Users are interested in soil functions for their decision making

As a conclusion § The « Quantifying and mapping soil functionnality » challenge : a new horizon for the pedometricians § The response should be collective (As the GlobalSoilMap project was) § Potential users and neighbor scientific communities should be more involved than before

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  f u n c t io n s ' p e r f o r m a n c e t r a d eo f f s b e t w e e n t h e s o il f u n c t io n s u n d e r c u r r e n t c o n d it io n s " s p a t ia ll y e x p li c it e v a lu a t io n o f c u r r e n t le v e ls o f s o il f u n c t io n a li t y e c o s y s t e m s e r v ic e s So il q u al it y in d ex su pp ly of so il fu nc tio ns s o il q u a li t y a b i l i t i e s T o e v a lu a te s o il s l o n gt e r m s o i l q u a l i t y l o c a l y i e l d p o t e n t i a l soil performances c a p a c i t y t o p e r f o r m f u n c t i o n s ( w a t e r p u r i f i c a t i o n a n d r e g u l a t i o n , t h e p r i m a r y p r o d u c t i v i t y f u n c t i o n ) m o st p ro b a b le ch a n g e s in so il q u a li ty in d ic a to rs soil health indicators (r e la ti v e ) s o il q u a li ty w it h in a g iv e n c o n te x t d e g r e o f f u n c t i o n n a l p e r f o r m a n c e p e rf o rm a n c e o f e c o s y s te m s e rv ic e s S o i l c o n d i t i o n § That could be classified into three distinct concepts… • Fulfilment level of a function observed or modelled at a given period and at a given location (context) • Capacity to satisfy a function in any context • Potential to satisfy a function in any context (based on perennial soil properties only) i c u l t u r a l . p r a c t i c e s Decision trees and score functions fed by expert knowledge and/or literature harvesting ( 90 % of studies) • Agro-environmental models outputs (for level of fullfilment of individual functions) • Final aggregation into an unique indicator (60% of studies) Low diversity of quantification methods, …with limitations § Most current methods • Decision trees and score functions fed by expert knowledge and/or literature harvesting ( 90 % of studies) • Agro-environmental models outputs (for level of fullfilment of individual functions) • Final aggregation into an unique indicator (60% of studies) § Some limitations • The embedded knowledges on soil functions are neither traceable nor revisable • Uncertainties are not considered (exception: Vrebos et al, 2020) • Weigthing, conflicts and trade-off between functions are rarely considered (Exceptions : Vrebos et al, 2020, Ellili et al, 2021) Low diversity of quantification methods, …with limitations § Diverse underlying concepts § Diverse soil, functions and context representations § Quantification methods with limitations Lack of stabilized and consensual conceptual and methodological framework to adress soil functionnality § Most of the 16 case studies on soil evaluation produced maps ( 70%) § Most of the soil function maps are derived from conventional soil maps § Still few studies using a DSM approach § Do inference trajectories inpact DSM results ? § If yes, how to select the best one ? Example: mapping soil available water capacity (Styc & Lagacherie, 2019) P T F i n p u t s : C l a y , s i l t , s a n d S o i l t h i c k n e s s C o a r s e f r a g m e n t H fc H fc H fc, H fc Inference trajectories for mapping Soil Avalaible Capacity and DSM performances Numbers of mapped soil layers DSM performances for different trajectories MEC § DSM performances vary following the inference trajectories § The best Inference trajectory is neither « mapping first » nor « calculating first » The most correlated soil properties should be aggregated first before mapping How to propagate uncertainty of soil function assessment and DSM ? § DSM errors propagated to SAWC by using analytical formulae of error propagation (Roman-Dobarco et al, 2019, Styc & Lagacherie, 2021) § DSM errors propagated to soil function fullfillments by using Monte Carlo simulations parametrized with estimated DSM uncertainties (Greiner et al, 2018) § DSM errors propagated to a soil multifunctionnality index by using stochastic simulations of soil properties derived from linear models of coregionalisation (Angelini et al, 2022)- § Soil function assessement uncertainties represented by a Bayesian Belief Network (Vrebos et al, 2020) Few studies… How to map the uncertainty associated with maps of soil functionnalities ? § *AFEP: using analytical formulae of error propagation (Roman-Dobarco et al, 2019, Styc & Lagacherie, 2021) § *MCS: using Monte Carlo simulations parametrized with estimated DSM uncertainties (Greiner et al, 2018) § *SLMC: using stochastic simulations of soil properties derived from linear models of coregionalisation (Angelini et al 2022) § *BBN: using a Bayesian Belief Network (Vrebos et al, 2020)

room for further improvements Proposed Agenda for future researches : soil functions and soil quality assessments

  § Converge toward a well-admitted conceptual and methodological framework • Setting ontologies • Clarify the representations of soils and of their context (scenarios for evaluations) • Identifying adequate numeric tools to represent the complex knowledge on Soil functions ( BBN ?) § Develop traceable (numeric) approaches to collect relevant knowledges on soil functions • Harvesting knowledge from literature (traceable and reproductible meta-analysis) • Assessing fullfillments of soil function using process-based models and derived metamodels • Elicing local expert knowledges (participatory approaches) • Managing uncertainties and conflicts between different sources of knowledge about soil functions • Avoid mixing scientific decisions and policy ones § Develop Multivariate DSM approaches • Optimizing the inference trajectories à Spatial Soil Inference system • Combining, propagating and representing uncertainties for decision-making • Experimenting multivariate machine learning algorithms § Develop new approaches for mapping time-variant soil properties § Develop dynamic user interfaces to communicate complex map contents

		AFEP*	MCS**	SLMC***	BBN****
	Account for DSM errors	✓	✓	✓	✘
	Account for Soil Function assessment errors	✘	✘	✘	✓
	Account for DSM error correlations	✓	✘	✓	✘
	Applicable to all aggregated values	✘	✓	✓	✓
	Still

Proposed Agenda for future researches : Mapping soil functions and soil quality

Systems

Digital Soil Mapping and Soil function/multifunctionnality mapping Rutgers et al , 2019, Soil Systems Angelini et al , 2022, EJSS Greiner et al , 2018, Soil Systems Harms et al, 2015, Global Food Security Kidd et al, 2015, Geoderma R. Zeraatpisheh et al, 2020, Geoderma Vrebos et al, 2020, EJSS Fernadez et al , 2020, Rev. Bras. Ciènc. Solo