give me the - Summary of evidence and key findings from studies focusing on [specific subtopic].
- Common themes or trends identified within the literature.
- Recommendations or implications based on the available evidence.
OF "Citizen science and Co-design are considered by many to be natural corollaries. There is a growing body of literature and projects that deploy the two in tandem. It proposes that ‘proper’ citizen science must include some element of co-design to be legitimate (Feick & Robertson, 2021). In this view, co-design is what elevates a project from volunteer science to a true citizen science project. Co-design is defined as the process of developing projects in partnership with the intended users/operators of the project (Burkett, 2016). 
For example, one of the ‘pillars of citizen science’ outlined by Feick & Robertson (2021) is the:
 “Continuous interaction between experts and volunteers for the sharing of results and the implementation of any corrective measures in scientific co-production processes”. 
This ‘continuous interaction’ is a hallmark of the deep, substantiative collaboration characteristic of co-designed projects, but not necessarily of all citizen science projects.
This boundary between citizen science and co-design is ‘fuzzy’, and certain projects penned as citizen science would—due to their lack of co-design—be designated ‘volunteer observatories’ by other authors. An example is the citizen science flood monitors discussed by Ferri et al (2020), which was a system of citizen observatories using pre-built researcher apps to report river level data. Though effective in reducing flood damage, the lack of design collaboration with volunteers excludes it from the citizen science criteria of authors like Feick & Robertson (2021). According to Robinson et al (2018), citizen scientists here were ‘contributors’ rather than ‘collaborators’ or ‘project leaders’, due to a lack of co-creation. 
The following definitions can be used to assess the nature of citizen science involvement in projects (Feick & Robertson, 2021): 
1.	Contributary: projects designed by expert scientists, where volunteered contribution is limited to data collection.
2.	Collaborative: volunteers can contribute to refine research design and activities such as data collection and analysis, and dissemination of outcomes. In a socio-hierarchical perspective, stakeholders can replace or work alongside expert scientists in project definition.
Ten Principles of Citizen Science
(Robinson L.D., Cawthray, J.L., West, S.E., Bonn, A., & Ansine, J., 2018)
Active Involvement	Citizen science projects actively involve citizens in scientific endeavour that generates new knowledge or understanding. Citizens may act as contributors, collaborators or as project leaders and have a meaningful role in the project.
Scientific Outcomes	Citizen science projects have a genuine science outcome. For example, answering a research question or informing conservation action, management decisions or environmental policy.
Mutual Benefit	Both the professional scientists and the citizen scientists benefit from taking part. Benefits may include the publication of research outputs, learning opportunities, personal enjoyment, social benefits, satisfaction through contributing to scientific evidence, for example, to address local, national and international issues, and through that, the potential to influence policy.
Multi-stage Citizen Participation	Citizen scientists may, if they wish, participate in multiple stages of the scientific process. This may include developing the research question, designing the method, gathering and analysing data, and communicating the results.
Feedback Provision	Citizen scientists receive feedback from the project. For example, how their data are being used and what the research, policy or societal outcomes are.
Treatment as a Research Methodology	Citizen science is considered a research approach like any other, with limitations and biases that should be considered and controlled for. However unlike traditional research approaches, citizen science provides opportunity for greater public engagement and democratisation of science.
Open Access Data/Meta-data	Citizen science project data and metadata are made publicly available and where possible, results are published in an open-access format. Data sharing may occur during or after the project, unless there are security or privacy concerns that prevent this.
Citizen Acknowledgment	Citizen scientists are acknowledged in project results and publications.
Tailored Evaluation	Citizen science programmes are evaluated for their scientific output, data quality, participant experience and wider societal or policy impact
Unique Legal/Ethical Framework	The leaders of citizen science projects take into consideration legal and ethical issues surrounding copyright, intellectual property, data-sharing agreements, confidentiality, attribution and the environmental impact of any activities.
3.	Co-created: collaboration of scientists and volunteers from the co-design and co-conceptualization phase, where participants are actively involved in most or all stage of the scientific process Co-created citizen science can assume transformative functions when a local community leads a project. Both work together on ALL aspects of the research
The ‘Ten Principles of Citizen Science’ by Robinson et al (2018) consider all of these to be legitimate modes of engagement. However, Feick and Robertson (2021) suggest ‘collaborative’ and co-created are more legitimacy as citizen science. 
Neset et al (2021) see citizen science as a way to democratize science, introducing wider public decision making into research. Rather than following the traditional, top-down approach of academic research, it is a more horizontal way of decision making. This horizontal methodology of citizen science, where participants have more say in the way their work is carried out and used, is sometimes taken to be synonymous with co-design (Neset et al, 2021). Van den Driesche et al (2020) suggest that without constant input from participants (continuous co-design) a project cannot be legitimately classified as citizen science.
Though there is good evidence to support the view that collaboration (at all stages of the project) does improve citizen science projects, there is no inherent connection between the two (Hecker et al, 2018). One study found only 4% of citizen science projects (based around hydrological modeling and ecosystem service management) fulfilled the criteria for co-created project (Njue et al, 2019). Effective citizen science can be relatively hierarchical, and so implementing a successful project does not necessarily mean it was a co-designed project. Van Noordwijk et al (2021) outlines 4 types of citizen science project, but how much citizens participate is not a major factor in any of the types:
1.	Place based community projects: focus on improving environment in specific area and appeals to ‘their’ home.
2.	Captive learning projects: the purpose is to increase knowledge, but they have a very specific focus and participants have little agency.
3.	Interest group projects: Many citizen science projects primarily attract participants who are already skilled or at least interested in a specific research topic, I.e., birdwatchers.
4.	Mass participation projects: If the project task is simple, has clear societal relevance, requires limited time commitment from participants, and is widely advertised, then citizen science projects can achieve mass participation.

There is robust literature to suggest that co-design does markedly improve citizen science outcomes, as well as lead to emergent positive outcomes (Taylor et al, 2023). These emergent outcomes, such as building local empowerment and different relationships to land and community (both for stakeholders and researchers) are sometimes considered among the main goals of citizen science projects (Taylor et al, 2021). 
In the case of Integrated Catchment Management, citizen science and co-design methodologies are particularly well suited. This is because environmental management problems are inherently polycentric (in need of multiple, independent centers of decision making):
“Governance of natural resources in general, and water in particular, is inherently multi-scalar and poly-centric (Ostrom and Cox, 2010). The citizen science concept clearly shows the deficiencies of the technocratic model of knowledge generation”. (Buytaert et al, 2014)
The inclusion of stakeholders in process building allows the complexity of collectively managed resources to be reflected within project design. Likewise, where environments are split between many private plots, co-designed can provide access. By making the process participatory, and thus avoiding feelings of outside intrusion, land managers are more likely to engage with a project. An Australian citizen science initiative, WildTracker, demonstrated the importance of deep, meaningful co-design (Taylor et al, 2023):
“Presented as a broad project for discovering something about their Land, there was a much higher level of participation in and enthusiasm for the research and ongoing conservation program than the research team had anticipated and that had occurred previously when non-participatory approaches have been tried.” 
Furthermore, the level of access to the location-based data is higher when stakeholders are included in the design process. Their knowledge of their land, and its attributes can be included through co-design methods. This improves not just the quantity of data gathered, but also its quality. 
Co-designed citizen science in environmental projects aligns more closely with how participants view their relationship with a particular place. Participants in the WildTracker project had non-hierarchical, “flat web” ecosystem concept of the projects area of study. As opposed to the more hierarchical, stratified models of researchers. This aligns with the distributed decision making of co-design, where all members (researchers and citizens) have equal though differing roles in the project. Taylor et al (2023) point out that this does not imply a more accurate understanding of ecological systems. Other studies demonstrate a greater affinity to ecological solutions/perspectives from stakeholders engaged in co-design, than those who are not. One example is found in a study of the ‘Managing borderlands: adaptive decision making amongst specialists and non-specialists’ project (Cinderby, 2016). This studied co-designed local flood management techniques. Stakeholder participants emphasised ‘soft’ solutions to flood management, as opposed to using only “conventional (hard-engineered) measures” favoured by local authorities. They proposed:
“Novel, adaptive, flood-management proposals that had not previously been identified through official processes. These adaptive measures included riverine and wetland habitat restoration, engineering log jams to slow river flow, and building leaky ponds to store water in peak water flow events.” 
Participants favoured what could be called nature-based solutions. This can be contrasted with another Scottish study of river catchment management that, whilst using citizen data, did not utilise co-design methods. This study by Barnes et al (2013) emphasised that farmers had little concern for ecological solutions, often conceiving it as “an insignificant problem”. They rejected nature-based solutions as impositions, either by local authorities or outside “green groups”. In the Cinderby (2016) study, the co-designed solutions were more ecosystem oriented than the local authorities, but in the Barnes et al (2016) study, farmers rejected technocratically applied environmental regulations as going too far. This suggests co-designed decision processes have a tendency towards more ecological outcomes.
The literature suggests a relationship between co-design and more ecological outcomes in citizen science projects. 
Other work (Keith et al, 2022) also suggests co-design offers advantages to ecosystem-based citizen science. The literature shows a stronger positive relationship between co-design and citizen science in general. when combined, they lead to unexpected positive outcomes alongside general improvements in data quality. Conversely, citizen science without co-design appears less successful. 
In a paper by Rollason et al (2018), they found a sharp contrast between a traditional, top-down approach to citizen science (run by the Rivers Trust) and “horizontally integrated management” style employed by the council (see fig 1). This latter approach included more co-design, relying less on top-down decision making. The Rivers Trust gave their volunteers very little say in the overall project, only the ability to participate. The council’s approach engaged in a variety of consultations and workshops. This included some deliberative functions and developed long term relationships with stakeholders. This latter approach was far more successful and avoided the negative characterisation as a “helicopter project” that the Rivers Trust project received. The Rivers Trust project had trouble retaining participants, and relied on a small, unrepresentative cohort that failed to spread the project more broadly. These failings are the most common reasons for citizen science projects to fail, according to an analysis by Sauermann et al (2020): 
“Although systematic evaluations of citizen science co-design approaches are lacking, we conjecture that co-design…may also help address the first challenge discussed earlier: Broadening participation and increasing the motivation of citizens to contribute their effort and knowledge resources.”
Co-design within a citizen science project presents its own issues. By introducing a level of collective decision making, of “democratising” science, researchers may feel they are “[relinquishing] control to non-professionals” (Loorbach et al., 2017) (Eden, 1996). Sauermann et al (2020) suggest that the challenges of co-design can cut both ways, as whilst scientists must share control, citizen participants must accept additional deliberative responsibilities—usually requiring the investment of more time and effort. The more thoroughly co-designed, the more chance there is for the researcher goals to shift overtime, which can frustrate narrow, goal oriented projects. Though whether this is an issue depends on the project and the researchers. As mentioned earlier, some place the emergent outcomes of community building at least as high as the production of data (Taylor et al, 2023) (Buytaert et al, 2019) (Van Noordwijk et al, 2021). Indeed, Druschke & Seltze (2012) considered a citizen science project they conducted—which was successful in its scientific goals—as a failure because the citizen scientists involved:
“Did not achieve the knowledge, attitudinal, and behavioural goals we had hoped for. And we realize now that they did not achieve these goals because we failed to effectively engage our citizen scientists and bring them into the collaborative research effort.” 
This demonstrates a common feature of co-designed citizen science projects, in that their success (or lack of) is determined partially by normative values. Suggesting that what makes a citizen science project—especially a co-designed one—successful cannot be determined by its data output alone. 
"