Author(s)

Christian Jonathan Anoma Kouassi¹, Dilawar Khan¹, Lutumba Suika Achille¹, James Kehinde Omifolaji^2,3, Mikouendanandi Mouendo Rahmat Brice Espoire⁴, Kebin Zhang¹, Xiaohui Yang^5*

¹School of Soil and Water Conservation, Beijing Forestry University, Beijing, China.
²School of Ecology and Nature Conservation, Beijing Forestry University, Beijing, China.
³Department of Forestry and Wildlife Management, Federal University Dutse, Dutse, Jigawa State, Nigeria.
⁴School of Economics and Management, Beijing Forestry University, Beijing, China.
⁵Institute of Desertification Studies, Chinese Academy of Forestry, Beijing, China.

Lamto Reserve area is a savannah landscape threatened by periodic drought, and anthropogenic activities leading to natural ecological imbalance. The ecological support services of the landscape had been significantly impacted by the grassland ecosystem. The Breaks for Additive Season and Trend Algorithms have been implemented in R to analyze the land cover/land use dynamic in relation to the climatic driver of Lamto forest from 2000 to 2020. We examine the vegetation state breaks using vegetation phenological patterns, and several time series including the Normalized Difference Vegetation Index and the Enhanced Vegetation Index, were studied utilizing Breaks for Additive Season and Trend. The findings indicate that the phenological changes in the vegetation in 2020 resulted from an increased temperature from (27.7°C) to (32.17°C), and a decrease in precipitation (71.75 millimeters). The analysis of variance ANOVA of the non-parametric Mann-Kendall test reveals a strong correlation between Precipitation/Evapotranspiration Grass (p < -0.413), Temperature/Evapotranspiration Grass (p < 0.311), and Temperature/Normalized Difference Vegetation Index (p < -0.468). The findings show that the breaks in vegetation detected by the Breaks for Additive Season and Trend Algorithms were caused by temperature extremes and reduced rainfall.

Assessing, Break, Change Detection, Land Cover, Climate Extreme, Vegetation Vulnerability

Anoma Kouassi, C. , Khan, D. , Achille, L. , Omifolaji, J. , Espoire, M. , Zhang, K. and Yang, X. (2022) Assessing Change of Lamto Reserve Area Based on the MODIS Time Series Data and Bioclimatic Factors Using BFAST Algorithms. American Journal of Plant Sciences, 13, 517-540. doi: 10.4236/ajps.2022.134034.