article · Heliyon
Long-term analysis of the Beressa watershed in the Ethiopian Highlands shows substantial structural changes in landscape cover between 1972 and 2017, with projections extending to 2047. Satellite imagery reveals that natural vegetation, grassland, barren land, and waterbodies shrank drastically, with natural vegetation declining by nearly ninety percent. Concurrently, plantation cover surged by over six hundred and ninety percent, while settlements and farmland expanded steadily. These shifts reflect intensifying human activity, resulting in severe fragmentation and depletion of natural habitats over the forty-five-year period. Landscape metrics showed an initial rise in overall patch numbers across several land categories, though natural vegetation patches dropped significantly. Future projections through 2032 and 2047 anticipate a reversal in patch numbers, indicating reduced fragmentation and the consolidation of land into fewer, larger patches dominated by human land uses.
Understanding how watersheds transform over decades helps communities and authorities recognise the impacts of human expansion on vital natural habitats. The dramatic depletion of natural vegetation and water bodies in critical highlands highlights severe ecological pressures. Reliable historical and predictive models offer environmental decision-makers crucial insights needed to design effective resource conservation programmes and reverse unsustainable habitat loss.
The abstract suggests these spatial metrics and forecasting methods can support landscape management planning and resource conservation decision-making. Potential end users include environmental planning agencies, conservation bodies, and land-use regulators seeking data to guide zoning and ecological interventions. This represents early-stage decision-support research that would require translation into dedicated planning software, data services, or formal consultancy toolkits before achieving direct operational use.
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Analyzing long-term dynamics of landscape patterns can provide important insights into the changes in landscape functions, that are necessary for optimizing resource management strategies. This study primarily aimed at quantifying landscape structural change. The Land use/land cover (LULC) layers of 1972, 1987, 2002, and 2017 were mapped from Landsat images, and projected to 2032 and 2047. Factor analysis was then employed to select independent core metrics of landscape composition and configuration to characterize the landscape. A post-classification comparison indicated that, between 1972 and 2017, natural vegetation, grassland, barren land and waterbody covers declined by 89.9%, 67.9%, 67.8 and 15.9%, respectively. On the other hand, plantation increased by 692.1% followed by human settlement (138%) and farmland (21.8%). A similar trend is likely to continue in 2032 and 2047 with a slight decline in the plantation category in 2047. Analysis of landscape metrics revealed that between 1972 and 2017, the number of patches increased. Specifically, plantation, barren land, settlement and grassland increased by 171.4%, 69.7%, 65.8% and 28.6%, respectively. In contrast, natural vegetation, farmland and waterbody declined by 53.1%, 46.3% and 33.9%, respectively. Future predictions showed a declining trend of the number of patches for all LULC types. An increasing trend in the largest patch index and patch size for farmland, plantation, and settlement categories was observed across all years, suggesting intensified human activities in the landscape. Consequently, natural habitat category has declined and become fragmented. Landscape pattern has changed considerably and become more fragmented over the last 45 years. Nevertheless, the future projections suggest a decline in fragmentation and potentially increased assemblage of patches forming simple patterns with fewer number of large size class patches. The results of this study could perhaps be applied in designing strategies for landscape management planning and resource conservation decision-making.
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DOI: 10.1016/j.heliyon.2020.e04859
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