Trait evolution within bipartite ecological networks


  • Cang Hui* Stellenbosch University & African Institute for Mathematical Sciences
  • Henintsoa Onivola Minoarivelo Stellenbosch University & Centre of Excellence in Mathematical and Statistical Sciences
  • Andriamihaja Ramanantoanina Stellenbosch University
  • Savannah Nuwagaba Stellenbosch University
  • Feng Zhang Gansu Agricultural University
  • Pietro Landi Stellenbosch University


Bipartite ecological networks are formed by interactions between speciesВ which exploit each other for survival and are crucial components to sustainВ ecosystem function and services, foster biodiversity and aect community stability [1]. Despite their diversity, bipartitle mutualistic interactions exhibit surprisingly well-organised structures. In particular, they are often found to beВ within a certain range of connectance, nestedness and modularity, as well as aВ right skewed degree distribution (e.g. [2]). Connectance measures the proportion of realised interactions among all possible ones in a network, and bipartiteВ networks often have a low to moderate level of connectance. A high level ofВ nestedness, where specialists only interact with a subset of species with whichВ generalists interact, is also a common feature of bipartite ecological networks.В Modularity depicts the extent to which a network is compartmentalized intoВ delimited modules where species are strongly interacting with species withinВ the same module but not those from other modules. Being a typical feature ofВ food webs and antagnostic bipartite networks, high modularity is also commonВ in some mutualistic networks. Most species are poorly connected, with only aВ small number being well connected, resulting in a degree distribution followingВ mostly a truncated power law. Evidently, these multiple features of mutualistic networks are not independent of each other, suggesting that an integratedВ model is required to better capture the intrinsic dynamic features of speciesВ interactions [1, 3].

Here, we review a list of eco-evolutionary models for investigating the pattern emergence in bipartite ecological networks with trait-mediated interactionsВ phylogenetic modelling [4, 5], adaptive interaction switching [6-8] and adaptiveВ dynamics [9-11]. Firstly, using knowledge of the phylogenies of the interactingВ species, our model yielded a signicantly better t to 21% of a set of plant-frugivore mutualistic networks. This highlights the importance, in a substantialВ minority of cases, of inheritance of interaction patterns without excluding theВ potential role of ecological novelties in forming the current network architecture. Second, the model allowing interaction switches between partner speciesВ produced predictions which fit remarkably well with observations, and thus theВ interaction switch is likely a key ecological process that results in nestedness ofВ real-world networks. Finally, trait-based adaptive dynamics models highlightВ the importance of assortative interactions and the balance of costs incurred byВ coevolving species as factors determining the eventual phenotypic outcome of co-evolutionary interactions. The interplay of ecological and evolutionary processesВ through trait-mediated interactions can explain these widely observed architectures in bipartite networks. Coevolutionary networks provide an ideal model forВ modelling complex adaptive systems, which can help to address challenges fromВ global changes facing many complex social-ecological systems [3, 12].


C. Hui, H.O. Minoarivelo, S. Nuwagaba, A Ramanantoanina, Adaptive diversication in coevolutionary systems. In: P. Pontarotti (ed.) Evolutionary Biology: Biodiversication from Genotype to Phenotype. Springer, Berlin, pp.167-186, 2015

S. Nuwagaba, C. Hui, The architecture of antagonistic networks: Node degree distribution, compartmentalization and nestedness, Computational Ecology and Software 5 317-327, 2015

C. Hui, D.M. Richardson, Invasion Dynamics, Oxford University Press, Oxford, 2017

H.O. Minoarivelo, C. Hui, J.S. Terblanche, S.L. Kosakovsky Pond, K. Scheffler, Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model, Oikos 123 1250-1260, 2014

H.O. Minoarivelo, G. Diedericks, C. Hui, An introduction to phylogenetic analyses and modelling in ecology, Computational Ecology and Software 5 328-339, 2015

C. Hui, M.A. McGeoch, Evolution of body size, range size and food composition in a predator-prey metapopulation, Ecological Complexity 3 148-159, 2006

F. Zhang, C. Hui, J.S. Terblanche, An interaction switch predicts the nested architecture of mutualistic networks, Ecology Letters 14 797-803, 2011

S. Nuwagaba, F. Zhang, C. Hui, A hybrid behavioural rule of adaptation and drift explains the emergent architecture of antagonistic networks, Proceedings of the Royal Society B: Biological Sciences 282 20150320, 2015

F. Zhang, C. Hui, A. Pauw, Adaptive divergence in Darwins race: how coevolution can generate trait diversity in a pollination system, Evolution 67 548-560, 2013

H.O. Minoarivelo, C. Hui, Trait-mediated interaction leads to structural emergence in mutualistic networks, Evolutionary Ecology 30 105-121, 2016

H.O. Minoarivelo, C. Hui, Invading a mutualistic network: To be or not to be similar, Ecology and Evolution 6 4981-4996, 2016

C. Hui, D.M. Richardson, P. Landi, H.O. Minoarivelo, J. Garnas, H.E. Roy, Defining invasiveness and invasibility in ecological networks, Biological Invasions 18 971-983, 2016






Keynote/Invited Presentations