Climatic seasonality may affect ecological network structure: Food webs and mutualistic networks

Ecological networks exhibit non-random structural patterns, such as modularity and nestedness, which indicate ecosystem stability, species diversity, and connectance. Such structure-stability relationships are well known. However, another important perspective is less well understood: the relationship between the environment and structure. Inspired by theoretical studies that suggest that network structure can change due to environmental variability, we collected data on a number of empirical food webs and mutualistic networks and evaluated the effect of climatic seasonality on ecological network structure. As expected, we found that climatic seasonality affects ecological network structure. In particular, an increase in modularity due to climatic seasonality was observed in food webs; however, it is debatable whether this occurs in mutualistic networks. Interestingly, the type of climatic seasonality that affects network structure differs with ecosystem type. Rainfall and temperature seasonality influence freshwater food webs and mutualistic networks, respectively; food webs are smaller, and more modular, with increasing rainfall seasonality. Mutualistic networks exhibit a higher diversity (particularly of animals) with increasing temperature seasonality. These results confirm the theoretical prediction that stability increases with greater perturbation. Although these results are still debatable because of several limitations in the data analysis, they may enhance our understanding of environment-structure relationships.

💡 Research Summary

This paper investigates how climatic seasonality influences the structural properties of ecological networks, focusing on two contrasting interaction types: trophic food webs and mutualistic plant–pollinator networks. The authors begin by highlighting that ecological networks are not random assemblages; they exhibit characteristic patterns such as modularity (the degree to which the network can be partitioned into relatively independent sub‑communities) and nestedness (the tendency for specialist species to interact with a subset of the partners of generalist species). These patterns have been linked to ecosystem stability, species coexistence, and overall connectance, yet the environmental drivers shaping them remain underexplored.

To address this gap, the authors compiled a global dataset comprising roughly 30 empirically documented freshwater food webs and about 50 plant–pollinator networks from published literature and online repositories. For each network they extracted standard topological metrics: number of nodes (species richness), number of links, connectance (C), modularity (Q, calculated with the Louvain algorithm), nestedness (NODF), and animal versus plant diversity. Climate data were obtained from the WorldClim 2.1 database at a 1‑km² resolution, providing four key variables for each network’s geographic centroid: annual precipitation, precipitation seasonality (coefficient of variation of monthly precipitation), mean annual temperature, and temperature seasonality (coefficient of variation of monthly temperature).

Statistical analyses employed generalized linear models (GLMs) and multiple regression to test the relationships between each climatic variable and the network metrics while controlling for network size (a known confounder of modularity and nestedness). Variance inflation factors (VIF) were examined to avoid multicollinearity, and stepwise model selection identified the most parsimonious predictors.

The results reveal distinct, ecosystem‑specific responses to climatic seasonality. In freshwater food webs, precipitation seasonality emerges as the strongest predictor: higher seasonal variability in rainfall is associated with smaller networks (fewer species) and significantly higher modularity (p < 0.01). The authors interpret this as a consequence of fluctuating water availability fragmenting habitats and localizing predator–prey interactions, thereby fostering a more compartmentalized (modular) structure that is theoretically more resilient to perturbations. By contrast, temperature seasonality does not exert a clear effect on food‑web modularity or nestedness.

For mutualistic networks, the pattern is reversed. Temperature seasonality, rather than precipitation seasonality, positively correlates with animal (pollinator) diversity, especially among insects (p < 0.05). Networks experiencing greater temperature fluctuations tend to host a richer assemblage of pollinators, which can broaden the range of plant partners and potentially enhance ecosystem services such as pollination. However, modularity in these networks does not show a consistent increase with temperature seasonality, suggesting that mutualistic systems may respond to climatic variability primarily through species turnover rather than structural re‑organization. Nestedness (NODF) remains largely insensitive to both precipitation and temperature seasonality in both network types, implying that the trade‑off between modularity and nestedness observed in theoretical models may be at play. Connectance, after accounting for network size, shows no systematic relationship with either climatic variable, indicating that the total proportion of realized interactions is not the main pathway through which seasonality shapes network architecture.

The authors discuss these findings in the context of existing theory. Prior modeling work predicts that environments with higher temporal variability select for more modular networks because modularity buffers the spread of disturbances across the whole system. The empirical confirmation of this prediction in food webs lends support to the hypothesis that modularity is an adaptive response to fluctuating abiotic conditions. The weaker or absent modularity response in mutualistic networks suggests that different interaction modalities (mutual benefit versus predator–prey dynamics) may mediate distinct evolutionary and ecological pathways under climatic stress.

Several limitations are acknowledged. The geographic coverage is biased toward temperate regions of the Northern Hemisphere, limiting extrapolation to tropical or polar ecosystems where seasonality manifests differently. Network construction methods vary (field observations, literature synthesis, database extraction), potentially introducing methodological noise into the topological metrics. The climate data’s spatial resolution (1 km²) may not capture micro‑climatic heterogeneity that can be crucial for small‑scale aquatic or pollinator habitats. Finally, the cross‑sectional nature of the dataset precludes definitive causal inference; longitudinal studies or experimental manipulations would be needed to confirm the directionality of the observed relationships.

In conclusion, this study provides one of the first large‑scale empirical examinations of how climatic seasonality shapes ecological network structure. It demonstrates that (1) precipitation seasonality drives increased modularity and reduced size in freshwater food webs, (2) temperature seasonality boosts pollinator diversity in plant–pollinator networks, and (3) nestedness appears robust to these climatic drivers across both interaction types. The findings reinforce the theoretical link between environmental variability and network modularity, while also highlighting that the specific climatic factor (rainfall versus temperature) and the type of ecological interaction determine the nature of the structural response. The authors propose future work integrating high‑resolution climate projections, long‑term monitoring of network dynamics, and experimental perturbations to deepen our understanding of environment‑structure relationships and to inform conservation strategies under accelerating climate change.