GIS-based assessment of climate change impacts on forest habitable Aframomum corrorima (Braun) in Southwest Ethiopia coffee forest GIS-based assessment of climate change impacts on forest habitable Aframomum corrorima (Braun) in Southwest Ethiopia coffee forest

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Vol17 No.10: 2432-2446

Title】GIS-based assessment of climate change impacts on forest habitable Aframomum corrorima (Braun) in Southwest Ethiopia coffee forest

Author】Ayehu FEKADU1*; Teshome SOROMESSA1; Bikila Warkineh DULLO2

Addresses】1 Center of Environmental Science, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia; 2 Department of Plant Biology and Biodiversity Management, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia

Corresponding author】Ayehu FEKADU

Citation】Fekadu A, Soromessa T, Dullo BW (2020) GIS-based assessment of climate change impacts on forest habitable Aframomum corrorima (Braun) in Southwest Ethiopia coffee forest. Journal of Mountain Science 17(10). https://doi.org/10.1007/s11629-019-5722-2

DOI】https://doi.org/10.1007/s11629-019-5722-2

Abstract】Climate change is thought to have a greater impact on crops that require particular conditions for their productivity. Southwest Ethiopia is a region where important cash crops such as Coffeaarabica and Aframomum corrorima (korerima) originate. These crops are known to require shade for their growth and productivity. This study was conducted to assess the impacts of climate change on an important but neglected cash crop of A. corrorima using GIS-based species distribution approaches. Local meteorological data and bioclimatic data from WorldClim were used to map past, present, and future distribution of the crop in the Coffee Forest System of Southwest Ethiopia. Moreover, 96 key informants were interviewed and completed questionnaires to complement the distribution modeling. The key informants mapped the history and present occurrences of A. corrorima and based on this,ground-truthing survey was conducted. The interpolation method of the Inverse Distance Weighted was used in ArcGIS 10.5 to develop bioclimatic variables for modelingpast and present distribution while data from IPCC (AR4) Emissions Scenarios was used for the future occurrence prediction using Principal Component Analysis.Eleven best bioclimatic variables were selected and MaxEnt was used to model past, present and future distribution of A. corrorima. The output of our model was validated using Area Under the Curve (AUC) approach. Temperature and precipitation are the most important environmental variable, then temperature increased by 1.3°C in the past (from 1988 to 2018) while it is predicted to increase further by at least 1.4°C before 2050. On the contrary, precipitation decreased by an average of 10.1 mm from the past while it is predicted to decrease further by 12.5 mm before 2050. Our model shows that the area suitable for korerima in 1988 was 20,638.2 ha and it was reduced by half and became 10,545.3 ha in 2018, similarly predicted to shrink into 3225.5 ha by 2050. The findings from the key informants confirm the model results whereby 89.1% of the respondent replied korerima producing area has been shifted into the mountains over the last 30 years (by 150 m a.s.l. from 1988to 2018) and thus expected to be pushing upin the next 32 years (by 133 m before 2050). The community claims that the length of the rainy season of the area has been shortening from 9 months in the past to an average of 5.5 months recently which also coincides with increasing temperature. We conclude that with thechanging climatic condition,the suitable habitat of korerima has already shrank by 48.9%(from 1988 to 2018) and the trend may lead to a shrink by84.38% before 2050 (from 1988 to 2050). Therefore, it is important to develop site-specific climate adaptation strategies for the region such as promoting alternative livelihoods and avoidingfurther coffee forest degradation and deforestation.

KeywordsAframomum corrorima;Coffee forest;Bioclimatic variables;Suitability;GIS;MaxEnt