NDVI-Derived Vegetation Trends and Driving Factors in West African Sudanian Savanna

The Sudanian savanna is a key vegetation biome in West Africa providing food and vital ecosystem services. Recently, it has been reported alarming vegetation loss in this biome, calling for more investigation, relevant to tackle land degradation and ensure food security. However, vegetation dynamics in this area remains a matter of debate, and one of the main challenges is to document consistently the underlying driving factors. This study aimed at assessing vegetation trends and driving factors from 2000 to 2022. NDVI trend, detected using the Mann-Kendall’s monotonic trend test, was used as proxy to express vegetation dynamics. In addition to the non-parametric Spearman correlation analysis, variables importance scores, derived from Random Forest (RF) classifications, were used to determine key driving factors among climatic, topographic, edaphic, accessibility and demographic factors. During 2000-2022, no significant trends largely characterised the vegetation cover of the study area. However, patterns of strong (weak) browning and strong (weak) greening affected 7.1% (10.6%) and 12.8% (19.1%) of the study area respectively. According to the driving factors analysis, the observed vegetation trends were mainly driven by rainfall dynamics (trend and mean annual), population growth and anthropogenic activities. The results of this study can support the development of efficient strategies for safeguarding vegetation cover in the Sudanian savanna of Burkina Faso.

Forest aboveground biomass estimates in a tropical rainforest in Madagascar: new insights from the use of wood specific gravity data

To generate carbon credits under the Reducing Emissions from Deforestation and forest Degradation program（REDD＋）, accurate estimates of forest carbon stocks are needed. Carbon accounting efforts have focused on carbon stocks in aboveground biomass（AGB）.Although wood specific gravity（WSG） is known to be an important variable in AGB estimates, there is currently a lack of data on WSG for Malagasy tree species. This study aimed to determine whether estimates of carbon stocks calculated from literature-based WSG values differed from those based on WSG values measured on wood core samples. Carbon stocks in forest biomass were assessed using two WSG data sets：（i） values measured from 303 wood core samples extracted in the study area,（ii） values derived from international databases. Results suggested that there is difference between the field and literaturebased WSG at the 0.05 level. The latter data set was on average 16 % higher than the former. However, carbon stocks calculated from the two data sets did not differ significantly at the 0.05 level. Such findings could be attributed to the form of the allometric equation used which gives more weight to tree diameter and tree height than to WSG. The choice of dataset should depend on the level of accuracy（Tier II or III） desired by REDD＋. As higher levels of accuracy are rewarded by higher prices, speciesspecific WSG data would be highly desirable.