Abstract
Ecological networks are valuable for ecosystem analysis but their use is often limited by a lack of data because many types of ecological interaction, for example, predation, are short‐lived and difficult to observe or detect. While there are different methods for inferring the presence of interactions, they have rarely been used to predict the interaction strengths that are required to construct weighted, or quantitative, ecological networks.Here, we develop a trait‐based approach suitable for inferring weighted networks, that is, with varying interaction strengths. We developed the method for seed‐feeding carabid ground beetles (Coleoptera: Carabidae) although the principles can be applied to other species and types of interaction.Using existing literature data from experimental seed‐feeding trials, we predicted a per‐individual interaction cost index based on carabid and seed size. This was scaled up to the population level to create inferred weighted networks using the abundance of carabids and seeds from empirical samples and energetic intake rates of carabids from the literature. From these weighted networks, we also derived a novel measure of expected predation pressure per seed type per network.This method was applied to existing ecological survey data from 255 arable fields with carabid data from pitfall traps and plant seeds from seed rain traps. Analysis of these inferred networks led to testable hypotheses about how network structure and predation pressure varied among fields.Inferred networks are valuable because (a) they provide null models for the structuring of food webs to test against empirical species interaction data, for example, DNA analysis of carabid gut regurgitates and (b) they allow weighted networks to be constructed whenever we can estimate interactions between species and have ecological census data available. This permits ecological network analysis even at times and in places when interactions were not directly assessed.
Highlights
Networks are a valuable tool for understanding the structure and dynamics of ecosystems (Kaiser-Bunbury & Blüthgen, 2015; Ma et al, 2019; Pocock et al, 2012; Tylianakis et al, 2010)
Inferred networks are valuable because (a) they provide null models for the structuring of food webs to test against empirical species interaction data, for example, DNA analysis of carabid gut regurgitates and (b) they allow weighted networks to be constructed whenever we can estimate interactions between species and have ecological census data available
The lack of data on species interactions is because many interactions are relatively brief or cryptic
Summary
Networks are a valuable tool for understanding the structure and dynamics of ecosystems (Kaiser-Bunbury & Blüthgen, 2015; Ma et al, 2019; Pocock et al, 2012; Tylianakis et al, 2010). It has been applied to biodiversity data, where citizen science provides a large number of co-occurrence records (Milns et al, 2010) One challenge with this approach is that when an association does occur, further information is required to determine the type of interaction (Faust & Raes, 2012; Freilich et al, 2018); for example, an association between two species could be due to predation, mutualism, or shared resource use. We develop a mechanistic model of prey preference (frequency-dependent foraging) to infer weighted interactions of carabid ground beetles preying upon weed seeds at the soil surface of arable fields and apply it to a large dataset of weed seed and carabid abundances
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