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Benchmarking soil multifunctionality
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Abstract. Healthy soils provide multiple functions that importantly contribute to human wellbeing, including primary production, climate and water regulation, and supporting biodiversity. These functions can partially be combined and some functions also clearly trade-off: this motivates soil multifunctionality research. Society needs scientists to help assess which soils are best for which soil functions and to determine appropriate long-term management of any given soil for optimal function delivery. However, for both tasks science lacks coherent tools and in this paper I propose a way forward. Critically, we lack a common measurement framework that pins soil functioning measurements on a common scale. Currently the field is divided with respect to the methods we use to measure and assess soil functioning and indicators thereof. Only three indicator variables (SOM, acidity, and available P) were commonly measured (>70 % of schemes) across 65 schemes that aim to measure soil health or quality, and no biological measure is implemented in more than 30 % of the 65 schemes. This status quo prevents us from systematically comparing across and within soils; we lack a soil multifunctionality benchmark. We can address this limitations systematically by setting a common measurement system. To do this, I propose to use latent variable modelling based on a common set of functional measurements, to develop a common ‘IQ test for soils’. I treat soil functions as latent variables, because they are complex processes that cannot be measured directly, we can only detect drivers and consequences of these complex processes. Latent variable modelling has a long history in social, economic and psychometric fields, where it is known as factor analysis. Factor analysis aims to derive common descriptors – the factors – of hypothesized constructs by linking measurable response variables together on a common scale. Here, I explain why such a new approach to soil multifunctionality and soil health is needed and how it can be operationalized. The framework developed here is only an initial proposal, the issue of soil multifunctionality is too complex and too important to be addressed in one go. It needs to be resolved iteratively by bands of scientist working intensively together. We need to bring our best science together, in a collaborative effort, to develop progressively more refined ways of sustainably managing one of humanity’s most precious resources: our soils.
Title: Benchmarking soil multifunctionality
Description:
Abstract.
Healthy soils provide multiple functions that importantly contribute to human wellbeing, including primary production, climate and water regulation, and supporting biodiversity.
These functions can partially be combined and some functions also clearly trade-off: this motivates soil multifunctionality research.
Society needs scientists to help assess which soils are best for which soil functions and to determine appropriate long-term management of any given soil for optimal function delivery.
However, for both tasks science lacks coherent tools and in this paper I propose a way forward.
Critically, we lack a common measurement framework that pins soil functioning measurements on a common scale.
Currently the field is divided with respect to the methods we use to measure and assess soil functioning and indicators thereof.
Only three indicator variables (SOM, acidity, and available P) were commonly measured (>70 % of schemes) across 65 schemes that aim to measure soil health or quality, and no biological measure is implemented in more than 30 % of the 65 schemes.
This status quo prevents us from systematically comparing across and within soils; we lack a soil multifunctionality benchmark.
We can address this limitations systematically by setting a common measurement system.
To do this, I propose to use latent variable modelling based on a common set of functional measurements, to develop a common ‘IQ test for soils’.
I treat soil functions as latent variables, because they are complex processes that cannot be measured directly, we can only detect drivers and consequences of these complex processes.
Latent variable modelling has a long history in social, economic and psychometric fields, where it is known as factor analysis.
Factor analysis aims to derive common descriptors – the factors – of hypothesized constructs by linking measurable response variables together on a common scale.
Here, I explain why such a new approach to soil multifunctionality and soil health is needed and how it can be operationalized.
The framework developed here is only an initial proposal, the issue of soil multifunctionality is too complex and too important to be addressed in one go.
It needs to be resolved iteratively by bands of scientist working intensively together.
We need to bring our best science together, in a collaborative effort, to develop progressively more refined ways of sustainably managing one of humanity’s most precious resources: our soils.
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