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While there is growing demand for use of climate model projections to understand the potential impacts of future climate on resources, there is a lack of effective visuals that convey the range of possible climates across spatial scales and with uncertainties that potential users need to inform their impact assessments and studies. We use usability testing including eye tracking to explore how a group of resource professionals (foresters) interpret and understand a series of graphical representations of future climate change, housed within a web-based decision support system (DSS), that address limitations identified in other tools. We find that a three-map layout effectively communicates the spread of future climate projections spatially, that location-specific information is effectively communicated if depicted both spatially on a map and temporally on a time series plot, and that model error metrics may be useful for communicating uncertainty and in demonstrating the utility of these future climate datasets.

Decision support systems—collections of related information located in a central place to be used for decision-making—can be used as platforms from which climate information can be shared with decision-makers. Unfortunately, these tools are not often evaluated, meaning developers do not know how useful or usable their products are. In this study, a web-based climate decision support system (DSS) for foresters in the southeastern United States was evaluated by using eye-tracking technology. The initial study design was exploratory and focused on assessing usability concerns within the website. Results showed differences between male and female forestry experts in their eye-tracking behavior and in their success with completing tasks and answering questions related to the climate information presented in the DSS. A follow-up study, using undergraduate students from a large university in the southeastern United States, aimed to determine whether similar gender differences existed and could be detected and, if so, whether the cause(s) could be determined. The second evaluation, similar to the first, showed that males and females focused their attention on different aspects of the website; males focused more on the maps depicting climate information while females focused more on other aspects of the website (e.g., text, search bars, and color bars). DSS developers should consider the possibility of gender differences when designing a web-based DSS and include website features that draw user attention to important DSS elements to effectively support various populations of users.