|Ana Iglesias, David Santillán, Luis Garrote and contributions from ISS (China)
|Iglesias, A. et al. (2018) Report on definition of typical combinations of farming systems and agricultural practices in Europe and China and their effects on soil quality. iSQAPER Project Deliverable 7.1, 87 pp
|1. Gaps in knowledge and data
|2. Further work
The work reported in this section of iSQAPERiS has made use of available knowledge and data to define the framework for upscaling. However, available knowledge and data is far from complete, and the upscaling process necessarily involves filling these gaps with ad-hoc decisions.
The data compiled from upscaling have been collected by different disciplines, and different schools within each discipline concerned, and often for different purposes. They have been collected with different questions in mind, different disciplinary epistemologies, different methods and techniques. This challenge is particularly relevant in the upscaling context, where we need to merge natural science (systemic) models with social-science.
Regardless of the scale considered in a spatial analysis of the effect of soil management practices on soil environmental footprint, it is important to remember that, as is the case with most statistical analyses, these can only describe a pattern and changes in a pattern; only if the local data validate the continental results, these are useful, since only local observed measurement provide some underlying processes can be inferred.
In the mapping examples described here, the spatial statistical analysis was used to describe possible pattern of effect on soil quality indicators, but we cannot infer on the process of effect. Combined results from global and local analyses are essential to indicate that the process improving soil environmental footprint.
General questions that need to be considered in geospatial studies include the following:
- what are the best criteria for selecting the spatial (and temporal) unit of analysis?
- how do the key measures of effect dynamics vary with scale?
- how do we integrate processes occurring at diverse spatial and temporal scales?
- are we uncovering new relevant information or covering up the lack of data with massive environmental correlates?
- how do we decide which environmental or climate changes to follow?
- how do we move beyond considering isolated indicators to considering overall soil health and the factors contributing to it?
All of these questions can only be addressed through solid biological, agronomic and socioeconomic understanding of the system in time and space. As far as whether to go upscale (extrapolate) or downscale (interpolate), we quote Levins (1968), who stated, “the detailed analysis of a model for purposes other than that which it was constructed may be as meaningless as studying a map under a microscope.”
The continental soil health perspective demands an understanding of both the soil system, the human-derived forces and impacts, and the possibilities of threshold-dependent changes and tipping points (Moore et al., 2001).
Static indicators of soil health are perhaps insufficient to understand the impacts ofchanging conditions (Jackson et al., 2009). Modelling the dynamical relationships between social and soil processes is needed as part of the evidence base for making appropriate management decisions. The approach presented here will help to address the management questions that can only be addressed by upscaling.
Complex socio-ecological systems are unpredictable and parameteriszing social dynamics, such as individual behaviour and governance, is probably impossible (Silver 2012). Therefore, the ability of a model to provide consistent output for evaluating scenarios is very useful.
In this section of iSQAPERiS we have set up the framework for upscaling in iSQAPER by defining typical combinations of farming systems and agricultural practices in Europe and China and identifying their effects on soil quality. This work will be refined in »Effect of management on soil quality, where the potential of agricultural management practices will be assessed by involving the case studies and other project partners and stakeholders.
Further analysis to be carried includes the following steps:
- Step 1 Engagement of the case study managers in iSQAPER to fill a questionnaire relevant to the adequacy of the approach to evaluate the environmental footprint in the case studies, and the data that could be provided to validate the approach.
- Step 2 Revised methods based on the results of the questionnaire and evaluate what we need to know in addition to the data provided that will be helpful to assess the effect of soil management practices on the environmental footprint.
Note: For full references to papers quoted in this article see