2020 project update

It turns out that 'New Year New You' is an academic thing as well..
Which I find odd when the 'new academic year' starts in September.

But this month seems to have been the month of reviewing, summarising and setting new targets; which has its benefits and disadvantages.

Benefit - if I'd had much time off over Christmas I'd have probably forgotten what I was doing, and sitting down for a rethink would have been a good idea.
Downsides - if you didn't take any time off you feel like you've lost a month getting everyone else up to speed and creating summaries when you should be ploughing on.

I didn't really take any time off - I'm taking a February holiday instead; when my partner can also get some time off his job. I did find however, that everything was starting to get a bit messy over December and it was harder to get data / chat to people / get things moving.

Now, despite the feeling of spending time off project, I've unravelled most of the data issues I had, and have a (rough) strategic plan. All this stopping and reviewing has helped me realise that the learning/unravelling process was, in itself, really important and part of the whole 'gaining experience and learning new skills' aspect of the PhD. My 'getting everyone else up to speed' is also due to the fact that I've done a hell of a lot of work over the past 2 months.

Being an interdisciplinary project I've shifted from a social science to physical science approach whilst still maintaining links with catchment and the shifting, ongoing world that messy social science inhabits. Explaining what I'm doing to different parties will always involve a little 'getting up to speed' as I'm never working entirely in anyones area of expertise.

The real benefit to all this summarising is that I have two really key conferences at the end of this month, one catchment based and one is the annual meeting of our institute BIFoR. I'm excited about both: the BIFoR meeting is about networking and getting an overview of current research at the Institute - so I'm just Poster presenting and will be excitedly reading everyone else's. The second conference is an NFM seminar local to the catchment I'm working in, the guest list is a whole bunch of people I want to talk to and I'm doing a 15min presentation... so... yes all this summarising has been rather useful.

To give you the super short version of where I am:
Last year we completed the logistics and foundations of the research:

• Literature review
• Methodologies
• Ethics review

And started stage one of the research itself:

• Exploring landmanagers preferences, perceptions and expertise
• Case study data collection of the catchment itself, both physical, remote sensed and archive data (for example; historical records of landuse, key GPS location of important features, aerial photographs)

Methods include emplaced semi-structured interviews, participant mapping, photograph, empirical measurements etc.

From November and for the next six months I'm taking all of this data and preparing the inputs to run a computer model of the hydrological behaviour (how the water moves).

Or in picture form - here's this years poster... enjoy!

p.s. the link in the sidebar takes you to a larger, more readable version...

What you do matters

I just finished reading 'The Thesis Whisperer's latest post (here) and the title is directly from that.
She's sitting in Canberra helping organise face mask distribution as the smoke thickens and they pack emergency 'go' bags, waiting to see if the bushfires hit.

At the end of the post she hits the nail on the head

"At the best of times, the narrative around the PhD is that it’s pointless. In the middle of a real and pressing disaster, many of you might be feeling even more existential angst about your PhD than usual".

It's hard not to feel like the PhD is a lost cause. To little to late. But she followed this up with another statement

"what you do is important"

I felt like I had to reflect on that. It does feel like our world has shifted somehow, but that's because I can relate to the society in Australia, it's pretty close (colonialism) to the way in which I live.
In reality the 'real impacts' of climate change have been devastating communities already, I just haven't related to it in the same way. That realisation can make you feel pretty lousy on top of the whole 'apocalpyse' thinking.

I'm lucky in a way. It may feel like to little, to late, but I can see how my PhD directly relates to the problem, or to the solutions if I get it done. It might be to late already. But if it isn't then the way in which we understand landuse and landscapes will be central in how we go on to adapt to this new shifted world. Also, trees and floods, pretty much up there.

The terrifying bit is that I'm not due to finish for another 2 years. What use will that be?!
I don't know, but I also can't change that outcome. I can only keep working, stay active in the communities I've become a part of, develop more links and keep working.. 

Maybe I can also do one active thing each month, make one change, plant a tree, make a pollinator hotel for the garden, buy beef from a local farm - ideally practising agroforestry?, fix my bike and cycle instead of driving, one thing each month. We do I bunch of stuff already: recycle or make clothes, avoid buying; reduced plastic; eat less but spend more on better quality meat, avoid flying. Still, most of these things haven't been taxing, and if anything they've improved my quality of life. So here's to change.  Oh and continuing to work on my PhD.

On which note I need to get back to analysing soils data, and trying to remember how to use R Studio properly.

By the way, if you want to know more about my research, I entered a really obscure image into a competition: Images of Research. You can even vote for it if you like! I'll probably write a post about it after the deadline at this rate... but it was a good challenge (procrastination opportunity) and the research may be of interest to some

Data: When is enough enough?!

Reflecting on Research: Data – when is enough enough

For context:

My research focuses on a case study, a single river with a catchment of +100km2 that is the tributary of a much larger catchment. The landscape is, in description, on the borders of the lowlands and the uplands, hilly but not mountainous, diverse, predominantly agricultural rural and wet.

It is wet both in weather and in leakage, the hills leak. (not a geography term. probably.)

My project is combining the social and physical sciences by incorporating landmanager/owner perspectives and expertise with traditional GIS (Geographic Information Systems) and computer modelling, to explore tree planting for NFM as a landuse change.

Collecting 'Data':

I have between one year to 18months for data collection. This seems like a long time, but it really isn't

My project breaks down into three key areas

• Explore social perceptions, preference and expertise to co-create understanding and knowledge of the catchment
• Model a known flood event and develop sceanrios of alternative landuse
• Analyse and evaluate the case study with and including participant evaluation

Each one of these stages could involve an epic amount of data collection.

So when is enough enough.

I spent all summer walking farms, gathering data and most importantly, listening. But when you are considering peoples opinions, their perceptions and preferences, how many people do you talk to? When everyone is of equal value shouldn’t you talk to everyone?! If that’s not possible (which it isn’t, not everyone would want to talk to me I’m sure, let alone the time limits), 

How do you decide who to target? 

How do you decide when you have done enough?

Actually the first of those two questions is the more easily tackled, there’s vast amounts of literature supporting how to select participants; random selection, snowball selection etc. in reality it often comes down to who you can contact, who answers the phone or who happens to be in when you knock on the door. I used a number of different methods to try and speak to a diverse, roughly representative range of people.

The second question is much much harder. Strictly speaking I think I have enough qualitative data to have been able to make conclusions from what I’ve been told. Officially I have ‘finished’ this initial aspect of data collection, but there are areas of the catchment I’d really like to know more about, and people and landscapes of interest I think might be really important. I’m not going to not speak to these people if I get the chance, but I also have to move on to the next stage of the project; computer models do not run themselves. Well, yes, they do, but I have to tell it what to do first. Actually first I have to work out what I want it to do, then work out how to tell it to do that. Urgh.

As I accept the situation and move on I find that I am still tackling the same question. How much data is enough? I am using a ‘physically based spatially distributed’ model; more simply it uses information about the physical characteristics and where things are in relation to each other to work out what’s happening. The alternative is to use a conceptual lumped model, which I’m not going to explain, but it’s more ‘pure maths’ and doesn’t allow me to explore landuse change in quite the same detail. The ‘conceptual’ bit is a bit of a red herring as the model I’m using is obviously conceptual; I am not, for example, actually going to fill my computer with soil when I do the soil input. I do however, have to put in a value for the soil quality (quantity, depth etc). Here resides the difficulty, I am using physical data to represent the catchment and to an extent the finer the detail and the data the more accurate the model… sort of

But there’s a line where the quality and quantity of the data runs out, and by running a more complex model I’m more likely to create errors and uncertainties which I wouldn’t have had with the simpler model. So I have to ask not only ‘how much data is enough’ but also ‘how much is to much?’!

I am still tackling this one – the endless problem with a PhD is that no one else really knows what you’re doing, so no one can really tell you what you do or don’t need until you need it.

For now, having access to the data when I need it is more important than not having it, or having it and not needing it.

So I’ve ordered a pair of waders and I’m either going to sit in front of my supervisor and cry until he tells me what to do or (more likely) I’m going to get some help and go and walk in the river with some kit and collect some data that I may or may not need.

This is normal right?

Fieldwork and flooding: muddy reflections

October and November have been defined for me, and I would assume many others, by flood.

In mid-October the extreme rainfall meant that the river catchment I am studying hit its highest ever recorded peak. The previous two major peaks and most in memory (I am yet to check the data in detail for this) were in January/February after months of already saturated ground. The summer was wet, but still, the timing is unusual.

With good data for rainfall, landuse and flood peak, this gives me two extreme flood events in the last five years to compare.

It also created a before/after line in the social data, as perception and effect of the flood within the catchment became evident. Participants were cut off, blocked in, land and infrastructure were damaged, winter feed lost.

Was I thinking about all this when the floods occured?

Well, I was watching the height data with increasing interest (and amazement) during the event. From a long way off. I was also in touch with some participants during the event and many have sent photos and videos afterwards that they took at the time.

Despite considering it I did not go into the catchment for a week, there were two key reasons for this:

Rather than being interested in the data, I was emailing around to check if those most likely to be affected were okay. At the end of the day data is data, but people are people.
Having a professional relationship doesn't mean that you don't care and any scientist that trys to tally this up with being 'objective' has a few screws loose in my opinion.

Secondly, I was more interested in being safe, and able to get home, I live very near the Severn and my catchment is a tributary of the the River Wye, I had significantly greater issues to deal with than the flooding of 'my' river. As, in fact, did most of the population of the catchment. I feel that between 'being committed to my PhD' and 'not drowing' I will choose the latter every time. I also refuse to be the person who gets swept away because they believe they are safe in their car. As a very wise lady stated, when you're thinking about crossing flood water, remember "the road was there".

In early November the rivers rose again, again I was not local (actually I was in Scotland on holiday). Interestingly I would have been far more likely to go to the catchment because the river did not seem to be getting as high as it might. It is the larger rivers that draw the attention, but perhaps the smaller ones from which we can learn so much. Given that the Severn, however, was still flooding this probably still wouldn't have been wise. In any case my river may be 'low risk' due to population density, but that doesn't mean it's not dangerous. Aside from falling in, the risk to roads and bridges is still possible and more likely to fool one; "the road was there".
Again I am wondering about the impact on the community (human and more-than-human); given the recent floods and weather I am also, significantly interested in the effect on the landscape.

Nb: Here the human/natural are so entwinned it is impossible and perhaps unwise to think of them as separate. The behaviour of a flood, the shape of the land, the land cover; to try and distinguish a 'perpetrator' for change as either human or natural seems to be missing the point.

Landscape change is fascinating to me, hence the focus on tree planting in my work. But researching the added aspect of flooding means working with this intertwinned nature of society, landscapes and environmental risk.

There is a further extension to this which I think is important to reflect on; and it's to do with my relationship with the landscape and its people; staying safe, caring, when and how to be where and do what...

When the landscape you are researching is a landscape of which you are a part (which, sorry, includes everyone because the act of researching, just being there, will make you a part of that landscape) then you become entwinned in that research. As is the case for all research when you really look at it.
Untangling the impacts of that is part of the job.

Staying safe can be trickier. The impacts on you, as a researcher, caring about the outcomes for those who live in the landscapes. That's something I don't think we reflect on often enough.

A Summer of Listening

Science and policy have a somewhat chequered history when it comes to listening. (See Shelia Jasanoff, Brian Wynne, Alan Irwin as key authors for further reading..)

I don’t think anyone would be surprised by that statement applied to policy makers (except perhaps the politicians as I imagine / hope that’s what they think their job is). With ‘Science’ however it’s a little trickier. We might not expect a doctoral student studying quantum mechanics, particle physics or the obscure DNA of a prehistoric grain, to listen to the views of the populace. If I said however, that their work would contribute to artificial intelligence, flood management and genetic modification. Suddenly the ‘view of the populace’ becomes significantly more important.

When working in landscapes there are also local and situated knowledges to consider; high levels of expertise, outside the formal scientific and political institutions.

I was introduced to this rethinking of science through my MSc (in Science and Technology Studies at UCL). However, it’s through my PhD research that the complex interactions between the social, environmental and physical factors that form landscapes have become really significant.

As an interdisciplinary scientist (geographer!) I am trying to act on all the lessons I’ve learnt. I am exploring the flood characteristics of a river catchment and the potential impact of tree planting. However, rather than starting here, the project starts with the recognition of the impact of people’s values, preferences, perceptions, lived experience, history etc. on not only the way we talk about flooding, but the very shape of the catchment itself; taking into account the importance of the social in future planning, but also engaging with expertise and developing co-production of knowledge with those who live and work in the catchment.

So, I have spent my summer listening…

… and walking, seeing, recording, smelling (I have a whole blog post to write about the importance of the smell of silage). I have been trying to understand the landscape through the lived experience of those who have made it.

I have heard (seen, experienced) a wealth of knowledge. Narratives that contain and emplace good good old fashioned ‘facts’ of physical characteristics of the land, but also the values and perceptions that inform the behaviour that shapes it. I have experienced how the physical characteristics of the landscape (both static and everchanging with the water and the weather) shape the behaviours and values of its inhabitants (human and more than human).

This is an ongoing learning process; I am working with a single case study catchment and will continue this experiential data collection whilst moving onto the more traditional approaches of model building and evaluation.

(I have asked my supervisors if I can use clay, but they’ve said I have to use a computer)

The work I’m doing raises interesting methodological questions. How does the social, value-based data impact the numerical / quantitative computer model? How much can I / should I, include? (I can’t see a way of getting the smell of silage in there, I wish I could). Very practical questions include how I balance the need for maintaining confidentiality of participants with the methods of ensuring my model can be scrutinized and checked?

These questions are challenges which make this a PhD. Each one is solvable in a very simple way (no, don’t, can’t). But each richer solution will lead to a more integrated approach to interdisciplinary science. Which hopefully, will enable more people to experience the absolute joy of listening.

Graduating (again): an MSc in Science and Technology Studies

Today was the official graduation for our 2017/18 MSc in Science and Technology Studies at UCL (a brilliant department). I find this weird that it happens over a year after you've finished but there it is.

After (in my mind) nearly failing the first term, the work that went into turning that year around was ridiculous. Tackling my dyspraxia both in terms of its impact on my writing and the mental block it creates in my belief that I could write; but also tackling the subject: literature and research. 

It was a game changer. I came out with a Distinction overall and the STS prize for my dissertation. It also put me on the path to my PhD as a Leverhulme scholar for Forest Edge at BIFoR UoB.

I'm really proud of the dissertation, hopefully I'll get a paper out of it and at least I can make it available here: Forest vs afforestation: identifying forest futures from definitions and values

PhD Poster for the BIFoR Annual Conference

Originally published 24 January 2019

So I’m attending my first academic conference as a PhD Researcher. This one is very much a ‘home’ affair as its the Birmingham University Forest Institutes (BIFoR) Annual Conference (link). As Forest Edge Scholars we’re all preparing academic posters outlining our research. As PhD students with less than six months experience this research is limited to scope and overviews only! But it’s been a good experience trying to summarise the initial ideas of what I’m planning to do…

Having spent far to long worrying about this I’m now going to send off my poster for printing – seeing my work in A1 size is going to be a bit terrifying – here’s hoping the layout / spelling / pictures don’t look to ridiculous! (If I start worrying about the actual content again I’m never going to get this finished….)