Cross-scale morphology
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چکیده
The scaling of physical, biological, ecological, and social phenomena is a major focus of efforts to develop simple representations of complex systems. Much of the attention has been on discovering universal scaling laws that emerge from simple physical and geometric processes. However, there are regular patterns of departures both from those scaling laws and from continuous distributions of attributes of systems. Those departures often demonstrate the development of self-organized interactions between living systems and physical processes over narrower ranges of scale. Cross-scale morphology refers to morphological attributes of animals that are influenced by interaction with ecological structures and patterns at different scales. Body mass is often the attribute considered, because it correlates strongly with and integrates a broad array of species’ characteristics, such as energy use and home-range size. Growing evidence from nature, ecological modeling, and theory suggests that ecosystem structure and dynamics are dominated by the influence of a small set of plant, animal, and abiotic processes [1–3]. Each set of processes operates at characteristic frequencies and spatial extents (i.e., occur at distinct scales in space and time) [2, 4]. Small and fast scales are dominated by biophysical processes that control plant morphology and function. At larger and slower scales, interspecific plant competition for nutrients, light, and water interacts with climate and affects local species composition and regeneration. At the scale of forest stands, meso-scale processes of fire, storm, insect outbreak, plant diseases, and large mammal herbivory determine structure and succession dynamics from tens of meters to kilometers and years to decades. The largest landscape scales have geomorphological and evolutionary processes that affect structure and dynamics over hundreds of kilometers and millennia. An example for such a forested landscape is shown in Figure 1. This, therefore, is a hierarchical representation of a nested set of variables [4, 6] where each set is controlled by processes sufficiently different in speed and
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