Tag Archives: PhD

The “true nature of the university” as told by John Williams

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I’ve been appointed as a lecturer a since the beginning of March; my first real academic job. In my short time in the ivory tower, I’ve wondered about my role at the university and how it complements my own career ambitions. This form of navel-gazing rarely results in any meaningful epiphanies, but it does push me towards interesting sources of guidance.

One such source is the novel Stoner, by John Williams (It’s excellent. I highly recommend it). Below is an extended excerpt on the ‘true nature of the university’, which struck a chord with me. I can relate to all the characters and especially to the closing paragraph. It’s a beautifully written novel and I wouldn’t want to spoil it, but, for those in a rush, I annotated the best bits in bold.

To set the scene: three young English lecturers, Mrs Masters, Finch and Stoner, are having a casual conversation after work when the following exchange takes place. Continue reading →

The scalability of macroecology

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Russian Dolls

No matter at which scale you look at it, nature is remarkable.

Like many others, I was taught ecology in a very hierarchical way: individual organisms are part of a wider populations of species, collections of species form communities and communities come together to make up ecosystems. Similarly, single trees are nested within forests, which aggregate to form biomes. I’m sure you can come up with many comparable examples.

The trouble with such neat spatial hierarchies is that they lure us into believing that if patterns appear similar at several different spatial scales, then the processes leading to these patterns should also be similar. It’s so easy to assume that nature is like a set of Russian Dolls: each daughter exactly the same as its mother, only slightly smaller. But this is not necessarily the case.

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Species distribution modelling is not as simple as you think

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One of the most fruitful sub-fields in ecology is using climate variables to predict species’ geographic distributions. For the uninitiated, species distribution modelling assumes that species are limited in their distributions to suitable climate zones. By studying the environmental conditions where species are known to occur, you can infer the total geographic distribution by calculating the suitability of unsampled regions based on the environmental. Furthermore, using the same principle, species distribution modelling can forecast the effect of future climate change of the distribution of life on earth.

Unfortunately, studies have shown that these fancy climate-based techniques cannot consistently outperform much simpler ones based on spatial phenomena. For instance, spatial interpolation between point occurrences outperforms sophisticated climate-based predictions. Similarly, elaborate climate-based predictions perform no better than expected from random chance.

The trouble lies in the spatially-structured world we live in. Species distributions, especially at large spatial scales, are spatially-autocorrelated due to constrained dispersal. Similarly, climate variables are also spatially structured because the meteorological processes at proximal regions are generally more similar than those at distant sites.

When trying to link species distributions to climate conditions, the challenge lies is separating spatial and environmental correlations in species distributions. Specifically, we should identify three patterns in the geographical species distributions.

  • We must first identify ‘true’ correlations with the environment, which are independent of spatial patterns (E|S).
  • Next, we must identify the environmental-associations that also have a strong spatial structure (E∩S). This is known as exogenous spatial autocorrelation because it is due to autocorrelation is the underlying variables.
  • Finally, we need to identify spatial patterns that are completely independent of environmental conditions (S|E). This is called endogenous spatial autocorrelation because it supposedly stems from spatial processes, such as dispersal.

In our latest study just published online at Ecography, we set out to quantify the degree of environmental correlation, exogenous and endogenous spatial autocorrelation in the distributions of 4 423 species of amphibians, reptiles, birds and mammals in Africa. Continue reading →

Some motivation to get you through your PhD

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If there is one thing I hate, it’s the stereotype that PhD students are pathetic, dependent, helpless creatures bogged down by self-doubt and self-pity. It annoys me even more that PhD students are responsible for perpetuating this myth. We laugh along with popular websites like Piled Higher and Deeper (a.k.a PhD comics) and What Should We Call Grad School, which regularly make jokes about the futility of grad school.

Sure, these sites are funny because there is an element of truth in them, but I believe that they cause more harm than good. Although they are well-meaning and try to foster a culture of solidarity among students, they are more likely to cause complacency than empowerment.

We don’t need another shoulder to cry on, we need a kick in the arse!

As I am nearing the end of my PhD experience, I thought I’d share a bit of motivational advice I found especially useful. It is the final chapter of Adam Ruben’s book, Surviving your stupid, stupid decision to go to grad school. Some of you may be familiar with Ruben’s writing, because he also writes a monthly column in Science Magazine, Experimental Error.

Here it is, enjoy.

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