Month: October 2014

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On the writing of a PhD thesis

writing“Writing a [thesis] is an adventure. To begin with it is a toy and an amusement. Then it becomes a mistress, then it becomes a master, then it becomes a tyrant. The last phase is that just as you are about to be reconciled to your servitude, you kill the monster and fling him to the public.” Winston Churchill

I’ve just finished my PhD thesis and thought I’d share some of my opinions on how best to go about writing one. But before we get there I’d like to express my skepticism of the value of writing a thesis as a means to evaluate a budding scientist. I don’t know of any papers in journals that run over a 100 pages but classically this is what was expected of us at PhD level. It’s rare that a scientist writes a monograph. Instead we compose pieces of research that can be explained in around 10 pages. Scientists use mathematics and statistics to make our points, in that way our numbers do the talking so we can afford to be succinct. This is in contrast to students of the arts who typically draw on argument and rhetoric in their works building to a singular point or thesis! But that’s irrelevant to this topic because you still have to write one and many departments are quite flexible with their definition of thesis.

So my first piece of advice is write chapters with the aim of publishing them. You’re training to be a scientist and papers are your currency so keep that in mind. Three or four data chapters with a general introduction and discussion seem to be the way to go. If you have this approach you’ll be able to finish up parts long before the deadline. If you can get papers published, all the better, a peer-reviewed chapter looks very well and will be an improved piece of work for having gone through the process. The final body should be a coherent whole but these are not book chapters in a story. That said be aware of how you want to frame the whole thing.

Try to be concise; it’ll be easier for you to write, easier for your examiners to correct and more attractive to anyone else who wants to read it. There may be some work you did over the course of your PhD that has to get the chop to achieve this.

There’s no problem in seeking help. Science is meant to be collaborative, even more so today. In 2012 only 11% of all papers were single authored. You’ll be able to get much better chapters if you include people who can add a bulwark to any of your weaknesses. Just make sure you do the bulk of the work and properly credit your collaborators where necessary.

Give some thought to the program you’ll use to write up the project. MS Word isn’t the only way. I found assembling the whole thing in LaTeX went quite smoothly because it’s specifically made for writing technical documents. The downside was it was difficult for others to comment on it. There are ways to do this but I was a novice at the time.

Step back from the cult of the busy too. I found giving myself a break from the write up helped me come up with a much better frame for my discussion.

Start early, don’t write much, aim for papers, and use LaTeX. Simple. How’s that for concise?

(The contents of this post are subject to change after my thesis defence)

Author: Adam Kane, @P1zPalu, kanead[at]tcd.ie
Photo credit: http://centrum.org/2014/08/creative-nonfiction-workshop-nov-6-9/

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PhD – Pretty Huge Disaster

Dresden

This is a mini series of two posts about finding positive things in negative results. Science is often a trial and error process and, depending on what you’re working with, errors can be fatal. As people don’t usually share their bad experiences or negative results beyond the circle of close colleagues and friends, I thought (and hope!) that sharing my point of view, as a PhD student might be useful.

If you’re about to do a PhD you will fail and if you’ve already successfully finished one, you have failed. At least a little bit… come on… are you sure? Not even a teeny tiny bit? By failure, I just mean scientific failure here, as if you ran an experiment and the result was… a fail, no results, do it again. There are millions of ways to fail, from errors in the experimental design to clumsiness but in this series of posts, I want to emphasize the consequences of failure more than its causes. I think that it is an important thing to learn and to embrace as a young future scientist, as much as journal rejection and other annoying and common silent academic failures.

During the two first years of my PhD, I went from the idea of quickly testing some assumptions as a starting point for a bigger question to some detailed and time consuming simulations on a detailed part of these assumptions. The time spent appeared to be completely useless scientifically because the analysis failed leading to false negative results and kept me away from going back to the bigger question. Or did it?

When wrong is right part 1

Since the summer of last year, I was working on an intensive computational project. I was running a kind of sensitivity analysis to see the effect of missing data on the phylogenies that have both living and fossil species (that’s called Total Evidence to link back to former posts, here and here). In brief I was simulating datasets with a known (right) result by removing data from it to see how the results were affected. Because of my wide ignorance at the start in coding, simulations and the method I was testing, the project took way longer than planned. And all that was of course ignoring Hofstadter’s law (‘it always takes longer than you think, even when you take into account Hofstadter’s Law’).

The expected result, as for any sensitivity-like analysis, was that as you reduce the amount of data, the harder it would be to get the right results. That wasn’t what I found at all. Instead, my simulations seemed to be suggesting that whatever the amount of data, you never get the right results. Suspicious, I tried to check my simulations and asked advice from competent and talented people that helped me finding caveats in my project. But still, after checking and testing everything over and over again, the simulation results appeared to be the same: the amount of data doesn’t matter, the method just don’t work.

Even though these results were negative, they were intriguing and, if they were right, probably important because of the number of people willing to try the Total Evidence method over the last three years. From that perspective, I presented my results at the Evolution 2014 conference in Raleigh. There, I got even more comments from even more people but still, the results appeared to be right. Until one person that had a similar unexpected result suggested that should try an older version of some of the software I was using.

It appeared that person was right and all the weirdness in the results that I tried for months to fix, check and explain were caused by a bug in the latest update (don’t use MrBayes 3.2.2 for Total Evidence analysis, prefer the version 3.2.1).

After an obvious moment of relief, came an obvious negative feeling of having lost my time and how I should have given up instead of continuing to dig. But a posteriori, I’m actually glad of this misadventure and learned two really important lessons: (1) published software is not 100% reliable; always test their behaviour; (2) there is nothing more productive than sending your work to colleagues and experts for pre-reviewing. Even though, the bug appeared to be “trivial and easy to fix”, the amount of comments I had definitely helped improve both my understanding and my standards for this project.

Author: Thomas Guillerme, guillert[at]tcd.ie, @TGuillerme

Photo credit: wikimedia commons

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Sustainability Through Stability

image001I recently took part in a Tansley working group, an initiative that has a main working theme of advancing the ecological foundations of sustainability science. In this specific case we are seeking to construct a unified framework to help understand the multidimensional stability of ecosystems.

In an era of increased human activity, significant climate change and biodiversity loss, an understanding of the mechanisms and drivers of ecosystem stability has vast implications for both ecological theory and the management of natural resources.

One large challenge in the study of ecological stability comes from the complexity of ecosystems. The dynamics of an ecosystem depend not only on the network structure, the interactions among different species, but also on external perturbations that vary in context, intensity and frequency.

Another huge challenge is the multidimensional nature of ecological stability, with its many measures and definitions including resistance, resilience and temporal variation, all of which are themselves interrelated. Stuart Pimm, a member of the Tansley working group, reviewed four measures of stability in one of his early publications in Science (Pimm, 1984) and one blog from Jeremy Fox even summarized 20 different stability concepts!

Both theoretical and empirical ecologists have spent decades exploring the role of community structure, interaction strength and disturbance in determining the dynamics and stability of ecosystems. However, most of these studies only focused on a single aspect of ecological stability, underestimating the impacts and recoveries of populations and communities.

Failure to consider the multidimensionality of stability is magnified when the relationships among these stability elements are quite fragile. For example, one lake or reservoir may maintain its stability in total biomass following a disturbance by adjusting its nutrient load, but the community composition has changed dramatically. 

To create a unified concept of stability across theoretical, field-based and experimental research the confusion in using and defining these different elements of stability must be cleared up.

A typical confusion arises from the usage of the term resilience, which can be defined as the recovery time or speed following a disturbance to a pre-disturbed state; for instance the time taken for an area of scrubland to recover from a wild fire. The method used to calculate resilience in the local stability of theoretical communities is impossible to detect in the real world. So there is an urgent need to fill this gap by making a framework that suits both empirical scientists and theory development.

And that is one of the main challenges the Tansley working group seeks to face. We aim to construct a framework of ecological stability across major global ecosystems through a review of the most up to date measures of ecological stability (both empirical and theoretical) using specific case studies. This will help researchers adopt a more comprehensive approach to investigate stability and facilitate the comparison across different systems and scales in the future. We will also evaluate the feasibility in applying theoretical stability measurements to real ecosystems and abandon those which will are next to impossible to obtain from the real world.

To communicate the importance of the stability concept to a much broader audience, we will provide videos as well as vivid examples to illustrate the concepts of the different stability elements and how to measure them. We have an enthusiastic belief that the Tansley group will make a big contribution to the standardization of concepts and measurement of the multidimensional stability.

Author: Marvin Qiang, qyang@tcd.ie, @MarvinQiangYang

Photo credit: http://www.changedbygrace.net/2012/09/21/faith-floods-and-finances/

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What has nature ever done for us?

dogs watching tvAnti-environmentalists and apathists often ask why bother to conserve nature – what does it do for us? Cue enthusiastic green arm-waving and heavy sighs from environmental scientists and ecologists who have faced this attitude their entire careers.

Nature is undeniably important for the human race – we wouldn’t be here without plants fixing the sun’s energy into carbohydrates and producing oxygen as a by-product, we wouldn’t be able to grow any food to eat without the myriad of organisms which create and maintain the soil, and exposure to nature has numerous psychological and physical benefits for our health. And yet, it is not valued in political decision-making. The environment, particularly the living biological part of it, is a “cross-cutting” issue which means it’s ignored by most government departments, including those that should be valuing it the most (e.g. Department of the Environment, Community and Local Government; Department of Agriculture Food and the Marine; Department of Communications, Energy and Natural Resources). This is because most decision-making is driving by economics.

International momentum has been building for governments, businesses and organisations to begin valuing nature. This doesn’t just mean putting a price on nature – it’s not all about price-tags – but valuing natural capital in the same way that any other capital (financial, human, built etc.) would be valued. And accounting for this capital in decision-making processes at all levels (from individuals up to government policy).

Some countries and individual corporations have made good progress with this (e.g. the UK has a Natural Capital Committee, Coca-Cola and Puma have famously adopted Natural Capital Accounting systems), but there has been little progress in Ireland, until now.

In April, the first Natural Capital Ireland Conference was held, which brought together academics, government representatives from national and local levels, government organisations, NGOs, business and finance and other stakeholders. The point of the meeting was to try and increase understanding of valuing nature nationally, and progress natural capital accounting at all levels.

The report from this conference is now available on the Natural Capital Ireland website (www.naturalcapitalireland.com) and will be launched at the EPA Environment Ireland conference. In addition, the EPA and NPWS have been working with the conference organising committee to create a national Natural Capital Forum.

Whether this will bump the natural environment up the political agenda, and increase people’s interest and enthusiasm for nature remains to be seen… But we need to keep trying to convince people that nature is important, and that not having it is more expensive and economically damaging.

Author: Jane Stout, stoutj[at]tcd.ie