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Modelling the Potential Ecological Niche of Fagus (Beech) Forest in Majella National Park, Italy

Gelete, Desalegn Chala (2010) Modelling the Potential Ecological Niche of Fagus (Beech) Forest in Majella National Park, Italy.

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Abstract:Beech forest is the dominant forest type in the Italian Apennines including in the Majella National Park. Following depopulation and improvement of social and economic conditions within the Apennine mountain communities since the middle of the last century, the forest is spontaneously expanding to claim its ecological niche that had been masked by the anthropogenic impacts. Though, the expansion has both positive and negative social and ecological significances, owing to the closed canopy and allelopathic effect of beech forest and the presence of large number of endemic taxa in the other habitat types, the adverse impact may be high on the unique floral life of the national park. Thus the main target of this paper is to investigate the underlining environmental factors that determine the ecological niche of beech forest and to predict the forthcoming areas (land cover types) to which the forest potentially spreads out. To achieve the objective, ranges of topo-climatic variables [altitude, slope angle, slope aspect, incoming solar radiation (ISR) of the hottest and coldest months] were derived from a 30 m resolution raster cells of aster DEM for the whole national park and for the areas of the park which is covered by the beech forest in the secondary vegetation map in ARC GIS 9.3. For each raster values of these variables, the ratio of pixel counts containing beech forest to total pixel counts of the national park having corresponding raster values were calculated. Kruskal-Wallis test was carried out in SPSS version 16; to check the preference of the beech forest certain ranges of ratios of the topo-climatic variables to the others. To model the ecological niche of the beech forest, maximum entropy model (Maxent 3.2) was selected and run with 1000 presence data that has been randomly generated in the beech land cover type in the secondary vegetation map using Hawth’s tool in ARC GIS 9.3. All the DEM derived topo-climatic variables were used in the model along with the soil parameter as potential niche determining ecological variables of the beech forest. The model was trained with 75% of the presence data and tested with the rest, 25%. Evaluation of the model was carried out using area under the ROC curve (AUC).The model output was further classified into four probability classes of habitat suitability and overlaid with the land cover map of the study area to investigate the land cover types that share common ecological niche with the beech forest and thus under the potential threat of the forest expansion. Though, there is a tendency of the pixels containing beech forest to aggregate on the north facing slope aspects and gentle slope angles, the Kruskal-Wallis test supports only the preference of the forest to lower ISR of the hottest months and altitudinal ranges of 1000 m to 1, 800 m a. s . l. (P < 0.05). The heuristic estimate of the relative contributions of environmental variables in the Maxent model also shows the environmental variable with highest gain when used in isolation is altitude, which therefore appears to have the most useful information by itself followed by ISR of the hottest month with the contribution of 77.6 % and 10.1%, respectively (AUC = 0.81 for the test data). The soil variable, the slope angle, ISR of the coldest months and slope aspect hardly contributed 4.8%, 3.8%, 3.5% and 0.3% to the overall model output in their respective order. The result obtained by overlaying the model output with the secondary vegetation map shows, sparse grass/dwarf shrub, bare rock, subalpine pasture, shrub wood and abandoned crop lands have remarkable spatial extent within the high probable ecological niche of the beech forest. Key words: Area under the ROC curve (AUC), Beech, Ecological niche, Maximum entropy model, Kruskal-Wallis test, Topo-climatic variables
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
Link to this item:https://purl.utwente.nl/essays/90745
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