The Soil Food Web Ontology: aligning trophic groups, processes, and resources to harmonise and automatise soil food web reconstructions

Abstract

Although soil ecology has benefited from recent advances in describing the functional and trophic traits of soil organisms, data reuse for large-scale soil food-web reconstructions still faces challenges. These obstacles include: (1) most data on the trophic interactions and feeding behaviour of soil organisms being scattered across disparate repositories, without well-established standard for describing and structuring trophic datasets; (2) the existence of various competing terms, rather than consensus, to delineate feeding-related concepts such as diets, trophic groups, feeding processes, resource types, leading to ambiguities that hinder meaningful data integration from different studies; (3) considerable divergence in the trophic classification of numerous soil organisms, or even the lack of such classifications, leading to discrepancies in the resolution of reconstructed food webs and complicating the reuse and comparison of food-web models within synthetic studies. To address these issues, we introduce the Soil Food Web Ontology, a novel formal conceptual framework designed to foster agreement on the trophic ecology of soil organisms. This ontology represents a collaborative and ongoing endeavour aimed at establishing consensus and formal definitions for the array of concepts relevant to soil trophic ecology. Its primary objective is to enhance the accessibility, interpretation, combination, reuse, and automated processing of trophic data. By harmonising the terminology and fundamental principles of soil trophic ecology, we anticipate that the Soil Food Web Ontology will improve knowledge management within the field. It will help soil ecologists to better harness existing information regarding the feeding behaviours of soil organisms, facilitate more robust trophic classifications, streamline the reconstruction of soil food webs, and ultimately render food-web research more inclusive, reusable and reproducible.