Feeding habits and multifunctional classification of soil‐associated consumers from protists to vertebrates
Bibliographic record
Abstract
Soil organisms drive major ecosystem functions by mineralising carbon and releasing nutrients during decomposition processes, which supports plant growth, aboveground biodiversity and, ultimately, human nutrition. Soil ecologists often operate with functional groups to infer the effects of individual taxa on ecosystem functions and services. Simultaneous assessment of the functional roles of multiple taxa is possible using food-web reconstructions, but our knowledge of the feeding habits of many taxa is insufficient and often based on limited evidence. Over the last two decades, molecular, biochemical and isotopic tools have improved our understanding of the feeding habits of various soil organisms, yet this knowledge is still to be synthesised into a common functional framework. Here, we provide a comprehensive review of the feeding habits of consumers in soil, including protists, micro-, meso- and macrofauna (invertebrates), and soil-associated vertebrates. We have integrated existing functional group classifications with findings gained with novel methods and compiled an overarching classification across taxa focusing on key universal traits such as food resource preferences, body masses, microhabitat specialisation, protection and hunting mechanisms. Our summary highlights various strands of evidence that many functional groups commonly used in soil ecology and food-web models are feeding on multiple types of food resources. In many cases, omnivory is observed down to the species level of taxonomic resolution, challenging realism of traditional soil food-web models based on distinct resource-based energy channels. Novel methods, such as stable isotope, fatty acid and DNA gut content analyses, have revealed previously hidden facets of trophic relationships of soil consumers, such as food assimilation, multichannel feeding across trophic levels, hidden trophic niche differentiation and the importance of alternative food/prey, as well as energy transfers across ecosystem compartments. Wider adoption of such tools and the development of open interoperable platforms that assemble morphological, ecological and trophic data as traits of soil taxa will enable the refinement and expansion of the multifunctional classification of consumers in soil. The compiled multifunctional classification of soil-associated consumers will serve as a reference for ecologists working with biodiversity changes and biodiversity-ecosystem functioning relationships, making soil food-web research more accessible and reproducible.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".