Relevance of evolutionary history for food web structure

Abstract

Explaining the structure of ecosystems is one of the great challenges of ecology. Simple models for food web structure aim at disentangling the complexity of ecological interaction networks and detect the main forces that are responsible for their shape. Trophic interactions are influenced by species traits, which in turn are largely determined by evolutionary history. Closely related species are more likely to share similar traits, such as body size, feeding mode and habitat preference than distant ones. Here, we present a theoretical framework for analysing whether evolutionary history-represented by taxonomic classificationprovides valuable information on food web structure. In doing so, we measure which taxonomic ranks better explain species interactions. Our analysis is based on partitioning of the species into taxonomic units. For each partition, we compute the likelihood that a probabilistic model for food web structure reproduces the data using this information. We find that taxonomic partitions produce significantly higher likelihoods than expected at random. Marginal likelihoods (Bayes factors) are used to perform model selection among taxonomic ranks. We show that food webs are best explained by the coarser taxonomic ranks (kingdom to class). Our methods provide a way to explicitly include evolutionary history in models for food web structure.

Evaluating factors that predict the structure of a commensalistic epiphyte–phorophyte network

“…A phylogenetic signal is not uncommon in mutualistic and antagonistic interactions [13,14,59]. Similar to our findings, the commensalistic networks between orchid epiphytes and their host trees do not show a phylogenetic signal [26].…”

“…There has been debate on whether neutral or biological factors such as complementarity in species phenotypes determine structural patterns of networks [9][10][11][12]. Phylogenetic analyses can help understand network topology because evolutionary history can influence ecological interactions [13,14]. Recent advances have been made in identifying the factors that influence network structure in mutualisms [12,[15][16][17] and antagonisms [18 -20], though there is a lag in the study of commensalistic interactions.…”

Selection on stability across ecological scales

“…Similar nonrandom motif profiles could also arise by network assembly, the effects of which have been found in both mutualistic and trophic networks [33][34][35][36][37]. Only by developing strong models of network assembly can one separate the effect of dynamical pruning from that of network growth and development.…”

Components of Phylogenetic Signal in Antagonistic and Mutualistic Networks

“…Specifically, when studying ecological networks, they have concluded that network patterns have a phylogenetic signal and that, therefore, one cannot fully understand network architecture without considering the evolutionary history of constituent species (Cattin et al 2004;Bersier and Kehrli 2008;Eklof et al 2012;Mouquet et al 2012;Naisbit et al 2012). These studies have immediate implications for our understanding of network assembly (Cattin et al 2004;, the rate at which evolutionary history is lost as networks disassemble , and which ecological variables best correlate with network structure Bersier and Kehrli 2008;Eklof et al 2012;Naisbit et al 2012). They also pave the road toward a predictive assessment of the networkwide consequences of biological invasions (Ives and Godfray 2006).…”