A common framework for identifying linkage rules across different types of interactions

By Ignasi Bartomeus, Dominique Gravel, J. Tylianakis, M. Aizen, Ian A. DICKIE, Maud Bernard‐Verdier. bioRxiv, 2015

210 citations recorded by the source corpus.

Species interactions, ranging from antagonisms to mutualisms, form the architecture of biodiversity and determine ecosystem functioning. Understanding the rules responsible for who interacts with whom, as well as the functional consequences of these interspecific interactions, is central to predicting community dynamics and stability. Species traits sensu lato may affect different ecological processes determining species interactions through a two-step process. First, ecological and life-history traits govern species distributions and abundance, and hence determine species co-occurrence, which is a prerequisite for them to interact. Second, morphological traits between co-occurring potential interaction partners should match for the realization of an interaction. Moreover, inferring functioning from a network of interactions may require the incorporation of interaction efficiency. This efficiency may be also trait-mediated, and can depend on the extent of matching, or on morphological, physiological or behavioural traits. It has been shown that both neutral and trait-based models can predict the general structure of networks, but they rarely accurately predict individual interactions, suggesting that these models may be predicting the right structure for the wrong reason. We propose to move away from testing null models with a framework that explicitly models the probability of interaction among individuals given their traits. The proposed models integrate both neutral and trait-matching constraints while using only information about known interactions, thereby overcoming problems originating from under-sampling of rare interactions (i.e. missing links). They can easily accommodate qualitative or quantitative data, and can incorporate trait variation within species, such as values that vary along developmental stages or environmental gradients. We use three case studies to show that they can detect strong trait matching (e.g. predator-prey system), relaxed trait matching (e.g. herbivore-plant system) and barrier trait matching (e.g. plant-pollinator systems). Only by elucidating which species traits are important in each process, i.e. in determining interaction establishment, frequency, and efficiency, can we advance in explaining how species interact and the consequences for ecosystem functioning.

Subfields: Ecology, Evolution, Behavior and Systematics

View Paper: https://www.semanticscholar.org/paper/1f3d0e67d510a2ff93400e5165f0b6129b3195a3

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In Ecology, Evolution, Behavior and Systematics

Citations in the corpus

Morphological trait matching shapes plant–frugivore networks across the Andes (2018, background): “Knowledge about trait matching rules that govern the interactions between resource and consumer species can be used to make projections about which pairs of species are likely to interact in current or potential future communities (Morales-Castilla et al. 2015, Bartomeus et al. 2016).”
Identifying Causes of Patterns in Ecological Networks: Opportunities and Limitations (2017, background): “…various effects of community composition on (observed) network structure put forward by the abundance-driven view (see, e.g., Wells & O’Hara 2013, Crea et al. 2015, and Bartomeus et al. 2016 for new developments in statistical network models, which may inform the integration into dynamical models).”
AVONET: morphological, ecological and geographical data for all birds. (2022, background): “…across animal and plant trait data may provide the key to understanding complex trophic interaction networks at the heart of ecological processes, such as nutrient and energy transfer, seed dispersal, pollination and predation (Bartomeus et al., 2016; Harfoot et al., 2014; Schleuning et al., 2015).”
Analysing ecological networks of species interactions (2018, background): “More recently, several models suggested that species traits can be used to approximate the structure of networks (Santamaría & Rodríguez-Gironés, 2007; Bartomeus, 2013; Olito & Fox, 2015; Crea et al., 2015; Bartomeus et al., 2016).”