The increasing strain on cash-strapped natural resource agencies that are contending with environmental issues has underscored the need to foster civic participation in collaborative environmental management. Projects that involve citizens in environmental science and research are widely acknowledged for helping to supplement resource management efforts, but effective monitoring requires a reliable pool of participants, typically trained in standard protocols.

However the advent of smartphone and web-based technology has created opportunities to recruit more people to participate in environmental monitoring with minimal time or effort. With built-in GPS, digital cameras, and the capacity to upload directly to web-based databases, smartphones are user-friendly tools, equipped for accurate data collection.

A partnership between the University of Massachusetts Amherst and the Massachusetts Department of Environmental Conservation, the Outsmart Invasive Species Project is a new effort that capitalizes on personal smartphone technology to increase the effectiveness of environmental monitoring in the state. Using the free Outsmart Invasive Species application, anyone with an iPhone can contribute to invasive-species monitoring while spending leisure time outdoors. 

The Project aims to strengthen collaborative monitoring efforts in the state by facilitating social exchange between resource managers, environmental advocacy groups, and citizens, who have the opportunity to become informed stakeholders in the environmental management by participating in environmental protection.

This paper will: (1) provide theoretical foundations related to collaborative environmental management, citizen science and engagement, and the idea of crowdsourcing using smartphones and web-based systems; (2) describe the objectives of the Outsmart Invasive Species Project; and (3) reflect on the progress and problems encountered at (almost) the end of a first field season in production, with particular attention to issues around citizen recruitment and data quality.