Figure 1.
Predicted and actual distribution of indigenous Arabica.
Green dots show recorded data-points. Coloured areas (yellow to red) show predicted distribution based on MaxEnt modelling (see internal legend). A context map is given in the top left hand corner.
Figure 2.
Predicted and actual distribution of indigenous Arabica.
Figure 2A. Green dots show recorded data-points. Coloured areas (yellow to red) show predicted distribution based on MaxEnt modelling (see internal legend). Highest predicted area (dark red) indicates ‘core region’. Figure 2B. The same map with thresholds of bioclimatic suitability applied at 68% (optimal), 95% (intermediate) and 100% (marginal) to the localities. Prediction values for each locality are represented by colour and size (see internal legend) with values for low predictions labelled in red, superimposed on predicted surface (space) according to the area analysis. Localities with the smallest (dark green) circles represent ‘core localities’; highest (optimal) predicted area (green) indicates the ‘core region’. See main text for further details.
Figure 3.
Predicted climate change outcomes for indigenous Arabica localities for the year interval 2000, 2020, 2050 and 2080. Stacked bar-charts based on Table 1. Green = optimal [bioclimatic] localities (68%); yellow = intermediate (suboptimal) [bioclimatic] localities (95%); red = marginal (extreme) [bioclimatic] localities (100%); grey = unsuitable bioclimatic localities.
Figure 4.
Locality analysis overview II.
Predicted climate change outcomes for indigenous Arabica localities (349 in total) for the year intervals 2000, 2020, 2050 and 2080. Histograms for actual predicted values, under each scenario. Dashed line and red text indicate thresholds (68%, 95%, 100%, of the 2000 models). This figure provides finer-scale detail than Figure 3, including the subtle shifts around the thresholds that are evident in the locality analysis. For example in scenario B2A, in 2000 there are a high proportion of localities in optimum bioclimatic space (0.6 and 0.65), but by 2080 most of the localities are outside of all suitable bioclimatic space, with a small number of localities (‘core localites’) still occupying optimal bioclimatic space.
Figure 5.
Predicted climate change outcomes for indigenous Arabica for the year intervals 2020, 2050 and 2080. Thresholds (of bioclimatic suitability) applied at 68% (optimal), 95% (intermediate) and 100% (marginal). Black dots show historical and present day localities.
Figure 6.
Predicted climate change outcomes for indigenous Arabica for the year intervals 2020, 2050 and 2080. Stacked bar-charts based on area analysis maps (Figure 5).
Table 1.
Number of (unique) localities in each threshold class for each climate change (emission) scenario and date.
Figure 7.
Locality analysis predictions superimposed on main protected areas in the study region.
Point size and colour represent the total predicted score for each locality across all scenarios and time intervals (until 2080). Large dots (high score) represent ‘core localities’, i.e. those that predicted to withstand climate change until at least 2080. See internal legend for further details. Protected area data from [70]. Dedicated coffee reserves: Yayu = Yayu Coffee Forest UNESCO MAN Biosphere Reserve (http://www.unesco.org/mabdb/br/brdir/directory/biores.asp?code=ETH02&mode=all. Accessed 2012 May 10), included within the Yayu National Forest Priority Area (NFPA) (http://www.ecff.org.et/component/content/article/10-yayu/6-yayu-coffee-forest-biosphere-reserve.html. Accessed 2012 May 10); Kafa = Kafa Coffee Biosphere Reserve UNESCO Biosphere Reserve (http://www.kafa-biosphere.com/. Accessed 2012 May 10). Note. Controlled Hunting Areas not shown.