Beescape: Characterizing user needs for environmental decision support in beekeeping

Anthony C. Robinson, Jamie L. Peeler, Tim Prestby, Sarah C. Goslee, Kate Anton, Christina M. Grozinger

Research output: Contribution to journalArticlepeer-review

Abstract

Pollinators, particularly managed honey bees, are crucial for global food systems. However, declines in populations of both wild and managed pollinators have been reported across the world. In the United States, approximately 30% of managed honey bee colonies die each year. The factors underlying these losses are well understood and include reductions in the abundance and diversity of flowering plants that pollinators depend on for food, increased insecticide use, and reduced nesting habitat for wild bees. However, translating pollinator research findings into actionable knowledge for beekeepers presents a sizable spatial decision support challenge. In this work we evaluate the utility and usability of a prototype system called Beescape which intends to support environmental decision-making for beekeepers and other stakeholders. Beescape includes tools for exploring and visualizing maps that link to modeled environmental factors that impact managed bees, including honey bees, and wild bee health. Thirty beekeepers were recruited to take part in an online user study that included task analysis and survey components to elicit user input on areas of improvement for future Beescape development. The results of our evaluation of usability and utility metrics for Beescape highlighted the need for spatially-specific foraging information, better descriptions of modeled habitat quality measures, and actionable guidance to help them manage their hives. The results of our study highlight the challenges and opportunities associated with providing decision support systems that attempt to translate emerging environmental science for audiences that may be motivated by a common goal to improve honey bee survival, but who have a diverse range of technical backgrounds, applied practices, and reasons for their interest.

Original languageEnglish (US)
Article number101366
JournalEcological Informatics
Volume64
DOIs
StatePublished - Sep 2021

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Modeling and Simulation
  • Ecological Modeling
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Applied Mathematics

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