Page - 136 - in Biodiversity and Health in the Face of Climate Change

136 predicted environment, one that is currently out of view, requires two information qualities. Legibility helps facilitate understanding of the environment. A legible environment is “easy to understand and to remember” (Kaplan and Kaplan 1989, p.  55) and suggests that one can proceed further into the environment without get- ting lost. Features of legibility include landmarks and trails. Mystery is the promise of additional information with a change of vantage point, the possibility of more information just around the corner. Mystery encourages future involvement (there is some partially hidden information) and continued exploration of the environment (to find out what it is, what is over there). Features of mystery include a bend in a path, partial obstruction of a view, or a modest change in environmental features (Kaplan and Kaplan 1989). 7.2.2.1 Connection to  Biodiversity in  the  Preference Matrix In the Preference Matrix, biodiversity is implicitly mentioned as complexity; Kaplan and Kaplan (1989, p.  53) discuss an environment’s “diversity” and “richness” when describing this information quality. Van den Berg et  al. (2016) investigated whether perceived complexity of natural and urban scenes would explain differences in viewing times and ratings of mental restoration (a composite measure assessing fascination, beauty, relaxation, positive affect) (see Sect. 7.3.2 for further discussion on these concepts). Perceived complexity in this study was assessed as the number of different elements to see in the environment. Participants rated natural scenes as more complex than urban scenes. Further, within the type of environment, viewing times and mental restoration differed according to the complexity of the environ- ment. More complex natural scenes with “information-rich tree-tops and forest” were viewed longer and rated as more restorative, than less complex natural scenes with shrubs and fields (van den Berg et  al. 2016, p.  400). The authors suggest that complexity may be an important indicator of a scene’s restorative potential. 7.2.3 Fractal Geometry and  Visual Fluency The term fractal is used to describe shapes, processes or systems that contain repeat- ing patterns that are reduced-size copies of the whole (Bourke 1991; Ibanez and Bockheim 2013). As such, the defining feature of fractals is self-similarity; a “shape is made of smaller copies of itself…same shape but different size” (Frame et  al. n.d.). This self-similarity can be identified and quantified by the fractal dimension, D. The equation for fractal dimension, D, is log(NR)/log(1/SR), where N equals the number of line segments in the pattern, S is the scale factor, and R is the number of recursions of the pattern (Bies et  al. 2016). For example, a fractal line will have a fractal dimension D score that is between 1.0 and 2.0, whilst a fractal surface will have a D score between 2.0 and 3.0 (Hagerhall et  al. 2004). M. R. Marselle