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Accounting for diversity of practices in conservation agriculture

A field of wheat with a raining storm cloud in the distance. Image by Ottó from Pixabay

This article assesses the diversity of practices being implemented in Walloon, Belgium, which are considered to align with conservation agriculture’s three agronomic pillars (or principles): (i) minimum mechanical soil disturbance, (ii) permanent soil organic cover, and (iii) species diversification (FAO 2023). The authors aimed to determine the diversity of practices in a given area to understand the impacts of these practices and why farmers adopt them. They also sought to guide policy decisions and improve communication within the scientific community and between science and field actors. The authors present a novel classification method to categorise the diversity of CA practices on a regional scale that they present as applicable for comparing and assessing CA in different regions and other agricultural systems such as regenerative farming and organic farming. 

Summary

This article assesses the diversity of practices being implemented in Walloon, Belgium, which are considered to align with Conservation Agriculture’s three agronomic pillars (or principles): (i) minimum mechanical soil disturbance, (ii) permanent soil organic cover, and (iii) species diversification (FAO 2023). The authors define conservation agriculture as “an alternative farming system that enables productive and profitable agriculture, improves soil and water conservation offering better adaptation to climate change, mitigates GHG emissions, and contributes to carbon sequestration in soils.” 

The authors aimed to determine the diversity of practices in a given area to understand the impacts of these practices and why farmers adopt them. They also sought to guide policy decisions and improve communication within the scientific community and between science and field actors. They found that no previous research produced a systematic method for categorising the diversity of CA practices in relation to the three pillars implemented by farmers. The authors present a novel classification method to categorise the diversity of CA practices on a regional scale. They combine two common statistical methods used for determining the diversity within groups. The authors aim to address methodological issues of each method used in isolation.

The main takeaway from this article is the importance of studying the diversity of CA types as the practice continues to grow in popularity. The authors call for research on the adoption of specific CA-types rather than the general concept of CA, which they emphasise is not a homogenous set of practices. They claim this would help to understand why a farmer practises a particular type of CA and help identify the influential factors related to the barriers and incentives for farmers to switch to a CA type or from one type to another. Broadly, they view CA as heterogeneous with a diversity of practices, impacts and pathways that can encourage others to adopt the same view. The specific method would be broadly relevant to future research on the diversity of sustainable agriculture practices such as regenerative farming, organic farming, and agroecological practices within a given area.

The article is a technical statistical analysis which uses the case study of Belgium to test a novel method. Two statistical methods are combined: archetypal analysis (AA) and an agglomerative Hierarchical Clustering on Principal Components (HCPC) - or simply a cluster analysis. AA designates farmers within archetypal groups, but often leaves large numbers of farmers who do not fall within these designations. Cluster analysis categorises all individuals but can often mix farmers within a cluster that have diverging practices. The combination of cluster analysis with AA, the authors argue, allows for the capture of those farmers who fall in between the extremes of the archetypes, allowing for the classification of all individuals and avoiding mixing within clusters. 

Each farmer in the study had a mix of CA practices. The authors found that the most common practice was the abandonment of ploughing whilst fewer farmers had established temporary grassland. The researchers found five types of CA. Three types (CIO, GEM and CIN) were classified as reference types, meaning they had well defined characteristics that separated them from other types and strong association with one of four identified archetypes. Two types (Ig1 and Ig2) were classified as intermediate and were not given specific labels as they did not have well-defined characteristics. 

Scores were given to each CA type and were based on each pillar of CA and derived by adding scores of the five variables for each pillar. For example pillar 1 was scored on wheel traffic and tillage depth, pillar 2 on grassland cover and total soil cover and pillar 3 was scored on total species and combinations of specific species mixes present. The researchers found no single CA-type scored highest or lowest in all three pillars. In other words, different CA types have different advantages and disadvantages with trade-offs between the types. The five types and their scores across the variables used within each pillar can be seen in figure 1.

Figure 1: A radar chart of the average scores of CA types for the variables used within the three pillars of CA. Higher scores, or scores further from the centre of the chart, indicate better scores for each variable.

Figure 1: A radar chart of the average scores of CA types for the variables used within the three pillars of CA. Higher scores, or scores further from the centre of the chart, indicate better scores for each variable. 

The researchers expect scores for the various CA types would vary in different geographic contexts. They present their method as broadly applicable with potential for extension to various CA contexts and farming systems beyond the scope of this article. It may also have potential for conventional and organic farmers to compare their tillage, soil cover, and species diversification practices with CA farmers. Additionally, the method could be used to categorise the diversity of other farming systems by adapting the input variables of this study.

Abstract

Conservation Agriculture (CA) is actively promoted as an alternative farming system that combines environmental, economic, and social sustainability. Three pillars define CA: (i) minimum mechanical soil disturbance, (ii) permanent soil organic cover, and (iii) species diversification. The local context, constraints, and needs of the farmers influence the translation of the pillars into practices. Currently, there is no method for categorizing this diversity of CA practices, which hampers impact assessment, understanding of farmer choices and pathways, stakeholder communication, and policymaking. This paper presents a systematic method to identify and categorize the diversity of CA practices at the regional level, anchored in the three pillars and based on practices implemented by CA farmers. The classification method is grounded on the intersection of an archetypal analysis and a hierarchical clustering analysis. This method was used to study CA practices in Wallonia, Belgium, based on a survey of practices in a sample of 48 farmers. Combining the two clustering methods increases the proportion of classified farmers while allowing for the distinction between three CA-types with extreme and salient practices, and two intermediate CA-types comprising farmers whose practices fall between these references. The study reveals that three explanatory factors influence the implementation of CA practices in Wallonia: (i) the proportion of tillage-intensive crops and (ii) temporary grasslands in the crop sequence, and (iii) the organic certification. These factors lead to trade-offs that hinder the three pillars of CA from being fully implemented simultaneously. This new classification method can be replicated in other regions where CA is practiced, by adapting input variables according to context and local knowledge

Reference

Ferdinand, M.S., Baret, P.V., 2024. A method to account for diversity of practices in Conservation Agriculture. Agron. Sustain. Dev. 44, 31.

Read more here. See also the TABLE explainer What is sustainable intensification?

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