One of the facts about academic funding and outputs (that is, academic publications), is that there isn’t a simple relationship between the amount of funding and the number, size, or quality of outputs. One of the things that I have noticed over the years is that a fairly limited amount (about £4000-£10,000) are disproportionately effective. I guess that the reason for it is that on the one hand, it allow a specific period of dedicated time, but the short period focuses the mind on a specific task.
A case in point is the funding through the UCL Grand Challenges Small Grants programme. In 2014, together with Dr Elizabeth Boakes and Gianfranco Gliozzo, I secured funding for a short project on ‘Using citizen science data to assess the impact of biodiversity on human wellbeing‘. We have enlisted other people to work with us, and this has led the analysis of citizen science contributions across London. On the basis of this work, and in collaboration with researchers in ExCiteS (Gianfranco Gliozzo, Valentine Seymour), GiGL (Chloe Smith), Biological Records Centre (David Roy), and the Open University (Martin C. Harvey), we have developed a paper that is now published in Scientific Reports. The paper experienced a rejection and subsequent improvements along the way, which have made its analysis more robust and clear. Lizzie’s perseverance with the peer reviews challenges was critical in getting the paper published.
At the core of the paper is examination of the information from citizen science projects, and using this information to understand the behaviour of the volunteers, and what we can learn from this about biodiversity citizen science projects in general.
The paper full citation is: Boakes, E., Gliozzo, G., Seymour, V., Harvey, M.C., Roy, D.B., Smith, C., and Haklay, M., 2016, Patterns of contribution to citizen science biodiversity projects increase understanding of volunteers’ recording behaviour, Scientific Reports
The abstract of the paper reads:
Citizen science has become a well-established method of biological recording but the opportunistic nature of biodiversity data gathered in this way means that they will likely contain taxonomic, spatial and temporal biases. Although many of these biases can be accounted for within statistical models, they are usually seen in a negative light since they add uncertainty to biodiversity estimates. However, they also give valuable information regarding volunteers’ recording behaviour, thus providing a way to enhance the fit between volunteers’ interests and the needs of scientific projects. Using Greater London as a case-study we examined the composition of three citizen science datasets – Greenspace Information for Greater London (GiGL), iSpot and iRecord – with respect to recorder contribution and spatial and taxonomic biases. We found each dataset to have its own taxonomic and spatial signature suggesting that volunteers’ personal motivations for recording may attract them towards particular schemes although there were also patterns common to all three recording systems. We found most volunteers contribute only a few records and are active for one day only. Our analyses indicate that species’ abundance and ease of identification of birds and flowering plants are positively associated with number of records, as was plant height. We found clear hotspots of recording activity, blue space (waterbodies) being associated with birding hotspots. We note that biases are accrued as part of the recording process (e.g. species’ detectability, media coverage) as well as from volunteer preferences.