Learning and the transformative potential of citizen science

Bela, Györgyi; Peltola, Taru; Young, Juliette; Balázs, Bálint; Arpin, Isabelle; Pataki, György; Hauck, Jennifer; Kelemen, Eszter; Kopperoinen, Leena; Herzele, Ann Van; Keune, Hans; Hecker, Susanne; Suškevičs, Monika; Roy, Helen E.; Itkonen, Pekka; Külvik, Mart; Miklós, László; Başnou, Corina; Pino, Joan; Bonn, Aletta

doi:10.1111/cobi.12762

Cited by 162 publications

(155 citation statements)

References 37 publications

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“…Such growth of CS is clearly associated with technological development (Nature Publishing Group, 2015), which not only facilitated the communication with all participants but also reduced the costs of equipment needed for the collection of the data and broadened the variety of tasks that can be performed (Blaney, Jones, Philippe, & Pocock, 2016). Public engagement now ranges from generating research questions to the collection and scientific analysis of data and to communicating the research results back to the public (Bela et al, 2016;Shirk et al, 2012). Citizen science has been successfully implemented in various scientific fields, not only in biology, ecology and conservation (e.g., Brooks, 2013;Fore, Paulsen, & O'Laughlin, 2001;Howard, Aschen, & Davis, 2010;Penrose & Call, 1995), but also in biochemistry (Lee et al, 2014), astronomy (Lintott et al, 2008), comparative genetics (Singh et al, 2017) and physics (Barr, Kalderon, & Haas, 2017;Sørensen et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Citizen science and wildlife biology: Synergies and challenges

et al. 2018

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Citizen science (CS) has evolved over the past decades as a working method involving interested citizens in scientific research, for example by reporting observations, taking measurements or analysing data. In the past, research on animal behaviour has been benefitting from contributions of citizen scientists mainly in the field of ornithology but the full potential of CS in ecological and behavioural sciences is surely still untapped. Here, we present case studies that successfully applied CS to research projects in wildlife biology and discuss potentials and challenges experienced. Our case studies cover a broad range of opportunities: largescale CS projects with interactive online tools on bird song dialects, engagement of stakeholders as citizen scientists to reduce human-wildlife conflicts, involvement of students of primary and secondary schools in CS projects as well as collaboration with the media leading to successful recruitment of citizen scientists. Each case study provides a short overview of the scientific questions and how they were approached to showcase the potentials and challenges of CS in wildlife biology.Based on the experience of the case studies, we highlight how CS may support research in wildlife biology and emphasise the value of fostering communication in CS to improve recruitment of participants and to facilitate learning and mutual trust among different groups of interest (e.g., researchers, stakeholders, students).We further show how specific training for the participants may be needed to obtain reliable data. We consider CS as a suitable tool to enhance research in wildlife biology through the application of open science procedures (i.e., open access to articles and the data on publicly available repositories) to support transparency and sharing experiences.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Introductionmentioning

confidence: 99%

Citizen science and wildlife biology: Synergies and challenges

et al. 2018

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“…The engagement of volunteers in data collection (i.e. citizen science) has the potential to provide unparalleled amounts of data over large temporal and spatial scales, as well as help encourage the public to participate in the scientific process (Tewksbury et al, 2014;Bela et al, 2016). Today, as much as 45% of the ca.…”

Section: Introductionmentioning

confidence: 99%

What determines spatial bias in citizen science? Exploring four recording schemes with different proficiency requirements

Geldmann

Heilmann‐Clausen

Holm

et al. 2016

Diversity and Distributions

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Aim To understand how the integration of contextual spatial data on land cover and human infrastructure can help reduce spatial bias in sampling effort, and improve the utilization of citizen science‐based species recording schemes. By comparing four different citizen science projects, we explore how the sampling design's complexity affects the role of these spatial biases. Location Denmark, Europe. Methods We used a point process model to estimate the effect of land cover and human infrastructure on the intensity of observations from four different citizen science species recording schemes. We then use these results to predict areas of under‐ and oversampling as well as relative biodiversity ‘hotspots’ and ‘deserts’, accounting for common spatial biases introduced in unstructured sampling designs. Results We demonstrate that the explanatory power of spatial biases such as infrastructure and human population density increased as the complexity of the sampling schemes decreased. Despite a low absolute sampling effort in agricultural landscapes, these areas still appeared oversampled compared to the observed species richness. Conversely, forests and grassland appeared undersampled despite higher absolute sampling efforts. We also present a novel and effective analytical approach to address spatial biases in unstructured sampling schemes and a new way to address such biases, when more structured sampling is not an option. Main conclusions We show that citizen science datasets, which rely on untrained amateurs, are more heavily prone to spatial biases from infrastructure and human population density. Objectives and protocols of mass‐participating projects should thus be designed with this in mind. Our results suggest that, where contextual data is available, modelling the intensity of individual observation can help understand and quantify how spatial biases affect the observed biological patterns.

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“…Practically, this means achieving a continuous collaboration of scientists and local stakeholders, including the municipal administration. The goal is active participation of all sides at each stage of the process, from problem definition and data generation to agenda setting and interpretation of results, using an array of citizen science methods, including crowd sourcing, distributive intelligence, participatory and collaborative science, and transformative learning (Bela et al, 2016;Sterling, 2011). This 'formalisation' of the iterative feedback process between the research team and the local community is designed to (i) inform the local community of research findings, (ii) provide a plausibility check for scientific interpretations, (iii) highlight conflicts of interest, (iv) build synergies with already defined municipal priorities, and, finally, (iv) provide guidance to future decision-makers.…”

Section: Citizen Sciencementioning

confidence: 99%

The role of science in sustainability transitions: citizen science, transformative research, and experiences from Samothraki island, Greece

Petridis¹,

Fischer‐Kowalski²,

Singh³

et al. 2017

ISJ

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ABSTRACT:We highlight the importance of island research that aims to achieve sustainability transitions. All too often, developmental priorities are largely defined by economic policy imperatives, and island research either ignores or masks such normative connotations. This article reports on ten years of transdisciplinary socioecological research on the Greek island of Samothraki. We sequentially: (i) introduce socioecological thinking and the conceptual framework of social ecology, and show how this is operationalised and applied on this case study, and (ii) highlight the importance of a transdisciplinary research approach, in promoting island sustainability. We conclude with a plea for more transformative research and citizen research in the direction of sustainability within island studies.

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Learning and the transformative potential of citizen science

Abstract: The number of collaborative initiatives between scientists and volunteers (i.e., citizen science)is increasing across many research fields. The promise of societal transformation together with scientific breakthroughs contributes to the current popularity of citizen science (CS)

Cited by 162 publications

References 37 publications

Citizen science and wildlife biology: Synergies and challenges

Citizen science and wildlife biology: Synergies and challenges

What determines spatial bias in citizen science? Exploring four recording schemes with different proficiency requirements

The role of science in sustainability transitions: citizen science, transformative research, and experiences from Samothraki island, Greece

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