Detecting phenological changes in plant functional types over West African savannah dominated landscape

Phenology is an important component in the climate system, and play a key role in controlling many feedbacks of vegetation to the climate systems. Differences in phenology of plant functional types (PFTs) due to the variation in seasonal cycles (e.g. changes in weather variability), the impact from land-use activities (e.g. fire) and their mechanisms for adaptation (e.g. climate change, regrowth/post-fire regeneration) have major implications in conservation planning and monitoring actions. Detecting phenological variations in PFTs is therefore of great importance to quantitative remote sensing applications, especially in a biome as diverse and complex as savannah. In this study, we implement Savitzky–Golay filtering and the Breaks For Additive Seasonal and Trend (BFAST) algorithms to detect changes in PFTs based on their phenological events using Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI) data from 2001 to 2018. In this region, PFTs present distinct seasonal, annual and interannual variability. Woody phenology presents early green-up dates with a prolonged senescence period and invariably observed the longest growing season length (GSL). The relationship between the start of season (SOS) or end of season (EOS) was assessed for each PFT to find out the extent to which they determine GSL for different PFTs. GSL is mostly determined by the SOS in woody savannah (coefficient of determination (R²) =0.41, p <0.01), open shrubs and (R² =0.79, p <0.001), grassland (R² =0.35, p <0.01) while EOS determined the GSL for both dryland crops (R² =0.75, p <0.001) and paddy rice (R² =0.69, p <0.001). We compared the interannual variability of woody savannah and other PFTs by measuring the differences of their phenological indicators using Welch’s t-test. All PFTs show statistically significant difference with the GSL of woody savannah except open shrubs (p = 0.23). The abrupt vegetation changes estimated with BFAST varied by PFT. Some PFTs are more resilient to harsh environmental conditions than others. While woody species present a few abrupt changes, grass phenology is more vulnerable to disturbance, seasonally as well as in the trend components (large number of abrupt changes) with browning trend following an abrupt negative change. In all PFTs, breakpoint (disturbance) assessed using BFAST negatively correlate with precipitation data which means the magnitude of disturbance decreases with increasing precipitation. Woody species had an r (correlation coefficient) value of -0.5 while grassland had r = -0.7 which is a further indication that grass phenology responds more strongly to annual precipitation than the woody species. These results show that MODIS NDVI time-series data can be used to distinguish the phenological events of different PFTs in West African savannah dominated landscape.