Anna Keller

Stage models are becoming increasingly popular in explaining change from current behavior to more environmentally friendly alternatives. We review empirical applications of a recently introduced model, the stage model of self-regulated behavioral change (SSBC). In the SSBC, change toward pro-environmental behavior takes place in four, qualitatively different stages (predecisional, preactional, actional, and postactional) which are each influenced by constructs taken from theories previously established to describe and predict pro-environmental behavior. We performed a systematic literature search to retrieve peer-reviewed SSBC-based studies. The review includes 10 studies published between 2013 and 2018, six of which employed a cross-sectional, three an interventional and one a correlational longitudinal design. The cross-sectional and longitudinal studies generally support the model, although there are some irregularities that warrant further investigation. The interventional studies found stage-tailored informational measures to be more effective than non-stage-tailored measures in promoting stage progression and behavioral change. Furthermore, we identified several challenges that researchers may face when applying the SSBC. These include whether and how to analyze multiple behavioral alternatives; how to address the challenge of measuring a comprehensive model while keeping questionnaire length manageable; selecting and defining the role of model constructs in a behavioral context while keeping results comparable; and establishing a validated and reliable tool to diagnose a person’s stage of change. Based on these insights, we develop recommendations for researchers designing SSBC studies, in order to support a founded and efficient advancement of the theory which will then serve both researchers and practitioners aiming to promote pro-environmental behavior.

Due to their unique properties, copper-based nanopesticides are emerging in the market. Thus, understanding their effect on crop plants is very important. Metabolomics can capture a snapshot of cellular metabolic responses to a stressor. We selected maize and cucumber as model plants for exposure to different doses of Cu2 nanopesticide. GC-TOF-MS-based metabolomics was employed to determine the metabolic responses of these two species. Results revealed significant differences in metabolite profile changes between maize and cucumber. Furthermore, the Cu2 nanopesticide induced metabolic reprogramming in both species, but in different manners. In maize, several intermediate metabolites of the glycolysis pathway and tricarboxylic acid cycle were up-regulated, indicating the energy metabolism was activated. In addition, the levels of aromatic compounds and their precursors were enhanced, indicating the activation of shikimate-phenylpropanoid biosynthesis in maize leaves, which is an antioxidant defense-related pathway. In cucumber, arginine and proline metabolic pathways were the most significantly altered pathway. Both species exhibited altered levels of fatty acids and polysaccharides, suggesting the cell membrane and cell wall composition may change in response to Cu2 nanopesticide. Thus, metabolomics helps to deeply understand the differential response of these plants to the same nanopesticide stressor.