Ecology and Development Series No. 10, 2003 - ZEF
Ecology and Development Series No. 10, 2003 - ZEF Ecology and Development Series No. 10, 2003 - ZEF
Conservation of the wild Coffea arabica populations in situ6.2.3 Regression analysis and criteria map layers developmentDigital elevation data were overlain with sample plot locations to estimate elevation andother terrain derived data for each plot. The terrain data used as environmental or explanatoryvariables were elevation, percent slope, and aspect. In addition, the first and second PCAaxes site scores were used as explanatory variables. The response variables were abundancedata of C. arabica, and the Shannon diversity index. The abundance data of coffee was logtransformedto ensure a better fit of the values in the regression model (Jager and Looman1995).The map layers of the PCA axes were produced by regressing the PCA axes scoresagainst the terrain-derived environmental variables. The relationships of the abundance ofcoffee and Shannon diversity index with the PCA axes’ site scores and terrain data (aspect,elevation, and slope) were investigated using linear regression. Step-wise linear regressionwas used to sort out the significant explanatory variables. Those variables significant at 5%level were used in the analysis. Linear regression models were fit to the plot data, regressingcoffee abundances and Shannon diversity index against the significant explanatory variables.Table 6.1 Variable used in regression model to predict and map potential distribution patternsof coffee and diversity indexVariable Source Use1 Species abundance data Vegetation survey Response variable2 Shannon diversity index Calculated from vegetation survey Response variabledata at each plot3 PCA I site scores Vegetation survey data analysis in Explanatory variableChapter 4.3.34 PCA II site scores Vegetation survey data analysis in Explanatory variableChapter 4.3.35 Aspect Derived from DEM using Surface Explanatory variableAnalysis6 Elevation Derived from DEM using Surface Explanatory variableAnalysis7 Slope Derived from DEM using SurfaceAnalysisExplanatory variableThe resulting equations were then used to map the predicted potential distributionpattern of the response variables using the map equation function in ArcView GIS. Theresulting distribution maps were evaluated in two ways: first, the maps were visually103
Conservation of the wild Coffea arabica populations in situinspected and viewed for consistency, agreement of general trends with knownenvironmental gradients, and distribution patterns; second, the predicted results werecompared with the known data from the 57 sample plots. To compare the predicted valueswith the measured values from the sample plots, the predicted values at the plot locationswere extracted from the map. The difference between the predicted and the measured valueswere tested using the paired t-test.6.2.4 Input criteria and pre-processingThe criteria mapsThree criteria, i.e., one physical and two biological criteria, and a constraint, were used toevaluate reserve area suitability in this study. These criteria were the spatial patterns of theabundance of coffee, species diversity index, and elevation. The first two are biologicalcriteria, and were used to address the conservation of coffee and other plant species diversityin the decision. Elevation was used to incorporate the topographic position in the decisionmaking.All criteria are continuous variables. In addition to the input criteria for evaluation, aconstraint criterion of land-use right was also used to incorporate qualitative data concerningsocial suitability.The coffee criterion map is the most important map, since the major objective is toconserve the wild coffee populations occurring in the forest. The diversity of other plantspecies as the evaluation criterion was accounted for by using the map layer of the Shannondiversity index. Beside conservation of biodiversity, conservation of the landscape,especially of the riverine vegetation on steep slopes at low elevation, can also be consideredimportant part of forest conservation. Areas at lower and mid elevation in the study sites arealso more valuable for conservation, since they represent areas that are less disturbed bypeople and have a diverse plant species. This was accounted for using the elevation maplayer as a physical input criterion.Standardization of criteria mapsMulti-criteria evaluation involves different techniques of combining various criterion maplayers. The different map layers may have different units and ranges of scales. In such case,the input map layers should be transformed to a common scale or comparable unit104
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- Page 136 and 137: ReferencesBatisse M. 1986 Developin
- Page 138 and 139: ReferencesDavis A.P. and Rokotonaso
- Page 140 and 141: ReferencesESRI. 1996. ArcView GIS:
- Page 142 and 143: ReferencesIUCN 1992. Protected Area
- Page 144 and 145: ReferencesMesfin Ameha and Bayetta
- Page 146 and 147: ReferencesSmith R.F. 1985. A histor
- Page 148 and 149: ReferencesVan Jaarsveld A.S., Freit
- Page 150 and 151: Appendices9 APPENDICESAppendix 1 Li
- Page 152 and 153: AppendicesD. repandum (Vahl) DC, [H
- Page 154 and 155: AppendicesSapotaceaeAningeria altis
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Conservation of the wild Coffea arabica populations in situinspected <strong>and</strong> viewed for consistency, agreement of general trends with knownenvironmental gradients, <strong>and</strong> distribution patterns; second, the predicted results werecompared with the known data from the 57 sample plots. To compare the predicted valueswith the measured values from the sample plots, the predicted values at the plot locationswere extracted from the map. The difference between the predicted <strong>and</strong> the measured valueswere tested using the paired t-test.6.2.4 Input criteria <strong>and</strong> pre-processingThe criteria mapsThree criteria, i.e., one physical <strong>and</strong> two biological criteria, <strong>and</strong> a constraint, were used toevaluate reserve area suitability in this study. These criteria were the spatial patterns of theabundance of coffee, species diversity index, <strong>and</strong> elevation. The first two are biologicalcriteria, <strong>and</strong> were used to address the conservation of coffee <strong>and</strong> other plant species diversityin the decision. Elevation was used to incorporate the topographic position in the decisionmaking.All criteria are continuous variables. In addition to the input criteria for evaluation, aconstraint criterion of l<strong>and</strong>-use right was also used to incorporate qualitative data concerningsocial suitability.The coffee criterion map is the most important map, since the major objective is toconserve the wild coffee populations occurring in the forest. The diversity of other plantspecies as the evaluation criterion was accounted for by using the map layer of the Shannondiversity index. Beside conservation of biodiversity, conservation of the l<strong>and</strong>scape,especially of the riverine vegetation on steep slopes at low elevation, can also be consideredimportant part of forest conservation. Areas at lower <strong>and</strong> mid elevation in the study sites arealso more valuable for conservation, since they represent areas that are less disturbed bypeople <strong>and</strong> have a diverse plant species. This was accounted for using the elevation maplayer as a physical input criterion.St<strong>and</strong>ardization of criteria mapsMulti-criteria evaluation involves different techniques of combining various criterion maplayers. The different map layers may have different units <strong>and</strong> ranges of scales. In such case,the input map layers should be transformed to a common scale or comparable unit<strong>10</strong>4