Attitudes and opportunities: comparing climate change adaptation intentions and decisions of agricultural producers in Shaanxi, China, and British Columbia, Canada.

Climate change poses a major challenge for agricultural producers. There are a variety of adaptation strategies producers can use to enhance their resilience to the changing climate. The theory of planned behavior is applied as a framework to compare the adaptation intentions and choices of producers in Cariboo and Okanagan regions of the province of British Columbia (BC), Canada, and Baoji and Xi'an city prefectures of Shaanxi (SX) province, China. In BC, producers are more likely to explore the use of new crop varieties, and BC producers also seem to have a stronger intention to invest in irrigation efficiency. In contrast, producers in SX are far more likely to use online marketing methods to connect directly with consumers. Based on transcripts from a set of focus groups, community meetings, and interviews, differences in attitudes, social norms, and perceived behavioral control between SX and BC producers are identified that may contribute to their different adaptation choices. Multiple barriers to adaptation existed in both areas. Limited technical knowledge and doubts about adaptation effectiveness were more serious in BC, while limited support from local government and normative expectations were notable in SX. Education, targeted research, and public investments in irrigation and marketing may contribute to addressing some of these differences, improving the resilience of agricultural climate adaptation in both provinces.

Modelling spatial association in pattern based land use simulation models.

Pattern based land use models are widely used to forecast land use change. These models predict land use change using driving variables observed on the studied landscape. Many of these models have a limited capacity to account for interactions between neighbouring land parcels. Some modellers have used common spatial statistical measures to incorporate neighbour effects. However, these approaches were developed for continuous variables, while land use classifications are categorical. Neighbour interactions are also endogenous, changing as the land use patterns change. In this study we describe a single variable measure that captures aspects of neighbour interactions as reflected in the land use pattern. We use a stepwise updating process to demonstrate how dynamic updating of our measure impacts on model forecasts. We illustrate these results using the CLUE-S (Conversion of Land Use and its Effects at Small regional extent) system to forecast land use change for the Deep Creek watershed in the northern Okanagan Valley of British Columbia, Canada. Results establish that our measure improves model calibration and that ignoring changing spatial influences biases land use change forecasts.