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

被引:38
作者
Baas, Andreas C. W. [1 ]
Nield, Joanna M. [2 ]
机构
[1] Kings Coll London, Dept Geog, London WC2R 2LS, England
[2] Univ Southampton, Sch Geog, Southampton, Hants, England
关键词
modelling; phase-space; vegetation; dunes; DECAL; PARABOLIC DUNES; SAND-DUNES; COASTAL DUNES; GREAT-PLAINS; GEOMORPHOLOGY; STABILIZATION; CLIMATE; SIMULATIONS; NETHERLANDS; ADAPTATIONS;
D O I
10.1002/esp.1990
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Cellular automaton modelling for the simulation of dune field 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 influence 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 quantifiable principles. This study presents a methodological framework or protocol for numerically quantifying various ecogeomorphic attributes, using a suite of mathematically defined landscape metrics, to provide a rigorous and statistical evaluation of vegetated dune field 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 simplified scenario of parabolic dunes developing out of blow-outs the resulting dune field 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 defines 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. Copyright (C) 2010 John Wiley & Sons, Ltd.
引用
收藏
页码:717 / 731
页数:15
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