann-Kendall Test Statistics, Sen's Slope, ensemble, Kernel Density Estimation (KDE), and Pearson correlation methods. Our results revealed (i) widespread vegetation browning along elephant migration routes and within National Parks, (ii) Pearson correlation (p-value = 5.5 × 10-8) showed that vegetation browning areas do not sustain high population densities of elephants. Currently, the Zambezi has about 12,008 elephants while these numbers were 1468, 7950, and 5242 in 1989, 1994, and 2005, respectively, (iii) settlements and artificial barriers have a negative impact on wildlife movement, driving vegetation browning, and (iv) vegetation greening was found mostly within communal areas where intensive farming and cattle grazing is a common practice. The findings of this study will serve as a reference for policy and decision makers. Future studies should consider integrating higher resolution multi-platform datasets for detailed micro analysis and mapping of vegetation cover change.

Keywords: MODIS; Mann–Kendall; TSS-RESTREND; Zambezi region; drivers of deforestation; greening and browning; land degradation; vegetation cover change; vegetation monitoring; wildlife management.

MeSH terms

  • Animals
  • Animals, Wild
  • Cattle
  • Ecosystem
  • Elephants*
  • Namibia
  • Satellite Imagery*

Grants and funding

We acknowledge the Government of Namibia (Ministry of Environment, Tourism and Forestry), especially the, University of Eastern Finland and the Kone Foundation for funding. CSC–IT Centre for Science, Finland (urn:nbn:fi:research-infras-2016072531) and the Open Geospatial Information Infrastructure for Research (Geoportti, urn:nbn:fi:research-infras-2016072513) for computational resources and support.