Assessing the peatland hummock-hollow classification framework using high-resolution elevation models: Implications for appropriate complexity ecosystem modelling

Abstract. The hummock-hollow classification framework used to categorize peatland ecosystem microtopography is pervasive throughout peatland experimental designs and current peatland ecosystem modelling approaches. However, identifying what constitutes a representative hummock-hollow pair within a site and characterizing hummock-hollow variability within or between peatlands remains largely unassessed. Using structure-from-motion (SfM), high resolution digital elevation models (DEM) of hummock-hollow microtopography were used to: 1) examined how much area needs to be sampled to characterize site-level microtopographic variation; and 2) examine the potential role of microtopographic shape/structure on biogeochemical fluxes using data from 9 norther peatlands. To capture 95 % of site-level microtopographic variability, on average an aggregate sampling area of 32 m2 composed of ten randomly located plots with vegetation removed was required. We further present non-destructive transect-based results as an alternative to the SfM approach. Microtopography at the plot-level was often found to be non-bimodal, as assessed using a Gaussian mixture model (GMM). Our findings suggest that the non-bimodal distribution of microtopography at the plot-level may result in an under-sampling of intermediate topographic position. Extended to the modelling domain, an under-representation of intermediate microtopographic positions is shown to lead to large flux biases over a wide range of water table positions for ecosystem processes which are non-linearly related to water and energy availability at the moss surface. A range of tools examined herein can be used to easily parameterize peatland models, from GMMs used as simple transfer functions, to spatially explicit fractal landscapes based on simple power law relations between microtopographic variability and scale.