Species abundance and asymmetric interaction strength in ecological networks

By D. P. Vázquez, Carlos J. Melián, N. Williams, N. Blüthgen, B. Krasnov, Robert Poulin. 2007

661 citations recorded by the source corpus.

The strength of interactions among species in a network tends to be highly asymmetric. We evaluate the hypothesis that this asymmetry results from the distribution of abundance among species, so that species interactions occur randomly among individuals. We used a database on mutualistic and antagonistic bipartite quantitative interaction networks. We show that across all types of networks asymmetry was correlated with abundance, so that rare species were asymmetrically affected by their abundant partners, while pairs of interacting abundant species tended to exhibit more symmetric, reciprocally strong effects. A null model shows that abundance provides a sufficient explanation of the asymmetry structure in some networks, but suggests the role of additional factors in others. Although not universal, our hypothesis holds for a substantial fraction of networks analyzed here, and should be considered as a null model in all studies aimed at evaluating the ecological and evolutionary consequences of species interactions.

Subfields: Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation, Plant Science

View Paper: https://www.semanticscholar.org/paper/470478eb4e09153847ca6efd59e2b61dd979f821

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Citations in the corpus

Diversity of Interactions: A Metric for Studies of Biodiversity (2010, background): “This general approach of using neutral models to examine species interactions has proven profitable in recent studies on the asymmetry (Vazquez et al. 2007) and nestedness (Krishna et al. 2008) of mutualistic interactions.”
The tolerance of island plant–pollinator networks to alien plants (2011, background): “…visitation frequencies as a surrogate for interaction strength (Vázquez, Morris & Jordano 2005; Bascompte, Jordano&Olesen 2006; Sahli & Conner 2007; Vázquez et al. 2007) and expressed mean visitation frequency per hour (‘interaction frequency’) as the total number of visits ⁄ flower ⁄ hour of…”
Identifying Causes of Patterns in Ecological Networks: Opportunities and Limitations (2017, background): “Supporting the abundance-driven view, network patterns are often strongly driven by species numbers and abundance distributions (e.g., Vázquez et al. 2007, Krishna et al. 2008).”
Parasites in food webs: the ultimate missing links (2008, background): “Sometimes authors consider networks of hosts and parasites in a narrower context than a community food web (Martinez et al. 1999; Muller et al. 1999; Memmott et al. 2000; Rott & Godfray 2000; Vazquez et al. 2007; Mouillot et al. 2008).”
Influence of extrafloral nectary phenology on ant–plant mutualistic networks in a neotropical savanna (2013, background): “The fact that the generalist core in our study site is stable indicates that different species of plants and ants can be interacting in the same way, with the potential to drive the coevolution of the whole network (Vázquez et al., 2007; Guimarães et al., 2011; Dáttilo et al., 2013).”
The ‘night shift’: nocturnal pollen‐transport networks in a boreal pine forest (2011, background): “It is generally assumed that abundance and ecological generalisation (measured as the number of different interaction partners) are highly correlated: the most abundant species are the ones with high numbers of interaction partners (Vázquez & Aizen, 2003; Vázquez, 2005; Vázquez et al., 2007).”
A comparative study of ecological specialization estimators (2012, methodology): “2003), and methods exist to remove the impact of the relative frequencies of resources on the interaction data (Vázquez et al. 2007).”
Metabarcoding From Microbes to Mammals: Comprehensive Bioassessment on a Global Scale (2020, background): “For example, hierarchical models could incorporate relative read abundance information, and outputs from these models could be integrated into ecological networks and heuristic food webs to estimate interaction strengths and calculate probabilities of interaction [sensu (Vázquez et al., 2007; Morale”