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Quantitative food web modeling unravels the importance of the microphytobenthos-meiofauna pathway for a high trophic transfer by meiofauna in soft-bottom intertidal food webs

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  • van der Heijden, L.H.
  • Niquil, N.
  • Haraldsson, M.
  • Asmus, R.M.
  • Pacella, S.R.
  • Graeve, M.
  • Rzeznik-Orignac, J.
  • Asmus, H.
  • Saint-Béat, B.
  • Lebreton, B.

Abstract

Meiofauna are known to have an important role on many ecological processes, although, their role in food web dynamics is often poorly understood, partially as they have been an overlooked and under sampled organism group. Here, we used quantitative food web modeling to evaluate the trophic relationship between meiofauna and their food sources and how meiofauna can mediate the carbon flow to higher trophic levels in five contrasting soft-bottom intertidal habitats (including seagrass beds, mudflats and sandflats). Carbon flow networks were constructed using the linear inverse model-Markov chain Monte Carlo technique, with increased resolution of the meiofauna compartments (i.e. biomass and feeding ecology of the different trophic groups of meiofauna) compared to most previous modeling studies. These models highlighted that the flows between the highly productive microphytobenthos and the meiofauna compartments play an important role in transferring carbon to the higher trophic levels, typically more efficiently so than macrofauna. The pathway from microphytobenthos to meiofauna represented the largest flow in all habitats and resulted in high production of meiofauna independent of habitat. All trophic groups of meiofauna, except for selective deposit feeders, had a very high dependency on microphytobenthos. Selective deposit feeders relied instead on a wider range of food sources, with varying contributions of bacteria, microphytobenthos and sediment organic matter. Ecological network analyses (e.g. cycling, throughput and ascendency) of the modeled systems highlighted the close positive relationship between the food web efficiency and the assimilation of high-quality food sources by primary consumers, e.g. meiofauna and macrofauna. Large proportions of these flows can be attributed to trophic groups of meiofauna. The sensitivity of the network properties to the representation of meiofauna in the models leads to recommending a greater attention in ecological data monitoring and integrating meiofauna into food web models.

Suggested Citation

  • van der Heijden, L.H. & Niquil, N. & Haraldsson, M. & Asmus, R.M. & Pacella, S.R. & Graeve, M. & Rzeznik-Orignac, J. & Asmus, H. & Saint-Béat, B. & Lebreton, B., 2020. "Quantitative food web modeling unravels the importance of the microphytobenthos-meiofauna pathway for a high trophic transfer by meiofauna in soft-bottom intertidal food webs," Ecological Modelling, Elsevier, vol. 430(C).
  • Handle: RePEc:eee:ecomod:v:430:y:2020:i:c:s0304380020302015
    DOI: 10.1016/j.ecolmodel.2020.109129
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    References listed on IDEAS

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    1. Van den Meersche, Karel & Soetaert, Karline & Van Oevelen, Dick, 2009. "xsample(): An R Function for Sampling Linear Inverse Problems," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 30(c01).
    2. Saint-Béat, B. & Vézina, A.F. & Asmus, R. & Asmus, H. & Niquil, N., 2013. "The mean function provides robustness to linear inverse modelling flow estimation in food webs: A comparison of functions derived from statistics and ecological theories," Ecological Modelling, Elsevier, vol. 258(C), pages 53-64.
    3. Johnson, Galen A. & Niquil, Nathalie & Asmus, Harald & Bacher, Cédric & Asmus, Ragnhild & Baird, Daniel, 2009. "The effects of aggregation on the performance of the inverse method and indicators of network analysis," Ecological Modelling, Elsevier, vol. 220(23), pages 3448-3464.
    4. Guesnet, Vanessa & Lassalle, Géraldine & Chaalali, Aurélie & Kearney, Kelly & Saint-Béat, Blanche & Karimi, Battle & Grami, Boutheina & Tecchio, Samuele & Niquil, Nathalie & Lobry, Jérémy, 2015. "Incorporating food-web parameter uncertainty into Ecopath-derived ecological network indicators," Ecological Modelling, Elsevier, vol. 313(C), pages 29-40.
    5. Pacella, Stephen R. & Lebreton, Benoit & Richard, Pierre & Phillips, Donald & DeWitt, Theodore H. & Niquil, Nathalie, 2013. "Incorporation of diet information derived from Bayesian stable isotope mixing models into mass-balanced marine ecosystem models: A case study from the Marennes-Oléron Estuary, France," Ecological Modelling, Elsevier, vol. 267(C), pages 127-137.
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