Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-23T19:33:49.492Z Has data issue: false hasContentIssue false

Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system

Published online by Cambridge University Press:  03 October 2022

Aurore Receveur
Affiliation:
OFP/FEMA, Pacific Community, 95 Promenade Roger Laroque, BP D5, 98848 Nouméa, New Caledonia, France CESAB-FRB, 5 Rue de l’École de Médecine, 34000, Montpellier
Lucie Poulet
Affiliation:
Université Clermont Auvergne, Clermont Auvergne INP, CNRS, Institut Pascal, France
Benjamin Dalmas
Affiliation:
Computer Research Institute of Montreal, Montreal, QC H3N 1M3, Canada
Barbara Gonçalves
Affiliation:
Université Clermont Auvergne, Centre Michel de l’Hospital, F-63000 Clermont-Ferrand, France
Antoine Vernay*
Affiliation:
Univ Lyon, Université Claude Bernard Lyon 1, CNRS, ENTPE, UMR 5023 LEHNA, F-69622 Villeurbanne, France
*
Author for correspondence: Antoine Vernay, E-mail: [email protected]

Abstract

Quantitative plant biology is a growing field, thanks to the substantial progress of models and artificial intelligence dealing with big data. However, collecting large enough datasets is not always straightforward. The citizen science approach can multiply the workforce, hence helping the researchers with data collection and analysis, while also facilitating the spread of scientific knowledge and methods to volunteers. The reciprocal benefits go far beyond the project community: By empowering volunteers and increasing the robustness of scientific results, the scientific method spreads to the socio-ecological scale. This review aims to demonstrate that citizen science has a huge potential (i) for science with the development of different tools to collect and analyse much larger datasets, (ii) for volunteers by increasing their involvement in the project governance and (iii) for the socio-ecological system by increasing the share of the knowledge, thanks to a cascade effect and the help of ‘facilitators’.

Type
Review
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2022. Published by Cambridge University Press in association with The John Innes Centre

1. Introduction

Crowther et al. (Reference Crowther, Glick, Covey, Bettigole, Maynard, Thomas, Smith, Hintler, Duguid, Amatulli, Tuanmu, Jetz, Salas, Stam, Piotto, Tavani, Green, Bruce, Williams and Bradford2015) estimated that there are 3.04 trillion, or 3.04 × 1018 (± 0.096 × 1018), trees worldwide. Although this is an impressive number, it raises a question: How did the scientific team count all the trees on the planet? To better reflect reality, researchers need to collect and treat a huge amount of data sampled in contrasting ecosystems and environmental conditions, which is the role of quantitative plant science (Autran et al., Reference Autran, Bassel, Chae, Ezer, Ferjani, Fleck, Hamant, Hartmann, Jiao, Johnston, Kwiatkowska, Lim, Mahönen, Morris, Mulder, Nakayama, Sozzani, Strader, Tusscher and Wolf2021). However, a research team alone is limited in the amount of work necessary to reach a robust and valid result. International collaborations are part of the answer to overcome the lack of data, but this is insufficient and often not representative of the whole data and ecological diversity.

Citizen science (CS) is one way to cover large temporal and spatial scales for sampling. CS is a broad concept, and the definition is still debated (Heigl et al., Reference Heigl, Kieslinger, Paul, Uhlik and Dörler2019). We will merely refer to the general definition of Guerrini et al. (Reference Guerrini, Majumder, Lewellyn and McGuire2018): CS gathers ‘scientific endeavours in which individuals without specific scientific training participate as volunteers in one or more activities relevant to the research process other than (or in addition to) allowing personal data or specimens to be collected from them’. Even if CS projects that are solely based on data collection may partially solve some quantitative plant science challenges (data collection on large areas, at high temporal resolution, higher number of collectors who may quantify variables more often than a scientific team alone), they also require important scientific input to improve their own modelling issues, such as accounting for bias in data collection and heterogeneity in plant species, sites and/or dates of measurements, and ensuring that the protocol was accurately followed. CS projects in plant sciences have bloomed for a decade, gathering huge volunteer communities around scientific questions (Fig. 1, grey points). The number of publications related to CS projects has increased even faster than the total number of publications in plant sciences (Fig. 1, green bars). In turn, this approach allows researchers to share their experience, method and the purpose of the experiment and to directly communicate them to participants. In that sense, CS projects can be seen as collaborative work with a purely scientific interest to answer a question and as an efficient outreach action where ‘non-researchers’ are truly active and have the opportunity to practice the sciences (Heigl et al., Reference Heigl, Kieslinger, Paul, Uhlik and Dörler2019).

Fig. 1. Global trend of citizen science projects in the plant science literature from 2000 to 2020: The left grey y-axis (grey dots) represents the number of articles containing the mention ‘plant science’ AND ‘citizen science’ in their title, and the right green y-axis (green bars) represents the ratio of paper numbers with ‘plant science’ AND ‘citizen science’ and the paper numbers containing ‘plant science’ only. The number of papers was extracted from Google Scholar on 01/02/2022.

The benefits of these close and direct interactions between scientists and volunteers are not limited to the scientific sphere and/or the volunteers. Mixing scientists and volunteers, CS can be seen as a motor of complex socio-ecological systems, strengthening the interaction network between society and the environment. CS represents an efficient approach linking knowledge creation and transfer/co-construction with society (Rupprecht et al., Reference Rupprecht, Vervoort, Berthelsen, Mangnus, Osborne, Thompson, Urushima, Kóvskaya, Spiegelberg, Cristiano, Springett, Marschütz, Flies, McGreevy, Droz, Breed, Gan, Shinkai and Kawai2020). The benefits of CS projects spread much further than the scientists–volunteers’ interactions, and they also reach the socio-ecological system if the project is built as a participatory action research project (Cooper et al., Reference Cooper, Dickinson, Phillips and Bonney2007). Quantitative plant ecology can play a major role in encouraging these collaborative sciences. We chose to broaden the scope of this review from plant science to plant ecology and its quantitative aspect.

The goal of this review is to highlight (i) the diversity of tools and networks enabling scientists to run CS projects, (ii) the reciprocal benefits of CS projects between citizens, the scientific community and beyond with the socio-ecosystem and (iii) some remaining obstacles, such as the need to include a ‘facilitator’ in volunteer–scientist relationships; finally, this review (iv) proposes some perspectives for upcoming CS projects.

2. Some CS tools encouraging participation in CS projects

2.1. Plant CS project, a mean to manipulate plant

Plant science is mainly based on trait measurement to explain plants’ trait response to a tested variable (Autran et al., Reference Autran, Bassel, Chae, Ezer, Ferjani, Fleck, Hamant, Hartmann, Jiao, Johnston, Kwiatkowska, Lim, Mahönen, Morris, Mulder, Nakayama, Sozzani, Strader, Tusscher and Wolf2021). The number of replicates is crucial to make the study quantitative and the lab facilities are often limiting as plant culture or field experiment needs space and time. Increasing the number of experimenters may help to solve this issue. Participating to this measurement campaign may be source of motivation for volunteers to engage in CS project and to bring their contribution to the study. Projects including trait measurements allow a direct contact with plant science tools and plant material, which represent a data collection activity very close to the scientific work in a lab. McDonough MacKenzie et al. (Reference McDonough MacKenzie, Gallinat and Zipf2020) described the great interest to engage volunteers in projects including traits’ measurement such as flower phenology; volunteers only need a pencil and a sheet to note their observation regularly. These data may be complementary to dataset at global scale gathering observations at larger scale and with experiments such as twig cutting to assess season effect on leafing-out time (McDonough MacKenzie et al., Reference McDonough MacKenzie, Gallinat and Zipf2020; Primack et al., Reference Primack, Laube, Gallinat and Menzel2015). Moreover, herbaria data and metadata (from label) may also help to increase the phenology legacy of a species (Funk, Reference Funk2003; Nualart et al., Reference Nualart, Ibáñez, Soriano and López-Pujol2017). Extracting and implementing a database are very time consuming; therefore, herbarium may solicit the volunteer’s help to treat each specimen, which what Recolnat or Nature’s Notebook programs propose in France and in the USA, respectively, for instance.

Plant’s traits variation to environmental changes can be studied in a common garden where different species, genotype, cultivars are grown with the same condition. The number of common gardens limits the number of tested environments. The project ‘1000 gardens – the soybean experiment’ benefited from 1000 gardens of volunteers to grow 1710 soybean lines (Würschum et al., Reference Würschum, Leiser, Jähne, Bachteler, Miersch and Hahn2019). Participants received 10 lines or varieties and 16 traits were measured by participant until the harvest such as germination rate, plant height and start of flowering. This project led the scientist to know the most adapted lines for the different Germany regions for future soybean production (Würschum et al., Reference Würschum, Leiser, Jähne, Bachteler, Miersch and Hahn2019). Similarly, a CS project focused on carrot, solicited farmers to assess intraspecific foliar trait variation in Canada. Each farmer was in charge of five varieties of carrot and to collect and send dry leaf samples to the scientific teams for trait’s measurement. Even if farmers did not participate to trait measurements, they allow to test different environment to estimate the intraspecific variability of leaf trait (Isaac & Martin, Reference Isaac and Martin2019). This collaborative CS project leads to closer relationship between research and farms without excessive cost or particular technology.

However, the development of connected tool facilitates data sharing and data availability, which can help to democratize CS participation.

2.2. Make the CS project more global

The tool diversity in CS projects has increased with the number of projects developed. Smartphones are certainly the best example of making collaborative and quantitative sciences an almost ‘common’ activity (Adriaens et al., Reference Adriaens, Sutton-Croft, Owen, Brosens, van Valkenburg, Kilbey, Groom, Ehmig, Thürkow and Van Hende2015; Newman et al., Reference Newman, Wiggins, Crall, Graham, Newman and Crowston2012; Teacher et al., Reference Teacher, Griffiths, Hodgson and Inger2013). The smartphone is useful and promising, especially for quantitative plant science, as it allows high-resolution phenotyping activity to supply deep learning techniques and monitor plants’ responses to stress and diseases (Mohanty et al., Reference Mohanty, Hughes and Salathé2016; Singh et al., Reference Singh, Ganapathysubramanian, Sarkar and Singh2018). For instance, Adriaens et al. (Reference Adriaens, Sutton-Croft, Owen, Brosens, van Valkenburg, Kilbey, Groom, Ehmig, Thürkow and Van Hende2015) reported two applications RINSE and KORINA to record and monitor invasive plant species: volunteers can record the localisation of invasive species with their apps. Their data are then used by scientists and managers to monitor wetlands. However, volunteer participation in a CS program strongly depends on the ease of using the tools, since volunteers can become discouraged if the tools are too difficult to use. Once the tools are available, the research community can rely on a large pool of potential volunteers among social networks (Serret et al., Reference Serret, Deguines, Jang, Lois and Julliard2019). The connected tools play an important role in creating a dynamic and virtuous loop among volunteers and an easy way to interact with scientists (Nov et al., Reference Nov, Arazy and Anderson2014), especially if face-to-face interactions with the research team are organised concomitantly (Cappa et al., Reference Cappa, Laut, Nov, Giustiniano and Porfiri2016). We acknowledge that it may be particularly difficult for the scientific team to interact directly with each volunteer, especially in projects involving hundreds or thousands of participants. This challenge clearly shows the need for intermediaries to avoid losing volunteer motivation and the quantitative benefit of volunteer work (Cappa et al., Reference Cappa, Laut, Nov, Giustiniano and Porfiri2016). Some data, such as geolocation, can be updated and visualised by all the project participants directly after the data are collected and incremented. This may represent a tangible, encouraging reward for volunteers and may motivate them to continue working on the project. Moreover, from a research point of view, collected plant-related data may be used with other datasets, such as meteorological and climate data, increasing the power of the collected data. A recent study showed that from crowd-sourced flower identification data, it was possible to rebuild spatial macroecological gradients (Mahecha et al., Reference Mahecha, Rzanny, Kraemer, Mäder, Seeland and Wäldchen2021). This means that we can potentially extract more information than the app was initially designed to deliver.

The almost global internet access allows an instantaneous sharing of data and facilitates their verification by scientists or volunteers (Deguines et al., Reference Deguines, Flores, Loïs, Julliard and Fontaine2018); hence, it makes data quantity compatible with data quality. However, while the size of the available datasets is growing very fast (e.g., satellite images, video recording, pictures, for instance https://www.zooniverse.org/projects/zooniverse/floating-forests: 750,000 pictures of kelp forests were classified by over 7000 volunteers), the number of scientists available to analyse these data is not growing as fast. Depending on their expertise level, some volunteers may help the leading team check data gathered by other volunteers, a peer-to-peer cross-validation process (Deguines et al., Reference Deguines, Flores, Loïs, Julliard and Fontaine2018; Kosmala et al., Reference Kosmala, Wiggins, Swanson and Simmons2016). Therefore, with the emergence of ‘big data’ and the development of machine learning methods and artificial intelligence, volunteer participation has become increasingly necessary to amplify and to refine the exponential progress in treatment and analysis methods (Ceccaroni et al., Reference Ceccaroni, Bibby, Roger, Flemons, Michael, Fagan and Oliver2019). A successful example is the development of the ‘Leafsnap’ or ‘Pl@ntNet’ mobile app that identifies tree species from pictures of their leaves, fruits, flowers or barks (Joly et al., Reference Joly, Bonnet, Goëau, Barbe, Selmi, Champ, Dufour-Kowalski, Affouard, Carré, Molino, Boujemaa and Barthélémy2016; Kumar et al., Reference Kumar, Belhumeur, Biswas, Jacobs, Kress, Lopez, Soares, Fitzgibbon, Lazebnik, Perona, Sato and Schmid2012).

2.2.1. Topic

It is worth noting that big data from CS project raise some ethical questions such as the intellectual property of the data and the level of acknowledgement for the volunteers (Vohland et al., Reference Vohland, Weißpflug and Pettibone2019): some authors propose to include volunteers in the authorship at least under a collective identity (Vayena & Tasioulas, Reference Vayena and Tasioulas2015; Ward-Fear et al., Reference Ward-Fear, Pauly, Vendetti and Shine2020). These challenges would deserve a review per se, which is not the scope of this one.

2.3. Make a CS community

Online project platforms facilitate discussion between experts and volunteers to share results and questions about the project (Gouveia et al., Reference Gouveia, Fonseca, Câmara and Ferreira2004). Scientists can present preliminary or intermediate results based on the first collected data to inform participants about project progress. Concomitantly, it allows interactions through forums, chats or even video meetings, where volunteers are free to ask questions. These discussions bring scientists closer to the public, and vice versa, and make the relationships less hierarchical. This point is very important regardless of the scientific background of the participants: novices can feel more confident and progress rapidly, which is highly fulfilling (Deguines et al., Reference Deguines, Flores, Loïs, Julliard and Fontaine2018), whereas the more knowledgeable volunteers may be part of the discussion in the data analysis. Engaging volunteers in data analysis is, however, time-consuming if the scientific team aims to achieve volunteer empowerment. The task may be ensured by a ‘facilitator’, that is, someone dedicated to training or educating volunteers on a CS project (Lorke et al., Reference Lorke, Golumbic, Ramjan and Atias2019), but we propose to enlarge this role to align classes/teachers expectations and scientific objectives of the research team. The facilitator should not be substituted for the interactions between volunteers and scientists but instead be a hyphen between both, facilitating their interactions.

2.4. CS in the classrooms

An increasing number of CS projects involve schools (Kermish-Allen et al., Reference Kermish-Allen, Peterman and Bevc2019; Nistor et al., Reference Nistor, Clemente-Gallardo, Angelopoulos, Chodzinska, Clemente Gallardo, Gozdzik, Gras-Velazquez, Grizelj, Kolenberg and Mitropoulou2019; Van Haeften et al., Reference Van Haeften, Milic, Addison-Smith, Butcher and Davies2021), even if they are often not specifically designed for students (Bopardikar et al., Reference Bopardikar, Bernstein and McKenney2021; Williams et al., Reference Williams, Hall and O’Connell2021). The scientific team can take advantage of the time dedicated by the class to the project to train students and improve data quality (Castagneyrol et al., Reference Castagneyrol, Valdés-Correcher, Bourdin, Barbaro, Bouriaud, Branco, Centenaro, Csóka, Duduman, Dulaurent, Eötvös, Faticov, Ferrante, Fürjes-Mikó, Galmán, Gossner, Harvey, Howe, Kaennel-Dobbertin and Tack2020). This does not avoid the requirement for another check after data collection, but it also creates a time for discussion with pupils and teachers about scientific methods and epistemology. This aspect of CS is at least as important as the larger time and spatial scale of data collection because it allows students, and people in general, to be more aware of the world’s complexity (Morin, Reference Morin2007). From a quantitative plant sciences perspective, it is important to clearly explain the benefits of acquiring a large amount of data for building a robust answer to the initial questions, stressing the importance of the variability at different levels of organisation.

Although developing CS with schools appears to be relevant, scientists need to factor in educational constraints that are often incompatible with the protocols. Indeed, teachers do not have an infinite amount of time to allocate to the project, which can have consequences on data validity or decrease the project’s relevance for students and teachers, despite the educational benefits of CS initiatives (Esch et al., Reference Esch, Burbacher, Dodrill, Fussell, Magdich, Norris and Midden2020). Tools and protocols may have been thought to be easily used by non-scientific experts, and the classroom constraints may limit the involvement in a CS project. Moreover, cost, logistical tensions or effort to motivate students with ‘fun’ activities for instance are some knock-down barriers that still remain in addition to schedule constrains (Roche et al., Reference Roche, Bell, Galvão, Golumbic, Kloetzer, Knoben, Laakso, Lorke, Mannion, Massetti, Mauchline, Pata, Ruck, Taraba and Winter2020). Therefore, a ‘facilitator’ may allow, at the genesis of the project, to build a project that meets the requirements of all participants.

3. CS projects: Reciprocal benefits for citizens and academia

3.1. Main benefits for the scientific community

From the scientist point of view, CS projects represent an unprecedented opportunity to rely on an important number of volunteers collecting data (Fig. 2, orange arrow). The ‘many-eyes hypothesis’ has been developed to describe the efficiency of CS in generating, scrutinising and analysing data across vast spatiotemporal scales and multiple taxa (Dickinson et al., Reference Dickinson, Shirk, Bonter, Bonney, Crain, Martin, Phillips and Purcell2012; Earp & Liconti, Reference Earp, Liconti, Jungblut, Liebich and Bode-Dalby2020; Thomas et al., Reference Thomas, Gunawardene, Horton, Williams, O’Connor, McKirdy and van der Merwe2017). In the case of CS, the hypothesis demonstrates that a larger group of people increases the chance of detecting a species/phenomenon and can survey a vaster region. For instance, ‘The conker tree science’ project studied the effect of pest controllers on leaf-mining moths damaging leaf conker trees (http://www.conkertreescience.org.uk/). Researchers asked volunteers to collect infected leaves and count insects that had hatched out. The protocol was very simple, and 3500 citizens, covering all Great Britain, sent their results to the researchers (Pocock & Evans, Reference Pocock and Evans2014). The ‘Oak Bodyguard Citizen Science Project’ has also successfully estimated caterpillar herbivory on Quercus robur in Europe, thanks to an easy protocol, freely available, proposed to different European classes (Castagneyrol, Reference Castagneyrol2019). These two examples highlight the larger area covered by participants: ‘The conker tree science’ project provides results at a national scale when the ‘Oak Bodyguard Citizen Science Project’, on a European scale, has increased the number of sampling points in different countries. It now includes new countries such as Latvia and Lithuania where no scientist works on the project (Castagneyrol et al., Reference Castagneyrol, Valdés-Correcher, Bourdin, Barbaro, Bouriaud, Branco, Centenaro, Csóka, Duduman, Dulaurent, Eötvös, Faticov, Ferrante, Fürjes-Mikó, Galmán, Gossner, Harvey, Howe, Kaennel-Dobbertin and Tack2020). The large-scale response of Conker and Oak trees was obtained, thanks to local volunteers, which would have been unreachable with professional scientists only.

Fig. 2. Conceptual framework of the reciprocal benefits from the CS project to the socio-ecological system. Circles represent participants of a CS project, and black arrows show how the scientific and epistemological benefit spreads beyond the project per se. The two dotted arrows represent the indirect added value of the facilitator to spread the CS results to the socio-ecological system.

The development of CS is also an efficient way to widely communicate the results from a research topic. Indeed, CS projects imply generally some side activities, which are not directly linked to the scientific experiment itself. These activities take place in the context of the scientific project, and it is then easier to develop outreach activities with the volunteers as they benefit of the same background. However, to be the most effective, it would judicious to plan it when project leaders build the project (Lakeman-Fraser et al., Reference Lakeman-Fraser, Gosling, Moffat, West, Fradera, Davies, Ayamba and van der Wal2016).

An increasing number of funders (e.g., the European Union) ask to make the results of projects they supported publicly available. We strongly support the spread of scientific result, whatever the means (Poulet et al., Reference Poulet, Dalmas, Goncalves, Noûs and Vernay2021), but we recognise the holistic benefit from participating to a scientific project while learning about the scientific topic and research functioning. The implementation of CS in the research project makes this dissemination step easier, combining scientific knowledge production and outreach activities.

3.2. Important benefits for volunteers

The direct benefits for volunteers participating in CS projects consist first of increasing their own knowledge and/or scientific and technical skills. Practising science makes the learning process more efficient because volunteers face the same constraints as scientists, which makes more sense to the volunteers (Fig. 2, blue arrow, Bonney et al., Reference Bonney, Phillips, Ballard and Enck2016; Freitag, Reference Freitag2016; Kermish-Allen et al., Reference Kermish-Allen, Peterman and Bevc2019; Shirk et al., Reference Shirk, Ballard, Wilderman, Phillips, Wiggins, Jordan, McCallie, Minarchek, Lewenstein, Krasny and Bonney2012). This praxeological approach may be seen as a much more stimulating method than passively listening to a lecture or conference (Barragan-Jason et al., Reference Barragan-Jason, de Mazancourt, Parmesan, Singer and Loreau2021; Smith et al., Reference Smith, Allf, Larson, Futch, Lundgren, Pacifici and Cooper2021). The relationship between professional researchers and the public is often limited to conferences and questions to the researcher who ‘knows’ and the audience who ‘learns’. This method of knowledge transmission is important but should be completed by peer exchanges, that is, between non-professionals, when a volunteer belonging to the project community becomes the link between the project and the audience. The discussion among non-professionals allows the removal of the potential distance that the public can feel between themselves and the researcher (Burke et al., Reference Burke, Welch-Devine, Gustafson, Heynen, Rice, Gragson, Evans and Nelson2016; Watermeyer & Montgomery, Reference Watermeyer and Montgomery2018).

We think that transdisciplinary research programs may be more attractive, as they mix different fields. For example, the Growing Beyond Earth (based in the USA) project enables students to work on a transdisciplinary project where quantitative plant science meets microgravity and space exploration via a CS project led by the Fairchild Botanic Garden (Miami, FL) in partnership with NASA (https://fairchildgarden.org/gbe/). The objective is to identify resistant crops for spaceflight, and as a result, astronauts have grown Pak Choi on the ISS after it was identified as suitable by the large amount of data collected by students. The European Space Agency is pursuing the same objective as the Astroplant project, encouraging citizens and classrooms to gather data on plant growth using a DIY desktop greenhouse (https://www.esa.int/Science_Exploration/Human_and_Robotic_Exploration/AstroPlant_citizen_science_for_growing_plants_in_space).

The Space Chile Grow a Pepper Plant Challenge (https://five.epicollect.net/project/the-spacechilechallenge-cose) is another NASA CS project launched in preparation for an ISS experiment that engages citizens in collecting data on indoor chilli pepper cultivation to tackle some of its inherent challenges. The high valuation of space research in the media makes the task very exciting for volunteers, and it becomes easier for researchers to ‘reward’ participants with visible communication.

3.3. CS: A ways to link citizens with research projects

This deeper understanding of science would strongly support ecological preservation and restoration (Fig. 2). Ecological restoration and preservation programs have succeeded, thanks to the implication of volunteers in different steps of the project and in the decision-making process (Buldrini et al., Reference Buldrini, Simoncelli, Accordi, Pezzi and Dallai2015; Conrad & Hilchey, Reference Conrad and Hilchey2011; Kobori et al., Reference Kobori, Dickinson, Washitani, Sakurai, Amano, Komatsu, Kitamura, Takagawa, Koyama and Ogawara2016). Indeed, volunteers involved in CS projects can be seen as vectors of knowledge dissemination by speaking about the project and the results to people around them (Burke et al., Reference Burke, Welch-Devine, Gustafson, Heynen, Rice, Gragson, Evans and Nelson2016). In this way, volunteers become ‘advocates of environment conservation’, such as in the ‘Ansa e Valli del Mincio’ protected wetlands where volunteers have monitored invasive species (Buldrini et al., Reference Buldrini, Simoncelli, Accordi, Pezzi and Dallai2015). Similarly, a successful program was designed in Texas to monitor Arundo donax. The CS program reported an increase in the giant reed area distribution and can be a scientific resource for ecosystem management (Gallo & Waitt, Reference Gallo and Waitt2011). In 5 years (2005–2010), volunteers reported 9004 observations, which represent 3416.75 h of work. The large-scale monitoring, during a long period, may be hard to set up and the assistance of volunteers helps make plant monitoring more sustainable in space and time. Another fulfilling aspect of CS projects consists of the more important involvement of volunteers in environmental protection agencies (Owen & Parker, Reference Owen and Parker2018). Even if there are still some challenges with some CS projects regarding the inclusion of results in environmental policies despite the merits of the CS approach (see Section 3 and MacPhail & Colla, Reference MacPhail and Colla2020), an increasing number of governments recognise the significant role of citizens in nature preservation and rely on CS projects to act and make decisions. Similarly, a recent global scale review has highlighted that involvement of Indigenous peoples and local communities in the management and decision making represents the primary pathway to effective long-term conservation of biodiversity (Dawson et al., Reference Dawson, Coolsaet, Sterling, Loveridge, Gross-Camp, Wongbusarakum, Sangha, Scherl, Phan, Zafra-Calvo, Lavey, Byakagaba, Idrobo, Chenet, Bennett, Mansourian and Rosado-May2021). Nascimento et al. (Reference Nascimento, Rubio Iglesias, Owen, Schade and Shanley2018) recall that the Scottish government helped some CS projects with training and tools to improve their data collection. This action shows the confidence and value of citizen engagement in nature conservation. Governmental acceptance of CS projects in the formation of policy allows reciprocal benefits not only between volunteers and scientists, but it allows the benefits to spread across society, thanks to the higher citizen involvement in public policies, which is reflected by the increased financial support to CS (Schade et al., Reference Schade, Pelacho, van Noordwijk, Vohland, Hecker, Manzoni, Vohland, Land-Zandstra, Ceccaroni, Lemmens, Perelló, Ponti, Samson and Wagenknecht2021).

CS projects would help to reconnect our society to nature (Barragan-Jason et al., Reference Barragan-Jason, de Mazancourt, Parmesan, Singer and Loreau2021; Gaston & Soga, Reference Gaston and Soga2020) and increase public awareness of the current status of the environment and the threat that humans represent to ecosystem stability (Cerrano et al., Reference Cerrano, Milanese and Ponti2017; Schläppy et al., Reference Schläppy, Loder, Salmond, Lea, Dean and Roelfsema2017). In line with these authors, we want to show that the objectives of CS go far beyond helping research teams or educating the public about the sciences (Bonney et al., Reference Bonney, Shirk, Phillips, Wiggins, Ballard, Miller-Rushing and Parrish2014; Vignola et al., Reference Vignola, Locatelli, Martinez and Imbach2009): In a global change context and a highly complex world, the involvement of citizens and researchers in a more socio-ecological democracy is critical to facing the dangerous global crisis in which we are currently living (Gardner & Wordley, Reference Gardner and Wordley2019; Hagedorn et al., Reference Hagedorn, Kalmus, Mann, Vicca, Berge, Ypersele, Bourg, Rotmans, Kaaronen, Rahmstorf, Kromp-Kolb, Kirchengast, Knutti, Seneviratne, Thalmann, Cretney, Green, Anderson, Hedberg and Hayhoe2019; Steffen et al., Reference Steffen, Broadgate, Deutsch, Gaffney and Ludwig2015).

4. Remaining challenges to improve CS

4.1. Data quality

The suspicion about data quality often rises first in CS projects (Kosmala et al., Reference Kosmala, Wiggins, Swanson and Simmons2016). Data quality is the outcome of several components (Pipino et al., Reference Pipino, Lee and Wang2002), but data accuracy emphasises most of the criticism, that is, the precision of the data relative to its real value. In other words, is the data reported by a volunteer correct or not? The concern may be legitimate because of the diversity of background, training and involvement of volunteers. However, this concern may also be true for professionals (Castagneyrol et al., Reference Castagneyrol, Valdés-Correcher, Bourdin, Barbaro, Bouriaud, Branco, Centenaro, Csóka, Duduman, Dulaurent, Eötvös, Faticov, Ferrante, Fürjes-Mikó, Galmán, Gossner, Harvey, Howe, Kaennel-Dobbertin and Tack2020; McKinley et al., Reference McKinley, Miller-Rushing, Ballard, Bonney, Brown, Evans, French, Parrish, Phillips and Ryan2015; McKinley et al., Reference McKinley, Miller-Rushing, Ballard, Bonney, Brown, Cook-Patton, Evans, French, Parrish, Phillips, Ryan, Shanley, Shirk, Stepenuck, Weltzin, Wiggins, Boyle, Briggs, Chapin and Soukup2017) and should not be an initial bias in the mind of editors and reviewers. Indeed, Kosmala et al. (Reference Kosmala, Wiggins, Swanson and Simmons2016) started their review about CS data quality by citing several projects that led to many publications (Fig. 1), which should make quantitative plant scientists and others more confident about their involvement in CS projects.

As it is not yet a common practice, researchers will need to design CS-dedicated experimental protocols (Burgess et al., Reference Burgess, DeBey, Froehlich, Schmidt, Theobald, Ettinger, HilleRisLambers, Tewksbury and Parrish2017; Pocock & Evans, Reference Pocock and Evans2014), and sometimes researchers are challenged by short-term funding (Crall et al., Reference Crall, Newman, Jarnevich, Stohlgren, Waller and Graham2010; Vasiliades et al., Reference Vasiliades, Hadjichambis, Paraskeva-Hadjichambi, Adamou and Georgiou2021). Therefore, the help of citizen organisations may first link researchers and volunteers by training and supporting volunteers during the process. However, we think that it is of great importance that researchers become involved in the process of sharing science (i.e., training, interacting with volunteers), which is part of their duties. It is not the role of NGOs or associations to remedy the malfunctioning of states or scientific financial institutions, especially in context of social, health, economic and environmental crises (Vohland et al., Reference Vohland, Weißpflug and Pettibone2019). What is today a potential ‘waste of time’ in the mind of some researchers should become part of their daily work and will provide a high return on investment during data analysis. Similarly, the data check should be a necessary task, as is the case when professional scientists collect data (Castagneyrol et al., Reference Castagneyrol, Valdés-Correcher, Bourdin, Barbaro, Bouriaud, Branco, Centenaro, Csóka, Duduman, Dulaurent, Eötvös, Faticov, Ferrante, Fürjes-Mikó, Galmán, Gossner, Harvey, Howe, Kaennel-Dobbertin and Tack2020; Cox et al., Reference Cox, Philippoff, Baumgartner and Smith2012). As researchers, we have to consider the great advantage of CS for quantifying variables of interest at a larger scale and then accept that we will have to spend more time cleaning the data and supporting volunteers.

4.2. Volunteer motivation

Cherry trees in Japan have been monitored for more than a thousand years (Kobori et al., Reference Kobori, Dickinson, Washitani, Sakurai, Amano, Komatsu, Kitamura, Takagawa, Koyama and Ogawara2016). This example highlights the critical aspect of volunteer motivation for the success of these research programs. The resilience of CS projects (i.e., their ability to keep running or restart despite obstacles) is an asset for medium-long-term data requirements (Couvet et al., Reference Couvet, Jiguet, Julliard, Levrel and Teyssedre2008).

To increase volunteer motivation, we believe that the feeling of being a useful piece of the research program may strengthen the involvement of volunteers in the project and open it to new people, as volunteers devote their free, unpaid time (Conrad & Hilchey, Reference Conrad and Hilchey2011; Lakshminarayanan, Reference Lakshminarayanan2007). Volunteer engagement increases if at least the subset of the data they collected may participate in answering local challenges (Freitag, Reference Freitag2016). Schools may represent a more reliable way to ensure student involvement, at least for 1 year. The CS project would benefit from dedicated time by the class to the project tasks but also to an educational time on science epistemology with the teacher and the researcher involved in the project (Castagneyrol et al., Reference Castagneyrol, Valdés-Correcher, Bourdin, Barbaro, Bouriaud, Branco, Centenaro, Csóka, Duduman, Dulaurent, Eötvös, Faticov, Ferrante, Fürjes-Mikó, Galmán, Gossner, Harvey, Howe, Kaennel-Dobbertin and Tack2020; Poulet et al., Reference Poulet, Dalmas, Goncalves, Noûs and Vernay2021). We acknowledge that the project might be a mandatory part of the curriculum rather than a voluntary one, but we hope that students’ contributions to CS projects may open them to new topics and inspire them for future participation.

To involve more volunteers generally in the sciences through CS projects, it is also important to deconsecrate researchers in the eyes of the public. Without the volunteers’ contribution, the scientific project would not exist. Therefore, the project not only belongs to the research team but also to the volunteers who sometimes contribute to the easiest but essential and/or tedious tasks. The globalisation of research collaboration can be enhanced by CS and by considering volunteers worldwide. Currently, there is a high CS project concentration in the Northern Hemisphere, especially in Europe and North America (Earp & Liconti, Reference Earp, Liconti, Jungblut, Liebich and Bode-Dalby2020; Thiel et al., Reference Thiel, Penna-Díaz, Luna-Jorquera, Salas, Sellanes and Stotz2014). However, to multiply the positive feedback of CS projects, it would be necessary to extend the spatial localisation of these projects.

4.3. Connecting scientists and volunteers

Finally, to make science an efficient citizen tool, researchers must involve volunteers deeper into the project’s governance (Conrad & Hilchey, Reference Conrad and Hilchey2011; Heigl et al., Reference Heigl, Kieslinger, Paul, Uhlik and Dörler2019). The basic level of CS consists of collecting data, which per se has a significant impact in increasing the size of a dataset – which is particularly interesting in quantitative science. However, a transition from projects whereby participants mainly collect data to more collaborative and co-created approaches has started and needs to continue (Bonney et al., Reference Bonney, Cooper, Dickinson, Kelling, Phillips, Rosenberg and Shirk2009; Teleki, Reference Teleki2012), with major socio-ecological benefits such as promoting environmental awareness and literacy and empowering citizens and communities. We acknowledge that it is not an easy task to build such a project (Eleta et al., Reference Eleta, Clavell, Righi and Balestrini2019). Coordinating the group requires a lot of time and energy, a task that could be carried by facilitator. However, there are already some encouraging examples. ‘The gardenroots’ project worked on the role of soil contamination in edible plants and human health and it is driven by a non-expert group in collaboration with a researcher. The whole group participates in the experimental design, data collection, analysis, and decision-making process (Ramirez-Andreotta et al., Reference Ramirez-Andreotta, Brusseau, Artiola, Maier and Gandolfi2015). Reis and Glithero (Reference Reis and Glithero2015) showed that even at school, students participating in a CS project can go further than the scientific question, even raising some ecojustice considerations for the benefit of all. However, examples are rare and this holistic goal of CS deserves more research and discussion among stakeholders. The task is huge to democratise this approach but we hope that the scientists working with CS will mobilise in that sense in the future.

Different classifications exist in the literature (Table 1) to highlight a gradient of volunteers’ involvement in the project’s tasks. It is out of the scope of this review to clarify the possible overlap among the terms, but all recognised that the more that volunteers participate in the scientific process (from conception to solution application when the goal was to solve a local issue), the greater they are empowered. It has positive consequences on the citizenry because they become aware of how the data are collected and how data are used, they understand where the money comes from and how it is spent, and finally, they can participate in the decision-making process more easily. This can lead to substantial policy changes, thanks to an awareness of involvement in scientific and societal issues (Hagedorn et al., Reference Hagedorn, Kalmus, Mann, Vicca, Berge, Ypersele, Bourg, Rotmans, Kaaronen, Rahmstorf, Kromp-Kolb, Kirchengast, Knutti, Seneviratne, Thalmann, Cretney, Green, Anderson, Hedberg and Hayhoe2019). Therefore, a specific effort from research teams is needed to allow democratic shared governance (Watermeyer & Montgomery, Reference Watermeyer and Montgomery2018) regardless of the degree of involvement of volunteers.

Table 1 Summary of citizen science governance types

To conclude, the strength and weakness of CS projects are the participant diversity in terms of scientific level, expectations and motivation. To avoid disappointment, we agree with Lorke et al. (Reference Lorke, Golumbic, Ramjan and Atias2019), who encourage the participation of a facilitator early in the co-construction of the project.

4.4. We need more than guidelines for citizen science

Working on these different points can result in good practice guidelines and toolkits for the future of CS (Silvertown, Reference Silvertown2009). Bonney et al. (Reference Bonney, Cooper, Dickinson, Kelling, Phillips, Rosenberg and Shirk2009) and Tweddle et al. (Reference Tweddle, Robinson, Pocock and Roy2012) offered a roadbook to efficiently start a biodiversity CS projects with some plant science precisions. The main points can be summarised as: (1) choose a scientific question; (2) form a scientist/educator/technologist/evaluator team; (3) develop, test and refine protocols, data forms and educational support materials; (4) recruit participants; (5) train participants; (6) accept, edit and display data; (7) analyse and interpret data; (8) disseminate results and (9) measure outcomes (Castagneyrol, Reference Castagneyrol2019; Hill et al., Reference Hill, Guralnick, Smith, Sallans, Gillespie, Denslow, Gross, Murrell, Conyers, Oboyski, Ball, Thomer, Prys-Jones, Torre, de la Kociolek and Fortson2012; Teacher et al., Reference Teacher, Griffiths, Hodgson and Inger2013). We advise readers to refer to the chapter written by García et al. (Reference García, Pelacho, Woods, Fraisl, See, Haklay and Arias2021) for a more detailed review of the existing guidelines in the book directed by Vohland et al. (Reference Vohland, Land-Zandstra, Ceccaroni, Lemmens, Perelló, Ponti, Samson and Wagenknecht2021). Online platform sharing protocol is also a way to give or to check experimental instructions before engaging in a project as Castagneyrol (Reference Castagneyrol2019) did for the ‘Oak bodyguard Citizen Science project’ on https://www.protocols.io. However, as this review aims to demonstrate, a CS project is not as simple as a ‘recipe’ because each group of volunteers has its own features.

The potential of CS projects for spreading science and the scientific method to the socio-ecosystem may be enhanced if the objectives and limits of each group of participants are taken into account (Freitag & Pfeffer, Reference Freitag and Pfeffer2013). A third party may ensure the match between each stakeholder: For global projects, finding a local interest for volunteers is important to reinforce their engagement and empower them scientifically and democratically (Esch et al., Reference Esch, Burbacher, Dodrill, Fussell, Magdich, Norris and Midden2020; Golumbic et al., Reference Golumbic, Orr, Baram-Tsabari and Fishbain2017; Lorke et al., Reference Lorke, Golumbic, Ramjan and Atias2019). In a classroom, teachers are limited in adapting the curriculum; therefore, the facilitator may help scientific project leaders adapt the protocol to academic constraints. More generally, the interest and skills of volunteers may evolve during the project, leading to changes in their motivations (Rotman et al., Reference Rotman, Preece, Hammock, Procita, Hansen, Parr, Lewis and Jacobs2012). Anticipating the dynamics of volunteer involvement in the project design can enhance the expectations of all participants by stimulating volunteers. As suggested by Zoellick et al. (Reference Zoellick, Nelson and Schauffler2012), the university may play this role of facilitator with students or a specialist of scientific mediation could also assume the role. Local organisations interested in a project may also make the link between scientific teams and the volunteers such as naturalist or environmentalist associations, or at a bigger scale, naturalist learned societies or NGOs.

5. Perspectives and conclusion

CS is currently at a crossroads of demonstrated successes, unresolved challenges and unrealised potential. In particular, the potential mutual benefits for researchers, volunteers and society are still undervalued. These mutual benefits occur at different scales: to solve the research question driving the project, the educational aspect towards the volunteers and the dissemination of knowledge through society. Depending on the involvement of the volunteers in the project, the outreach exchanges can be more or less integrative. Finally, the ongoing crises (health, economic, social and environmental) have highlighted the crucial role of science in explaining the world’s complexity and overcoming obstacles.

On the other hand, citizens are increasingly solicited in the decision-making process in society, and thus they need to have the strongest background possible to make decisions and change their behaviours (Eymard, Reference Eymard2020; Vignola et al., Reference Vignola, Locatelli, Martinez and Imbach2009). Ecology and especially plant ecology have used CS for a long time and are precursors in CS. Applications to identify plants are widely available to the public, and an increasing number of people have participated in global databases, such as those about plant phenology, sometimes for hundreds of years (Amano et al., Reference Amano, Smithers, Sparks and Sutherland2010; Amano et al., Reference Amano, Freckleton, Queenborough, Doxford, Smithers, Sparks and Sutherland2014; Bopardikar et al., Reference Bopardikar, Bernstein and McKenney2021). The long experience of CS projects has allowed to know the strengths and weaknesses of this approach and to propose tools to limit biases (Bird et al., Reference Bird, Bates, Lefcheck, Hill, Thomson, Edgar, Stuart-Smith, Wotherspoon, Krkosek, Stuart-Smith, Pecl, Barrett and Frusher2014; Bonney et al., Reference Bonney, Cooper, Dickinson, Kelling, Phillips, Rosenberg and Shirk2009; Kosmala et al., Reference Kosmala, Wiggins, Swanson and Simmons2016). Still related to plants, the space field has also largely included CS projects, with exciting perspectives for space exploration (see the examples mentioned in Section 2.2). Thanks to this experience, it appears that CS requires changing the typical project construction approach by including, ideally, a facilitator, changing the typical way to make a protocol. This may be the strongest upheaval that some researchers have to face, especially in quantitative plant science but also in other disciplines. We hope this review provides exciting examples and a large body of literature to help quantitative plant biologists become more confident in this approach. The benefit may be significant from a scientific production point of view, but it can also have a crucial social role for public opinion of science and CS. Therefore, we encourage researchers and citizens to promote and launch a CS program for the essential benefit at the socio-ecological scale, spreading the benefits of CS to a more global scale (Fig. 2, Devictor et al., Reference Devictor, Whittaker and Beltrame2010; Hano et al., Reference Hano, Wei, Hubbell and Rappold2020; Lawson et al., Reference Lawson, Stevenson, Peterson, Carrier, Strnad and Seekamp2019).

In our opinion, this may be the main point of CS: Science and knowledge result from a long and rigorous demonstrative process, which gives it a different status from beliefs, ideology or opinion, and this is what researchers should emphasise during their collaboration with volunteers (Poulet et al., Reference Poulet, Dalmas, Goncalves, Noûs and Vernay2021). The active participation of people in scientific research facilitates the transmission of this approach to world complexity and the associated processes. It helps people disentangle scientific arguments from other information and opinions during debates and fight against obscurantism (Eleta et al., Reference Eleta, Clavell, Righi and Balestrini2019). Finally, it can help people build stronger critical thinking skills about our socio-ecological issues and influence the decision-making process (Fig. 2, Carolan, Reference Carolan2006; Heathcote et al., Reference Heathcote, Hobday, Spaulding, Gard and Irons2019; Shanley & López, Reference Shanley and López2009).

However, one point still deserves more attention: How can we honestly ‘reward’ volunteers for their contributions? The publication of articles is very rewarding for researchers. It contributes to the progress of their careers and helps to find new funding for projects. However, it is impossible to include all volunteers in the authorship (but see Ward-Fear et al., Reference Ward-Fear, Pauly, Vendetti and Shine2020), and they would not strongly benefit from this acknowledgement. The project we have launched, the outreach research journal DECODER, proposes publishing an outreach version of an article published in international scientific journals in collaboration with one of the authors and articles written by classes and reviewed by an expert (Poulet et al., Reference Poulet, Vernay, Goncalves, Dalmas and Vernay2020; Poulet et al., Reference Poulet, Dalmas, Goncalves, Noûs and Vernay2021). We acknowledge that this is not strictly a CS project, as it does not produce new scientific knowledge. However, it may be a way to value the work of a class or volunteers by producing and publishing a public-targeted version of their work. A similar initiative was created by Frontiers journal, https://kids.frontiersin.org/. Volunteers can use the whole dataset or only a subsample corresponding to the data they collected, and they can reformulate the question in the context of their environment (Ledley et al., Reference Ledley, Dahlman, McAuliffe, Haddad, Taber, Domenico, Lynds and Grogan2011). Publishing results and manuscripts from volunteers and classes in open access give more value to their contribution (Burke et al., Reference Burke, Welch-Devine, Gustafson, Heynen, Rice, Gragson, Evans and Nelson2016). It can be a way to ‘reward’ them for their work. Then, a comparison with the published version of the research may constitute an interesting tool to address the role of big data in the impact of environmental conditions on the variables, for instance. Another approach would be to have the researcher or institution leading the project gives a certificate to volunteers. It would be interesting to build a standard nomenclature to recognise the work of the volunteers and allow them to use the training they received during the project for a new one, thanks to this standardised system of skills acquisition.

Acknowledgements

We want to thank all the teachers, students and researchers who have trusted us on the DECODER project. They have inspired us to engage in outreach science and to write this review. We also thank Geoffrey Volat for the interesting discussion about the praxeological approach and Pr Olivier Hamant for inviting us to write this review.

Financial support

This research received no specific grant from any funding agency or from commercial or not-for-profit sectors.

Conflict of interest

None.

Authorship contributions

A.R. and A.V. wrote the first draft of the manuscript. A.R. drew Fig. 2, and B.D. and A.R. drew Fig. 1. All authors contributed equally to improving the first version.

Data availability statement

This review does not rely on any data, code or other resources.

References

Adriaens, T., Sutton-Croft, M., Owen, K., Brosens, D., van Valkenburg, J., Kilbey, D., Groom, Q., Ehmig, C., Thürkow, F., & Van Hende, P. (2015). Trying to engage the crowd in recording invasive alien species in Europe: Experiences from two smartphone applications in northwest Europe. Management of Biological Invasions, 6(2), 215.CrossRefGoogle Scholar
Amano, T., Freckleton, R. P., Queenborough, S. A., Doxford, S. W., Smithers, R. J., Sparks, T. H., & Sutherland, W. J. (2014). Links between plant species’ spatial and temporal responses to a warming climate. Proceedings of the Royal Society B: Biological Sciences, 281(1779), 20133017. https://doi.org/10.1098/rspb.2013.3017 CrossRefGoogle ScholarPubMed
Amano, T., Smithers, R. J., Sparks, T. H., & Sutherland, W. J. (2010). A 250-year index of first flowering dates and its response to temperature changes. Proceedings of the Royal Society B: Biological Sciences, 277(1693), 24512457. https://doi.org/10.1098/rspb.2010.0291 CrossRefGoogle ScholarPubMed
Autran, D., Bassel, G. W., Chae, E., Ezer, D., Ferjani, A., Fleck, C., Hamant, O., Hartmann, F. P., Jiao, Y., Johnston, I. G., Kwiatkowska, D., Lim, B. L., Mahönen, A. P., Morris, R. J., Mulder, B. M., Nakayama, N., Sozzani, R., Strader, L. C., Tusscher, K. ten, … Wolf, S. (2021). What is quantitative plant biology? Quantitative Plant Biology, 2, e10. https://doi.org/10.1017/qpb.2021.8 CrossRefGoogle Scholar
Barragan-Jason, G., de Mazancourt, C., Parmesan, C., Singer, M. C., & Loreau, M. (2021). Human–nature connectedness as a pathway to sustainability: A global meta-analysis. Conservation Letters, 15, e12852. https://doi.org/10.1111/conl.12852 Google ScholarPubMed
Bird, T. J., Bates, A. E., Lefcheck, J. S., Hill, N. A., Thomson, R. J., Edgar, G. J., Stuart-Smith, R. D., Wotherspoon, S., Krkosek, M., Stuart-Smith, J. F., Pecl, G. T., Barrett, N., & Frusher, S. (2014). Statistical solutions for error and bias in global citizen science datasets. Biological Conservation, 173, 144154. https://doi.org/10.1016/j.biocon.2013.07.037 CrossRefGoogle Scholar
Bonney, R., Cooper, C. B., Dickinson, J., Kelling, S., Phillips, T., Rosenberg, K. V., & Shirk, J. (2009). Citizen science: A developing tool for expanding science knowledge and scientific literacy. BioScience, 59(11), 977984.CrossRefGoogle Scholar
Bonney, R., Phillips, T. B., Ballard, H. L., & Enck, J. W. (2016). Can citizen science enhance public understanding of science? Public Understanding of Science, 25(1), 216.CrossRefGoogle ScholarPubMed
Bonney, R., Shirk, J. L., Phillips, T. B., Wiggins, A., Ballard, H. L., Miller-Rushing, A. J., & Parrish, J. K. (2014). Next steps for citizen science. Science, 343(6178), 14361437. https://doi.org/10.1126/science.1251554 CrossRefGoogle ScholarPubMed
Bopardikar, A., Bernstein, D., & McKenney, S. (2021). Designer considerations and processes in developing school-based citizen-science curricula for environmental education. Journal of Biological Education, 126. https://doi.org/10.1080/00219266.2021.1933134 CrossRefGoogle Scholar
Buldrini, F., Simoncelli, A., Accordi, S., Pezzi, G., & Dallai, D. (2015). Ten years of citizen science data collection of wetland plants in an urban protected area. Acta Botanica Gallica, 162(4), 365373. https://doi.org/10.1080/12538078.2015.1080187 CrossRefGoogle Scholar
Burgess, H. K., DeBey, L. B., Froehlich, H. E., Schmidt, N., Theobald, E. J., Ettinger, A. K., HilleRisLambers, J., Tewksbury, J., & Parrish, J. K. (2017). The science of citizen science: Exploring barriers to use as a primary research tool. Biological Conservation, 208, 113120. https://doi.org/10.1016/j.biocon.2016.05.014 CrossRefGoogle Scholar
Burke, B. J., Welch-Devine, M., Gustafson, S., Heynen, N., Rice, J. L., Gragson, T. L., Evans, S. R., & Nelson, D. R. (2016). Can science writing collectives overcome barriers to more democratic communication and collaboration? Lessons from environmental communication praxis in Southern Appalachia. Environmental Communication, 10(2), 169186. https://doi.org/10.1080/17524032.2014.999695 CrossRefGoogle Scholar
Cappa, F., Laut, J., Nov, O., Giustiniano, L., & Porfiri, M. (2016). Activating social strategies: Face-to-face interaction in technology-mediated citizen science. Journal of Environmental Management, 182, 374384. https://doi.org/10.1016/j.jenvman.2016.07.092 CrossRefGoogle ScholarPubMed
Carolan, M. S. (2006). Science, expertise, and the democratization of the decision-making process. Society & Natural Resources, 19(7), 661668. https://doi.org/10.1080/08941920600742443 CrossRefGoogle Scholar
Castagneyrol, B. (2019). Predation assessment on fake caterpillars and leaf sampling: Protocol for partner schools. https://doi.org/10.17504/protocols.io.42pgydn CrossRefGoogle Scholar
Castagneyrol, B., Valdés-Correcher, E., Bourdin, A., Barbaro, L., Bouriaud, O., Branco, M., Centenaro, G., Csóka, G., Duduman, M.-L., Dulaurent, A.-M., Eötvös, C. B., Faticov, M., Ferrante, M., Fürjes-Mikó, Á., Galmán, A., Gossner, M. M., Harvey, D., Howe, A. G., Kaennel-Dobbertin, M., … Tack, A. J. M. (2020). Can school children support ecological research? Lessons from the Oak Bodyguard Citizen Science Project. Citizen Science: Theory and Practice, 5(1), 111. https://doi.org/10.5334/cstp.267 CrossRefGoogle Scholar
Ceccaroni, L., Bibby, J., Roger, E., Flemons, P., Michael, K., Fagan, L., & Oliver, J. L. (2019). Opportunities and risks for citizen science in the age of artificial intelligence. Citizen Science: Theory and Practice, 4(1), 29. https://doi.org/10.5334/cstp.241 Google Scholar
Cerrano, C., Milanese, M., & Ponti, M. (2017). Diving for science - science for diving: Volunteer scuba divers support science and conservation in the Mediterranean Sea. Aquatic Conservation: Marine and Freshwater Ecosystems, 27(2), 303323. https://doi.org/10.1002/aqc.2663 CrossRefGoogle Scholar
Conrad, C. C., & Hilchey, K. G. (2011). A review of citizen science and community-based environmental monitoring: Issues and opportunities. Environmental Monitoring and Assessment, 176(1), 273291. https://doi.org/10.1007/s10661-010-1582-5 CrossRefGoogle ScholarPubMed
Cooper, C. B., Dickinson, J., Phillips, T., & Bonney, R. (2007). Citizen science as a tool for conservation in residential ecosystems. Ecology and Society, 12(2), 11. http://www.jstor.org/stable/26267884 CrossRefGoogle Scholar
Couvet, D., Jiguet, F., Julliard, R., Levrel, H., & Teyssedre, A. (2008). Enhancing citizen contributions to biodiversity science and public policy. Interdisciplinary Science Reviews, 33(1), 95103. https://doi.org/10.1179/030801808X260031 CrossRefGoogle Scholar
Cox, T., Philippoff, J., Baumgartner, E., & Smith, C. (2012). Expert variability provides perspective on the strengths and weaknesses of citizen-driven intertidal monitoring program. Ecological Applications, 22(4), 12011212.CrossRefGoogle ScholarPubMed
Crall, A. W., Newman, G. J., Jarnevich, C. S., Stohlgren, T. J., Waller, D. M., & Graham, J. (2010). Improving and integrating data on invasive species collected by citizen scientists. Biological Invasions, 12(10), 34193428. https://doi.org/10.1007/s10530-010-9740-9 CrossRefGoogle Scholar
Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., Smith, J. R., Hintler, G., Duguid, M. C., Amatulli, G., Tuanmu, M. N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S. J., … Bradford, M. A. (2015). Mapping tree density at a global scale. Nature, 525(7568), 201. https://doi.org/10.1038/nature14967 CrossRefGoogle ScholarPubMed
Dawson, N., Coolsaet, B., Sterling, E., Loveridge, R., Gross-Camp, N., Wongbusarakum, S., Sangha, K., Scherl, L., Phan, H., Zafra-Calvo, N., Lavey, W., Byakagaba, P., Idrobo, C. J., Chenet, A., Bennett, N., Mansourian, S., & Rosado-May, F. (2021). The role of Indigenous peoples and local communities in effective and equitable conservation. Ecology and Society, 26(3) 19. https://doi.org/10.5751/ES-12625-260319CrossRefGoogle Scholar
Deguines, N., Flores, M. de, Loïs, G., Julliard, R., & Fontaine, C. (2018). Fostering close encounters of the entomological kind. Frontiers in Ecology and the Environment, 16(4), 202203. https://doi.org/10.1002/fee.1795 CrossRefGoogle Scholar
Devictor, V., Whittaker, R. J., & Beltrame, C. (2010). Beyond scarcity: Citizen science programmes as useful tools for conservation biogeography. Diversity and Distributions, 16(3), 354362. https://doi.org/10.1111/j.1472-4642.2009.00615.x CrossRefGoogle Scholar
Dickinson, J. L., Shirk, J., Bonter, D., Bonney, R., Crain, R. L., Martin, J., Phillips, T., & Purcell, K. (2012). The current state of citizen science as a tool for ecological research and public engagement. Frontiers in Ecology and the Environment, 10(6), 291297. https://doi.org/10.1890/110236 CrossRefGoogle Scholar
Earp, H. S., & Liconti, A. (2020). Science for the future: The use of citizen science in marine research and conservation. In Jungblut, S., Liebich, V., & Bode-Dalby, M. (Éds.), YOUMARES 9—The oceans: our research, our future: Proceedings of the 2018 conference for young marine researcher in Oldenburg, Germany (pp. 119). Springer International Publishing. https://doi.org/10.1007/978-3-030-20389-4_1 Google Scholar
Eleta, I., Clavell, G. G., Righi, V., & Balestrini, M. (2019). The promise of participation and decision-making power in citizen science. Citizen Science: Theory and Practice, 4(1), 8. https://doi.org/10.5334/cstp.171 Google Scholar
Esch, R. K., Burbacher, E., Dodrill, E., Fussell, K. D., Magdich, M., Norris, H., & Midden, W. R. (2020). Citizen science in schools: scientists’ perspectives on promise and pitfalls. Horizon Research, Inc. https://eric.ed.gov/?id=ED607598 Google Scholar
Eymard, L. (2020). From the French citizens’ convention on climate to the conference on the future of Europe: A participatory science and democracy perspective. European Law Journal, 26(1–2), 136140. https://doi.org/10.1111/eulj.12369 CrossRefGoogle Scholar
Freitag, A. (2016). A typology for strategies to connect citizen science and management. Environmental Monitoring and Assessment, 188(9), 519. https://doi.org/10.1007/s10661-016-5513-y CrossRefGoogle ScholarPubMed
Freitag, A., & Pfeffer, M. J. (2013). Process, not product: Investigating recommendations for improving citizen science “success”. PLOS One, 8(5), e64079. https://doi.org/10.1371/journal.pone.0064079 CrossRefGoogle Scholar
Funk, V. A. (2003). 100 uses for an herbarium: Well at least 72. American Society of Plant Taxonomists Newsletter.Google Scholar
Gallo, T., & Waitt, D. (2011). Creating a successful citizen science model to detect and report invasive species. BioScience, 61(6), 459465. https://doi.org/10.1525/bio.2011.61.6.8 CrossRefGoogle Scholar
García, F. S., Pelacho, M., Woods, T., Fraisl, D., See, L., Haklay, M. M., & Arias, R. (2021). Finding what you need: A guide to citizen science guidelines. In The science of citizen science (pp. 419435). Springer.CrossRefGoogle Scholar
Gardner, C. J., & Wordley, C. F. R. (2019). Scientists must act on our own warnings to humanity. Nature Ecology & Evolution, 3, 12711272. https://doi.org/10.1038/s41559-019-0979-y CrossRefGoogle ScholarPubMed
Gaston, K. J., & Soga, M. (2020). Extinction of experience: The need to be more specific. People and Nature, 2(3), 575581. https://doi.org/10.1002/pan3.10118 CrossRefGoogle Scholar
Golumbic, Y. N., Orr, D., Baram-Tsabari, A., & Fishbain, B. (2017). Between vision and reality: A study of scientists’ views on citizen science. Citizen Science: Theory and Practice, 2(1), 6. https://doi.org/10.5334/cstp.53 Google Scholar
Gouveia, C., Fonseca, A., Câmara, A., & Ferreira, F. (2004). Promoting the use of environmental data collected by concerned citizens through information and communication technologies. Journal of Environmental Management, 71(2), 135154. https://doi.org/10.1016/j.jenvman.2004.01.009 CrossRefGoogle ScholarPubMed
Guerrini, C. J., Majumder, M. A., Lewellyn, M. J., & McGuire, A. L. (2018). Citizen science, public policy. Science, 361(6398), 134136. https://doi.org/10.1126/science.aar8379 CrossRefGoogle ScholarPubMed
Hagedorn, G., Kalmus, P., Mann, M., Vicca, S., Berge, J. V. den, Ypersele, J.-P. van, Bourg, D., Rotmans, J., Kaaronen, R., Rahmstorf, S., Kromp-Kolb, H., Kirchengast, G., Knutti, R., Seneviratne, S. I., Thalmann, P., Cretney, R., Green, A., Anderson, K., Hedberg, M., … Hayhoe, K. (2019). Concerns of young protesters are justified. Science, 364(6436), 139140. https://doi.org/10.1126/science.aax3807 CrossRefGoogle ScholarPubMed
Hano, M. C., Wei, L., Hubbell, B., & Rappold, A. G. (2020). Scaling up: Citizen science engagement and impacts beyond the individual. Citizen Science: Theory and Practice, 5(1), 1. https://doi.org/10.5334/cstp.244 Google ScholarPubMed
Heathcote, G., Hobday, A. J., Spaulding, M., Gard, M., & Irons, G. (2019). Citizen reporting of wildlife interactions can improve impact-reduction programs and support wildlife carers. Wildlife Research, 46(5), 415428. https://doi.org/10.1071/WR18127 CrossRefGoogle Scholar
Heigl, F., Kieslinger, B., Paul, K. T., Uhlik, J., & Dörler, D. (2019). Opinion: Toward an international definition of citizen science. Proceedings of the National Academy of Sciences, 116(17), 80898092. https://doi.org/10.1073/pnas.1903393116 CrossRefGoogle ScholarPubMed
Hill, A., Guralnick, R., Smith, A., Sallans, A., Gillespie, R., Denslow, M., Gross, J., Murrell, Z., Conyers, T., Oboyski, P., Ball, J., Thomer, A., Prys-Jones, R., Torre, J., de la Kociolek, P., & Fortson, L. (2012). The notes from nature tool for unlocking biodiversity records from museum records through citizen science. ZooKeys, 209, 219233. https://doi.org/10.3897/zookeys.209.3472 CrossRefGoogle Scholar
Isaac, M. E., & Martin, A. R. (2019). Accumulating crop functional trait data with citizen science. Scientific Reports, 9(1), 15715. https://doi.org/10.1038/s41598-019-51927-x CrossRefGoogle ScholarPubMed
Joly, A., Bonnet, P., Goëau, H., Barbe, J., Selmi, S., Champ, J., Dufour-Kowalski, S., Affouard, A., Carré, J., Molino, J.-F., Boujemaa, N., & Barthélémy, D. (2016). A look inside the Pl@ntNet experience. Multimedia Systems, 22(6), 751766. https://doi.org/10.1007/s00530-015-0462-9 CrossRefGoogle Scholar
Kermish-Allen, R., Peterman, K., & Bevc, C. (2019). The utility of citizen science projects in K-5 schools: Measures of community engagement and student impacts. Cultural Studies of Science Education, 14(3), 627641. https://doi.org/10.1007/s11422-017-9830-4 CrossRefGoogle Scholar
Kobori, H., Dickinson, J. L., Washitani, I., Sakurai, R., Amano, T., Komatsu, N., Kitamura, W., Takagawa, S., Koyama, K., & Ogawara, T. (2016). Citizen science: A new approach to advance ecology, education, and conservation. Ecological Research, 31(1), 119.CrossRefGoogle Scholar
Kosmala, M., Wiggins, A., Swanson, A., & Simmons, B. (2016). Assessing data quality in citizen science. Frontiers in Ecology and the Environment, 14(10), 551560. https://doi.org/10.1002/fee.1436 CrossRefGoogle Scholar
Kumar, N., Belhumeur, P. N., Biswas, A., Jacobs, D. W., Kress, W. J., Lopez, I. C., & Soares, J. V. B. (2012). Leafsnap: A computer vision system for automatic plant species identification. In Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., & Schmid, C. (Éds.), Computer vision – ECCV 2012 (pp. 502516). Springer. https://doi.org/10.1007/978-3-642-33709-3_36 CrossRefGoogle Scholar
Lakeman-Fraser, P., Gosling, L., Moffat, A. J., West, S. E., Fradera, R., Davies, L., Ayamba, M. A., & van der Wal, R. (2016). To have your citizen science cake and eat it? Delivering research and outreach through Open Air Laboratories (OPAL). BMC Ecology, 16(1), 16. https://doi.org/10.1186/s12898-016-0065-0 CrossRefGoogle ScholarPubMed
Lakshminarayanan, S. (2007). Using citizens to do science versus citizens as scientists. Ecology and Society, 12(2), r2.CrossRefGoogle Scholar
Lawrence, A. (2006). ‘No personal motive?’ Volunteers, biodiversity, and the false dichotomies of participation. Ethics, Place & Environment, 9(3), 279298. https://doi.org/10.1080/13668790600893319 CrossRefGoogle Scholar
Lawson, D. F., Stevenson, K. T., Peterson, M. N., Carrier, S. J., Strnad, R. L., & Seekamp, E. (2019). Children can foster climate change concern among their parents. Nature Climate Change, 9, 458462. https://doi.org/10.1038/s41558-019-0463-3 CrossRefGoogle Scholar
Ledley, T. S., Dahlman, L., McAuliffe, C., Haddad, N., Taber, M. R., Domenico, B., Lynds, S., & Grogan, M. (2011). Making Earth science data accessible and usable in education. Science, 333(6051), 18381839. https://doi.org/10.1126/science.1199348 CrossRefGoogle Scholar
Lorke, J., Golumbic, Y. N., Ramjan, C., & Atias, O. (2019). Training needs and recommendations for Citizen Science participants, facilitators and designers (AV.tp-01486). https://nhm.openrepository.com/handle/10141/622589.Google Scholar
MacPhail, V. J., & Colla, S. R. (2020). Power of the people: A review of citizen science programs for conservation. Biological Conservation, 249, 108739. https://doi.org/10.1016/j.biocon.2020.108739 CrossRefGoogle Scholar
Mahecha, M. D., Rzanny, M., Kraemer, G., Mäder, P., Seeland, M., & Wäldchen, J. (2021). Crowd-sourced plant occurrence data provide a reliable description of macroecological gradients. Ecography, 44, 112. https://doi.org/10.1111/ecog.05492 CrossRefGoogle Scholar
McDonough MacKenzie, C., Gallinat, A. S., & Zipf, L. (2020). Low-cost observations and experiments return a high value in plant phenology research. Applications in Plant Sciences, 8(4), e11338. https://doi.org/10.1002/aps3.11338 CrossRefGoogle ScholarPubMed
McKinley, D., Miller-Rushing, A., Ballard, H., Bonney, R., Brown, H., Evans, D., French, R., Parrish, J., Phillips, T., & Ryan, S. (2015). Can investing in citizen science improve natural resource management and environmental protection. Issues in Ecology, 19.Google Scholar
McKinley, D. C., Miller-Rushing, A. J., Ballard, H. L., Bonney, R., Brown, H., Cook-Patton, S. C., Evans, D. M., French, R. A., Parrish, J. K., Phillips, T. B., Ryan, S. F., Shanley, L. A., Shirk, J. L., Stepenuck, K. F., Weltzin, J. F., Wiggins, A., Boyle, O. D., Briggs, R. D., Chapin, S. F., … Soukup, M. A. (2017). Citizen science can improve conservation science, natural resource management, and environmental protection. Biological Conservation, 208, 1528. https://doi.org/10.1016/j.biocon.2016.05.015 CrossRefGoogle Scholar
Mohanty, S. P., Hughes, D. P., & Salathé, M. (2016). Using deep learning for image-based plant disease detection. Frontiers in Plant Science, 7, 1419. https://www.frontiersin.org/article/10.3389/fpls.2016.01419 CrossRefGoogle ScholarPubMed
Morin, E. (2007). Restricted complexity, general complexity. In Science and us: philosophy and complexity (pp. 125). World Scientific.Google Scholar
Nascimento, S., Rubio Iglesias, J., Owen, R., Schade, S., & Shanley, L. (2018). Citizen science for policy formulation and implementation (AV.tp-01474). UCL Press.Google Scholar
Newman, G., Wiggins, A., Crall, A., Graham, E., Newman, S., & Crowston, K. (2012). The future of citizen science: Emerging technologies and shifting paradigms. Frontiers in Ecology and the Environment, 10(6), 298304.CrossRefGoogle Scholar
Nistor, A., Clemente-Gallardo, J., Angelopoulos, T., Chodzinska, K., Clemente Gallardo, M., Gozdzik, A., Gras-Velazquez, A., Grizelj, A., Kolenberg, K., & Mitropoulou, D. (2019). Bringing Research into the Classroom–The Citizen Science approach in schools. Scientix Observatory.Google Scholar
Nov, O., Arazy, O., & Anderson, D. (2014). Scientists@Home: What drives the quantity and quality of online citizen science participation? PLOS One, 9(4), e90375. https://doi.org/10.1371/journal.pone.0090375 CrossRefGoogle ScholarPubMed
Nualart, N., Ibáñez, N., Soriano, I., & López-Pujol, J. (2017). Assessing the relevance of herbarium collections as tools for conservation biology. The Botanical Review, 83(3), 303325. https://doi.org/10.1007/s12229-017-9188-z CrossRefGoogle Scholar
Owen, R. P., & Parker, A. J. (2018). Citizen science in environmental protection agencies (AV.tp-01504). UCL Press.Google Scholar
Pipino, L. L., Lee, Y. W., & Wang, R. Y. (2002). Data quality assessment. Communications of the ACM, 45(4), 211218.CrossRefGoogle Scholar
Pocock, M. J. O., & Evans, D. M. (2014). The success of the Horse–Chestnut leaf-miner, Cameraria Ohridella, in the UK revealed with hypothesis-led citizen science. PLOS One, 9(1), e86226. https://doi.org/10.1371/journal.pone.0086226 CrossRefGoogle ScholarPubMed
Poulet, L., Dalmas, B., Goncalves, B., Noûs, C., & Vernay, A. (2021). As researchers, we need to engage more into public outreach towards children in the future. Journal of futures studies, 26(1), 7582. https://doi.org/10.6531/JFS.202109_26(1).0006 Google Scholar
Poulet, L., Vernay, A., Goncalves, B., Dalmas, B., & Vernay, M. (2020). A multidisciplinary scientific outreach journal designed for and made by middle and high school students to bring research closer to the classroom (AV.tp-01104). https://ttu-ir.tdl.org/handle/2346/86423 Google Scholar
Primack, R. B., Laube, J., Gallinat, A. S., & Menzel, A. (2015). From observations to experiments in phenology research: Investigating climate change impacts on trees and shrubs using dormant twigs. Annals of Botany, 116(6), 889897.CrossRefGoogle ScholarPubMed
Ramirez-Andreotta, M. D., Brusseau, M. L., Artiola, J., Maier, R. M., & Gandolfi, A. J. (2015). Building a co-created citizen science program with gardeners neighboring a superfund site: The Gardenroots case study. International Public Health Journal, 7(1), 13.Google ScholarPubMed
Reis, G., & Glithero, L. (2015). Provoking EcoJustice—Taking citizen science and youth activism beyond the school curriculum. In Ecojustice, citizen science and youth activism (pp. 3961). Springer.Google Scholar
Roche, J., Bell, L., Galvão, C., Golumbic, Y. N., Kloetzer, L., Knoben, N., Laakso, M., Lorke, J., Mannion, G., Massetti, L., Mauchline, A., Pata, K., Ruck, A., Taraba, P., & Winter, S. (2020). Citizen science, education, and learning: Challenges and opportunities. Frontiers in Sociology, 5, 110. https://doi.org/10.3389/fsoc.2020.613814 CrossRefGoogle ScholarPubMed
Rotman, D., Preece, J., Hammock, J., Procita, K., Hansen, D., Parr, C., Lewis, D., & Jacobs, D. (2012). Dynamic changes in motivation in collaborative citizen-science projects. In Proceedings of the ACM 2012 conference on computer supported cooperative work (pp. 217226). ACM. https://doi.org/10.1145/2145204.2145238 CrossRefGoogle Scholar
Rupprecht, C. D. D., Vervoort, J., Berthelsen, C., Mangnus, A., Osborne, N., Thompson, K., Urushima, A. Y. F., Kóvskaya, M., Spiegelberg, M., Cristiano, S., Springett, J., Marschütz, B., Flies, E. J., McGreevy, S. R., Droz, L., Breed, M. F., Gan, J., Shinkai, R., & Kawai, A. (2020). Multispecies sustainability. Global Sustainability, 3, e34. https://doi.org/10.1017/sus.2020.28 CrossRefGoogle Scholar
Schade, S., Pelacho, M., van Noordwijk, T. (C. G. E.), Vohland, K., Hecker, S., & Manzoni, M. (2021). Citizen science and policy. In Vohland, K., Land-Zandstra, A., Ceccaroni, L., Lemmens, R., Perelló, J., Ponti, M., Samson, R., & Wagenknecht, K. (Éds.), The science of citizen science (pp. 351371). Springer International Publishing. https://doi.org/10.1007/978-3-030-58278-4_18 CrossRefGoogle Scholar
Schläppy, M.-L., Loder, J., Salmond, J., Lea, A., Dean, A. J., & Roelfsema, C. M. (2017). Making waves: Marine citizen science for impact. Frontiers in Marine Science, 4, 146. https://doi.org/10.3389/fmars.2017.00146 CrossRefGoogle Scholar
Serret, H., Deguines, N., Jang, Y., Lois, G., & Julliard, R. (2019). Data quality and participant engagement in citizen science: Comparing two approaches for monitoring pollinators in France and South Korea. Citizen Science: Theory and Practice, 4(1), 22.Google Scholar
Shanley, P., & López, C. (2009). Out of the loop: Why research rarely reaches policy makers and the public and what can be done. Biotropica, 41(5), 535544. https://doi.org/10.1111/j.1744-7429.2009.00561.x CrossRefGoogle Scholar
Shirk, J. L., Ballard, H. L., Wilderman, C. C., Phillips, T., Wiggins, A., Jordan, R., McCallie, E., Minarchek, M., Lewenstein, B. V., Krasny, M. E., & Bonney, R. (2012). Public participation in scientific research: A framework for deliberate design. Ecology and Society, 17(2), 2948. http://www.jstor.org/stable/26269051 CrossRefGoogle Scholar
Silvertown, J. (2009). A new dawn for citizen science. Trends in Ecology & Evolution, 24(9), 467471. https://doi.org/10.1016/j.tree.2009.03.017 CrossRefGoogle ScholarPubMed
Singh, A. K., Ganapathysubramanian, B., Sarkar, S., & Singh, A. (2018). Deep learning for plant stress phenotyping: Trends and future perspectives. Trends in Plant Science, 23(10), 883898. https://doi.org/10.1016/j.tplants.2018.07.004 CrossRefGoogle ScholarPubMed
Smith, H., Allf, B., Larson, L., Futch, S., Lundgren, L., Pacifici, L., & Cooper, C. (2021). Leveraging citizen science in a college classroom to build interest and efficacy for science and the environment. Citizen Science: Theory and Practice, 6(1), 29. https://doi.org/10.5334/cstp.434 Google Scholar
Steffen, W., Broadgate, W., Deutsch, L., Gaffney, O., & Ludwig, C. (2015). The trajectory of the Anthropocene: The great acceleration. The Anthropocene Review, 2(1), 8198.CrossRefGoogle Scholar
Teacher, A. G. F., Griffiths, D. J., Hodgson, D. J., & Inger, R. (2013). Smartphones in ecology and evolution: A guide for the app-rehensive. Ecology and Evolution, 3(16), 52685278. https://doi.org/10.1002/ece3.888 CrossRefGoogle ScholarPubMed
Teleki, K. A. (2012). Power of the people? Aquatic Conservation: Marine and Freshwater Ecosystems, 22(1), 16. https://doi.org/10.1002/aqc.2219 CrossRefGoogle Scholar
Thiel, M., Penna-Díaz, M. A., Luna-Jorquera, G., Salas, S., Sellanes, J., & Stotz, W. (2014). Citizen scientists and marine research: Volunteer participants, their contributions, and projection for the future. In Oceanography and marine biology (pp. 257314). CRC Press. https://doi.org/10.1201/b17143-6 CrossRefGoogle Scholar
Thomas, M. L., Gunawardene, N., Horton, K., Williams, A., O’Connor, S., McKirdy, S., & van der Merwe, J. (2017). Many eyes on the ground: Citizen science is an effective early detection tool for biosecurity. Biological Invasions, 19(9), 27512765. https://doi.org/10.1007/s10530-017-1481-6 CrossRefGoogle Scholar
Tweddle, J. C., Robinson, L. D., Pocock, M. J. O., & Roy, H. E. (2012). Guide to citizen science: Developing, implementing and evaluating citizen science to study biodiversity and the environment in the UK. NERC/Centre for Ecology & Hydrology. http://www.ukeof.org.uk/documents/guide-to-citizen-science.pdf Google Scholar
Van Haeften, S., Milic, A., Addison-Smith, B., Butcher, C., & Davies, J. M. (2021). Grass Gazers: Using citizen science as a tool to facilitate practical and online science learning for secondary school students during the COVID-19 lockdown. Ecology and Evolution, 11(8), 34883500. https://doi.org/10.1002/ece3.6948 CrossRefGoogle ScholarPubMed
Vasiliades, M. A., Hadjichambis, A. C., Paraskeva-Hadjichambi, D., Adamou, A., & Georgiou, Y. (2021). A systematic literature review on the participation aspects of environmental and nature-based citizen science initiatives. Sustainability, 13(13), 7457. https://doi.org/10.3390/su13137457 CrossRefGoogle Scholar
Vayena, E., & Tasioulas, J. (2015). “We the Scientists”: A human right to citizen science. Philosophy & Technology, 28(3), 479485. https://doi.org/10.1007/s13347-015-0204-0 CrossRefGoogle Scholar
Vignola, R., Locatelli, B., Martinez, C., & Imbach, P. (2009). Ecosystem-based adaptation to climate change: What role for policy-makers, society and scientists? Mitigation and Adaptation Strategies for Global Change, 14(8), 691. https://doi.org/10.1007/s11027-009-9193-6 CrossRefGoogle Scholar
Vohland, K., Land-Zandstra, A., Ceccaroni, L., Lemmens, R., Perelló, J., Ponti, M., Samson, R., & Wagenknecht, K. (2021). The science of citizen science. Springer Nature.CrossRefGoogle Scholar
Vohland, K., Weißpflug, M., & Pettibone, L. (2019). Citizen science and the Neoliberal transformation of science—An ambivalent relationship. Citizen Science: Theory and Practice, 4(1), 25. https://doi.org/10.5334/cstp.186 Google Scholar
Ward-Fear, G., Pauly, G. B., Vendetti, J. E., & Shine, R. (2020). Authorship protocols must change to credit citizen scientists. Trends in Ecology & Evolution, 35(3), 187190. https://doi.org/10.1016/j.tree.2019.10.007 CrossRefGoogle ScholarPubMed
Watermeyer, R., & Montgomery, C. (2018). Public dialogue with science and development for teachers of STEM: Linking public dialogue with pedagogic praxis. Journal of Education for Teaching, 44(1), 90106. https://doi.org/10.1080/02607476.2018.1422621 CrossRefGoogle Scholar
Williams, K. A., Hall, T. E., & O’Connell, K. (2021). Classroom-based citizen science: Impacts on students’ science identity, nature connectedness, and curricular knowledge. Environmental Education Research, 27(7), 10371053. https://doi.org/10.1080/13504622.2021.1927990 CrossRefGoogle Scholar
Würschum, T., Leiser, W. L., Jähne, F., Bachteler, K., Miersch, M., & Hahn, V. (2019). The soybean experiment ‘1000 Gardens’: A case study of citizen science for research, education, and beyond. Theoretical and Applied Genetics, 132(3), 617626. https://doi.org/10.1007/s00122-018-3134-2 CrossRefGoogle Scholar
Zoellick, B., Nelson, S. J., & Schauffler, M. (2012). Participatory science and education: Bringing both views into focus. Frontiers in Ecology and the Environment, 10(6), 310313.CrossRefGoogle Scholar
Figure 0

Fig. 1. Global trend of citizen science projects in the plant science literature from 2000 to 2020: The left grey y-axis (grey dots) represents the number of articles containing the mention ‘plant science’ AND ‘citizen science’ in their title, and the right green y-axis (green bars) represents the ratio of paper numbers with ‘plant science’ AND ‘citizen science’ and the paper numbers containing ‘plant science’ only. The number of papers was extracted from Google Scholar on 01/02/2022.

Figure 1

Fig. 2. Conceptual framework of the reciprocal benefits from the CS project to the socio-ecological system. Circles represent participants of a CS project, and black arrows show how the scientific and epistemological benefit spreads beyond the project per se. The two dotted arrows represent the indirect added value of the facilitator to spread the CS results to the socio-ecological system.

Figure 2

Table 1 Summary of citizen science governance types

Author comment: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R0/PR1

Comments

Dear Pr Hamant,

First of all, on behalf of the authorship, I would like to thank you to invite us to write this review. I am pleased to propose a review article to the journal Quantitative Plant Biology, currently entitled “Citizen Science: reciprocal benefits from the project community to the socio-ecological system ” by Aurore Receveur (CPS, France), Benjamin Dalmas (Ecole des Mines de St Etienne, France), Barbara Goncalves (Université Clermont Auvergne, France), Lucie Poulet (NASA, US) and Antoine Vernay (Université Claude Bernard Lyon 1, France).

In this review, we propose to highlight the benefits of citizen science from the community associated with the project, to the whole socio-ecological system. In this context, quantitative science should embrace the opportunity offered by citizen science to increase data collection but also to empower volunteers about the scientific method (Conrad & Hilchey, 2011). The benefits of this interaction will spread to society, which will help to face the major crisis we are undergoing (Hagedorn et al., 2019).

Our current version of the manuscript contains 4964 words divided into four main sections. We add the contents of the paper at the end of this letter. First, we show the importance of new technologies in data acquisition. These tools are easily accessible, facilitating the volunteer’s involvement in the project and the check by the research team to then, produce robust quantitative studies (Kosmala et al., 2016). Second, we remind the reciprocal benefits of citizen science projects for the research team and the volunteers. We also broadenour demonstration to show how these benefits have an important effect on the socio-ecosystem. It makes citizen science a powerful praxeological approach to make science closer to the citizens. Third, we analyse some remaining challenges to improve the benefits of citizen science projects, especially from the data quality perspective. Finally, we end the article with further encouraging perspectives for researchers and future volunteers.

We hope that this will encourage the scientific community to engage in citizen science projects. Quantitative plant science will take advantage of this approach in terms of collected data and, by involving volunteers deeper in the scientific method of the project (Autran et al., 2021), the benefits will be exacerbated until the society.

Sincerely yours,

Dr Antoine Vernay, on behalf of the authorship

Autran D, Bassel GW, Chae E, Ezer D, Ferjani A, Fleck C, Hamant O, Hartmann FP, Jiao Y, Johnston IG, et al. 2021. What is quantitative plant biology? Quantitative Plant Biology 2.

Conrad CC, Hilchey KG. 2011. A review of citizen science and community-based environmental monitoring: issues and opportunities. Environmental Monitoring and Assessment 176: 273–291.

Hagedorn G, Kalmus P, Mann M, Vicca S, Berge JV den, Ypersele J-P van, Bourg D, Rotmans J, Kaaronen R, Rahmstorf S, et al. 2019. Concerns of young protesters are justified. Science 364: 139–140.

Kosmala M, Wiggins A, Swanson A, Simmons B. 2016. Assessing data quality in citizen science. Frontiers in Ecology and the Environment 14: 551–560.

Review: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R0/PR2

Conflict of interest statement

Reviewer declares none.

Comments

Comments to Author: Dear Dr Chae, dear authors,

Receveur and colleagues wrote a review of citizen science (CS) approaches that may be used in plant science. I must say that I strongly agree with the authors that CS has a great potential to change both the way we produce new scientific knowledge and the relationship between science and the society. Although I agree with most of the arguments made by the authors, I think there are several points that would deserve more careful consideration. I list them below. I also attached the pdf with hand made notes, hoping you can read them!

0 – Overall, I am ambivalent with the manuscript. On the one hand, I would have liked to write it myself (!) and I may well have had the same arguments; I am therefore positive about the paper. On the other hand, I realize that much has been written on that topic, and I am unsure what is the original angle of the paper that would make a strong, original contribution. Should this be clarified and the arguments streamlined, the paper could make a worth contribution to the readership of the journal, but this probably requires profound revisions.

1 – Novelty. Much has been written about citizen science, the way it modifies the way researchers consider research and their role in the society, as well as the way the public perceives science. The authors cite relevant literature in this respect, as far as I know. It was not completely clear to me what this review brings new, but I confess I may have missed important things. I suggest the authors make a clear case about their own contribution to a field that has been reviewed quite a lot already.

2 – Plant science. Plant science is a very general term. In my understanding, it generally refers to a reductionist approach of plant biology, deeply focused on the plant individual, its physiology and its genome. Maybe I am wrong, but spontaneously, I consider plant science and ecology as complementary, but different fields of life science. Ecology CS is very well developed, with many project aiming to describe biodiversity; I am not sure this is the case for plant science. The manuscript would greatly gain clarity, should plant science be clearly defined and the distinction with ecology be made. Note that I am fine with broadening the scope of the review to life science in general – excluding medical sciences – but then it should be made clear. At present, the lack of clear definition gives the general impression that the manuscript is a bit unfocused.

3 – Win-win relationship. I do agree CS is a great way to acquire data over large areas and time periods. I also agree it might be useful to make a case to plant biologists that CS can be a valuable approach. However, CS is much more than harvesting. I agree it is mentioned in the manuscript that CS is not a one way road, from volunteers to scientists, and that volunteers receive something from their contribution. However, the manuscript is unbalanced in this respect. I found that there was a disproportionate emphasis on what scientists can earn from citizen science. There is an increasing body of research addressing what volunteers get, or nor from their contribution. Sometimes, we plant scientists/ecologists overstate the contribution of CS to volunteers and the society. I think it is important this kind of statement is backed up with strong references. Otherwise it sounds like a kind of magic. It is probably not. On the contrary, I believe it is important to understand and acknowledge what CS does NOT. Only by then we will be able to improve our approach to CS and the win-win relationship.

4 – Opinion/facts. This fourth item is very related to the previous one. In some places, there were general statements I could not tell whether the authors expressed their own opinion or referred to the results of the research in plant science/social science/education science. Some statements also sounds like political. It was not written that way, of course, but I could read that “CS is needed because governments do not invest in tech/lab technicians anymore”. I kind of agree, but I don’t think this is the kind of argument we should use to justify CS. Otherwise the said governments could say “well, if you do such a good job with free workers, why should we keep investing in tech/lab supports”? I trust you see what I mean =D.

5 – English. As you can read, there might be typos of grammatical glitches in my comments above. I am therefore very forgiving of stylistic errors. However, the writing could be sharpened, and sometimes the grammar should be checked. Not only because the paper would read more easily, but because in some places, I was unsure what the authors really meant.

I hope this helps.

Bastien Castagneyrol

Review: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R0/PR3

Conflict of interest statement

Reviewer declares none.

Comments

Comments to Author: Thank you for your submission to review the merit of the citizen science approach to provide benefits to the socio-ecological system. The manuscript provides sufficient background and review of the applications, potential and need for the citizen science approach to aid in collection and analysis of big data (albeit other reviews have already completed this), but the manuscript poorly explains or justifies how the approach ‘gives back’ to society as the authors suggest. Greater evaluation of the socio benefits are needed to actually demonstrate the reciprocal benefits as suggested by the title and abstract. More examples are needed to provide evidence for the external benefits if it is a core message of the manuscript.

Recommendation: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R0/PR4

Comments

Comments to Author: Dear Antoine Vernay,

Thank you for submitting your article " Citizen Science: reciprocal benefits from the project community to the socio-ecological system " for consideration by Quantitative Plant Biology. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by myself as an Associate Editor. I apologize for the delay in the return of review comments due to unexpected difficulties in identifying reviewers.

On the basis of reviews’ comments, I have decided to invite a major revision of your work for further consideration in our journal. Your revision should address all the points raised by our reviewers. I strongly agree with all the points, in particular ones raised on novelty of this article as well as on benefits that volunteers receive. As your article title includes the notion of “reciprocal benefits”, it will be an important calibre to evaluate your revised manuscript.

I also found that it would be necessary for you to define sub-areas of plant biology to articulate your perspectives on citizen science. Preferably, past experiences and published works should be introduced in detail under the domain of a sub-field, such as in the plant ecology research field or else that you are familiar with, so that members belonging to other sub-areas could benefit from the examples. As citizen science is not being considered seriously in some sub-areas of plant biology, QPB aims to put forward the benefits coming from a success story to bring in new perspectives for broad audience in plant biology. You may consider to comprehensively cover the scope of citizen science so that adequate attention shall be drawn to this article from community members taking many different approaches in plant sciences.

When submitting your revised article, you must provide a point-by-point response to the reviewers’ comments. Please show all changes in the manuscript text file with track changes or colour highlighting, which will help revision proceed with ease.

Reviewer #1

Receveur and colleagues wrote a review of citizen science (CS) approaches that may be used in plant science. I must say that I strongly agree with the authors that CS has a great potential to change both the way we produce new scientific knowledge and the relationship between science and the society. Although I agree with most of the arguments made by the authors, I think there are several points that would deserve more careful consideration. I list them below. I also attached the pdf with hand made notes, hoping you can read them!

0 – Overall, I am ambivalent with the manuscript. On the one hand, I would have liked to write it myself (!) and I may well have had the same arguments; I am therefore positive about the paper. On the other hand, I realize that much has been written on that topic, and I am unsure what is the original angle of the paper that would make a strong, original contribution. Should this be clarified and the arguments streamlined, the paper could make a worth contribution to the readership of the journal, but this probably requires profound revisions.

1 – Novelty. Much has been written about citizen science, the way it modifies the way researchers consider research and their role in the society, as well as the way the public perceives science. The authors cite relevant literature in this respect, as far as I know. It was not completely clear to me what this review brings new, but I confess I may have missed important things. I suggest the authors make a clear case about their own contribution to a field that has been reviewed quite a lot already.

2 – Plant science. Plant science is a very general term. In my understanding, it generally refers to a reductionist approach of plant biology, deeply focused on the plant individual, its physiology and its genome. Maybe I am wrong, but spontaneously, I consider plant science and ecology as complementary, but different fields of life science. Ecology CS is very well developed, with many project aiming to describe biodiversity; I am not sure this is the case for plant science. The manuscript would greatly gain clarity, should plant science be clearly defined and the distinction with ecology be made. Note that I am fine with broadening the scope of the review to life science in general – excluding medical sciences – but then it should be made clear. At present, the lack of clear definition gives the general impression that the manuscript is a bit unfocused.

3 – Win-win relationship. I do agree CS is a great way to acquire data over large areas and time periods. I also agree it might be useful to make a case to plant biologists that CS can be a valuable approach. However, CS is much more than harvesting. I agree it is mentioned in the manuscript that CS is not a one way road, from volunteers to scientists, and that volunteers receive something from their contribution. However, the manuscript is unbalanced in this respect. I found that there was a disproportionate emphasis on what scientists can earn from citizen science. There is an increasing body of research addressing what volunteers get, or nor from their contribution. Sometimes, we plant scientists/ecologists overstate the contribution of CS to volunteers and the society. I think it is important this kind of statement is backed up with strong references. Otherwise it sounds like a kind of magic. It is probably not. On the contrary, I believe it is important to understand and acknowledge what CS does NOT. Only by then we will be able to improve our approach to CS and the win-win relationship.

4 – Opinion/facts. This fourth item is very related to the previous one. In some places, there were general statements I could not tell whether the authors expressed their own opinion or referred to the results of the research in plant science/social science/education science. Some statements also sounds like political. It was not written that way, of course, but I could read that “CS is needed because governments do not invest in tech/lab technicians anymore”. I kind of agree, but I don’t think this is the kind of argument we should use to justify CS. Otherwise the said governments could say “well, if you do such a good job with free workers, why should we keep investing in tech/lab supports”? I trust you see what I mean =D.

5 – English. As you can read, there might be typos of grammatical glitches in my comments above. I am therefore very forgiving of stylistic errors. However, the writing could be sharpened, and sometimes the grammar should be checked. Not only because the paper would read more easily, but because in some places, I was unsure what the authors really meant.

Reviewer #2

Thank you for your submission to review the merit of the citizen science approach to provide benefits to the socio-ecological system. The manuscript provides sufficient background and review of the applications, potential and need for the citizen science approach to aid in collection and analysis of big data (albeit other reviews have already completed this), but the manuscript poorly explains or justifies how the approach ‘gives back’ to society as the authors suggest. Greater evaluation of the socio benefits are needed to actually demonstrate the reciprocal benefits as suggested by the title and abstract. More examples are needed to provide evidence for the external benefits if it is a core message of the manuscript.

Best regards,

Eunyoung Chae

------------------------------------------------------

Eunyoung Chae, Ph.D.

Assistant Professor

National University of Singapore

Department of Biological Sciences

16 Science Drive 4, Block S1A #5-15

Singapore 117558

Tel. +65 65162915

Fax. +65 6779 2486

E-mail: [email protected]

Decision: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R0/PR5

Comments

No accompanying comment.

Author comment: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R1/PR6

Comments

Comments to the Author:

Dear Antoine Vernay,

Thank you for submitting your article " Citizen Science: reciprocal benefits from the project community to the socio-ecological system " for consideration by Quantitative Plant Biology. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by myself as an Associate Editor. I apologize for the delay in the return of review comments due to unexpected difficulties in identifying reviewers.

On the basis of reviews’ comments, I have decided to invite a major revision of your work for further consideration in our journal. Your revision should address all the points raised by our reviewers. I strongly agree with all the points, in particular ones raised on novelty of this article as well as on benefits that volunteers receive. As your article title includes the notion of “reciprocal benefits”, it will be an important calibre to evaluate your revised manuscript.

I also found that it would be necessary for you to define sub-areas of plant biology to articulate your perspectives on citizen science. Preferably, past experiences and published works should be introduced in detail under the domain of a sub-field, such as in the plant ecology research field or else that you are familiar with, so that members belonging to other sub-areas could benefit from the examples. As citizen science is not being considered seriously in some sub-areas of plant biology, QPB aims to put forward the benefits coming from a success story to bring in new perspectives for broad audience in plant biology. You may consider to comprehensively cover the scope of citizen science so that adequate attention shall be drawn to this article from community members taking many different approaches in plant sciences.

When submitting your revised article, you must provide a point-by-point response to the reviewers’ comments. Please show all changes in the manuscript text file with track changes or colour highlighting, which will help revision proceed with ease.

Authors: First of all, we would like to thank the Associate Editor for her comments on the manuscript and for her invitation to revise it. We have tried to emphasize the novelty of this paper in the new version by enlarging our literature review and focusing on the crucial role of a “facilitator” to reach the goal of reciprocal benefits between participants and beyond, until the socio-ecological system. We also defined sub-areas in the perspective to encourage reluctant disciplines to take the CS step. However, we did not dedicate specific sections to one of this sub-field because we chose to provide examples from different disciplines to share the benefit from CS in general. We hope that QPB readers will find interesting information for their own CS projects.

To facilitate reviewers’ work, we chose to supply two documents, one named “Receveur_et_al_CitizenScience_QPB_R2_trackedchanges”, which is the tracked changes version and the one named “Receveur_et_al_CitizenScience_QPB_R2_acceptedchanges” with all modifications accepted, which may help to read as the previous version required major revisions. In our answer to the reviewers, the lines refer to the tracked changes version.

We specified in our introduction that the readers may find only a few QPS examples because this work reveals the poor involvement of QPS in CS (L143-160): “Quantitative sciences must play a major role in encouraging these collaborative sciences. Indeed, quantitative plant science is strongly related to plant’s traits measurements to analyse large dataset and implement models or build global plant characterization in terms of biological processes. The discipline is therefore dependent on mathematics and statistics, for instance, which require lots of data (Autran et al., 2021). This review shows that quantitative plant science is poorly involve in CS whereas it could take advantage from this scientific approach. We chose to broaden the scope of this review from plant science to plant ecology and its quantitative aspect. However, we also propose some examples from other fields: We are convinced that some inherent issues related to CS are shared by the majority of CS projects regardless of the topic and may be solved by other CS projects. Interesting ideas from other fields may be reused in plant ecology and plant science CS projects.

The goal of this review is to highlight (i) the diversity of tools and networks enabling scientists to run CS projects, (ii) the reciprocal benefits of CS projects between citizens, the scientific community and beyond with the socio-ecosystem, and (iii) some remaining obstacles, such as the need to include a “facilitator” in volunteer-scientist relationships; finally, this review (iv) proposes some perspectives for upcoming CS projects.”.

We specified in the text some sub-fields with the associated examples, mainly plant ecology, an advanced field for using CS. In the perspectives (L668-673), we encourage QP scientists to indulge in CS “This may be the strongest upheaval that some researchers have to face, especially in quantitative plant science but also in other disciplines. We hope this review provides exciting examples and a large body of literature to help quantitative plant biologists become more confident in this approach. The benefit may be significant from a scientific production point of view, but it can also have a crucial social role for public opinion of science and CS.”

Reviewer #1

Receveur and colleagues wrote a review of citizen science (CS) approaches that may be used in plant science. I must say that I strongly agree with the authors that CS has a great potential to change both the way we produce new scientific knowledge and the relationship between science and the society. Although I agree with most of the arguments made by the authors, I think there are several points that would deserve more careful consideration. I list them below. I also attached the pdf with hand made notes, hoping you can read them!

Authors: thanks a lot for reviewing the manuscript and the comments to improve it. We replied to all your comments and we hope it makes the manuscript better.

0 – Overall, I am ambivalent with the manuscript. On the one hand, I would have liked to write it myself (!) and I may well have had the same arguments; I am therefore positive about the paper. On the other hand, I realize that much has been written on that topic, and I am unsure what is the original angle of the paper that would make a strong, original contribution. Should this be clarified and the arguments streamlined, the paper could make a worth contribution to the readership of the journal, but this probably requires profound revisions.

Authors: We agree that the novelty is certainly not as obvious as we believed. Therefore, we keep reviewing the literature to focus on the role of a “facilitator” in the team of participants in a CS project. Its role appears fundamental to be sure that the expectations of all participants are met and it will help the volunteers and scientists to be more efficient during the project. This idea is not ours but it is relatively new in the literature and it may represent the trigger to give CS the magnitude it deserves. We show its role in the different sections (L666-668): “Thanks to this experience, it appears that CS requires changing the typical project construction approach by including, ideally, a facilitator, changing the typical way to make a protocol.”, L268-272: “Providing volunteer access to scientific data is time-consuming if the scientific team aims to achieve volunteer empowerment. The task may be ensured by a “facilitator”, i.e., someone dedicated to training or educating volunteers on a CS project (Lorke et al., 2019), but we propose to enlarge this role to align classes/teachers expectations and scientific objectives of the research team.”, L307-310 “Tools and protocols may have been thought to be easily used by non-scientific experts, and the classroom constraints may limit the involvement in a CS project. Therefore, a “facilitator” may allow, at the genesis of the project, students to build a project that meets the requirements of all participants.” and add a paragraph about this topic in the third section (L629-644): “The potential of CS projects for spreading science and scientific methods to the socioecosystem may be enhanced if the objectives and limits of each group of participants are taken into account (Freitag & Pfeffer, 2016). This is very hard work, and among the reviews, we compiled a non-exhaustive list of situations in which a facilitator might be a key component to optimise the benefits of CS projects from the participant to the global socio-ecological system. Indeed, A third party may ensure the match between each stakeholder: For global projects, finding a local interest for volunteers is important to reinforce their engagement and empower them scientifically and democratically. Expectations can be extremely different between participants (Golumbic et al., 2017). Therefore, recent studies have highlighted the great advantage of including a “facilitator” to ensure that each group meets its own expectations (Esch et al., 2020; Lorke et al., 2019). In a classroom, teachers are limited in adapting the curriculum; therefore, the facilitator may help scientific project leaders adapt the protocol to academic constraints. More generally, the interest and skills of volunteers may increase during the project, leading to changes in the motivations of volunteers (Rotman et al., 2012). Anticipating the dynamics of volunteer involvement in the project design can enhance the expectations of all participants by stimulating volunteers.”

1 – Novelty. Much has been written about citizen science, the way it modifies the way researchers consider research and their role in the society, as well as the way the public perceives science. The authors cite relevant literature in this respect, as far as I know. It was not completely clear to me what this review brings new, but I confess I may have missed important things. I suggest the authors make a clear case about their own contribution to a field that has been reviewed quite a lot already.

Authors: in line with our previous answer, we complete our claim that the reciprocal benefits of CS projects may reach the participants but also the socio-ecological system thanks to collaborative projects, by highlighting the importance of a facilitator in this collaborative work. Indeed, we think that an early implication of this facilitator, at the origin of the project, is one of the condition allowing to reach the socio-ecological system for a CS project.”

2 – Plant science. Plant science is a very general term. In my understanding, it generally refers to a reductionist approach of plant biology, deeply focused on the plant individual, its physiology and its genome. Maybe I am wrong, but spontaneously, I consider plant science and ecology as complementary, but different fields of life science. Ecology CS is very well developed, with many project aiming to describe biodiversity; I am not sure this is the case for plant science. The manuscript would greatly gain clarity, should plant science be clearly defined and the distinction with ecology be made. Note that I am fine with broadening the scope of the review to life science in general – excluding medical sciences – but then it should be made clear. At present, the lack of clear definition gives the general impression that the manuscript is a bit unfocused.

Authors: we agree with the distinction proposed by reviewer 1 and following the associate editor comments we (i) clearly exposed that we reviewed the literature mainly about plant sciences by defining the differences between plant biology and ecology but enlarged the work to other fields to report issues and/or solutions that can be useful in plant biology (L143-160): “Quantitative sciences must play a major role in encouraging these collaborative sciences. Indeed, quantitative plant science is strongly related to plant’s traits measurements to analyse large dataset and implement models or build global plant characterization in terms of biological processes. The discipline is therefore dependent on mathematics and statistics, for instance, which require lots of data (Autran et al., 2021). This review shows that quantitative plant science is poorly involve in CS whereas it could take advantage from this scientific approach. We chose to broaden the scope of this review from plant science to plant ecology and its quantitative aspect. However, we also propose some examples from other fields: We are convinced that some inherent issues related to CS are shared by the majority of CS projects regardless of the topic and may be solved by other CS projects. Interesting ideas from other fields may be reused in plant ecology and plant science CS projects.

The goal of this review is to highlight (i) the diversity of tools and networks enabling scientists to run CS projects, (ii) the reciprocal benefits of CS projects between citizens, the scientific community and beyond with the socio-ecosystem, and (iii) some remaining obstacles, such as the need to include a “facilitator” in volunteer-scientist relationships; finally, this review (iv) proposes some perspectives for upcoming CS projects.”.

.

3 – Win-win relationship. I do agree CS is a great way to acquire data over large areas and time periods. I also agree it might be useful to make a case to plant biologists that CS can be a valuable approach. However, CS is much more than harvesting. I agree it is mentioned in the manuscript that CS is not a one way road, from volunteers to scientists, and that volunteers receive something from their contribution. However, the manuscript is unbalanced in this respect. I found that there was a disproportionate emphasis on what scientists can earn from citizen science. There is an increasing body of research addressing what volunteers get, or nor from their contribution. Sometimes, we plant scientists/ecologists overstate the contribution of CS to volunteers and the society. I think it is important this kind of statement is backed up with strong references. Otherwise it sounds like a kind of magic. It is probably not. On the contrary, I believe it is important to understand and acknowledge what CS does NOT. Only by then we will be able to improve our approach to CS and the win-win relationship.

Authors: Indeed, we miss something if reviewers 1 (and 2) did not clearly see the reciprocity between participants of CS projects. In our opinion, the biggest advantage for volunteers, beyond increasing their technical and learning skills, is then to have a better understanding of decision making, especially un environmental policies and to participate in democratic institutions thanks to their empowerment. We modified the text to make it clearer. We clarified section 2 by renaming the subtitles: 2.1 Main benefits for the scientific community and 2.2 Important benefits for volunteers.

Moreover, we have tried to highlight the potential “lack of efficiency” from scientists to reach out to the public. L275-310, we take the example with the classroom: “Similarly, an increasing number of CS projects involve schools (Kermish-Allen et al., 2019; Nistor et al., 2019; Van Haeften et al., 2021), even if they are often not specifically designed for students (Bopardikar et al., 2021; Williams et al., 2021). The scientific team can take advantage of the time dedicated by the class to the project to train students and improve data quality (Castagneyrol et al., 2020). This does not avoid the requirement for another check after data collection, but it also creates a time for discussion with pupils and teachers about scientific methods and epistemology. This aspect of CS is at least as important as the larger time and spatial scale of data collection because it allows students, and more people in general, to be aware of the world’s complexity (Morin, 2007). From a quantitative plant sciences perspective, it is important to clearly explain the benefits of acquiring a large amount of data for building a robust answer to the initial questions.

Although developing CS with schools appears to be relevant, scientists need to factor in educational constraints that are often incompatible with the protocols. Indeed, teachers do not have an infinite amount of time to allocate to the project, which can have consequences on data validity or decrease the project’s relevance for students and teachers, despite the educational benefits of CS initiatives (Esch et al., 2020). Tools and protocols may have been thought to be easily used by non-scientific experts, and the classroom constraints may limit the involvement in a CS project. Therefore, a “facilitator” may allow, at the genesis of the project, students to build a project that meets the requirements of all participants.”.

We added some pieces of literature in section 3.3 to underline some researchers deficiencies in their outreach activities (L572-594): “Finally, to make science a real citizen tool, researchers must involve volunteers deeper into the project’s governance (Conrad & Hilchey, 2011; Heigl et al., 2019). The basic level of CS consists of collecting data, which per se has a significant impact in increasing the size of a dataset - which is particularly interesting in quantitative science. However, a transition from projects whereby participants mainly collect data to more collaborative and co-created approaches has started and needs to continue (Bonney et al., 2009; Teleki, 2012), with major socio-ecological benefits such as promoting environmental awareness and literacy and empowering citizens and communities.

Different classifications exist in the literature (Table 1) to highlight a gradient of volunteers’ involvement in the project’s tasks. It is out of the scope of this review to clarify the possible overlap among the terms, but all recognised that the more that volunteers participate in the scientific process (from conception to solution application when the goal was to solve a local issue), the greater they are empowered. It has positive consequences on the citizenry because they become aware of how the data are collected and how data are used, they understand where the money comes from and how it is spent, and finally, they can participate in the decision-making process more easily. This can lead to substantial policy changes thanks to an awareness of involvement in scientific and societal issues (Hagedorn et al., 2019). Therefore, a specific effort from research teams is needed to allow democratic shared governance (Watermeyer & Montgomery, 2018) regardless of the degree of involvement of volunteers.

To conclude, the strength and weakness of CS projects is the participant diversity in terms of scientific level, expectations and motivation. To avoid disappointment, we agree with Lorke et al. (2019), who encourage the participation of a facilitator early in the co-construction of the project.”

Finally, paragraph L629-644 about the facilitator is a suggestion to help the scientists in their outreach activities (paragraph cited in point 0).

4 – Opinion/facts. This fourth item is very related to the previous one. In some places, there were general statements I could not tell whether the authors expressed their own opinion or referred to the results of the research in plant science/social science/education science. Some statements also sounds like political. It was not written that way, of course, but I could read that “CS is needed because governments do not invest in tech/lab technicians anymore”. I kind of agree, but I don’t think this is the kind of argument we should use to justify CS. Otherwise the said governments could say “well, if you do such a good job with free workers, why should we keep investing in tech/lab supports”? I trust you see what I mean =D.

Authors: some sentences, highlighted by reviewer 1, were effectively kind of militant, which was deliberated. However, they mixed with the more objective points of view, which can harm the global analysis of the role of CS and the take-home message. Militant sentences would better fit in an opinion paper or something similar, therefore, we removed them or rephrased them.

5 – English. As you can read, there might be typos of grammatical glitches in my comments above. I am therefore very forgiving of stylistic errors. However, the writing could be sharpened, and sometimes the grammar should be checked. Not only because the paper would read more easily, but because in some places, I was unsure what the authors really meant.

Authors: Despite English editing, we will recheck it before submitting the revised version. The revised version is edited and we provide the certificate.

Minor comments from reviewer 1 in the text:

As the text was significantly changed, the lines here refer to the first version of the manuscript where reviewer 1 made its comments.

Figures: edited according to reviewer 1 comments

L60: introductive sentence complemented after the CS definition

L63: spelling edited

L74: sentences edited

L78-79: we do not really understand the reviewer note, we simply paraphrase the definition from Heigl (2019).

L80-84: the sentence was simplified to avoid political statements.

L96-105: indicative mode was chosen

L107: the sentence was replaced by “facilitating the CS project running”

L121: success is very difficult to define in a CS project and may depend on the CS project objective. It is not our goal to start the discussion about CS success therefore we changed “success of” by “volunteers’ participation in”.

L123-125: we explained more carefully why we think that technology may help CS but without being insurance of data quality by itself.

L138-140: In our opinion, we think that we temperate the feeling of the reviewer after reading our sentence (technology is the ultimate solution) after in the text, L142-149, that’s why we do not change the sentence. If the feeling remains can you precise what seems confusing for you?

L142: deleted

L150-151: the sentence was simplified

L186: we added some references leaning our claim but acknowledged that there is still some work to popularize CS in schools

L189: we added “and teachers” instead of replacing “pupils” with “teachers” because we hope that scientists will talk about method and epistemology with both!

L194-206: we agree with reviewer 1 and we moved and shortened this paragraph in the perspectives

L210: “unexpected” was replaced by “unprecedented” as suggested.

L219: “they” referred to “researchers”, pronoun was replaced.

L236: we preferred keeping “resilience” instead of “longevity”, the first term is more integrative as it integrates the fact that the project may resist some obstacles with adaptative abilities. From our point of view, this adaptative aspect is not inherent to “longevity”.

L242-243: indeed, practice does not solve every learning issue. We tried to clarify our claim by adding references and detailing the paragraph as suggested.

Table 1: We defined and move the table earlier in the manuscript, as suggested.

L302: “usually” was unnecessary and then deleted.

L317-321: we complemented the text by detailing the benefits for the volunteers to participate in CS project

L350: the sentence was too extrapolated compared to what we found in the literature. We added “and sometimes, they have to deal with short term grants as funding” to the previous sentences with references and deleted “most of the grants do not include, for instance, the training period of the volunteers”.

L376: “research” was replaced by “researchers”, reviewer 1 was right.

L393-403: we agree with reviewer 1, we moved this part in the appropriate section (4°, perspectives) and shortened it to avoid repetition. We also complemented the guidelines section (3.3) with more appropriate content.

Reviewer #2

Thank you for your submission to review the merit of the citizen science approach to provide benefits to the socio-ecological system. The manuscript provides sufficient background and review of the applications, potential and need for the citizen science approach to aid in collection and analysis of big data (albeit other reviews have already completed this), but the manuscript poorly explains or justifies how the approach ‘gives back’ to society as the authors suggest. Greater evaluation of the socio benefits are needed to actually demonstrate the reciprocal benefits as suggested by the title and abstract. More examples are needed to provide evidence for the external benefits if it is a core message of the manuscript.

Authors: we thank reviewer 2 for its constructive comments. Its remark meets one of the reviewer 1, which strengthens our need to explain the reciprocity with more details. In our opinion, volunteers get empowered after a CS project, especially if they participate in its construction. Then, volunteers are more prone to embed discussion with public institutions, agencies to deliberate and make a decision or explain the consequences of a project related to the environmental issue.

In that sense, we first, clarified section 2 by renaming the subtitles: 2.1 Main benefits for the scientific community and 2.2 Important benefits for volunteers. Section 2.3 was also complemented to precise the benefits at the socio-ecological scale. Briefly, conservation programs and therefore, ecosystem functions and services are maintained but volunteers are more prone to get involved in the democratic institution addressing these conservations issues during and after the CS project (L447-483): “Indeed, ecological restoration and preservation programs have succeeded thanks to the implication of volunteers in different steps of the project and in the decision-making process (Buldrini et al., 2015; Conrad & Hilchey, 2011; Kobori et al., 2016).

Indeed, volunteers involved in CS projects can be seen as vectors of knowledge dissemination by speaking about the project and the results to people around them (Burke et al., 2016). In this way, volunteers become ‘advocates of environment conservation’, such as in the “Ansa e Valli del Mincio” protected wetlands where volunteers have monitored invasive species (Buldrini et al., 2015). Similarly, a successful program was designed in Texas to monitor Arundo donax. The CS program reported an increase in the giant reed area distribution and can be a scientific resource for ecosystem management (Gallo & Waitt, 2011). Another fulfilling aspect of CS projects consists of the more important involvement of volunteers in environmental protection agencies (Owen & Parker, 2018). Even if there are still some challenges with some CS projects regarding the inclusion of results in environmental policies despite the merits of the CS approach (see Section 3 and MacPhail & Colla, 2020), an increasing number of governments recognise the significant role of citizens in nature preservation and rely on CS projects to act and make decisions. Nascimento et al. (2018) recall that the Scottish government helped some CS projects with training and tools to improve their data collection. This action shows the confidence and value of citizen engagement in nature conservation. Governmental acceptance of CS projects in the formation of policy allows reciprocal benefits not only between volunteers and scientists, but it allows the benefits to spread across society thanks to the higher citizen involvement in public policies.

CS projects would help to reconnect our society to nature (Barragan-Jason et al., 2021; Gaston & Soga, 2020) and increase public awareness of the current status of the environment and the threat that humans represent to ecosystem stability (Cerrano et al., 2017; Schläppy et al., 2017). In line with these authors, we want to show that the objectives of CS go far beyond helping research teams or educating the public about the sciences (Bonney et al., 2014; Vignola et al., 2009): In a global change context and a highly complex world, the involvement of citizens and researchers in a more socio-ecological democracy is critical to facing the dangerous global crisis in which we are currently living (Gardner & Wordley, 2019; Hagedorn et al., 2019; Steffen et al., 2015). »

Best regards,

Eunyoung Chae

Review: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R1/PR7

Comments

Comments to Author: Please find my comments on the marked-up PDF.

Recommendation: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R1/PR8

Comments

Comments to Author: Dear Antoine Vernay,

Thank you for submitting the revision, which has been peer reviewed by one of the reviewers for the original manuscript. The reviewer still expressed a concern on the following notion, while the reviewer made an extensive mark-ups on the PDF that you can download from the site. Please inform me and QPB (c/of Rebecca Fitchett) if you run into technical difficulties in downloading the PDF.

Please find the notes from the reviewer below. I agree that defining an audience in the plant biology community will be a focus for handling your manuscript further. This is also part of the points raised by reviewers from the original manuscript.

Although the authors have made substantial changes to the manuscript, my feeling is that the text is still unfocused. The text covers exhaustively most of relevant aspects about citizen science. I believe this is a very important topic that does need to be discussed with the quantitative plant biology community. What I regret however is that the text does not seem to be directly addressed to plant biologists. It is on the contrary very broad. Yet, broad reviews of opportunities and challenges the citizen science represent have already been published. It follows that there is a risk that this paper does not reach its target, unless one consider plant biologists will me more curious about citizen science should they read this forum paper in your journal.

Best regards,

Eunyoung

Decision: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R1/PR9

Comments

No accompanying comment.

Author comment: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R2/PR10

Comments

Dear editors and reviewer,

We thank you for revising our manuscript. We considered all of your comments to improve our manuscript. We now mainly focus on plant biology with almost all examples coming from plant biology and ecology. We hope that the targeted audience of the journal will be more “caught” by our paper. We replied to the comments below and provide two versions of our revised manuscript: a track changes version and one with the accepted corrections to ease your reading. However, to reply to all comments we had to increase the length of our manuscript, although we deleted some paragraphs. We are looking forward to reading your opinion about this new version.

Review: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R2/PR11

Comments

Comments to Author: Dear editors, dear authors,

I am happy to recommend the paper for publication. I know I have been hard to convaincre, this is because the topic is if great intérêt to me. I commend the authors for the huge work they did on the paper since the first version. It is more focused now and well documented. I will be happy to share the final version.

Best wishes

Bastien

Recommendation: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R2/PR12

Comments

Comments to Author: Dear Antoine Vernay and colleagues,

I am happy to deliver the news of acceptance of your manuscript. I would like to express my huge gratitude for your patience and sincere efforts put into revising the manuscript. I enjoyed reading your work as the final version and do appreciate your expertise shared with us via QPB. I do hope that with your article in QPB, we could attract interests in CS further to make a frequent discussion on our journal.

Best regards,

Eunyoung

Decision: Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system — R2/PR13

Comments

No accompanying comment.