With an abundance of well-established programmes across North America, Canada and Europe to reflect on, what science and people-related priorities can be brought together to guide the development of new, long-term volunteer monitoring programmes?
Here are some thoughts summarised from chapter I wrote for Lake Restoration: A New Zealand Perspective, to be published by Springer late 2015/2016. Rather than sprinkle individual references throughout, I’ve added a list of sources used at the end of the blog.
1. Defined objectives and outcomes
Common citizen science objectives are to promote education and public engagement; contribute to scientific research on ecosystems and phenomena; enhance community capacity for decision making, provide data for environmental management, or to support policy development. Defining objectives and expected outcomes from the outset has major implications for who will participate and how; the nature of programme activities, research design, scale and location.
2. Fit-for-purpose programme structure
Citizen science approaches are usually summarised as consultative/scientist-led, co-created and community-led, each having evolved in response to differing information needs, funding availability, participant type etc. Scientist-led projects typically work best for large scale, long-term projects where data management is complex (like Florida Lakewatch). In contrast, locally-focussed programmes (like the LSPA) may rely on community volunteers to develop and run the programme. A mix of approaches may also used – a core group of volunteers become involved with project planning and data analysis, while the role of other volunteers is to collect data.
3. Robust monitoring design and appropriate protocols
Long-term data sets can provide unique insights into ecosystem function, but only when programmes are guided by research questions and not by ‘datakleptomania’ (just measuring without real purpose). User-friendly protocols appropriate to the research question along with quality assurance and quality control are integral to good monitoring programme design. QA/QC add measurable components for evaluation e.g., pilot studies where the quality of data generated by volunteers is tested to determine the suitability for the programme purpose and comparability with professionally collected data.
4. Ethical data use and ownership
Who owns and has access to the data has wide implications for sharing the research as well as the how the research outputs are used. Intellectual property law comes to sharp focus when considering the nature of volunteer participation and agreements (contractual or otherwise), made between volunteers and programme coordinators. Copyright may apply to volunteers’ photographs, videos and text-based contributions, however, programme designers that seek intellectual, innovative or creative input from participants, such as app design or improved methods, may need to address both copyright and patent considerations.
5. Adequate resourcing
With an abundance of volunteer monitoring programmes to learn from, the first step is identifying successful models of funding from other projects (including those from outside the environmental sector), most likely to suit the objectives and structure of the new programme. Sourcing long-term funding for monitoring will remain a challenge until the importance of long term data collection is acknowledged along with the role that communities can play in this. However, over-emphasising the cost-savings of volunteer participation risks other shortfalls: set-up costs, for example, can be substantial with the monitoring equipment required, ongoing volunteer support and training as well as infrastructure development (e.g., Smartphone apps, website and database design).
6. Engaged participants
Citizen science would not exist were it not for the willingness of volunteers to donate their time, knowledge, skills and, at times, personal resources. Although an ethic of inclusivity underpins much of citizen science discourse, educated, middle-class, white folk continue to be overrepresented. Encouraging wider participation requires a purposeful approach and the OPAL programme is a great example. Meaningful engagement relies on understanding volunteers’ motivations for participating in the monitoring programme (e.g., widening social networks; contributing to science or society; educational), and therefore understanding their expectations (e.g., social engagement; purposeful collection of data; quality communication). Yet, few professionals attempting to ‘engage in engagement’ are clear about specific programme objectives and outcomes relating to engagement, and whether the means used to facilitate engagement will achieve these ends.
7. Effective communication
The ability to communicate effectively, as well as promote the programme is becoming increasingly important as communication channels diversify. In the development phase of the programme, comms are typically targeted at establishing the programme team and at volunteer recruitment. During programme implementation, regular comms are needed that acknowledge volunteers’ input, staff and partner roles as well as funders’ support as this helps build a sense of community and shared purpose. Final comms may include informal updates or points of interest for the wider community or reports destined for volunteers, programme staff, resource managers, researchers and other stakeholders. Both OPAL and MLVMP have produced informative and accessible examples.
8. Ongoing evaluation
Although most volunteer monitoring programmes are conceptualised as a series of steps with feedback loops at specific points in reality, the process is repetitious and non-linear. This reinforces the dynamic and multi-faceted nature of volunteer monitoring programmes, which heightens the need for a considered approach to evaluation that captures the range of social educational, scientific or environmental management-related outcomes sought.
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