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Modeling the Underlying Drivers of Natural Vegetation Occurrence in West Africa with Binary Logistic Regression Method

doi: 10.3390/su13094673
The occurrence of natural vegetation at a given time is determined by interplay of multiple drivers. The effects of several drivers, e.g., geomorphology, topography, climate variability, accessibility, demographic indicators, and changes in human activities on the occurrence of natural vegetation in the severe drought periods and, prior to the year 2000, have been analyzed in West Africa. A binary logistic regression (BLR) model was developed to better understand whether the variability in these drivers over the past years was statistically significant in explaining the occurrence of natural vegetation in the year 2000. Our results showed that multiple drivers explained the occurrence of natural vegetation in West Africa at p < 0.05. The dominant drivers, however, were site-specific. Overall, human influence indicators were the dominant drivers in explaining the occurrence of natural vegetation in the selected hotspots. Human appropriation of net primary productivity (HANPP), which is an indicator of human socio-economic activities, explained the decreased likelihood of natural vegetation occurrence at all the study sites. However, the impacts of the remaining significant drivers on natural vegetation were either positive (increased the probability of occurrence) or negative (decreased the probability of occurrence), depending on the unique environmental and socio-economic conditions of the areas under consideration. The study highlights the significant role human activities play in altering the normal functioning of the ecosystem by means of a statistical model. The research contributes to a better understanding of the relationships and the interactions between multiple drivers and the response of natural vegetation in West Africa. The results are likely to be useful for planning climate change adaptation and sustainable development programs in West Africa.
- Chinese Academy of Sciences China (People's Republic of)
- "TECHNISCHE UNIVERSITEIT DELFT Netherlands
- Chinese Academy of Science China (People's Republic of)
- Delft University of Technology Netherlands
- Chinese Academy of Sciences (中国科学院) China (People's Republic of)
Climate, Underlying drivers, binary logistic regression, TJ807-830, Binary logistic regression, 910, TD194-195, natural vegetation, Renewable energy sources, Human activities, West Africa, GE1-350, climate, underlying drivers, Environmental effects of industries and plants, Natural vegetation, Environmental sciences, human activities
Climate, Underlying drivers, binary logistic regression, TJ807-830, Binary logistic regression, 910, TD194-195, natural vegetation, Renewable energy sources, Human activities, West Africa, GE1-350, climate, underlying drivers, Environmental effects of industries and plants, Natural vegetation, Environmental sciences, human activities
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).5 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10% visibility views 11 download downloads 4 - 11views4downloads
Data source Views Downloads TU Delft Repository 11 4


