| Main authors: | Luis Garrote, David Santillán, Ana Iglesias |
| iSQAPERiS Editor: | Jane Brandt |
| Source document: | Garrote L., Santillán D., Iglesias A. (2019) Report on the evaluation of scenarios of changed soil environmental footprint for a range of policy scenarios. iSQAPER Project Deliverable 7.4 64 pp |
The results of the application of the iSQAPER upscaling model to the three scenarios identified in »Soil management scenarios are presented in this section. The results are formulated in terms of projected increased values of the three soil ecosystem services selected for analysis: crop yield, soil organic content and soil biodiversity. The three ecosystem services are related to basic soil environmental functions and are the basis for evaluating the changed environmental footprint. For each scenario, a global overview of the results is presented first, showing maps of the projected increase of soil ecosystem services under the corresponding scenario. Secondly, the analysis is focused on the differential effect on agroclimatic regions of Europe and China. Finally, the variability of soil response to agricultural management practices is presented through box plots for the different agroclimatic regions.
| Contents table |
| 1. Effect of Expected scenario |
| 2. Effect of Towards 2050 scenario |
| 3. Effect of Regional Targets scenario |
| 4. Summary and conclusions |
1. Effect of Expected scenario
The Expected scenario is characterized by the maintenance of the observed tendency in the implementation of beneficial agricultural management practices.
1.1 Spatial effect of Expected scenario
The following figures present the spatial distribution of the effects of the Expected scenario on soil ecosystem services. The effects on crop yield are presented in Figure 14, the effects on soil organic matter are presented in Figure 15 and the effects on soil biodiversity are presented in Figure 16. The figures show the projected percentage increase in soil quality indicators as a result of the application of the additional management practices contemplated in the Expected scenario.
Figure 14 
Figure 15 
Figure 16
The results show a moderate increase of soil ecosystem services, with average increases between 0.27% for soil organic matter in China and 0.34% average increase for soil biodiversity in Europe. The increase of yield ranges from 0.23% to 0.40% in Europe, with an average value of 0.32%. The increase of yield in China ranges from 0.14% to 0.33%, with average of 0.27%. The spatial variability of soil organic matter is larger, ranging from an increase of 0.02% to 0.41% in Europe and 0.03% to 0.35% in China. Average values are 0.29% increase in Europe and 0.27% increase in China. Soil biodiversity shows the larger response to agricultural management practices. Average values are an increase of 0.34% in Europe and an increase of 0.28 in China. Values in Europe range from 0.20% to 0.54% and from 0.16% to 0.37% in China.
1.2 Effect of Expected scenario on agroclimatic regions
The compared values of average results of the upscaling of the Expected scenario in the agroclimatic regions of Europe and China are shown in Figure 20. Figure 20 shows that average impact is slightly above 0.30% in Europe and below 0.30% in China. Average response is an increase of 0.31% in Europe and 0.28% in China. The ecosystem service that is more sensitive to the implementation of agricultural management practices is soil biodiversity, followed by crop yield and soil organic matter.
The variability across agroclimatic regions is relatively low. The region that shows the greatest response in Europe is Mediterranean-South, with an average increase of 0.36% for the three ecosystem services. The European region that shows the least response is the Alpine region, with an average increase of 0.28%. In China, the largest response corresponds to the Continental-Cold region, with 0.31% increase. The least response is shown by the Subtropical-Wet region, with an increase of 0.23%.
Figure 17
The largest response in Europe for the Expected scenario corresponds to Mediterranean-South for soil biodiversity, with mean increase of 0.41%. The region that shows the smallest response is Continental-South for soil organic matter, with mean increase of 0.24% for soil organic matter. In China, the largest response corresponds to the Continental-Temperate region, with mean increase of 0.31% for soil biodiversity. The least response is shown by the Subtropical-Wet region, with a mean increase of 0.23% for crop yield and soil organic matter.
1.3 Variability of the effect of Expected scenario
The variability of the results of the upscaling for the Expected scenario is shown in Figure 18 and Figure 19. Both figures show box and whisker plots of the values of soil quality indicators in agroclimatic regions of Europe and China. Boxes show the values of the mean plus and minus one standard deviation and whiskers show the maximum and minimum values obtained for the region. The ecosystem service that shows larger variability in Europe is soil organic matter, with average standard deviation of 0.05%. In China, the largest variability corresponds to soil biodiversity, with a standard deviation of 0.04%. Crop yield shows the least variability in Europe and China with average standard deviations of 0.03% and 0.04% respectively. Soil organic matter also shows the largest dispersion, particularly regarding minimum values.
Figure 18
Results for Europe, presented in Figure 18, indicate that Mediterranean-North and Mediterranean-South are the regions where variability is largest, with average standard deviations of 0.05% for the three ecosystem services. Atlantic-North is the region with least variability with average standard deviation of 0.01%. The largest individual variability corresponds to Mediterranean-South for soil biodiversity, with standard deviation of 0.07%. The regions that show least variability are Boreal and Atlantic-North, both for yield, with standard deviation of 0.01%.
Figure 19
The regions where variability is largest in China are Subtropical-Wet and Steppe-Plateau, with average standard deviations of 0.03% for the three ecosystem services. Continental-Temperate is the region with least variability with average standard deviation of 0.01%. The region with the largest individual variabilities are Subtropical-Wet for soil organic matter and Steppe for soil organic matter and soil biodiversity, all with standard deviations of 0.03%. Continental-Temperate is the region that shows least variability with standard deviation of 0.01% for crop yield. Overall variabilities are similar in Europe and China, with average standard deviations for the three soil ecosystem services of 0.04%.
2. Effect of Towards 2050 scenario
The Towards 2050 scenario is characterized by an intensification of the rate of implementation of agricultural management practices induced by public policies. According to stakeholders from the case studies, the desirable rate of implementation is around three times the rate of implementation assumed in the Expected scenario.
2.1 Spatial effect of Towards 2050 scenario
The spatial distribution of the effects of the Towards 2050 scenario on soil ecosystem services is presented in the following figures. The effects on crop yield are presented in Figure 20, the effects on soil organic matter are presented in Figure 21 and the effects on soil biodiversity are presented in Figure 22. The figures show the projected percentage increase in soil quality indicators resulting from the application of the management practices contemplated in the scenario Towards 2050.
Figure 20 
Figure 21 
Figure 22
The results show a significant increase of soil ecosystem services, with average increases between 0.84% for soil organic matter in China and 0.99% average increase for soil biodiversity in Europe. The increase of yield ranges from 0.72% to 1.18% in Europe, with an average value of 0.95%. The increase of yield in China ranges from 0.45% to 1.01%, with average of 0.85%. The spatial variability of soil organic matter is larger, ranging from an increase of 0.07% to 1.21% in Europe and 0.08% to 1.05% in China. Average values are 0.86% increase in Europe and 0.84% increase in China. Soil biodiversity shows the larger response to agricultural management practices. Average values are an increase of 0.99% in Europe and an increase of 0.88 in China. Values in Europe range from 0.60% to 1.47% and from 0.49% to 1.13% in China.
2.2 Effect on agroclimatic regions
The compared values of average results of the upscaling of the Towards 2050 scenario in the agroclimatic regions of Europe and China are shown in Figure 23. Average impact is slightly below 1%. The threshold of 1% is exceeded in Europe by Mediterranean-South in yield and soil biodiversity and by Mediterranean-North, Atlantic-South and Continental-North in soil biodiversity. Average response is an increase of 0.93% in Europe and 0.86% in China. The ecosystem service that is more sensitive to the implementation of agricultural management practices is soil biodiversity, followed by crop yield and soil organic matter.
Figure 23
The variability across agroclimatic regions is larger than in the other scenarios. The region that shows the greatest response in Europe is Mediterranean-South, with an average increase of 1.05% for the three ecosystem services. The European region that shows the least response is the Alpine region, with an average increase of 0.84%. In China, the largest response corresponds to the Continental-Cold region, with 0.94% increase. The least response is shown by the Subtropical-Wet region, with an increase of 0.72%.
2.3 Variability of the effect of Towards 2050 scenario
The variability of the results of the upscaling for the Towards 2050 scenario is shown in Figure 24 and Figure 25. Both figures show box and whisker plots of the values of soil quality indicators in agroclimatic regions of Europe (Figure 24) and China (Figure 25). Boxes show the values of the mean plus and minus one standard deviation and whiskers show the maximum and minimum values obtained for the region. The ecosystem service that shows larger variability in Europe is soil organic matter, with average standard deviation of 0.15%. In China, the largest variability corresponds to soil biodiversity, with a standard deviation of 0.13%. Crop yield shows the least variability in Europe and China with average standard deviations of 0.08% and 0.11% respectively. Soil organic matter also shows the largest dispersion, particularly regarding minimum values.
Figure 24
Results for Europe, presented in Figure 24, indicate that Mediterranean-North and Mediterranean-South are the regions where variability is largest, with average standard deviations of 0.13% for the three ecosystem services. Atlantic-North is the region with least variability with average standard deviation of 0.04%. The largest individual variability corresponds to Continental-South for soil organic matter, with standard deviation of 0.17%. The regions that show least variability are Boreal and Atlantic-North, both for yield, with standard deviation of 0.02%.
Figure 25
The regions where variability is largest in China are Subtropical-Wet and Steppe-Plateau, with average standard deviations of 0.09% for the three ecosystem services. Continental-Temperate is the region with least variability with average standard deviation of 0.04%. The region with the largest individual variabilities are Subtropical-Wet for soil organic matter and Steppe for soil organic matter and soil biodiversity, all with standard deviations of 0.10%. Continental-Temperate is the region that shows least variability with standard deviation of 0.03% for crop yield. Overall variabilities are similar in Europe and China, with average standard deviations for the three soil ecosystem services of 0.12%.
3. Effect of Regional Targets scenario
The Regional Targets scenario is characterized by the same rate of implementation of agricultural management practices as Towards 2050, but considering that policy efforts are focused on areas where soil threats are more active and soil quality indicators are poorer.
3.1 Spatial effect of Regional Targets scenario
The spatial distribution of the effects of the Regional Targets scenario on soil ecosystem services is presented in the following figures. The effects on crop yield are presented in Figure 26, the effects on soil organic matter are presented in Figure 27 and the effects on soil biodiversity are presented in Figure 28. The figures show the projected increase in soil quality indicators (in percentage with respect to current values) resulting from the application of the additional management practices contemplated in the Regional Targets scenario.
Figure 26 
Figure 27 
Figure 28
The results show an effect on soil ecosystem services significantly better than in the case of the Towards 2050 scenario, with average increases between 0.94% for soil organic matter in China and 1.06% average increase for soil organic matter in Europe. The increase of yield ranges from 0.79% to 1.33% in Europe, with an average value of 1.05%. The average increase of crop yield in China is 0.95%, ranging from 0.49% to 1.30%. The effect on soil organic matter ranges from an increase of 0.74% to 1.35% in Europe and 0.53% to 1.16% in China. Average values are 1.16% increase in Europe and 0.94% increase in China. The average values of the effect on soil biodiversity are an increase of 1.01% in Europe and an increase of 0.97 in China. Values in Europe range from 0.58% to 1.58% and from 0.52% to 1.40% in China.
3.2 Effect on agroclimatic regions
The compared values of average results of the upscaling of the Regional Targets scenario in the agroclimatic regions of Europe and China are shown in Figure 29. The average impact is 1.04% for Europe and 0.95% for China. The ecosystem service that is more sensitive to the implementation of agricultural management practices is soil organic matter in Europe and soil biodiversity in China. Conversely, the ecosystem services that show the least sensitivity are soil biodiversity in Europe and soil organic matter in China. As in the case of the Expected scenario, different agroclimatic regions show relatively low variability. The region that shows the greatest average response in Europe is Mediterranean-South, with an average increase of 1.15% for the three ecosystem services. The European region that shows the least response is the Alpine region, with an average increase of 0.95%. In China, the largest average response corresponds to the Continental-Cold region, with 1.03% increase. The least response is shown by the Subtropical-Wet region, with an increase of 0.80%.
Figure 29
The largest response in Europe for the Expected scenario corresponds to Mediterranean-South for soil biodiversity, with mean increase of 1.20%. The region that shows the smallest response is the Alpine region for soil biodiversity, with mean increase of 0.86%. In China, the largest individual response corresponds to the Continental-Temperate region, with mean increase of 1.07% for soil biodiversity. The least response is shown by the Subtropical-Wet region, with a mean increase of 0.79% for soil organic matter.
3.3 Variability of the effect of Regional Targets scenario
The variability of the results of the upscaling for the Regional Targets scenario is shown in Figure 30 and Figure 31. Both figures show box and whisker plots of the values of soil quality indicators in agroclimatic regions of Europe (Figure 30) and China (Figure 31). Boxes show the values of the mean plus and minus one standard deviation and whiskers show the maximum and minimum values obtained for the region. The ecosystem service that shows larger variability in Europe is soil biodiversity with average standard deviation of 0.16%. In China, the largest variability corresponds to soil biodiversity, with a standard deviation of 0.15%. Crop yield and soil organic matter show the least variability in Europe, with average standard deviation of 0.09% for both. In China, the least variability is shown by soil organic matter, with average standard deviation of 0.12%. The dispersion is significantly reduced with respect to the Expected scenario, with much higher minimum values, particularly regarding soil organic matter.
Figure 30
Mediterranean-South is the region where variability is largest in Europe, with average standard deviation of 0.13% for the three ecosystem services. Atlantic-North is the region with least variability with average standard deviation of 0.04%. The largest individual variability corresponds to Mediterranean-South for soil biodiversity, with standard deviation of 0.20%. The region that shows least variability is Atlantic-North for crop yield, with standard deviation of 0.02%.
Figure 31
The region where variability is largest in China is Steppe-Plateau, with average standard deviation of 0.10% for the three ecosystem services. Continental-Temperate is the region with least variability with average standard deviation of 0.04%. The region with the largest individual variability is the Desertic region for soil biodiversity, with standard deviation of 0.13%. Continental-Temperate is the region that shows least variability with standard deviation of 0.04% for all three ecosystem services. Overall variabilities are slightly smaller in Europe that in China, with average standard deviations for the three soil ecosystem services of 0.11% in Europe and 0.13% in China.
4. Summary and conclusions
The results obtained for the three scenarios are compared here. Table 5 presents the global overview, showing the average results obtained for the three soil ecosystem services in the three scenarios for Europe and China. The same results are visualized in Figure 32.
Table 5. Average results for the three soil ecosystem services in the three scenarios for Europe (left) and China (right)
| Yield | Soil Organic Matter | Biodiversity | ||||
| Europe | China | Europe | China | Europe | China | |
| Expected | 0.32 | 0.27 | 0.29 | 0.27 | 0.34 | 0.28 |
| Towards 2050 | 0.95 | 0.85 | 0.86 | 0.84 | 0.91 | 0.88 |
| Regional Targets | 1.05 | 0.95 | 1.06 | 0.94 | 1.01 | 0.97 |
The average response in Europe is an increase of soil ecosystem services of 0.31% for Baseline, 0.91% for Towards 2050 and 1.04% for Regional Targets. In China, the average response is an increase of 0.28% for Baseline, 0.86% for Towards 2050 and 0.95% for Regional Targets. Overall, the response to policy in China is between 0.05% and 0.09% less than in Europe.
Figure 32
Figure 33 compares the results obtained in the Regional Targets and Towards 2050 scenarios to those obtained in the Expected scenario. The Towards 2050 and Regional Targets scenarios imply approximately three times the implementation levels of those in the Expected scenario (on average 3.1 times in Europe and 3.2 times in China). The straight lines in Figure 33 mark the projected effects of those implementation levels. However, the increase of soil ecosystem services are less than the projected ratios: 2.88 times in Europe and 3.1 times in China. The average efficiency is 93% in Europe and 97% in China. This is because, as implementation levels grow, the probability of having a model cell with implementation of more than one agricultural management practice also grows. In this case, intervention efficiency decreases, since the combined effect of two management practices is less than the sum of both effects considered separately. As seen in Figure 33, the soil ecosystem service that is more sensitive to both effects is soil biodiversity. The Regional Targets scenario implies the same level of implementation as the Towards 2050 scenario, but the intervention is focused on the areas where soil quality is poor. This produces a better response, with an average improvement of 11.50% in Europe and 11.23% in China.
Figure 33
Figure 34 and Figure 35 present the comparison of the results obtained in the Towards 2050 and Regional Targets scenarios to those obtained in the Expected scenario for individual agroclimatic regions in Europe (Figure 34) and China (Figure 35). The regional effect of focussing the intervention on the less quality soils is more distinct in soil organic matter, where the increases corresponding to the Regional Targets scenario are well above those for the projected ration corresponding to the implementation level. This effect is stronger in Europe than in China.
Figure 34 
Figure 35
Note: For full references to papers quoted in this article see