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[1] Field experiments were conducted to determine the characteristic spatial and temporal dimensions and behavior of aeolian streamers and to identify the processes responsible for their formation. An instrument array that included anemometer towers, piëzo-electric transport sensors (Safires), and hot-film probes was deployed to measure streamers and airflow dynamics on both a coastal dune and a desert sand mound in California. Aeolian transport occurs predominantly in the form of families of intertwining and bifurcating streamers, while under intense wind forcing, more complex patterns of nested streamers and clouds with embedded streamers develop. The streamers display a characteristic width of approximately 0.2 m and an average lateral spacing of about 1 m. These dimensions appear to be independent of mean airflow characteristics. The observations and measurements of streamers under different environmental conditions suggest that bed surface control in the form of differentiation in moisture content, grain size, or microtopography is not a necessary condition for the formation of streamers. The results show little correlation between possible streamwise vortices or burst sweep events and streamers. It is proposed that streamers are generated by near-surface gusts that originate from large eddies propagating to the ground from higher regions of the boundary layer. These elongated and stretched eddies scrape across the surface and initiate saltation along their path. This concept accounts for the characteristic size and spacing of streamers, their rapid propagation, and the fast response of saltation to wind speed fluctuations.

[1] This letter presents a self-organising cellular automaton model capable of simulating the evolution of vegetated dunes with multiple types of plant response in the environment. It can successfully replicate hairpin, or long-walled, parabolic dunes with trailing ridges as well as nebkha dunes with distinctive deposition tails. Quantification of simulated landscapes with eco-geomorphic state variables and subsequent cluster analysis and PCA yields a phase diagram of different types of coastal dunes developing from blow-outs as a function of vegetation vitality. This diagram indicates the potential sensitivity of dormant dune fields to reactivation under declining vegetation vitality, e.g. due to climatic changes. Nebkha simulations with different grid resolutions demonstrate that the interaction between the (abiotic) geomorphic processes and the biological vegetation component (life) introduces a characteristic length scale on the resultant landforms that breaks the typical self-similar scaling of (un-vegetated) bare-sand dunes. Citation: Baas, A. C. W., and J. M. Nield (2007), Modelling vegetated dune landscapes, Geophys. Res. Lett., 34, L06405,

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Vegetation plays an important role in shaping the morphology of aeolian dune landscapes in coastal and semi-arid environments, where ecogeomorphic interactions are complex and not well quantified. We present a Discrete ECogeomorphic Aeolian Landscape model (DECAL) capable of simulating realistic looking vegetated dune forms, permitting exploration of relationships between ecological and morphological processes at different temporal and spatial scales. The cellular automaton algorithm applies three simple rules that lead to selforganization of complex dune environments, including nebkhas with distinctive deposition tails that form in association with mesquite-type shrubs, and hairpin (long-walled) parabolic dunes with trailing ridges that evolve from blowouts in association with vegetation succession. Changing the conditions of simulations produces differing landscapes that conform qualitatively to observations of real-world dunes. The model mimics the response of the morphology to changes in sediment supply, vegetation distribution, density and growth characteristics, as well as initial disturbances. The introduction of vegetation into the model links spatial and temporal scales, previously dimensionless in bare-sand cellular automata. Grid resolutions coarser than the representative size of the modelled vegetation elements yield similar morphologies, but when cell size is reduced to much smaller dimensions, the resultant landscape evolution is dramatically different. The model furthermore demonstrates that the relative response characteristics of the multiple vegetation types and their mutual feedback with geomorphological processes impart a significant influence on landscape equilibria, suggesting that vegetation induces a characteristic length scale in aeolian environments. This simple vegetated dune model illustrates the power and versatility of a cellular automaton approach for exploring the effects of interactions between ecology and geomorphology in complex earth surface systems. Figure 3. Relationship between values of U * and c/q (solid blue line) and the range of appropriate slab heights (1/7·5 to 1/13) for use in the model. This figure is available in colour online at www.interscience.wiley.com/journal/espl 730 Figure 4. Flow diagram of the DECAL model. Yellow shaded sequence indicates the algorithm of an individual slab displacement. Green section represents the annual vegetation growth response. This figure is available in colour online at Figure 8. Nebkha dune formation under varying sediment flux (top) and speed (bottom) conditions compared with the standard conditions used for Figure 6; transport direction left to right. This figure is available in colour online at

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Aim Within fluvial and coastal ecosystems world-wide, flows of water, wind and sediment generate a shifting landscape mosaic composed of bare substrate and pioneer and mature vegetation successional stages. Pioneer plant species that colonize these ecosystems at the land-water interface have developed specific traits in response to environmental constraints (response traits) and are able to modify habitat conditions by modulating geomorphic processes (effect traits). Changes in the geomorphic environment under the control of engineer plants often feed back to organism traits (feedback traits), and thereby ecosystem functioning, leading to eco-evolutionary dynamics. Here we explain the joint foundations of fluvial and coastal ecosystems according to feedback between plants and the geomorphic environment.Location Dynamic fluvial and coastal ecosystems world-wide.Method Drawing from a pre-existing model of 'fluvial biogeomorphic succession' , we propose a conceptual framework showing that fluvial and coastal 'biogeomorphic ecosystems' are functionally similar due to eco-evolutionary feedbacks between plants and geomorphology. ResultsThe relationships between plant traits and their geomorphic environments within different fluvial and coastal biogeomorphic ecosystems are identified and classified within a framework of biogeomorphic functional similarity according to three criteria: (1) pioneer plants develop specific responses to the geomorphic environment; (2) engineer plants modulate the geomorphic environment; (3) geomorphic changes under biotic control within biogeomorphic ecosystems feed back to organisms. Main conclusionsThe conceptual framework of functional similarity proposed here will improve our capacity to analyse, compare, manage and restore fluvial and coastal biogeomorphic ecosystems world-wide by using the same protocols based on the three criteria and four phases of the biogeomorphic succession model.

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