Evidence for the Dominance of Indirect Effects in 50 Trophically-Based Ecosystem Networks

Indirect effects are powerful influences in ecosystems that may maintain species diversity and alter apparent relationships between species in surprising ways. Here, we applied Network Environ Analysis to 50 empirically-based trophic ecosystem models to test the hypothesis that indirect flows dominate direct flows in ecosystem networks. Further, we used Monte Carlo based perturbations to investigate the robustness of these results to potential error in the underlying data. To explain our findings, we further investigated the importance of the microbial food web in recycling energy-matter using components of the Finn Cycling Index and analysis of Environ Centrality. We found that indirect flows dominate direct flows in 37/50 (74.0%) models. This increases to 31/35 (88.5%) models when we consider only models that have cycling structure and a representation of the microbial food web. The uncertainty analysis reveals that there is less error in the I/D values than the $\pm$ 5% error introduced into the models, suggesting the results are robust to uncertainty. Our results show that the microbial food web mediates a substantial percentage of cycling in some systems (median = 30.2%), but its role is highly variable in these models, in agreement with the literature. Our results, combined with previous work, strongly suggest that indirect effects are dominant components of activity in ecosystems.

💡 Research Summary

This study investigates whether indirect flows dominate direct flows in trophically based ecosystem networks by applying Network Environ Analysis (NEA) to fifty empirically derived food‑web models. The authors first calculate the I/D ratio for each model, where I/D > 1 indicates that the total magnitude of indirect material or energy transfers exceeds that of direct predator‑prey transfers. In the full set of 50 models, 37 (74 %) exhibit I/D > 1, providing strong empirical support for the hypothesis that indirect effects are a major component of ecosystem activity.

To explore the influence of network structure, the authors isolate a subset of 35 models that explicitly contain cycling pathways and a representation of the microbial food web. Within this subset, 31 models (88.5 %) show I/D > 1, suggesting that the presence of recycling loops and microbial mediation amplifies indirect flows.

Robustness to data uncertainty is assessed through Monte Carlo perturbations. Each flow parameter is randomly varied by ±5 % and the NEA recalculated for 10,000 iterations per model. The resulting distributions of I/D values are narrow; the spread is considerably smaller than the imposed ±5 % perturbation, indicating that the dominance of indirect flows is not an artifact of measurement error.

The role of the microbial food web is quantified using two complementary metrics. The Finn Cycling Index (FCI) measures the proportion of total system throughput that is recycled, while Environ Centrality (EC) identifies nodes that disproportionately contribute to the redistribution of flows. Across the models, the microbial compartment accounts for a median of 30.2 % of the recycled throughput, but individual models range from as low as 5 % to as high as 60 %. EC values for microbial nodes are consistently high, especially in lake and coastal systems where nutrient recycling is intense, indicating that microbes act as central hubs in the flow network.

Key insights emerging from the analysis are: (1) indirect flows are the dominant pathway in the majority of real‑world trophic networks; (2) the inclusion of explicit cycling structure and microbial compartments strengthens this dominance; (3) the finding is robust to realistic levels of parameter uncertainty; and (4) microbial communities contribute variably but substantially to ecosystem recycling, aligning with the broader ecological literature on the importance of microbes for nutrient turnover.

These results have practical implications for ecosystem management. Strategies that protect or enhance microbial diversity and activity may bolster the overall resilience and productivity of aquatic ecosystems by reinforcing the indirect pathways that sustain energy and material fluxes. Moreover, the study underscores the necessity of incorporating microbial functional groups into ecosystem models to obtain accurate assessments of flow dynamics. Future work should extend this approach to terrestrial and soil food webs, examine temporal changes in indirect flow dominance, and evaluate how anthropogenic disturbances alter the balance between direct and indirect interactions.