Fieldwork at last for Sam 

Lockdown has taken it's toll on many projects in the MeaseyLab, and no more so than with Sam Peta who has been prevented from doing much of the fieldwork that was envisioned for his MSc. Happily, domestic travel was still an option for Sam, and so he has been able to conduct a trip to Durban this April to collect some needed samples for his work.

Despite it being very late in the toad season, Sam has done a fantastic job of getting all of the samples he needs to complete his second MSc chapter. 

Sam captures another Guttural toad for his work, and completes his sampling.

Battle of the dwarfs: Guttural Toads turn out to be the largest known shrinkage of any anuran island dwarf

Large analyses reveal a good idea of how major systems have shifted on an evolutionary scale. Yesterday a new paper published inNature Ecology & Evolutionby Ana Benítez-López and colleaguesbrought together more than a thousand species of vertebrates to explore the ‘island rule’:  insular dwarfism in large-bodied species and island gigantism in small-bodied species.

As keen readers of this blog will know we published a paper last year (Baxter-Gilbert et al 2020) about rapid shifts in the sizes of Guttural Toads introduced from Durban, South Africa to the islands of Mauritius and Réunion. That paper led by MeaseyLab postdoc, James Baxter Gilbert, revealed that female toads from Mauritius had significantly smaller snout vent length (SVL) than female toads from Durban by 33.9% (red data point below). Similarly female toads from Réunion had significantly smaller SVL than female toads from Durban by 25.9% (green data point below). For males the shift was somewhat smaller (and is not shown on the graph). 

We were quite surprised with the magnitude of these changes but we did not appreciate how large they really were until the publication of the study by Anna Bonita Lopez et al, yesterday.

Above I have graphed out their data on anuran SVL together with a one to one bar (blue) indicating size parity. Their data seems pretty globally comprehensive with 116 data points from 42 anuran species. You can see that most examples of frogs on islands show gigantism compared to their mainland counterparts. The two coloured data points represent mean size shifts between Durban and Mauritius (red) and Durban and Réunion (green). 

The biggest shift that they record for any taxon on from mainlands to islands is a 25% reduction from 43 mm to 32 mm from the Spanish mainland to Majorca for Alytes dickhilleni and A. muletensis, respectively (Arntzen & Garcia-Paris 1995). These sister taxa are believed to have been separated for more than 4 million years! 

As you can see, it is clear that the 33% shift we saw for female Guttural Toads (from Durban to Mauritius - red data point) in less than 100 years is not only remarkable but the largest reduction in body size of any anuran known on the planet! 

A nice fun fact for a Friday morning

 

References

Arntzen, J.W. and García-París, M., 1995. Morphological and allozyme studies of midwife toads (genus Alytes), including the description of two new taxa from Spain. Contributions to Zoology, 65(1), pp.5-34.

Baxter-Gilbert, J., Riley, J.L., Wagener, C., Mohanty, N.P. and Measey, J., 2020. Shrinking before our isles: the rapid expression of insular dwarfism in two invasive populations of guttural toad (Sclerophrys gutturalis). Biology letters, 16(11), p.20200651.

Benítez-López, A., Santini, L., Gallego-Zamorano, J. et al. The island rule explains consistent patterns of body size evolution in terrestrial vertebrates. Nat Ecol Evol (2021). https://doi.org/10.1038/s41559-021-01426-y

Graduation time

Every graduation is a celebration of achievements, and each year I am moved by how much our students achieve during their (relatively) short postgraduate studies. This April we had a double celebration of two MSc students, both of whom graduatedcum laude. Sadly, because of the ongoing pandemic situation, neither was able to attend the graduation ceremony in person. 

Nolwethu Jubase-Tshaliworked full-time during her MSc, including receiving a promotion to becoming Western Cape Regional Coordinator in SANBI’s Directorate on Biodiversity Evidence (DBE). Because Nolwethu worked full-time at her day job, we didn’t see her often in the lab. Nolwethu was co-supervised by Dr Ross Shackleton, previously a PhD student and post-doc at the CIB, but now Maitre assistant at the University of Lausanne, Switzerland. 

Nolwethu’s MSc thesis consists of 2 chapters. In the first, she asks what motivates volunteers to remove alien invasive plants in the Western Cape. In the second, she finds out what people from 8 towns in the Berg River catchment know about alien invasive species. Both chapters are placed into the framework of how to practically manage alien invasive species in the Western Cape province. Each progresses our understanding in the important topic of biological invasions. 

The first chapter: "Motivations and contributions of volunteer groups in the management of invasive alien plants in South Africa’s Western Cape province", is currently in press withBothalia, African Biodiversity & Conservation. 

The second chapter is being prepared for a special issue. For more news on this, stay tuned on the blog. 

Nolwethu’s graduation provides an important milestone for me, as she is my first student to graduate with a degree in Botany!

Carla Wagenerdid her undergraduate degree in Botany & Zoology, she did both her Honours project and MSc in the lab. Consequently, Carla had been in the department in Stellenbosch longer than anyone else, and knew the answers to practically anything we could think of. Carla’s MSc work was co-supervised by Dr Morne du Plessis (then) of SANBI at the Pretoria Zoo. Carla also received the covetedcum laudefor her thesis and presentation of her MSc in Zoology.

You can read blog posts about Carla’s work: 

Honours&fieldwork

With Brazilian guests:Carla&Adriana

Doing toady things inMauritius&Durban

Carla’s MSc has two chapters. One compares the gut microbiome of 1 native and 3 invasive populations of Guttural Toad,Sclerophrys gutturalis. The second chapter contains an experiment to determine the effect of transplanting gut microbial fauna from invasive to native populations, and vice versa. The first chapter is currently under review, while you can read a preprint of the second chapter here: 

The gut microbiome facilitates ecological adaptation in an invasive vertebrate

Last, but not least, Lisa Mertens, also graduated as a PhD. Due to some difficulties during the course of her studies, Lisa finally graduated with John as her supervisor. They both attended graduation on April 1st. 

Graduating theses:

Jubase-Tshali, N. (2021) Evaluating the effectiveness of citizen science to detect, report and control alien and invasive species in Western Cape, South AfricaMSc thesisStellenbosch University

Wagener, C. (2021) Spill your guts: the invasive amphibian gut microbiome.MSc thesisStellenbosch University

Mertens, L. (2021) Assessing the evolutionary and physiological resilience of southern African marine speciesPhD ThesisStellenbosch University

Doing a PhD is stressful and you'll need a support network

Stress is a natural part of life and many people are at their most productive when they are under pressure. This would most typically be a deadline. Although deadlines don’t work for everyone. Douglas Adams famously claimed to “...love the whooshing noise they make as they go by.” Problems arise when we become unable to fully respond. In the academic environment, pressures and expectations can elicit unpredictable survival responses as if you were surviving an attack and prompting you to fight, flight or freeze. Additional demands on your time may also push your life off balance, so that you start to neglect your personal relationships, exercise regime or even nutrition and personal hygiene. There is also the high likelihood that you will suffer feelings of inadequacy due to imposter syndrome (see here). 

Doing a PhD will be the cause of stress not only in your working life, but will also impact other areas of your life. Being aware of this at the outset will allow you to alert close members of your non-working life (think partner, family and friends) that they may well need to act as a support network. It is worth tracking your mental health during your PhD to check that you are not getting into difficulties. See part 5 to a guide on how to track your mental health.

Although there are not many studies on mental health for PhD students, those that exist (as well as surveys: Nature 2019) all suggest that there is a significant toll, which is proportionately higher than others in society (Levecque et al 2017). Whatever your prior experience of stress in a working environment, academia is known to be particularly stressful, and as a PhD student you are likely to absorb a significant amount of this stress into your own life (Strubb et al 2011). 

The General Health Questionnaire (GHQ) is a simple instrument used to measure occupational health. Because it is simple to score, you can perform it on yourself at any time during your PhD studies, and you can use your responses as an indication of whether you need to reach out to occupational or professional support networks. 

Right now, I suggest that you read through the questions in the GHQ and record your answers as a baseline. Keep the scores somewhere safe. During the course of your PhD, if you feel that your scores may have changed take the test again and compare them with your saved scores. Although there are no hard rules, if three or more of your scores have moved by two or more points then you need to discuss this with your support network and decide whether or not to seek professional help. 

General Health Questionnaire: Have you recently...	0	1	2	3
been feeling reasonably happy, all things considered?	Better than usual	Same as usual	Less than usual	Much less than usual
lost much sleep over worry?	Not at all	No more than usual	More than usual	Much more than usual
been feeling unhappy and depressed?	Not at all	No more than usual	More than usual	Much more than usual
felt you couldn’t overcome your difficulties?	Not at all	No more than usual	More than usual	Much more than usual
felt under constant strain?	Not at all	No more than usual	More than usual	Much more than usual
felt capable of making decisions about things?	Better than usual	Same as usual	Less than usual	Much less than usual
been able to face up to your problems?	Better than usual	Same as usual	Less than usual	Much less than usual
been thinking of yourself as a worthless person?	Not at all	No more than usual	More than usual	Much more than usual
been losing confidence in yourself?	Not at all	No more than usual	More than usual	Much more than usual
been able to enjoy your normal day-to-day activities?	Better than usual	Same as usual	Less than usual	Much less than usual
been able to concentrate on whatever you are doing?	Better than usual	Same as usual	Less than usual	Much less than usual
felt that you are playing a useful part in things?	Better than usual	Same as usual	Less than usual	Much less than usual

Even if you don’t feel that you need the support of your institution now, it is worth finding out how they can support your mental health. Although there has been some stigma attached to difficulties with mental health in the past, most institutions accept that pressures are mounting on postgraduate students and that they require support. They may well have experienced councilors for you to consult with. Importantly, you should realise that none of these symptoms is unusual and that there is a high chance that many of your colleagues are also feeling symptoms. Knowing that your problems are shared and reaching out to support networks is an excellent way to prevent them from escalating beyond your control. 

A study into the mental health of PhD students in Belgium exemplifies the kinds of difficulties that they face when compared with other similar groups (Levecque et al 2017).

A comparison of the mental health of PhD students (data from Levecque et al 2017) with highly educated general population, highly educated employees and higher education students using the General Health Questionnaire. The Risk Ratio (RR: adjusted for age and gender) in PhD students in Flanders, Belgium is consistently higher (>1) when compared to any of the other surveyed groups. 

No matter how you think of your own abilities to cope with mental health issues, doing a PhD will cause you additional stress and provoke your coping mechanisms into play. Additional stress could all be entirely beneficial, and could find yourself learning how stress affects your personality towards these positive outcomes. On the other hand, you may find that additional stress unexpectedly affects your personality, and that this will impact on both your home and working relationships. Some people will find that the additional stress will manifest itself in physical symptoms that need medical treatment. Moreover, as academia is a particularly stressful environment, you will likely take on some of this environmental stress in addition to any stress associated with your studies. Additional stressors come from home and family situations. Your best means of coping will be to have a support network in place and to understand where and with whom you can discuss any concerns. Knowing who this is and how and when to approach them will put you in a stronger position if you need them in future.

References

Levecque, K., Anseel, F., De Beuckelaer, A., Van der Heyden, J. and Gisle, L., 2017. Work organization and mental health problems in PhD students. Research Policy, 46(4), 868-879.

Stubb, J., Pyhältö, K. and Lonka, K., 2011. Balancing between inspiration and exhaustion: PhD students' experienced socio-psychological well-being. Studies in Continuing Education, 33(1), 33-50.

Being aware that you can get it wrong

With all the will in the world, when you are testing your hypothesis using statistics there is a chance that you will accept your alternative hypothesis when it is not valid. This is known as a ‘false positive’ or aType I error. It is also possible that you will accept your null hypothesis when you should have accepted your alternative hypothesis, also known as aType II error,or a ‘false negative’. While it won't be any fun to get a Type II error, as scientists we should be more worried about Type I errors and the way in which they occur. This is because following a positive outcome, there is more chance that the work will be published, and that others may then pursue the same line of investigation mistakenly believing that their outcome is likely to be positive. Indeed, there are then lots of ways in which researchers may inadvertently or deliberately influence their outcomes towards Type I errors. This can even become a cultural bias that then permeates the literature.

Humans have a bias towards getting positive results (Trivers 2011). If you’ve put a lot of effort towards an experiment, then when you are interpreting your result you might feel motivated towards your reasoning making you more likely to accept your initial hypothesis. This is called ‘motivated reasoning’, and is a rational explanation why so many scientists get caught up in Type I errors.  This is also known as a confirmation bias and we will discuss it in more detail elsewhere on this blog (see here). Another manifestation of this is publication bias which also tends to be biased towards positive results (see here). Put together this means that scientists being human are more vulnerable to making Type I errors than Type II errors when evaluating their hypotheses. It is important to understand that simply by chance you can make a Type I error, accepting your alternative hypothesis even when it is not correct. 

In this table, the columns refer to the truth regarding a hypothesis, even though the truth is unknown to the researcher. The rows are what the researcher finds when testing their hypothesis. The blue squares is what we are hoping to achieve when we set and test our hypothesis. The grey squares may happen if the hypothesis we set is indeed false. The other two possibilities are the false positive Type I error (red), and the false negative Type II error (black). In the table it seems that the chances of getting one of the four outcomes is equal, but in fact this is far from reality. There are several factors that can change the size of each potential outcome to testing a hypothesis.

The following figure has been redrawn after figure 1 in Forstmeier et al (2017). This is a graphical representation of an argument first made by Ioannidis (2005). Each figure shows 1000 hypotheses. You could think of these as outcomes of 1000 attempts at testing the same hypothesis, or as a more global scientific effort of testing lots of hypotheses all over the world. The difference between the figures is the likelihood that the hypotheses are correct changes. In the first one we see highly unlikely hypotheses that will only be correct one in a hundred times. The blue squares denote the proportion of times in which the hypotheses are tested and found to be true. The black squares denote false negative findings, i.e a Type II error. The red squares denote false positive findings, i.e. a Type I error. Because the hypothesis is highly unlikely to be correct the majority of squares are light grey denoting that it was correctly found to be untrue. Although it might seem unlikely that anyone would test such highly unlikely hypotheses, there are increasing numbers of governments around the world that create incentives for researchers to investigate what they term blue skies research, which might be better termed high risk research or investigations into highly unlikely hypotheses. The real problem with such hypotheses is that you are more likely to get a Type I error than actually find that your hypothesis is truly correct. 

In the next figure we see a scenario of unlikely hypotheses that are found to be correct approximately one in 10 times. Now we see that the possibility of committing a Type I error is roughly equivalent to a Type II error and to the probability of finding that the hypothesis is truly correct. Thus, if your result comes out positive, you are unlikely to know why.

Lastly we see the scenario in which the hypotheses are quite likely to be correct one in two times. Now we can see that the possibility of creating a Type II error is highest. Next the blue squares show us the chances that we find the hypothesis is truly correct. Lastly, there's only 11% chance of a type 1 error. 

In all of these figures (above) the power of the analysis is set at 40%. The statistical power of any analysis depends on the sample size (or number of replicates) you're able to use. Some research has suggested that in most ecological and evolutionary studies this is actually more like 20% (see references in Forstmeier et al 2017). What is important to notice in the next figure (below) is that when we change the power of the analysis (in this case from 40% to 20%) we influence the proportion of Type II errors over finding that the hypothesis is correct. While the overall numbers of Type I errors does not change, if your analysis tells you to accept your alternative hypothesis, there is now a 1 in 5 chance (20%) that it will be a false positive (Type I error).

What you should see when you look at these figures is that there is quite a high chance that we don't in fact correctly assign a true positive hypothesis. There's actually much more chance that we will commit a Type II error. Worse the more unlikely a hypothesis is, we are increasingly likely to commit the dreaded Type I error.

From the outset we should try to make sure that the hypotheses you are testing in your PhD are very likely to find positive results. In reality, this means that they are then iterations of hypotheses that are built on previous work. When you choose highly unlikely hypotheses, you need to be aware that this dramatically increases your chances of making a Type I error. The best way to overcome this is to look for multiple lines of evidence in your research. Once you have the most likely hypothesis that you can produce, you need to crank up your sampling so that you increase the power of your analysis, avoiding Type II errors.

References

Forstmeier, W., Wagenmakers, E.J. and Parker, T.H., 2017. Detecting and avoiding likely false‐positive findings–a practical guide.Biological Reviews,92(4), pp.1941-1968.

Ioannidis, J.P., 2005. Why most published research findings are false.PLoS medicine,2(8), p.e124.

Trivers, R., 2011. The folly of fools New York.NY: Basic Books.