The importance of easy wayfinding in complex urban settings has been recognized in spatial planning. Empirical measurement and explicit representation of wayfinding, however, have been limited in deciding spatial configurations. Our study proposed and tested an approach to improving wayfinding by incorporating spatial analysis of urban forms in the Guangdong-Hong Kong-Macau Great Bay Area in China. Wayfinding was measured by an indicator of intelligibility using spatial design network analysis. Urban spatial configurations were quantified using landscape metrics to describe the spatial layouts of local climate zones (LCZs) as standardized urban forms. The statistical analysis demonstrated the significant associations between urban spatial configurations and wayfinding. These findings suggested, to improve wayfinding, 1) dispersing LCZ 1 (compact high-rise) and LCZ 2 (compact mid-rise) and 2) agglomerating LCZ 3 (compact low-rise), LCZ 5 (open mid-rise), LCZ 6 (open low-rise), and LCZ 9 (sparsely built). To our knowledge, this study is the first to incorporate the LCZ classification system into the wayfinding field, clearly providing empirically-supported solutions for dispersing and agglomerating spatial configurations. Our findings also provide insights for human-centered spatial planning by spatial co-development at local, urban, and regional levels.
Benchmarking , Climate , Humans , China , Cognition , Excipients , Walking
There is growing interest to develop processes for creating user-informed watershed scale models of hydrology and water quality and to assist in decision-making for balanced policies for managing watersheds. Watershed models can be enhanced with the incorporation of social dimensions of watershed management as brought forward by participants such as the perspectives, values, and norms of people that depend on the land, water, and ecosystems for sustenance, economies, and overall wellbeing. In this work, we explore the value of combining both qualitative and quantitative methods and social science data to enhance salience and legitimacy of watershed models so that end-users are more engaged. We discuss pilot testing and engagement workshops for building and testing a systems dynamics model of the Qu'Appelle Valley to gather insights from local farmers and understand their perceptions of Beneficial Management Practices (BMPs). Mixed-method workshops with agricultural producers in the Qu'Appelle Watershed gathered feedback on the developing model and the incorporation of social determinants affecting decision-making. Analysis of focus groups and factor analysis of Q-sorts were used to identify the desired components of the model, and whether it supported farmers' understanding of the potential effects of BMPs on water quality. We explored farmers' engagement with models testing BMPs and the potential of incorporating their decision processes within the model itself. Finally, we discuss the reception of the process and the practicality of the approach in providing legitimate and credible decision support tools for a community of farmers.
Hydrology , Water Quality , Agriculture , Ecosystem , Grassland , Models, Theoretical , Rivers
A challenge for transdisciplinary sustainability science is learning how to bridge diverse worldviews among collaborators in respectful ways. A temptation in transdisciplinary work is to focus on improving scientific practices rather than engage research partners in spaces that mutually respect how we learn from each other and set the stage for change. We used the concept of Nicolescu's "Hidden Third" to identify and operationalize this transformative space, because it focused on bridging "objective" and "subjective" worldviews through art. Between 2014 and 2017, we explored the engagement of indigenous peoples from three inland delta regions in Canada and as a team of interdisciplinary scholars and students who worked together to better understand long-term social-ecological change in those regions. In working together, we identified five characteristics associated with respectful, transformative transdisciplinary space. These included (1) establishing an unfiltered safe place where (2) subjective and objective experiences and (3) different world views could come together through (4) interactive and (5) multiple sensory experiences. On the whole, we were more effective in achieving characteristics 2-5-bringing together the subjective and objective experiences, where different worldviews could come together-than in achieving characteristic 1-creating a truly unfiltered and safe space for expression. The novelty of this work is in how we sought to change our own engagement practices to advance sustainability rather than improving scientific techniques. Recommendations for sustainability scientists working in similar contexts are provided.
Water quality is increasingly at risk due to nutrient pollution entering river systems from cities, industrial zones and agricultural areas. Agricultural activities are typically the largest non-point source of water pollution. The dynamics of agricultural impacts on water quality are complex and stem from the decisions and activities of multiple stakeholders, often with diverse business plans, values, and attitudes towards practices that can improve water quality. This study proposes a framework to understand and incorporate stakeholders' viewpoints into water quality modeling and management. The framework was applied to the Qu'Appelle River Basin, Saskatchewan, Canada. Q-methodology was used to understand viewpoints of stakeholders, namely agricultural producers (annual croppers, cattle producers, mixed farmers) and cottage owners, regarding a range of agricultural Beneficial Management Practices (BMPs) that can improve water quality, and to identify their preferred BMPs. A System Dynamics (SD) approach was employed to develop a transparent and user-friendly water quality model, SD-Qu'Appelle, to simulate nutrient loads in the region before and after implementation of stakeholder identified BMPs. The SD-Qu'Appelle was used in real-time engagement of stakeholders in model simulations to demonstrate and explore the potential effects of different BMPs in mitigating water pollution. Stakeholder perspectives were explored to understand the functionality and value of the SD-Qu'Appelle, preferred policies and potential barriers to BMP implementation on their land. Results show that although there are differences between viewpoints of stakeholders, they identified wetland restoration/retention, flow and erosion control, and relocation of corrals near creeks to sites more distant from waterways as the most effective BMPs for improving water quality. Economics was identified as a primary factor that causes agricultural producers to either accept or refuse the implementation of BMPs. Agricultural producers believe that incentives rather than regulations are the best policies for increasing the adoption of BMPs. Overall, stakeholders indicated the SD-Qu'Appelle had considerable value for water quality management and provided a set of recommendations to improve the model.
Rivers , Water Quality , Agriculture , Animals , Canada , Cattle , Water Pollution
