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Research Blog: the Tropics and El Niño part 2

Map of Oxford’s forest plots (Illustration: Cécile Girardin) Map of Oxford’s forest plots (Illustration: Cécile Girardin)
28 Apr
Was last year’s El Niño a practice run for future climate change? In part two of a blog series for Geographical, Laura Cole shadows the University of Oxford’s Global Ecosystem Monitoring Network and its work to discover the impact of the world’s most well-known weather phenomenon on the planet’s tropical forests

Click here to read Research Blog: the Tropics and El Niño Part 1

‘Ca va?’ a colleague asks Cécile in passing.

‘Ca va,’ she replies over her shoulder in the usual French call and response, ‘I’m good’. More literally the phrase means ‘it’s going’ and for Dr Cécile Girardin – an environmental researcher by day, children’s illustrator by night, forever with 40 tabs open on her laptop – things are always going. Today, she tells me as we make our way to the Ecosystems Lab, lots of data has arrived from the tropics.

In the lab she hands me a memory stick with a friendly word but a look that says ‘don’t lose this’. The stick has travelled from Peru by special delivery and on it, she tells me, are a bunch of spreadsheets. Wouldn’t it have been easier to transfer them via the cloud, I wonder, putting stick-to-laptop. But when dozens of folders bloom on the screen, and within them dozens more folders and within those, dozens of sheets thousands of cells long, I realise my naïveté.

tambopataAndean cloud forest of Tambopata National Reserve, Peru (Image: Salparadis)

The files are the most recent datasets to come from an Andean tropical cloud forest in South America. They account for just a few of the 50 or so plots that the University of Oxford’s Ecosystems Lab has been monitoring, tracking the impact of last year’s El Niño. ‘There are three continent’s worth of data that need to be cleaned up before we can analyse them,’ says Cécile. ‘It’s quite a big job.’

That’s quite an understatement. For the past five years, Cecile has managed this global network of data, bringing in all the datasets from rainforests plots and turning them into clean, consistent ‘timeseries’ – a series of chronological charts that, in mid-May, the team will use to eke out what effect El Niño actually had on tropical regions all over the world.

‘The beauty of this dataset is its huge spatial and temporal scale,’ she says. The Oxford team has been taking the same field measurements regularly across the tropics, in some cases for as back as 2006. ‘Data like this really relies on the exceptional team here the and the effort it makes to collect data from plots that can be remote and difficult to get to.’

The scale is the data’s strength, but it can also be a challenge. Measurements have been collected in four different languages from eight countries, and sometimes methods have changed over time. Coding can help the process (and avoid rectangle-eyes from staring at cells too long) and I’ve been tasked with using software called R, a coding language and environment for statistical computing and graphics, to clean up the raw data from Peru. However, you have to know what you are looking at and I’m it’s not too long before I’m worried that I’ve mistranslated a whole set of Portuguese. ‘At least now you understand the anxiety of working in research,’ jokes Dr Cecilia Dahlsjö, who has been brought on to the project for this process (and can spin out clean datasets at an alarming rate). Her issue this week was making sure all the plot names are the same across the global dataset. ‘Because it stretches over so many places – and so many years – the names can change, which can make it difficult to know what you are looking at,’ she says.

carboncycleThe carbon cycle puzzle (Illustration: Cécile Girardin)

The other challenge is the complexity of the carbon cycle itself. A tree absorbs carbon from the atmosphere through photosynthesis (called its gross primary productivity, or GPP). It also stores some of this carbon as net primary productivity (NPP) and releases the rest through respiration (R – not the software this time). By adding up the components of NPP and R, we can calculate GPP. Finding the components involves taking about ten measurements from different portions of trees: their canopies, stems and roots, as well as the respiration soil and dead matter in the surrounding area.

‘We are drowning in measurements,’ says Cécile happily. ‘While that means there is so much to analyse, it’s thrilling because it will be the biggest study of El Niño of this magnitude.’

‘Last year, the El Niño turned the biosphere into a source of carbon, and the terrestrial tropics were a major contributor,’ says Cécile. ‘We want to know which mechanisms contributed to that – a decrease in photosynthesis and productivity, an increase in respiration? Once ecologists know how these components reacted to El Niño conditions, they can tackle the question of whether it can tell us how the tropics will react to more frequent extreme weather events and a hotter climate in the future?

From the carbon cycle, it is the respiration levels of Peru’s dead leaf litter that I have been cleaning. With a hint of masochism I let my spreadsheet cascade to last entry, which sits at the end of 30,000 rows of data, and that’s just for one measurement from one country. Though impossible to tell now, it’s exciting to know that there are new understandings of the rainforest system waiting in these numbers.

For those interested in getting started with R for research and data, here are some useful tutorials:

TryR by Code School
Cookbook for R by Winston Chang
Impatient R by Burns Statistics

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