Realising the full potential of citizen science monitoring programs

A recurrent complaint of members who attend ESA Annual Meetings is that the large number of concurrent sessions make it impossible to attend all the ones of interest. Symposium Reports from the ESA Annual Meeting is one response to this dilemma. They provide, for those who could not attend, an overview of the symposium presentations and the resulting discussion, as well as a convenient means to identify the presenters. And attendees can review the session! The Editor hopes these Reports are useful, and encourages future Symposium organizers to write Reports for the Bulletin when the presentations are given. For detailed instruction for contributions see: 〈http://esapubs.org/esapubs/journals/Bulletin.htm#Typ〉. Until recently if one were to ask "who is a scientist?" a common response would be, someone who works at a university or a government agency or in a laboratory. In other words, many of us tend to think of scientists as professionals who have been academically trained and conduct research through the auspices of a research institution, agency, nonprofit organization, or academic institution. Historically, though, individuals from outside this circle of professionals have been instrumental in shaping and contributing to science. In fact, some of the most renowned scientists and ecologists could be considered citizen scientists (e.g., Charles Darwin, Harold Mayfield, Alexander Skutch). But the view that the public could actively contribute to science faded greatly over the course of the 20th century (particularly in the United States) to such an extent that we were left with the view that only someone who was professionally trained could be a scientist. Recently, however, we have witnessed an increase in the extent and acceptability of public participation and engagement in science. In particular, over the past decade we have seen a marked increase in such "citizen science" (Fig. 1). Although explanations of citizen science vary slightly, they converge on this definition: the involvement of citizens from the nonscientific community in academic research (Trumbull et al. 2000, Lee et al. 2006). Historical trend of citizen science articles. Data represent peer-reviewed articles as identified in ISI Web of Science using the search term "citizen science" from 1980 through 2008. The number of unique articles (n = 55) published is indicated by "articles," and the number of unique citations (n = 353) is indicated by "citations." Because citizen science has seen a dramatic increase in recent years, both in terms of the number of participants and its spread into new disciplines, a symposium was held at the 2008 Ecological Society of America Annual Meeting to address the role of such activity in ecology. Eleven speakers from around the world converged in Milwaukee, Wisconsin, to share their work in "Citizen Science in Ecology: The Intersection of Research and Education," a symposium organized by Christopher Lepczyk, Owen Boyle, and Timothy Vargo. The goals of the symposium were to explore the following questions: (1) Is citizen science a new discipline, sub-discipline, or tool, relative to ecology? (2) Are data collected by citizen scientists valid, and if so, comparable to data collected by professional ecologists or their assistants? (3) Can citizen science be an effective tool to help bridge the gap between ecological research, communities, and education, both for the public and students? (4) Is citizen science the same as or different from ecological monitoring, or is one a subset of the other? (5) Are citizen scientists actively participating in the scientific process as ecologists, thus increasing their ecological literacy? To address these questions, speakers discussed citizen science both in general conceptual terms and in case-specific contexts from around the world. Rick Bonney of Cornell University opened the symposium with an overview of the history and evolution of citizen science in academic research. He explained that citizen science began as a series of monitoring projects designed to put the findings of hobbyists, such as bird watchers and star gazers, to meaningful scientific use. Following these early monitoring projects were ones designed with educational goals and even some set up as experiments. Eventually citizen science started to become an accepted technique for data collection in several scientific disciplines. Today, new citizen science efforts are involving participants in data analysis as well as data collection, and some are even starting to collect data from online images such as nestcams (readouts from recorders aimed at birds' nests). Following on the heels of the history of citizen science was a series of four case studies describing ecological research and monitoring projects that rely upon volunteers for their success. These case studies were arranged along a continuum from large-scale national projects with thousands of volunteers to regional and local projects. In addition, each case study represented varying degrees of interaction between researchers and volunteers. Leading off the case studies was David Ziolkowski of Patuxent Wildlife Refuge, who discussed how citizens drive the North American Breeding Bird Survey (BBS). Specifically, the BBS protocol conducts annual bird surveys along >4000 routes (Fig. 2) across the United States, Canada, and Mexico, using a highly skilled volunteer workforce. Part of the success of the BBS program has been its relatively straightforward field protocol and standardized design. Moreover, the BBS program has resulted in over 400 bird species being surveyed annually at a cost of less than $900 per species per year. Without citizen scientists, such accomplishments could not be achieved. Similarly, in the United Kingdom, a long-running insect monitoring project has been led by citizen scientists in conjunction with Rothamsted Research, the oldest agricultural research station in the world. Philip Gould highlighted how the Rothamsted Insect Survey has used light traps (Fig. 3) to capture insects across 460 sites in the UK for the past 50 years. This survey takes about five minutes each day to collect insects, which are then sent to Rothamsted Research for sorting and identification of the macro-moth fraction of the catch. To ensure a robust monitoring project, volunteers are reimbursed for any trap maintenance and provided with annual summaries of the moths collected from their trap. The success of the program has been built upon: (1) keeping the monitoring system simple; (2) ensuring that the volunteers are trained; (3) knowing when to discontinue sites; and (4) providing all volunteers with feedback on their work. The value of the insect survey was demonstrated in recent findings that two-thirds of common moth species across the UK have declined over the last 35 years, with 20% declining so fast that they should be considered threatened. As a result, several more species have now been added to Biodiversity Action Plans in the UK. Both the BBS and the Rothamsted Insect Survey demonstrate how large-scale monitoring can be used to denote changes in diversity and abundance over time. Furthermore, they both use protocols to filter data, thereby allowing for robust data set production. Locations of breeding bird survey routes. Figure credit: Curtis Flahter and Mike Knowles. Examples of (A) a light trap station in use, and (B) placement in a back yard. Photo credits: (A) Syd Wright MBE, and (B) Philip Gould. At the regional scale, Susanne Masi, manager of Chicago Botanic Garden's Plants of Concern Program, presented an overview and findings from the garden's rare plant monitoring project. The Chicago Botanic Garden established this program to monitor listed and rare plants in the greater Chicago metropolitan area. Initiated in 2001, the program involves ~250 trained volunteers each year in collecting plant data (Fig. 4), and has now accumulated 8+ years of standardized data on 205 plant species at 245 sites. Aside from simply monitoring rare plants, the program has demonstrated several key findings related to using citizen scientists. First, a two-year volunteer data validation study comparing randomly selected volunteer data to professional data showed a high degree of correlation between the two groups. For example, there was >80% correspondence between the two groups in critical data fields such as population numbers and presence of threats. Second, the results of a Plants of Concern citizen science focus group showed that volunteers participated actively in, and understood critical elements of, the scientific process. Furthermore, participants unanimously experienced an increase of their involvement in stewardship and conservation activities as a result of the program, and reported sharing this scientific understanding and enhanced conservation commitment with the broader public. Volunteers (A) determining plot locations and conducting rare and listed plant inventories (B–D) as part of the Chicago Botanic Garden's Plants of Concern Program. Photo credits: (A) Peter Jacobs, (B) Robin Carlson, (C) Emily Kapler, and (D) Dani Drekich. Capping off the case studies was a presentation by Bill Mueller, who introduced the Milwaukee County Avian Migration Monitoring Partnership (MCAMMP), an avian monitoring study focused on migratory bird stopover ecology in the urban parks of Milwaukee County, Wisconsin. To date the project has utilized the assistance of >140 citizen scientists over six migrations (three years) to help address the major goals of assessing habitat use and quality in both riparian and upland sites, and quantifying habitat use by migratory birds. Citizen science volunteers involvement includes training for transect counts, assistance with bird-banding operations, vegetation sampling and analysis, and recording of data. One major aim of training the citizen scientists is that they will be able to establish a long-term, urban avian monitoring project that can expand in the future. The second main portion of the symposium was devoted to a set of talks on the issues of the philosophy, policy, and technology of citizen science. Rebecca Jordan began this second portion with a discussion of a framework for promoting ecological literacy within the context of citizen science programs. She stressed that program design must balance both the scientific goals, which include ensuring data accuracy, and educational goals. Together these goals promote conceptual knowledge about the system of study, epistemological knowledge about science processes, and behavioral change with respect to environmental and civic action. While there is much evidence to support the promotion of conceptual knowledge, the latter two areas warrant further investigation. Integrating cognitive and environmental action theory will likely prove useful as practitioners seek to broaden program impact. David Bonter of Cornell's Laboratory of Ornithology next discussed the issue of data validation processes for large citizen science databases, such as Project FeederWatch. Currently, Project FeederWatch receives >100,000 checklists from >14,000 citizen scientists annually, yielding over 5,000,000 bird observations of ~500 individual species. Thus, it is critical that such large volumes of data be inspected for any problems; this requirement has led to the development of a quality control and quality assurance protocol. This protocol uses a review system, whereby unusual observations or potential errors are flagged and sent to experts for follow-up with the citizen scientists. Unverified reports remain flagged and are excluded from data analyses and web-based data output. The system also allows researchers to identify volunteers who are in need of support and to focus educational efforts accordingly, ultimately improving data quality and integrity. Moving from data editing to data collecting, Louis Liebenberg, founder of CyberTracker Conservation, presented a talk on how technology can be used to get people back in touch with nature. Specifically, Louis has developed the free software program CyberTracker (available at 〈http://www.cybertracker.org/〉), which enables volunteers of all ages to collect biodiversity data on simple portable devices, such as smartphones and PDAs (Fig. 5). CyberTracker is already in active use for both citizen science projects and environmental education around the world. For instance, in the United States, NatureMapping, BioKIDS, and BioBlitz are using PDAs with CyberTracker software to enable volunteers of all ages to collect biodiversity data. Similarly, in South Africa, the NaturalWorld web site allows participants to share and view bird sightings, and in the Kalahari trackers from local communities are being employed to survey wildlife conservation corridors. Finally, the WhaleForce project involves yachtsmen around the world using CyberTracker to monitor whales. Ultimately, the software allows for easy data collection by citizen scientists and helps to promote people who engage the outdoors by collecting field data. Bushmen in Africa using CyberTracker. Photo credit: Louis Liebenberg. Michelle Prysby next discussed more efficient ways for interested citizens to find a project, and for projects to find interested volunteers. One partnership for scientists and educators interested in reaching trained citizen scientists consists of the Master Naturalist programs. These programs are volunteer training and service programs that involve the public in natural resource education, citizen science, and stewardship. Currently there are >25 Master Naturalist programs in the United States that represent a ready pool of volunteers who have been trained in core citizen science skills, such as recording field observations and using taxonomic keys to identify organisms. These volunteers are well connected to their local environments, and are part of an existing infrastructure that can support their citizen science volunteer activities. (For more information on natural resource education and stewardship programs such as Master Naturalists, Watershed Stewards, and Conservation Stewards, please see the Alliance of Natural Resource Outreach and Service Programs 〈http://www.anrosp.org〉). The final presentation of the morning was by Hague Vaughan, of Canada's Ecological Monitoring and Assessment Network (EMAN), who wove together the themes of the morning's talks. He described how citizen science fosters a desperately needed means to better link ecological monitoring to policy development and decision-making. His argument was that the emphasis on certainty in ecological monitoring leaves decision-makers lacking sentinel and feedback information where timeliness is a key factor. If focused on outcomes, complementary citizen science can be a means of enhancing effectiveness. To illustrate how to integrate citizen science into policy, Vaughan discussed a project that combined citizen data with targeted research and air quality monitoring stations in Hamilton, Ontario, Canada to identify pollution and lichen hot-spots that was used to deliver feedback on municipal and industrial choices (Fig. 6). A map of arboreal lichens in Hamilton, Ontario, Canada, based upon citizen science data. Darker green locations represent greater numbers of lichens, and points represent sampling locations. The symposium concluded with a round table discussion of the morning's talks. Following the symposium, an additional workshop on citizen science was held over the weekend at the Urban Ecology Center of Milwaukee. At this workshop many of the symposium speakers gave an additional talk during the morning portion, with an afternoon of hands-on activities designed to train and educate citizen scientists. Overall, the symposium sought to address five major goals related to citizen science. In reflecting upon these five goals it is clear that there was progress made on all, but not necessarily agreement. For instance, the general view was that citizen science has new elements to offer ecology, but there was no definitive agreement among the speakers that it was a new discipline or subdiscipline. Whether or not this will change remains to be seen; citizen science is still very much an area of new ideas and growth. On the other hand, several speakers presented data from their research illustrating that the quality of data collected by citizen scientists is of the same or better quality than that collected by professional ecologists. Such quality is enhanced further with the aid of both software (e.g., Project FeederWatch and CyberTracker) and expert assistance. Similarly, there was strong evidence that citizen science can be an effective tool to help bridge the gap between ecologists and the public. In terms of the overlap with monitoring, it is clear that they share a number of similarities and will likely continue to do so in the future. However, many of the citizen science projects were much broader than monitoring alone, because they engaged the public in the scientific process or served to enhance ecological literacy. Based upon the talks and concluding discussions, citizen science is an increasing part of ecology, and has great promise for contributing knowledge, improving ecological literacy, training scientists to work with the public, and providing information for policy-makers.

The quality of data produced by citizen science (CS) programs has been called into question by academic scientists, governments, and corporations. Their doubts arise because they perceive CS groups as intruding on the rightful opportunities of standard science and industry organizations, because of a normal skepticism of novel approaches, and because of a lack of understanding of how CS produces data. I propose a three-pronged strategy to overcome these objections and improve trust in CS data. Develop methods for CS programs to advertise their efforts in data quality control and quality assurance (QCQA). As a first step the PPSR core could incorporate a field that would allow programs to point to webpages that document the QAQC practices of each program. It is my experience that many programs think carefully about data quality, but the CS community currently lacks an established protocol to share this information. Define and implement best practices for generating biodiversity data using different methods. Wiggins et al. 2011 published a list of approaches that can be used for QCQA in CS projects but how these approaches should be implemented has not been systematically investigated. Measure and report data quality. If one takes the point of view that citizen science is akin to a new category of scientific instruments, then the ideas of instrument measurement and calibration can be applied CS. Scientists are well aware that any instrument needs to be calibrated before its efficacy can be established. However, because CS is new approach, the specific procedures needed for different kinds of programs are just now being worked out for the first time. Develop methods for CS programs to advertise their efforts in data quality control and quality assurance (QCQA). As a first step the PPSR core could incorporate a field that would allow programs to point to webpages that document the QAQC practices of each program. It is my experience that many programs think carefully about data quality, but the CS community currently lacks an established protocol to share this information. Define and implement best practices for generating biodiversity data using different methods. Wiggins et al. 2011 published a list of approaches that can be used for QCQA in CS projects but how these approaches should be implemented has not been systematically investigated. Measure and report data quality. If one takes the point of view that citizen science is akin to a new category of scientific instruments, then the ideas of instrument measurement and calibration can be applied CS. Scientists are well aware that any instrument needs to be calibrated before its efficacy can be established. However, because CS is new approach, the specific procedures needed for different kinds of programs are just now being worked out for the first time. The strategy outlined above faces some specific challenges. Citizen science biodiversity programs must address two important problems that standard scientific entities encounter when sampling and monitoring biodiversity. The first is correctly identifying species. For citizens this can be a problem because they often do not have the training and background of scientist teams. Likewise, it may be difficult for CS projects to manage updating and maintaining the taxonomies of the species being investigated. A second set of challenges is the diverse kinds of biodiversity data collected by CS programs. For instances, Notes from Nature decodes that labels of museum specimens, Snapshot Serengeti identifies species of large mammals from camera trap photographs, iNaturalist collections images of species and then has a crowdsource identification processs, while eBird collects observations of birds that are immediately filtered with computer algorithms for review by the observer and if, subsequently flagged, reviewed by a local expert. Each of these programs likely requires a different set of best practices and methods to measure data quality.

Research on citizen science programmes has highlighted that they can foster science content and knowledge gain, enhance pro‐environmental behaviour and cultivate civic action among participants. Especially in the case of place‐based citizen science, which requires hands‐on repeated activity in an out‐of‐door setting through a scientific lens, evidence suggests that some of these outcomes may be linked to the unique people–place relationships and interactions afforded by such programmes.Even still, studies that empirically examine the influence of place on citizen science participant and programme outcomes are scant. This is due, in part, to the methodological challenges involved in interrogating complex aspects of a person's sense of place—aspects like place attachment—the emotional bonds between people and place.Here, an adapted three‐dimensional model of place attachment is proposed as a theoretical framework from which place‐based citizen science experiences and outcomes might be empirically examined in depth. The model, which posits personal, social and natural environment dimensions of place attachment is contextualized with research findings from the US‐based Coastal Observation and Seabird Survey Team (COASST) citizen science programme.Data from COASST suggest that participants do exhibit place attachment in all three dimensions of attachment, categorized within seven unique constructs, although questions remain regarding the unique intensity, make‐up (shape) and scale (spatial, social and nature‐science) of individual‐level attachment along the three central dimensions. Critically, more research is needed to investigate whether the unique place attachment ‘profile’ of participants is a function of personal, social or programmatic variables pre‐ and post‐programme participation.To encourage further scholarship on potential links between the experiences, exposures and programme components of place‐based citizen science and the place attachment profiles of participants, this paper includes a brief review of the research opportunities presented by the adapted three‐dimensional place attachment model discussed.Advancing this line of inquiry is an important component of broader efforts to understand how sense of place is altered via place‐based citizen science and whether or not that is linked to specific programme outputs or participant outcomes in science knowledge, ecological understanding and civic engagement.A freePlain Language Summarycan be found within the Supporting Information of this article.

Purpose The purpose of this paper is to provide a conceptual framework for using citizen science – defined as a data collection method through which non-professionals engage in contributing to authentic scientific inquiry – within the expedition cruise industry to contribute significantly to the collection of environmental data from hard-to-access Arctic areas. Design/methodology/approach The authors review trends in Arctic expedition cruise tourism and current needs in Arctic research and monitoring, and clarify where the expedition cruise tourism industry could have the most impact by providing data to the scientific community. The authors also compare the regulatory context in the Antarctic to that in the Arctic and discuss how these differences could affect the widespread use of citizen science. At last, the authors describe some general principles for designing citizen science programs to be successful on board, and highlight several existing programs that are being recognized for their contributions to a greater scientific understanding of the Arctic. Findings The authors find that citizen science data from the expedition cruise industry are underutilized as a tool for monitoring Arctic change. Numerous examples illustrate how citizen science programs on-board expedition ships can successfully collect robust scientific data and contribute to enhancing the knowledge and stewardship capacity of cruise passengers. Inclusion of citizen science data from the expedition cruise industry should be considered a critical part of international Arctic observing networks and systems. Social implications Active participation in Arctic citizen science by tourists on expedition cruise ships has many potential benefits beyond the collection of high quality data, from increasing passengers’ knowledge and understanding of the Arctic while on board, to affecting their attitudes and behaviors after they return home. Originality/value The potential for tourism to contribute to Arctic observing systems has been discussed previously in the scientific literature; the authors narrow the focus to citizen science programs in the expedition cruise industry, and provide concrete examples, in the hope that this will streamline acceptance and implementation of these ideas by researchers and tourism practitioners.

Simple SummaryCitizen science offers an excellent opportunity to engage the public in scientific data collection, educational opportunities, and applied management. However, the practicalities of developing a citizen science program, from generating ideas to developing tools, implementing programming, and evaluating outcomes, are complex and challenging. To address challenges and provide a foundation for practitioners, scientists, and the public, the Government of Alberta developed a set of citizen science principles. Here, we use these principles as an evaluative framework to assess the outcomes of the GrizzTracker program, which was developed to help inform provincial species-at-risk recovery efforts. While the program experienced some successes, we identified challenges, including skepticism from the scientific community about the utility of citizen science and a lack of program leadership, staff capacity, and funding needs for long-term implementation. Reflecting on the principles, we provide policy recommendations that future citizen science programs can consider.Citizen science offers an excellent opportunity to engage the public in scientific data collection, educational opportunities, and applied management. However, the practicalities of developing and implementing citizen science programming are often more complex than considered. Some challenges to effective citizen science include scientists’ skepticism about the ability of public participants to rigorously collect quality data; a lack of clarity on or confidence in the utility of data; scientists’ hesitancy in engaging the public in projects; limited financial commitments; and challenges associated with the temporal and geographic scales of projects. To address these challenges, and provide a foundation upon which practitioners, scientists, and the public can credibly engage in citizen science, the Government of Alberta developed a set of citizen science principles. These principles offer a framework for planning, designing, implementing, and evaluating citizen science projects that extend beyond Alberta. Here, we present a case study using these principles to evaluate GrizzTracker, a citizen science program developed to help inform provincial species-at-risk recovery efforts. While we found that GrizzTracker applied each of the six principles in some way, including successful public engagement, strengthened relationships, and raising public awareness about northwest Alberta’s grizzly bears, we also identified a number of challenges. These included ongoing skepticism from the traditional scientific community about the utility of citizen science and governance challenges related to program leadership, staff capacity, and funding. By using the principles as a guideline, we provide policy recommendations for future citizen science efforts, including considerations for program design, implementation, and evaluation.

Citizen science comes of age

The art and science of multi-scale citizen science support

14 INVITED Early phase drug development in the Children's Oncology Group

Building a More Scientifically Informed Community in the Delaware River Basin David W. Bressler, John K. Jackson, Matthew J. Ehrhart, and David B. Arscott Citizen Science (CS) programs inherently broaden societal science literacy by providing experiential scientific learning opportunities to a diverse cross-section of the public. Here we describe an expanding CS program that supports more than 50 nonprofit organizations in the Delaware River Basin (DRB). The motivation for this effort has been generated by investment from the William Penn Foundation to create the Delaware River Watershed Initiative (DRWI), a multi-year effort to support organizations working to protect and restore stream health in the DRB. In direct support of this initiative, the Stroud Water Research Center is facilitating CS efforts to improve the capacity of watershed groups to conduct scientific investigations associated with DRWI watershed protection and restoration projects, as well as to build general knowledge on the ecology of their watersheds and the broader DRB. This project benefits from cooperative efforts among a wide variety of citizen scientists, as well as professional scientists and environmental planners. Participants in these CS activities have diverse backgrounds ranging from volunteers with minimal or no formal training in science to retired Ph.D.-level scientists. There are full-time and part-time environmental professionals who volunteer in their spare time, college and high school students, teachers and professors, and many other individuals from a wide variety of science and non-science backgrounds. Some volunteers work multiple days per week carrying out or assisting the goals of the DRWI, while others put in a few hours per month—all helping to build valuable datasets on water quality and related outcomes of restoration and land protection. Through their engagement, these citizen scientists gain personal knowledge and experience that can inform the greater community and influence local environmental policy. Citizen Science depends on the experience and expertise of the individuals involved. In our case, professional scientists, environmental planners, and even environmental regulators help to frame monitoring approaches and guide groups and individuals on collecting samples, doing field measurements, analyzing data, and researching policy. Our vision of success is a collaborative environment that supports watershed groups and their citizen scientists in asking and answering their own ecological questions about local streams and rivers, and in translating this knowledge and experience into regional policies and practices that result in healthier streams and, subsequently, cleaner drinking water for future generations. Volunteers contributing to this initiative are not exclusively collecting data to feed into a single large study; nonetheless, combined across tributaries, this effort is also building an increasingly comprehensive and publicly accessible dataset for the whole DRB. Citizen Science enables certain things that conventional science does not. We are supporting CS programs to not only generate robust data sets but also to build a scientifically informed community in the DRB. Citizen Science is no different than ordinary science in that it follows the same [End Page 24] processes of developing and testing hypotheses (i.e., asking questions, making predictions, and coming up with ways to answer the questions), Quality Assurance (QA) and Quality Control (QC) (i.e., making plans to ensure data accuracy [QA] and then confirming data accuracy [QC] via specific data replication protocols), and summarizing and communicating results (i.e., preparing data summaries, reports, etc.). Citizen Science is different from ordinary science, however, in that it involves a far greater diversity of individuals with wide-ranging backgrounds and skills. From certain professional science perspectives, this variation among individuals may be considered a hindrance to the science. However, with improvements in technology and with people more often changing careers and increasing volunteer involvement during these transitions, in spare time, and in retirement, there continue to be more opportunities to build large viable datasets with new and unconventional CS methods. Perhaps most importantly, as societal and cultural pursuits are increasingly directed toward improving the environmental awareness and science-knowledge of the general population, CS not only presents opportunities to build useful datasets but also to make strides in building a scientifically informed community, which is rarely a goal in conventional science endeavors. Ideally, this building of science literacy then leads to communities making better environmental decisions...

Data quality (DQ) is a major concern in citizen science (CS) programs and is often raised as an issue among critics of the CS approach. We examined CS programs and reviewed the kinds of data they produce to inform CS communities of strategies of DQ control. From our review of the literature and our experiences with CS, we identified seven primary types of data contributions. Citizens can carry instrument packages, invent or modify algorithms, sort and classify physical objects, sort and classify digital objects, collect physical objects, collect digital objects, and report observations. We found that data types were not constrained by subject domains, a CS program may use multiple types, and DQ requirements and evaluation strategies vary according to the data types. These types are useful for identifying structural similarities among programs across subject domains. We conclude that blanket criticism of the CS data quality is no longer appropriate. In addition to the details of specific programs and variability among individuals, discussions can fruitfully focus on the data types in a program and the specific methods being used for DQ control as dictated or appropriate for the type. Programs can reduce doubts about their DQ by becoming more explicit in communicating their data management practices.

Citizen science facilitates cost‐effective ecological data collection at much larger scales than would otherwise be feasible. This is particularly useful for the study of highly migratory species with broad distributions, such as billfishes. Participants in citizen science benefit from an increase in scientific literacy, a sense of satisfaction and enhanced understanding. However, there are common challenges involved in citizen science projects, including the recruitment and long‐term retention of participants. Applying knowledge about participant motivations and concerns is needed to overcome these barriers. We conducted an anonymous online survey of 153 game fishers from across Australia, who were largely recruited through game fishing clubs. The survey investigated their perspectives on participating in citizen science on billfish, including their motivations and concerns. Overall, those surveyed were highly motivated to participate in billfish citizen science programmes and reported few barriers to their engagement in research. Alongside wanting to contribute to billfish research and management, game fishers were motivated to participate to counteractive potential negative perceptions of the sport. However, approximately one third of respondents had not participated in research. Therefore, opportunities for further recruitment exist as potential participants almost certainly exceed current participants. Impediments to participation included a lack of communication about opportunities and outcomes of citizen science research. The survey highlighted a need to strengthen citizen science programmes to ensure participant retention and recruitment through targeted engagement and collaboration across organisations, which includes harnessing technology. Improved communication about the purpose and outcomes of research is key. We anticipate that our findings and recommendations are applicable to broader citizen science programmes, particularly those involving recreational fishers or a specialised pool of highly motivated participants. Great opportunity exists for researchers, fisheries managers and fishing organisations to work together to expand citizen science programmes that strategically improve our knowledge of the biology and stocks of billfish and other recreationally important fish species. Read the free Plain Language Summary for this article on the Journal blog.

The number of collaborative initiatives between scientists and volunteers (i.e., citizen science) is increasing across many research fields. The promise of societal transformation together with scientific breakthroughs contributes to the current popularity of citizen science (CS) in the policy domain. We examined the transformative capacity of citizen science in particular learning through environmental CS as conservation tool. We reviewed the CS and social-learning literature and examined 14 conservation projects across Europe that involved collaborative CS. We also developed a template that can be used to explore learning arrangements (i.e., learning events and materials) in CS projects and to explain how the desired outcomes can be achieved through CS learning. We found that recent studies aiming to define CS for analytical purposes often fail to improve the conceptual clarity of CS; CS programs may have transformative potential, especially for the development of individual skills, but such transformation is not necessarily occurring at the organizational and institutional levels; empirical evidence on simple learning outcomes, but the assertion of transformative effects of CS learning is often based on assumptions rather than empirical observation; and it is unanimous that learning in CS is considered important, but in practice it often goes unreported or unevaluated. In conclusion, we point to the need for reliable and transparent measurement of transformative effects for democratization of knowledge production.

Citizen science programs provide opportunities for students to help professional scientists while fostering science achievement and motivation. Instruments which measure the effects of this type of programs on student motivational beliefs are limited. The purpose of this study was to describe the process of examining the reliability and validity of The Citizen Science Self-Efficacy Scale (CSSES) designed to measure the effectiveness of citizen science programs on student self-efficacy for scientific observation skills. Fifteen (n =15) field experts and 248 (n = 248) eighth grade students participated in three studies. The results suggest that the psychometric properties of this scale are sufficient. Implications for the development and utility of self-efficacy scales in a variety of citizen science contexts are discussed. The aim of the present study is twofold: (a) to establish the psychometric properties of a scale developed to measure student self-efficacy beliefs for scientific observations in citizen science programs and (b) to describe the process in the validation of a self-efficacy scale to support researchers who want to create their own scales for similar citizen science programs. Three studies were conducted to develop the Citizen Science Scale (CSSES) and evaluate its psychometric properties. The purpose of the CSSES was to develop a measure suitable for analysis within a social cognitive career framework and informal natural science contexts. The findings in the present study found that the measure had an acceptable unitary factorial structure and high internal reliability of .89 for the CSSES. The purpose of the Citizen Science Self-Efficacy Scale (CSSES) is to assess individual’s beliefs about their capabilities for scientific observational skills. This scale is applicable to measuring individual’s self-efficacy in outdoor learning contexts (e.g., horseshoe crab citizen science context). Given that self-efficacy is a strong predictor of academic achievement and motivation, self-efficacy scales like the CSSES may provide a way for stakeholders involved in outdoor education to measure student gains and to substantiate program effectiveness. From a methods standpoint, the contribution of this work is to serve as a guide of how to develop a self-efficacy scale.

How do marine and coastal citizen science experiences foster environmental engagement?

Most citizen science research inherently separates the observer (citizen science participant) from the observation (e.g. data point), placing artificial boundaries around what matters and how it comes to matter. We apply three elements of the philosophical framework of agential realism to reveal a more complex picture of how data arise within citizen science programmes, and its meaning to both the practice of science and the citizen science participant: ‘intra‐action’ (all entities have agency and are entangled with one another); ‘material becoming’ (what comes to matter); and ‘responsibility’ (accountability for what comes to matter and what is excluded from mattering). We draw on a case study of FrogID—an Australia‐wide citizen science program focused on calling frogs, with over 42,000 participants and over 1 million frog records. We conducted semi‐structured interviews with 30 FrogID users, completing two rounds of thematic and relational coding. Our findings reveal that as a consequence of their recording behaviours, FrogID participants become increasingly entangled with the nocturnal environment, with sound and with their own self. Expanding and reciprocal relationships and experiences shape the nature and frequency of their recordings. Second, meaning influences what comes to matter (i.e. what is recorded and submitted) for FrogID participants. We reveal meaning related to feedback (recognition and thus reciprocity), others (social networks and participation with family and friends) and the self (physical and mental well‐being and identity formation/becoming). These different forms of meaning influenced engagement with app use. Third, participants communicated responsibilities related to their involvement in citizen science, including responsibilities to create knowledge (e.g. longitudinal data collection), to conserve (e.g. actively conserving frog, formally committing areas to conservation) and to educate self and others (e.g. skills and competencies required for environmental action). Synthesis and applications: By recognizing a more comprehensive set of intra‐actions, beyond the observer and the observation, agential realism can reveal when, why and how citizen science observations are made; what observations come to matter and why; and how people can create a more just world. Agential realism can shape how citizen science participation, retention and biodiversity data generation are founded. We propose three opportunities for citizen science programs based on these findings. Read the free Plain Language Summary for this article on the Journal blog.