A Framework of Observer-Based Biases in Citizen Science Biodiversity Monitoring: Semi-Structuring Unstructured Biodiversity Monitoring Protocols

Research output: Contribution to journalArticlepeer-review

Abstract

Citizen science, whereby ordinary citizens participate in scientific endeavors, is widely used for biodiversity monitoring, most commonly by relying on unstructured monitoring approaches. Notwithstanding the potential of unstructured citizen science to engage the public and collect large amounts of biodiversity data, observers’ considerations regarding what, where and when to monitor result in biases in the aggregate database, thus impeding the ability to draw conclusions about trends in species’ spatio-temporal distribution. Hence, the goal of this study is to enhance our understanding of observer-based biases in citizen science for biodiversity monitoring. Toward this goals we: (a) develop a conceptual framework of observers’ decision-making process along the steps of monitor – > record and share, identifying the considerations that take place at each step, specifically highlighting the factors that influence the decisions of whether to record an observation (b) propose an approach for operationalizing the framework using a targeted and focused questionnaire, which gauges observers’ preferences and behavior throughout the decision-making steps, and (c) illustrate the questionnaire’s ability to capture the factors driving observer-based biases by employing data from a local project on the iNaturalist platform. Our discussion highlights the paper’s theoretical contributions and proposes ways in which our approach for semi-structuring unstructured citizen science data could be used to mitigate observer-based biases, potentially making the collected biodiversity data usable for scientific and regulatory purposes.

Original languageEnglish
Article number693602
JournalFrontiers in Ecology and Evolution
Volume9
DOIs
StatePublished - 19 Jul 2021

Bibliographical note

Funding Information:
We thank Yuval Nov, Ariel Shamir, Keren Kaplan Mintz and Carrie Seltzer for their insightful comments on drafts of this manuscript. We also thank students at the University of Haifa - Ofri Sheelo and Maria Nitsberg - for help in data analyses. Funding. This research was funded in part by the University of Haifa?s Data Science Research Center (DSRC).

Funding Information:
This research was funded in part by the University of Haifa’s Data Science Research Center (DSRC).

Publisher Copyright:
© Copyright © 2021 Arazy and Malkinson.

Keywords

  • biases
  • biodiversity
  • citizen science
  • framework
  • monitoring

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology

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