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
UMR 7266 Littoral, Environnement et Sociétés (CNRS - University of La Rochelle), Institut du littoral et de l'environnement, 2 rue Olympe de Gouges, 17000 La Rochelle, France.
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Wattenmeerstation Sylt, Hafenstrasse 43, 25992 List/Sylt, Germany.
Ecol Modell. 2020 Aug 15;430:1-16. doi: 10.1016/j.ecolmodel.2020.109129.
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.
已知小型底栖生物在许多生态过程中发挥着重要作用，尽管它们在食物网动态中的作用常常未得到充分理解，部分原因是它们一直是被忽视且采样不足的生物群体。在此，我们运用定量食物网模型来评估小型底栖生物与其食物来源之间的营养关系，以及小型底栖生物如何在五个不同的潮间带软底栖息地（包括海草床、泥滩和沙滩）中介导碳向更高营养级的流动。使用线性逆模型 - 马尔可夫链蒙特卡罗技术构建了碳流动网络，与大多数先前的建模研究相比，提高了小型底栖生物区室（即小型底栖生物不同营养组的生物量和摄食生态）的分辨率。这些模型强调，高生产力的微型底栖植物与小型底栖生物区室之间的流动在将碳转移到更高营养级方面发挥着重要作用，通常比大型底栖生物更有效。从微型底栖植物到小型底栖生物的路径在所有栖息地中都是最大的流动路径，并且导致了与栖息地无关的小型底栖生物的高产量。除选择性沉积取食者外，小型底栖生物的所有营养组对微型底栖植物都有很高的依赖性。相反，选择性沉积取食者依赖更广泛的食物来源，细菌、微型底栖植物和沉积物有机质的贡献各不相同。对建模系统的生态网络分析（例如循环、通量和优势度）突出了食物网效率与初级消费者（如小型底栖生物和大型底栖生物）对优质食物来源的同化之间的密切正相关关系。这些流动的很大一部分可归因于小型底栖生物的营养组。网络属性对模型中小型底栖生物表示的敏感性导致建议在生态数据监测中给予更多关注，并将小型底栖生物纳入食物网模型。
