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

Abstract

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.

Functional diversity and trait composition of vascular plant and Sphagnum moss communities during peatland succession across land uplift regions

“…Unlike for the vascular plants, there are no established set of traits for Sphagnum mosses. Therefore, we selected such properties that our recent study linked to the capacity to remain moist and, consequently, to photosynthesize (Gong et al, 2020). We defined the following Sphagnum traits: stand density (number of shoots cm −2 ), capitulum width (cap_width, mm) and dry weight (cap_dw, mg), fascicle density (number cm −1 ), capitulum dry matter content (CDMC, mg/g), capitulum water content (cap_wc, g/g) and capitulum C and N contents and C:N ratio.…”

Impact of long‐term water level drawdown on functional plant trait composition of northern peatlands

“…The release of nutrients after WLD does not apply to the Sphagnum mosses that lack a rooting system and which are therefore more dependent on nutrients in the surface runoff water. Furthermore, Sphagnum photosynthesis and growth are both dependent on the capitulum moisture content (Gong et al, 2020; Jassey & Signarbieux, 2019). Therefore, for Sphagnum mosses, we hypothesize that WLD will increase resource conservatism (Figure 1), although this effect could be offset if WLD increases the surface density of the moss layer, as it is the main mechanism for Sphagnum mosses to avoid desiccation (Clymo & Hayward, 1982).…”

Comparing UAS LiDAR and Structure-from-Motion Photogrammetry for Peatland Mapping and Virtual Reality (VR) Visualization

“…It is only a matter of time before peatland ecosystem models (e.g., [74][75][76]) become adapted for 3D spatially explicit input. Fine-scale microtopographic ecohydrological structures that can be represented from either UAS SfM or LiDAR would provide the resolution needed for models to quantify how peatland structure and function changes over time [67], which can lead to insights into the ecohydrological feedbacks [43].…”