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Cordillera Huayhuash | | @t_e_lee

In September 2017 I was fortunate enough to hike the Cordillera Huayhuash, Peru – one of the most beautiful treks in the world. If you have the magic triplet of time, money, and health all aligned, I strongly recommend doing this trek.

The whole trek is above 4,000km, so the concern of altitude sickness is very real. But we went with an excellent tour organiser. Every morning and evening we were asked to rate everything from headaches, to stomach problems, and they measured our oxygen saturation using a small, noninvasive, clip on our finger. Now, not only was I fortunate enough to have the magical triplet, an excellent tour organiser (which provided a lot of peanut butter – a fail safe way to win my approval), but my fellow trekkers were a happy, healthy and considerate group. And most importantly, tolerated me collecting their oxygen saturation data to play around with upon my return to normality.

I have returned!

The data

There were five women, aged between 24 (Nikki) to 56 (Phyl), and three men, aged between 24 (Matthew) and 60 (Joe). Bonny was taking Diamox, a medication to help acclimatise. Half way through Celia also started Diamox.

The altitude measure refers to the altitude we were at when measuring our oxygen saturation. When measuring the oxygen saturation in the evening, the highest altitude we reached that day was also recorded (the red circles in time series plots). We all completed the treks with smiles, although some more tired than others 🙂


With our very limited data set, there is not a clear correlation between altitude and oxygen saturation. Age, nor gender, seems to bear a relationship on the ability to acclimatise. This conclusion is reinforced when one sees the dendrogram, (using Ward’s method), where the clustering was based on our individual distributions (see histograms). For example, Joe and Matthew, the two extremes of our age range, are deemed to have the most similar distributions. However, as one can see from the histograms, all the distributions are generally very similar, except for Celia. That is, generally, everyone’s saturation was above 80% with a regular measurement of around 90%. Celia, who felt poorly until she started taking Diamox, has the widest range of oxygen saturation. The difference she must have felt after taking Diamox is apparent from her time series.


Altitude sickness is unpredictable and indiscriminate. However, Diamox really works! Bonny, who knew she was prone to alititude sickness, took Diamox before starting the trek, and throughout the trek. Her oxygen saturation is similar to the rest who were not taking Diamox. So if you know you’re prone to altitude sickness, take it*! And if you’re unsure, take it with you, and take it* as soon as you start feeling poorly.
* I am not a medical doctor! Talk to a doctor before taking any medication!







20170920_120928-01 | | @t_e_lee



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Research Interests

 I mostly work on extinction problems.  I have modelled two different Bayesian approaches to estimate extinction based on a sighting record. Both these models formally account for uncertainty within the sightings records, which is a key advancement on existing models. Further, one of the models easily includes survey effort, and is easily implemented in an Excel Spreadsheet (please email me for a copy).

Another project I’m working on predicts which species considered extinct are likely to be rediscovered (Lazarus species). We consider various traits such as body mass and habitat elevation, to determine a) what species traits are linked to true extinction, and b) how different traits affect the time to rediscovery (for species which are incorrectly considered extinct). This knowledge can aid future decisions about classing a species as extinct, and identify protected areas likely to be harbouring species waiting to be rediscovered.

Lastly, I’d like to expand the role of partial differential equation in ecology. Partial differential equations dynamically include changes in space and time. This approach is obviously useful for many environmental applications. I am working on modelling the spread of cane toads in Australia, where the effect of changing temperature with time can be observed. This allows various climate change scenarios to be included when forecasting the spread of cane toads. The partial differential equation will be included within a Hierarchical Bayesian model to account for uncertainty in the data and parameters. | | +61(0)3 83448091 | @t_e_lee
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