As a consequence, long-term and wide-scale monitoring initiatives are often limited to very few sampling sites within limited regions and to particular times, deeming the attempt to generalize to different places and times problematic. Traditional scientific monitoring methods rely on systematic protocols and professionally trained observers, and are thus costly and difficult to scale ( Robinson et al., 2021). However, several factors limit the ability of traditional methods to detect these changes. To take action in time and help in species conservation, scientists must be able to detect changes and identify warning signs much quicker ( Robinson et al., 2021). From a centennial perspective, these changes are clearly evident ( Attenborough, 2020). The world’s ecosystems are undergoing rapid and significant changes, characterized by a continuous decline in the abundance of insects, birds and mammals. 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. 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. Hence, the goal of this study is to enhance our understanding of observer-based biases in citizen science for biodiversity monitoring. 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. 2Department of Geography and Environmental Studies, Shamir Research Institute, University of Haifa, Haifa, IsraelĬitizen science, whereby ordinary citizens participate in scientific endeavors, is widely used for biodiversity monitoring, most commonly by relying on unstructured monitoring approaches. 1Department of Information Systems, University of Haifa, Haifa, Israel.
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