University of Oulu

Gong, J., Roulet, N., Frolking, S., Peltola, H., Laine, A. M., Kokkonen, N., and Tuittila, E.-S.: Modelling the habitat preference of two key Sphagnum species in a poor fen as controlled by capitulum water content, Biogeosciences, 17, 5693–5719, https://doi.org/10.5194/bg-17-5693-2020, 2020.

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

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Author: Gong, Jinnan1; Roulet, Nigel2; Frolking, Steve1,3;
Organizations: 1School of Forest Sciences, University of Eastern Finland, P. O. Box 111, 80101 Joensuu, Finland
2Department of Geography, McGill University and Centre for Climate and Global Change Research, Burnside Hall, 805 Sherbrooke Street West Montreal, Montréal, Québec H3A 2K6, Canada
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, 90014 Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 3.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202102023529
Language: English
Published: Copernicus Publications, 2020
Publish Date: 2021-02-02
Description:

Abstract

Current peatland models generally treat vegetation as static, although plant community structure is known to alter as a response to environmental change. Because the vegetation structure and ecosystem functioning are tightly linked, realistic projections of peatland response to climate change require the inclusion of vegetation dynamics in ecosystem models. In peatlands, Sphagnum mosses are key engineers. Moss community composition primarily follows habitat moisture conditions. The known species habitat preference along the prevailing moisture gradient might not directly serve as a reliable predictor for future species compositions, as water table fluctuation is likely to increase. Hence, modelling the mechanisms that control the habitat preference of Sphagna is a good first step for modelling community dynamics in peatlands. In this study, we developed the Peatland Moss Simulator (PMS), which simulates the community dynamics of the peatland moss layer. PMS is a process-based model that employs a stochastic, individual-based approach for simulating competition within the peatland moss layer based on species differences in functional traits. At the shoot-level, growth and competition were driven by net photosynthesis, which was regulated by hydrological processes via the capitulum water content. The model was tested by predicting the habitat preferences of Sphagnum magellanicum and Sphagnum 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 the capitulum water content being correctly specified. Neglecting the water content differences led to the failure of PMS to predict the habitat preferences of the species in stochastic simulations. Our work highlights the importance of the capitulum water content with respect to the dynamics and carbon functioning of Sphagnum communities in peatland ecosystems. Thus, studies of peatland responses to changing environmental conditions need to include capitulum water processes as a control on moss community dynamics. Our PMS model could be used as an elemental design for the future development of dynamic vegetation models for peatland ecosystems.

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Series: Biogeosciences
ISSN: 1726-4170
ISSN-E: 1726-4189
ISSN-L: 1726-4170
Volume: 17
Issue: 22
Pages: 5693 - 5719
DOI: 10.5194/bg-17-5693-2020
OADOI: https://oadoi.org/10.5194/bg-17-5693-2020
Type of Publication: A1 Journal article – refereed
Field of Science: 1181 Ecology, evolutionary biology
Subjects:
Funding: This research has been supported by the Academy of Finland (project no. 287039), the US National Science Foundation (grant no. 1802825), the Kone Foundation, and the Fulbright-Saastamoinen Foundation.
Copyright information: © Author(s) 2020. This work is distributed underthe Creative Commons Attribution 4.0 License.
  https://creativecommons.org/licenses/by/4.0/