Stoichiometric and structural uncertainty in soil food web models

Abstract

1. Soil food web models are a powerful tool for calculating the carbon and nitrogen mineralized by different soil organisms. Two limitations of the current models are that they use (a) fixed parameters for determining the relative efficiency of carbon and nitrogen conversion and (b) a generic set of trophic species (i.e. nodes). 2. We propose a new method for analysing soil food webs that varies production efficiency and diet mechanistically with resource stoichiometry. Then, we calculated how the lumping or splitting of trophic species affects carbon and nitrogen mineralization for both net mineralization rates as well as the distribution of mineralization (i.e. sources of mineralization). Our models with additional stoichiometric details better represent organisms that consume basal resources with high C:N ratios. 3. This is important because we show that lumping together trophic species at low trophic levels, which often differ in C:N ratios (i.e. microbial taxa), causes the largest deviations in estimates of carbon and nitrogen mineralization. One reason for the large effect of C:N ratio is that it impacts diet and production efficiency in our stoichiometric model. Conversely, lumping together species at higher trophic levels causes the largest errors when those species have different production and assimilation efficiencies. Finally, we demonstrate that differences in death rate and biomass are mostly important when lumping species that have different diets. 4. We suggest that C:N ratios are especially important when grouping microbial taxa because microbial C:N ratios vary widely and microbes feed at low trophic levels where differences in C:N ratio mattered the most. Conversely lumping higher consumers will be most problematic when they have differences in the conversion efficiencies. We provide an approach to calculate structural error and report it with parameter uncertainty. Then, we demonstrate, using oribatid mites as an example, that considering the life history of different taxa can help us group organisms more efficiently into trophic species. In doing so, we provide a way to reduce and report the uncertainty in soil food web models and to stimulate future empirical work measuring key life history parameters.

Multifunctionality of belowground food webs: resource, size and spatial energy channels

“…Accounting for nitrogen concentrations or C to N ratios in resources and consumers is thus a promising approach for predicting interaction strengths in soil food webs (Buchkowski & Lindo, 2020).…”

“…In soil, such groups are traditionally termed trophic guilds and have a more functional focus, being linked to the exploitation of a specific basal resource in a specific way, and even having similar microhabitat preferences (Moore, Walter, & Hunt, 1988;Brussaard, 1998). To get correct estimates of food consumption, such groups should also share similar physiology and stoichiometry (Buchkowski & Lindo, 2020). In most reconstructions, pure trophic classification such as detritivores, bacterivores, fungivores, herbivores, carnivores and omnivores are mixed with high-rank taxonomic classifications (Hunt et al, 1987;de Vries et al, 2013;Gongalsky et al, 2021).…”

“…CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is Among specific traits, elemental composition can be considered in the food selection (Buchkowski & Lindo, 2020). Node-specific cannibalistic interactions could be quantified and incorporated.…”

“…Among specific traits, elemental composition can be considered in the food selection (Buchkowski & Lindo, 2020). Node-specific cannibalistic interactions could be quantified and incorporated.…”

For flux's sake: General considerations for energy‐flux calculations in ecological communities

“…Although specific information on how topological resolution (aggregation of organisms into nodes) affects energy‐flux calculations is sparse, we can use insights from related topics (aggregation impacts on food‐web structure) to gain an idea of what impact the chosen level of aggregation might have, how much aggregation would be acceptable, and how different types of aggregation may affect our results. Aggregation is an important factor in ecology and the potential issues resulting from it have been discussed (Buchkowski & Lindo, 2020 ; Gardner et al., 1982 ; Gauzens et al., 2013 ; Pinnegar et al., 2005 ). Two distinct types of aggregation are relevant here: serial and parallel aggregation.…”