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139 (e.g. a Jackson Pollock painting) or computer simulation. They found that fractal patterns with a mid-range D score around 1.3–1.5 were aesthetically preferred, irre- spective of whether they were natural, human or computer generated (Spehar et  al. 2003). Further support for preference for mid-range D scores was found in Bies et  al.’s (2016) study investigating preferences for statistical (fractals that do not repeat exactly but have the same statistical qualities, like those found in nature) or exact (fractal patterns that repeat precisely, created by a computer programme) frac- tals. For statistical fractals mid-range D scores were preferred, whilst for exact frac- tals a higher D score was preferred (Bies et  al. 2016). Interestingly, the mid-range D score of 1.3 is most prevalent in nature (Hagerhall et  al. 2004, 2015), and found in species-rich habitats (Stevens 2018). These results fit with the environmental per- ception and preference theories that posit that intermediate levels of perceived visual complexity are most preferred (Kaplan and Kaplan 1989; Berlyne 1960, 1974; Wohlwill 1968) (see Sects. 7.2.1 and 7.2.2). 7.2.3.3 Fractal Dimension and  Restorative Outcomes One reason fractals are preferred could be due to perceptual fluency  – the ease with which a specific visual stimulus is perceptually processed (Joye and van den Berg 2013). Fractal characteristics of visual stimuli contain redundant information, due to their self-similar repeating patterns, which could contribute to the experience of easy perceptual processing by the brain. This ‘perceptual fluency’ could result in restorative outcomes, such as attention restoration (Joye and van den Berg 2013) (see Sect. 7.3.2). Natural stimuli with fractal geometry may be processed more eas- ily, resulting in lower cognitive resource demands of directed attention (Joye and van den Berg 2013) (see Sect. 7.3.2). This easier processing of natural stimuli may contribute to the restoration of directed attention (Joye and van den Berg 2013). Specifically testing the perceptual fluency hypothesis, Joye et  al. (2016) investi- gated the effect that viewing fractal stimuli would have on cognitive performance. Participants were asked to complete a cognitively effortful task whilst viewing either high fractal or low fractal computer-generated (non-nature) stimuli. Participant’s cognitive performance was better in the high fractal condition than in the low fractal condition (D scores were not assessed). Participants also perceived the cognitive tasks to be easier when looking at the high fractal stimuli, lending sup- port to the perceptual fluency hypothesis. Would fractals with a mid-range D score contribute to perceptual fluency? Juliani et  al. (2016) found that people were best at navigating through virtual, computer- generated fractal landscapes with D scores between 1.1 and 1.3. Hagerhall et  al. (2015) investigated participants’ brain activity while viewing statistical or exact fractals. Participants’ alpha brain waves were recorded as they looked at these frac- tal patterns. Alpha brain waves indicate a “wakefully relaxed state” and are com- monly found when a person has their eyes closed and their attention directed inward 7 Theoretical Foundations of  Biodiversity and  Mental Well-being Relationships
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Biodiversity and Health in the Face of Climate Change
Title
Biodiversity and Health in the Face of Climate Change
Authors
Melissa Marselle
Jutta Stadler
Horst Korn
Katherine Irvine
Aletta Bonn
Publisher
Springer Open
Date
2019
Language
English
License
CC BY 4.0
ISBN
978-3-030-02318-8
Size
15.5 x 24.0 cm
Pages
508
Keywords
Environment, Environmental health, Applied ecology, Climate change, Biodiversity, Public health, Regional planning, Urban planning
Categories
Naturwissenschaften Umwelt und Klima
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