A Bayesian Belief network to operationalize the concepts of Soil Quality and Health

Lead Research Organisation: Rothamsted Research
Department Name: Sustainable Agriculture Sciences-H

Abstract

'Soil Quality' and 'Soil Health' are general terms for indicators that are associated with 'Soil Security'. None of these terms within quotation marks is easy to define, however. Neither are they easy to quantify rigorously in a way that avoids dispute. Nonetheless all three terms have traction with policy makers and with land managers and regulators. Indicators provide benchmarks for ranking different places or practices and deciding where to deploy effort to bring about change as effectively and economically as possible and they provide a means to assess afterwards whether or not and to what extent this change has actually been brought about.

As a result, indicators of this kind are attractive to stakeholders. Indicators often rely on expert opinion for their derivation, but experts differ. Even apparently objective biophysical measurements are subject to error and worse, the soil itself varies from place to place and even time to time. It is not clear how to eliminate bias or how to weight the different kinds of information - opinion and measurement.
There is therefore scope for developing a rigorous, scientific approach to SQH that incorporates expert-derived opinion alongside physically-based measurements in our understanding of Soil Quality and Health (SQH) in a scientific manner.

Bayesian Belief Networks are graph-based, directional networks that can incorporate probability distributions of these various kinds of data. Essentially the directedness leads from multiple pieces of data to a conclusion - in our case a rating of SQH. The network is self-learning in that any additional soils and data for which quality assessments are available will re-inforce the pathways that decide the quality rating. In use, SQH ratings for additional soils that contain even partial data can still be obtained if the net defaults to mean values where data is missing.

To accommodate the various functions and scales needed to operationalise SQH, will require a set of Bayesian Belief Networks that considers the interactions of soil properties with SQH but also the impact of environmental change and land use and management on soil quality. There a numerous advantages to using BBNs: they can consider and integrate biological, economic and sociological factors and have effectively been use to determine the consequence of land-management decisions in land use decision behaviour. Bayesian modelling methods are a rigorous framework in which a complete characterization of the coupling and variability of soil quality is based on physical laws, empirical relationships but can easily incorporate expert knowledge formally and other kinds of soft data.

Planned Impact

Understanding and estimating soil quality and health is an issue of some national and international importance as was highlighted during the 2015 International Year of the Soil. Soil health and quality are vague concepts, yet much-needed by policy-makers and planners to inform decision making, both in the UK and globally. Most of our food derives from terrestrial agriculture, so decisions and policies that preserve or enhance the quality of our soils are of tremendous strategic importance.

Many stakeholders have expressed interest in or have funded work on indicators of soil quality. Our research should be of interest to a wide range of parties: AHDB, LEAF, food retailers and NFU for the farming industry, Defra, EA, SEPA, SG, Natural England for regulation and environmental issues, the EU and other policy and regulatory bodies overseas too have funded work on SQH and will value a robust and self-consistent approach to quantifying SQH.

A joined-up series of indicators or at least methodology for doing so could allow policy-makers and regulators with different fields of management the ability to refer and compare one anothers' needs with their own. Benchmarks and indicators of change would also be a step forward for regulations.

These tools could potentially be used by land managers too who have to combine different kinds and qualities of information in order to meet differing objectives from their land. Rules, structures and guidance for how to do this and how not to would be valuable.

Publications

10 25 50
 
Description Workshop Eliciting targets for the sustainable development goals and goal 2 in particular 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Other audiences
Results and Impact A workshop was convened in order to identify the views of stakeholders on the nature of agriculture in 2030 and 2050 and the ways in which agriculture might change to deliver to the UN SDGs in an full and meaningfull way as possible. Stakeholders were divided in to those representing arable, livestock or diary sectors and having identified reasonable targets by way of improving agriculture, reflected on pathways over time to reach these targets and goals
Year(s) Of Engagement Activity 2018
 
Description Workshop on Soil Health 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Other audiences
Results and Impact Views on the nature and determinants of soil quality and health were elicited from experts in the field during a 2 day workshop session. Participants were first trained with regard to the elicitation process and then introduced to the bespoke software with which we obtained their views. Networks were then constructed that expressed the interconnected way in which the components of soil quality lead to a quantitative expression of that concept
Year(s) Of Engagement Activity 2018