Inferring species interactions from ecological survey data: A mechanistic approach to predict quantitative food webs of seed feeding by carabid beetles

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.

The reliability of regional ecological knowledge to build local interaction networks: a test using seed-dispersal networks across land-bridge islands

“…We took n to be 5-24 for setting 20 gradients of species richness (i.e. 12-50 species), according to observed plant richness (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24) on study islands and the highest species richness on the largest island (50; electronic supplementary material, table S2). For each gradient of species richness, we set six levels of local interaction rewiring, i.e.…”

“…Recently, indirect ecological information was used to predict and collect potential pairwise species interactions [5,9,10]. For example, Ong et al built plant–frugivore interaction networks based on information on interactions accumulated through observations by many people in many local places over long periods of time [5]; hence the resulting networks may be more useful to describe broad-scale processes, or even historical interactions [11].…”

Estimating co‐extinction threats in terrestrial ecosystems

“…Although empirical data such as field observations quantifying interaction frequency and intensity (Wootton & Emmerson, 2005) can be used to infer an interaction strength between species, alternative approaches are necessary when such data are not available (as is often the case). Various mechanistic models can account for such effects, including those that use traits to incorporate the frequency of prey items in predator diets (Pocock et al, 2021), or those based on bioenergetic‐mechanistic models that link the energy flow between species and describe how they acquire and transform resources into traits (e.g. body size) that influence relationships (Passoni et al, 2022).…”

Functional redundancy of weed seed predation is reduced by intensified agriculture

“…Functional redundancy of weed seed predation has never been directly quantified using field data, in part due to difficulties in specifying predator seed choices in the field. Nevertheless, the considerable overlap in seed preferences between different seed feeding carabid species found in laboratory studies (Petit et al, 2014;Saska et al, 2008) and modelling approaches inferring interaction strength between carabids and seeds (Pocock et al, 2021), indicate that functional redundancy within this guild is high. Field management intensity can decrease seed predator diversity (Menalled et al, 2007;Purtauf et al, 2005) which is likely to reduce functional redundancy at the field scale and hence also the spatial stability of weed seed predation rates (Lami et al, 2020).…”