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Biogeosciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/bg-2019-366
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2019-366
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 18 Nov 2019

Submitted as: research article | 18 Nov 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Biogeosciences (BG).

Modelling the habitat preference of two key Sphagnum species in a poor fen as controlled by capitulum water retention

Jinnan Gong1, Nigel Roulet2, Steve Frolking1,3, Heli Peltola1, Anna M. Laine1,4, Nicola Kokkonen1, and Eeva-Stiina Tuittila1 Jinnan Gong et al.
  • 1School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland
  • 2Department of Geography, McGill University and Centre for Climate and Global Change Research, Burnside Hall, 805 rue Sherbrooke O., Montréal, Québec H3A 2K6
  • 3Institute for the Study of Earth, Oceans, and Space, and Department of Earth Sciences, University of New Hampshire, Durham, NH 03824, USA
  • 4Department of Ecology and Genetics, University of Oulu, P.O. Box 3000, FI-90014, Oulu, Finland

Abstract. Current peatland models generally lack dynamic feedback between the plant community structure and the environment, although the vegetation dynamics and ecosystem functioning are tightly linked. Realistic projections of peatland response to climate change requires including vegetation dynamics in ecosystem models. In peatlands, Sphagnum mosses are key engineers. The species composition in a moss community varies primarily following habitat moisture conditions. Hence, modelling the mechanisms in controlling the habitat preference of Sphagna is a good first step for modelling the community dynamics in peatlands. In this study, we developed the Peatland Moss Simulator (PMS), a process-based model, for simulating community dynamics of the peatland moss layer that results in habitat preferences of Sphagnum species along moisture gradients. PMS employed an individual-based approach to describe the variation of functional traits among shoots and the stochastic base of competition. At the shoot-level, growth and competition were driven by net photosynthesis, which was regulated by hydrological processes via capitulum water retention. The model was tested by predicting the habitat preferences of S. magellanicum and S. fallax, two key species representing dry (hummock) and wet (lawn) habitats in a poor fen peatland (Lakkasuo, Finland). PMS successfully captured the habitat preferences of the two Sphagnum species, based on observed variations in trait properties. Our model simulation further showed that the validity of PMS depended on the interspecific differences in capitulum water retention being correctly specified. Neglecting the water-retention differences led to the failure of PMS to predict the habitat preferences of the species in stochastic simulations. Our work highlights the importance of capitulum water retention to the dynamics and carbon functioning of Sphagnum communities in peatland ecosystems. Studies of peatland responses to changing environmental conditions thus need to include capitulum water processes as a control on the vegetation dynamics. For that our PMS model could be used as an elemental design for the future development of dynamic vegetation models for peatland ecosystems.

Jinnan Gong et al.
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Short summary
In this study, which combined field and lab experiment with modelling, we developed a process-based model for simulating dynamics within peatland moss communities. Model is useful because Sphagnum mosses are key engineers in peatlands; their response to changes in climate through altered hydrology controls the feedback of peatland biogeochemistry to climate. Our work showed that moss capitulum traits related to water retention are the mechanism controlling moss layer dynamics in peatlands.
In this study, which combined field and lab experiment with modelling, we developed a...
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