Oli Wilson is our new ecological modeller here at the NPMS. This exiting new role for the scheme will involve analysing the huge amount of data that is collected by our fantastically dedicated volunteers. Oli has great plans for exploring what the data can tell us. Read below to find out more about him and what he will be bringing to the scheme!
Can you tell us about yourself – what were you doing before you came to the NPMS?
I kind of struggle to define what kind of scientist I am – I think I’m probably a biogeographer because I’m interested in environmental change through space and time, but I’ve also got an MSc in ethnobotany (the study of the relationships between plants and people) and a degree in biological sciences. I’m just coming to the end of a PhD at the University of Reading which is a mix between ecology, palaeoecology and archaeology. I’ve been studying the links between plants, people and climate change in the past, present and future, focusing on the unique Araucaria forests of southern Brazil. And going back a bit further, I spent a few years as a school science teacher and a few more working in botanical gardens.
What was the main thing that attracted you to the role do you think?
The relationship between plants and climate change interests me a lot, and this role offers the opportunity to look at it in detail – particularly focusing on ecosystems and species that are (literally) closer to home than the ones I’ve studied so far. Researching UK plants is proving to be quite a step change though – the amount of data that’s available is mind-blowing! We’re so fortunate in this country to have genuinely world-leading data on our biodiversity – largely thanks to initiatives like NPMS – and the difference from what’s available for tropical diversity is really stark. These rich datasets make it possible to use much more complex research methods and advanced modelling techniques than I’ve employed previously, so I’m looking forward to getting to grips with them.
Are there any parts of the role that you are most looking forward to? Any specific areas of analysis for example?
Well the opportunity to develop new analytical techniques on fantastic data is certainly one, but I’m also looking forward to exploring how the research can connect with policy and the public. Working with the NPMS, those connections are already stronger than in other projects I’ve done, with national nature conservation organisations involved in running it and hundreds of members of the public actually conducting it. I think it’s really important to communicate research beyond just the research community – it’s something I’m really passionate about – and I’m looking forward to sharing our findings with these audiences, to showcase the importance of the UK’s plants and surveys like NPMS.
Why do you think it is so important to have someone investigating the dataset in real depth?
The NPMS is a really valuable dataset, brought to life by hundreds of people investing many thousands of hours of work over several years, and holding a potential goldmine of information on the UK’s plants in the early 21st Century. Research like this is a way of honouring that work and reflecting its importance – and it’s also a way of bringing to the foreground the plants and landscapes that everyone involved is so passionate about. I hope the research I do benefits all those parties – plants as well as people – but it’s also important to note that there’s so much data here I’ll only really be able to scratch the surface. I hope and expect that more researchers will use the data over the years to come, possibly even with methods that don’t yet exist!
One of the questions or comments we get from volunteers sometimes, is that they say their plot is boring or has none or little of the indicator species. Could you describe why data from these plots is equally important?
Boring plots are super important! Records of where species are form the foundation of so much ecological research, but records of where species aren’t open up a tonne of extra possibilities. For example, my PhD involved quite a bit of species distribution modelling, which depends hugely on the locality data you use as an input. The gold standard is to have both presences and true absences – sites that somebody has visited, surveyed, and recorded whether species were found or missing. You can work with just presence data that’s been recorded opportunistically, but you’re left with the problem of working out whether gaps in your species’ distribution are real or a result of patchy observations. True absence data points put species distribution patterns into sharper relief and let you tackle a whole range of important questions. So please keep surveying boring plots and entering null data – ecologists really will thank you!
