Ecogeomorphic state variables and phase‐space construction for quantifying the evolution of vegetated aeolian landscapes

Abstract

Cellular automaton modelling for the simulation of dune fi eld formation and evolution has developed progressively in aeolian geomorphology in the last decade or so. A model that incorporates the effects of vegetation and its interactions with geomorphic landscape development -the Discrete Ecogeomorphic Aeolian Landscapes (DECAL) model -can replicate a number of important visual and qualitative aspects of the complex evolution of aeolian dune landscapes under the infl uence of vegetation dynamics in coastal environments. A key challenge in this research area is the analysis and comparison of both simulated and real-world vegetated dune landscapes using objective and quantifi able principles. This study presents a methodological framework or protocol for numerically quantifying various ecogeomorphic attributes, using a suite of mathematically defi ned landscape metrics, to provide a rigorous and statistical evaluation of vegetated dune fi eld evolution. Within this framework the model parameter space can be systematically explored and simulation outcomes can be methodically compared against real-world landscapes. Based on a simplifi ed scenario of parabolic dunes developing out of blow-outs the resulting dune fi eld realizations are investigated as a function of variable growth vigour of two simulated vegetation types (pioneer grass and successional woody shrub) by establishing a typological phase-diagram of different landscape classes. The set of simulation outcomes furthermore defi nes a higher-dimensional phase-space, whose axes or dimensions can be interpreted by analysing how individual ecogeomorphic landscape metrics, or state variables, contribute to the data distribution. Principal component analysis can reduce this to a visual three-dimensional (3D) phase-space where landscape evolution can be plotted as time-trajectories and where we can investigate the effects of changing environmental conditions partway through a simulation scenario. The use of landscape state variables and the construction of a 3D phase-space presented here may provide a general template for quantifying many other eco-geomorphic systems on the Earth's surface.

Remote sensing and spatial analysis of aeolian sand dunes: A review and outlook

“…Parallel progress in the application of general geomorphometric techniques in allied branches of Earth-surface science provides some guidance on how to address this issue for dune fields. A variety of general geomorphometric variables could be calculated within a standardized local window (see Baas and Nield, 2010;Hugenholtz and Barchyn, 2010) for each pixel in a study area and summarized within a statistical framework. Statistical techniques could be used to reduce collinearity and isolate the metrics that characterize the most variability dune field (Baas and Nield, 2010).…”

“…A variety of general geomorphometric variables could be calculated within a standardized local window (see Baas and Nield, 2010;Hugenholtz and Barchyn, 2010) for each pixel in a study area and summarized within a statistical framework. Statistical techniques could be used to reduce collinearity and isolate the metrics that characterize the most variability dune field (Baas and Nield, 2010). We believe there are many opportunities to use or adapt existing metrics to the field of study, but acknowledge that an applicable framework has yet to be developed.…”

“…Moreover, Cataño-Lopera et al (2009) point out that this type of analysis can be used to compare bedform characteristics generated from computer models with those generated in flumes or under natural conditions. Objective methods that can be used to gauge model output are essential for refining the representativeness of the latter (Baas and Nield, 2010). At present, aeolian geomorphology is lacking these validation tools, Fig.…”

Environmental controls, morphodynamic processes, and ecogeomorphic interactions of barchan to parabolic dune transformations

“…Some progress has been made through an integration of computer modelling with field measurements and remote sensing techniques (Duran et al, 2008;Nield and Baas, 2008b;Barchyn and Hugenholtz, 2012a;Barchyn and Hugenholtz, 2012b) This paper presents simulation results from a cellular automaton model that has been extended from DECAL, the Discrete Eco-geomorphic Aeolian Landscapes model (Nield and Baas, 2008a;Nield and Baas, 2008b;Baas and Nield, 2010), by incorporating seasonality and a dynamic growth function, parameterised by field measurements and remote sensing of a vegetated dune field in Inner Mongolia, China. The Extended-DECAL is used to: 1) explore the role of key environmental factors in a barchan to parabolic dune transformation, 2) develop a non-dimensional 'stabilising index' that can be used to compare transformations across different dune systems, 3) illustrate eco-…”

Accommodation space indicates dune development potential along an urbanized and frequently nourished coastline

“…The latter condition is not disputed, as the reinforcing feedback between the 5 growth response of marram grass and burial by wind-blown sand is well documented (Huiskes, 1979;Disraeli, 1984;Maun and Lapierre, 1984;Van der Putten et al, 1988;Hesp, 1991;Maun, 1998) and recognized to be fundamental to coastal dune development in temperate regions around the world (e.g., Baas and Nield, 2010;Durán and Moore, 2013;Keijsers et al, 2016;Nolet et al, 2017). The positive feedback mechanism is thought to originate from a trait that all beach grasses of the genus Ammophila possess, namely potentially unlimited horizontal and vertical growth through its rhizomes (Gemmell et al, 1953;10 Ranwell, 1972).…”