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By 2040, climate change and human activities are expected to result in the loss of 49-55 per cent of the vegetation cover in the forest regions of Mount Kenya, according to a new study published in the journal Springer Nature on May 06, 2025.
Although extensive studies have been conducted on how climate change affects forest ecosystems worldwide, there are still crucial gaps in our understanding. This study uses multi-temporal satellite imagery, climate data and advanced machine learning models to analyse and predict the future vulnerability of forest ecosystem conditions, focusing on the Mount Kenya Forest Ecosystem (MKFE), to bridge these gaps.
Mt Kenya, the tallest peak in Kenya, is renowned for its varied ecosystems, spanning from montane forests to afro-alpine regions. It was chosen for research due to its ecological and hydrological importance, acting as a key biodiversity hotspot and crucial water source for Kenya, providing more than 40 per cent of the country’s freshwater. The varied vegetation zones on the mountain provide an ideal setting for examining how climate influences forest dynamics.
Moreover, Mt Kenya has experienced notable climate variability and anthropogenic pressures, making it a suitable case study for evaluating climate-vegetation interactions.
Mt Kenya’s glaciers rapidly vanished, mainly due to rising temperatures, intensifying hydrological imbalances, reducing water availability for both human and ecological needs. As a result, lower montane forests, which depend on stable moisture conditions, are experiencing increased vulnerability to drought stress and biomass loss.
Moreover, human activities such as illegal logging, agricultural encroachment and unregulated grazing exacerbate forest degradation, further threatening ecosystem stability.
Kenya's forests are under a severe and immediate threat due to swift deforestation. From 2002 to 2021, the nation experienced a 14 per cent reduction in its forest cover, losing around 5,000 hectares annually. The primary factors driving the depletion of this vital ecosystem are unregulated grazing, agricultural growth, timber harvesting, charcoal manufacturing, and poor forest management.
This research combines remote sensing with machine learning to evaluate past vegetation changes and forecast future risk areas. Landsat images from 2000 to 2020 were utilized to extract vegetation indices, including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil-Adjusted Vegetation Index (SAVI), and Bare Soil Index (BSI).
The study’s results reveal distinct temporal and spatial patterns in vegetation health across Mt Kenya.
Between 2000 and 2010, there was a significant improvement in vegetation indices attributed to favourable precipitation conditions and conservation efforts. However, from 2010 to 2020, a notable decline was observed.
Decline in vegetation health, particularly a 45.4 per cent decline in NDVI, 13.3 per cent decrease in EVI, 8.3 per cent decline in SAVI and 55.1 per cent increase in BSI, indicated widespread vegetation loss and bare soil exposure, according to the study.
These connections suggest that intense precipitation and temperature fluctuations are crucial factors influencing forest dynamics in MKFE. Significant vegetation loss was observed in lower montane regions, increasing their susceptibility to climate-related degradation.
Conversely, upper montane areas showed vegetation enhancement, whereas central zones experienced minimal alterations, highlighting the spatial diversity in climate effects.
The findings of the research emphasise the combined effects of deforestation, agricultural growth and climate-related stressors like unpredictable rainfall and increasing temperatures. This highlights the necessity to promptly address the reasons behind deforestation and put climate adaptation strategies into action.