摘要
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 mperature/Evapotranspiration Grass (p < 0.311), and Temperature/Normalized Difference Vegetation Index (p in vegetation detected by the Breaks for Additive Season and Trend Algorithms were caused by temperature extremes and reduced rainfall.
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 mperature/Evapotranspiration Grass (p < 0.311), and Temperature/Normalized Difference Vegetation Index (p in vegetation detected by the Breaks for Additive Season and Trend Algorithms were caused by temperature extremes and reduced rainfall.
作者
Christian Jonathan Anoma Kouassi
Dilawar Khan
Lutumba Suika Achille
James Kehinde Omifolaji
Mikouendanandi Mouendo Rahmat Brice Espoire
Kebin Zhang
Xiaohui Yang
Christian Jonathan Anoma Kouassi;Dilawar Khan;Lutumba Suika Achille;James Kehinde Omifolaji;Mikouendanandi Mouendo Rahmat Brice Espoire;Kebin Zhang;Xiaohui Yang(School of Soil and Water Conservation, Beijing Forestry University, Beijing, China;School of Ecology and Nature Conservation, Beijing Forestry University, Beijing, China;Department of Forestry and Wildlife Management, Federal University Dutse, Dutse, Jigawa State, Nigeria;School of Economics and Management, Beijing Forestry University, Beijing, China;Institute of Desertification Studies, Chinese Academy of Forestry, Beijing, China)
