The Nature-Disorder Paradox: A Perceptual Study on How Nature Is Disorderly Yet Aesthetically Preferred
Natural environments have powerful aesthetic appeal linked to their capacity for psychological restoration. In contrast, disorderly environments are aesthetically aversive, and have various detrimental psychological effects. But in our research, we have repeatedly found that natural environments are perceptually disorderly. What could explain this paradox? We present 3 competing hypotheses: the aesthetic preference for naturalness is more powerful than the aesthetic aversion to disorder (the nature-trumps-disorder hypothesis); disorder is trivial to aesthetic preference in natural contexts (the harmless-disorder hypothesis); and disorder is aesthetically preferred in natural contexts (the beneficial-disorder hypothesis). Utilizing novel methods of perceptual study and diverse stimuli, we rule in the nature-trumps-disorder hypothesis and rule out the harmless-disorder and beneficial-disorder hypotheses. In examining perceptual mechanisms, we find evidence that high-level scene semantics are both necessary and sufficient for the nature-trumps-disorder effect. Necessity is evidenced by the effect disappearing in experiments utilizing only low-level visual stimuli (i.e., where scene semantics have been removed) and experiments utilizing a rapid-scene-presentation procedure that obscures scene semantics. Sufficiency is evidenced by the effect reappearing in experiments utilizing noun stimuli which remove low-level visual features. Furthermore, we present evidence that the interaction of scene semantics with low-level visual features amplifies the nature-trumps-disorder effect—the effect is weaker both when statistically adjusting for quantified low-level visual features and when using noun stimuli which remove low-level visual features. These results have implications for psychological theories bearing on the joint influence of low- and high-level perceptual inputs on affect and cognition, as well as for aesthetic design.