Thursday, March 26, 2015

Ecology in evolutionary times

Ecological and evolutionary perspectives on community assembly. 2015. Gary G. Mittelbach, Douglas W. Schemske. Trends in Ecology and Evolution.

Phylogenetic patterns are not proxies of community assembly mechanisms (they are far better). 2015. Pille Gerhold, James F. Cahill Jr, Marten Winter, Igor V. Bartish and Andreas Prinzing. Functional Ecology

Community assembly has always provided some of the most challenging puzzles for ecologists. Communities are complex, vaguely delimited, involve multi-species interactions, and assemble with seemingly immense variation. Thousands of papers have been dedicated to understanding community assembly, and many have proposed different approaches understanding communities. These range from the ever popular abiotic/biotic filtering concept, functional traits, coexistence theory, island biogeography, metacommunity theory, neutral theory, and phylogenetic patterns. It is probably fair to say that no one existing approach is adequate to completely describe or predict community assembly.

One response to this problem is the growing demand to expand the lens of “community” to cover greater spatial and temporal scales. This owes a lot, directly and indirectly, to Robert Ricklefs’ influential Sewall Wright Award lecture on the Disintegration of the Ecological Community. There is also a strong trend towards re-integrating evolutionary history into studies of community ecology. Coincidentally, or perhaps not, this is occurring as so-called ‘eco-phylogenetic’ approaches have been increasingly criticised. If nothing else, eco-phylogenetics provided a path for, and popularized, the idea of reintegrating evolution into community ecology.

I’ll highlight two particular papers that address this re-integration in surprisingly convergent ways. Both have macroevolution slants (that is, they focus on the impacts and drivers of speciation and extinction, sympatry, allopatry, etc), and an interest in the feedbacks between community interactions and these processes. The first, from Pille Gerhold, James F. Cahill Jr, Marten Winter, Igor V. Bartish and Andreas Prinzing, positions itself as the phoenix from the ashes of eco-phylogenetics (as seen in their particularly enthusiastic title :) ). Evolutionary history, captured by phylogenies, was originally of interest to ecologists not for what it was, but because it could (sometimes, maybe) act as a proxy for species traits and niches. This paper does an excellent job of laying out the various hypotheses that went behind this type of approach and showing why they are not reliably true. If for no other reason, it is worth reading the paper for its clear critique of the foundation of eco-phylogenetics. Using patterns in phylogenies as proxies for the outcomes of particular ecological processes being clearly suspect, the authors argue that explicitly thinking of phylogenetic patterns as the result of both ecological and evolutionary processes is far more informative. [I’ll return to this in a bit with their examples below].

The second paper is written by two big names in their respective fields: Gary Mittlebach (ecology) and Doug Schemske (evolution). The title is a bit vague (“Ecological and evolutionary perspectives on community assembly”), but it turns out that they too have converged on the importance of considering evolutionary history in order to understand community assembly. In particular they focus on the problematic nature of the species pool: species pools are nearly always treated as a static object changing little through time or space and are notoriously difficult to define. However, the species pool underlies null model approaches used to test communities for differences from a random expectation. So defining it correctly is important.

From the early days, Elton and others defined the species pool as the group of species that can disperse to and colonize a community. However, the species pool may be dynamic, and they note “To date, relatively little attention has been focused on the feedback that occurs between local community species composition, biotic interactions, and the diversification processes that generate regional species pools.”

This paper does an excellent job of explaining how macroevolutionary processes can alter a regional species pool. The most obvious example is the process of adaptive radiation in island-like systems, where competition for resources drives ecological divergence and speciation. Darwin’s finches, Anolis lizards, and cichlid fishes provide well-known examples of this rapid expansion of the species pool through inter-specific interactions. On mainland systems, speciation may be more likely to occur in allopatry, and the rate limiting step for range expansion (leading to secondary sympatry and only then increasing a species pool) is often interspecific interactions. One study found that secondary sympatry took 7my on average, though speciation alone took only 3my. So the species pool is the outcome of constant feedbacks between species interactions and evolutionary processes.
From Mittlebach & Schemske. Figure illustrating the feedbacks between evolution and ecological interactions, in producing the species pool.
Both papers provide useful examples of how such incorporating evolution into community ecology may prove useful. As a simple example, Mittlebach and Schemske point out that evolution can greatly alter the utility of Island Biogeography Theory: given enough time, speciation events including adaptive radiations, greatly increase the (non-mainland) species pool and would strongly alter predictions of diversity, especially for distant islands.

The Gerhold et al. paper provides the below illustrations as additional possibilities for how evolution and community interactions may feedback.
From Gerhold et al. Two examples of how evolution and communities might interact.

It is certainly interesting to see this shift towards how we envision and study communities. The historical focus on local space and time no doubt reflects ecologists' attempt to limit the problem to a manageable frame. But there is some logic behind expanding our definition of communities to larger spatial scales and greater time periods, especially since there are usually no true boundaries defining communities in space and time. Answering which specific time scales and spatial scales most useful to understanding communities is difficult: if we increase the time or space we consider, how and when does the additional information provided decline? The next step is to consider evolution in this fashion for real organisms, and evaluate the true utility of this approach.  

Saturday, March 14, 2015

The fruits of our labour: the evolution of crops

#Guest post by Francesco Janzen.

Have you ever wondered how much work and time has been put into producing the food you eat today: that juicy apple, or that fresh loaf of bread? In modern times, we can easily recognize fruits and vegetables such as tomatoes, corn, and bananas, but would it surprise you that these foods have not always looked the way they do? Like all parts of the living world, food crops have changed much over time, and this change is directly linked to human efforts (Purseglove, 1965; Allaby et al., 2015). 

Agriculture began approximately 11,000-12,000 years ago, and has originated in several parts of the world (National Geographic, 2015). Humans domesticated wheat in the Fertile Crescent, or Near East approximately 8,000-9,000 years ago. (Nevo, 2014; National Geographic, 2015). In China, rice is proposed to have been domesticated 10,000-20,000 years ago (Gross & Zhao, 2014; National Geographic, 2015). Across the ocean, squash was domesticated about 10,000 years ago in what is known today as Mexico, and the beginning of sunflower cultivation began in North America around 5,000 years ago (Janick, 2013; National Geographic, 2015). All of these domestications began with wild progenitors of today’s crop species (Gross et al., 2014; Allaby et al., 2015).  

But how did the wild crops of ancient times develop into the modern ones we know today? John William Purseglove, a former tropical agricultural officer and director of the Singapore Botanic Gardens, discussed the ways in which humans have changed crop species over time in a chapter of “The Genetics of Colonizing Species” (1965). In his chapter, “The Spread of Tropical Crops”, Purseglove (1965) states that humans would have begun the first agricultural crops with a subset of desired plants from the original wild population. This subset would not possess the genetic diversity of the original population, essentially producing a genetic bottleneck effect (Purseglove, 1965). Furthermore, certain desired traits would be selected for in this new population, so breeding strategies would overtime change the traits expressed, such as larger fruit, seedless fruit, lack of defense mechanisms, etc. (Purseglove, 1965). Although they benefit humans, these changes could potentially decrease the competitive ability of these new plants. This intrinsically ties their survival to human assistance (Purseglove, 1965). 

Humans have not only changed the physical characteristics of crop plants; they have altered their geographic distributions as well. Compared to their wild ancestors, most crop plants are now grown in areas far removed from their origin, such as with vanilla (Vanilla planifolia). Vanilla originated in Mexico, but is now grown in large numbers in Madagascar (Purseglove, 1965). In fact, vanilla and most other crops are much more successful in their new environments, but why is this so? Purseglove (1965) proposed that by moving a crop plant into a new habitat where predators or disease are absent, little would control population sizes, and increase crop yields. 

Visible difference between a wild strawberry (Fragaria virginiana, left) and a domestic strawberry (Fragaria x ananassa, right), from

The new environments that domestic crops are exposed to may further increase the genetic gap with their wild ancestors. Under new, adverse environmental conditions, a population of a crop may be culled, save for a few individuals possessing recessive genes that confer a benefit to coping with the altered conditions (Purseglove, 1965). The remaining individuals reproduce, which shifts the next generation’s genotypic frequency (Purseglove, 1965). In addition, this can effectively expand the range of the domestic crop, whereas the wild type remains restricted to its original range (Purseglove, 1965). 

Science has come a long way since Purseglove proposed his ideas 50 years ago, and the advent of DNA has helped improve our understanding of evolution. With respect to the evolution of crops, DNA allows for testing of certain theories proposed, one such being the bottleneck effect. A study conducted by Gross et al. (2014) investigated whether perennial crop species, specifically the apple (Malus x domestica) showed a decrease in genetic diversity when compared to closely related wild species. They expected that there would have been a narrowing of genetic diversity at two moments in history. Firstly, during a domestication bottleneck, similar to that proposed by Purseglove (1965), and secondly during an improvement bottleneck, where desirable traits in the crop species were selected for to produce elite cultivars (Gross et al., 2014). 

A visual depiction of the bottleneck effect, where the bottleneck represents stochastic (random) events, from
By sequencing specific DNA regions of 11 varieties of apple cultivar (both ancient and modern), and that of three wild species, Gross et a. (2014) sought to demonstrate that domesticated cultivars show less genetic diversity than wild species. The regions selected were areas where each species show a variable amount of repeated sequence length, known as microsatellites, allowing for easy comparison of genetic quality (Gross et al., 2014). What they found, contrary to what was expected, was that domestic apples have not undergone a significant reduction of genetic diversity, either at the domestication or improvement phases (Gross et al., 2014). This evidence shows that not all theories produced 50 or more years ago withstand the test of time, especially when new tools to test these theories become available.   

So how does any of this information impact management practice of controlling invasive species? Purseglove (1965) stated in his chapter that by understanding the evolution of crop species, we gain insight into the success of introduced weed species. Although weeds do not require any human assistance in survival, the forces acting on them may be the similar to those acting on agricultural crops. Just as crops experience a release from predators and disease when removed from their native habitats, weeds may also undergo this release, contributing to their widespread success (Purseglove, 1965). This parallel could be quite useful in the understanding and management of weedy species.  


Allaby, R.G., Gutaker R., Clarke, A.C., Pearson, N., Ware, R., Palmer, S.A., Kitchen, 
J.L., and Smith, O. 2015. Using archaeogenomic and computational approaches to unravel the history of local adaptation in crops. Philosophical Transactions Royal Society  370: 20130377.

Gross, B.L., Henk, A.D., Richards, C.M., Fazio, G., and Volk, G.M. 2014. Genetic 
diversity in Malus × Domestica (Rosaceae) through time in response to domestication. American Journal of Botany 101(10): 1770-1779.   

Gross, B.L. & Zhao, Z. 2014. Archaeological and genetic insights into the origins of 
domesticated rice. Proceedings of the National Academy of Sciences 111(17): 6190-6197. 

Janick, J. 2013. Development of New World crops by indigenous Americans. 
Horticultural Science 48(4): 406-412.   

National Geographic Society. 2015. The development of agriculture. Retrieved from 

Nevo, E. 2014. Evolution of wild emmer wheat and crop improvement. Journal of 
Systematics and Evolution 52(6): 673-696. 

Purseglove, J.W. (1965). The spread of tropical crops. In H.G. Baker, and G.L Stebbins 
(Eds.). The Genetics of Colonizing Species. New York: Academic Press.

Tuesday, March 10, 2015

Scientific Presentations: the Dos and Don'ts

With the ESA submission deadline just passing, the Cadotte Lab decided that it would be helpful to dish out a few tips on how to make a presentation that is both enjoyable for your audience and fun for you to give. Presenting in front of people is never easy; giving a presentation about your own study can be even harder since you have to condense months (or even years) worth of information into a 15 minute time period. So with this in mind here are a few tips for each of the main sections of a presentation:

Note, the percentage by each section heading indicates the relative amount of time you should spend on that section.

Title Slide (5%)

This is the first chance you’ll get to catch your audience’s attention, so be interesting!

The title of your presentation depends on the type of audience you’ll be presenting to, so gauge it accordingly. If your audience is a bunch of people with only general biology backgrounds or people that are from completely different fields then don’t complicate things using heavy jargon.

Generally for the title, you want to:
  • Be witty and interesting
  • Convey the main message or main result from your study

If you’re speaking to a broad audience it could be helpful to have a broad title and then separate it from a more specific title.

Besides the title you’ll also want to include your name and affiliation. Depending on the type of talk, for instance an honors thesis, you should also include your supervisor’s name. If you are collaborating with many people on a study you should also include their names. However, make sure that your name is on the first slide, since you are the presenter, and then on a second slide include a special acknowledgement of the other people involved. It’s also recommended that you acknowledge these people throughout the talk, such as in the methods. 

Introduction (10-15%)

Don’t make this section too long. Give just enough background that the audience can understand the concepts that you’ll be discussing and how it relates to the question you are trying to answer.
Generally for the introduction, you want to:
  • Have the background information displayed in a simple to understand way
    • You could use info-graphs here to reinforce an idea
  • By the 2nd or 3rd slide you’ll want to state your study objectives or hypotheses
    • You could create ‘toy’ graphs to describe your hypotheses / predictions

Methods (10-15%)

Be very concise with this section. Everyone understands that a lot of work went into performing your study; however, you don’t want to overwhelm your audience with all the nitty-gritty things you had to do. Give enough detail that people understand what you did and if possible try and summarize your methods in a simple figure.

Generally for the methods, you want to talk about:
  • The treatments used, sample size, the measurements taken and how they were done, and the statistics that you performed

A note on statistics: try to steer clear of very complicated statistics. Most likely your audience will have a basic understanding of stats, but you may lose people if you get too complicated. When talking about your stats, make sure that you can give an easy to understand explanation of how they work.

Results (50%)

This is the biggest and best section; it’s where you get to show people all the cool and exciting things you’ve done! However, the only way you can convey how awesome your results are is by clearly explaining them.

Generally for the results, you want to:
  • Stick to the main results
    • You may have a lot different results but always make sure that what you are describing relates directly to the main message of your study
    • Don’t overwhelm your audience
  • Always thoroughly describe your graphs
    • Describe what variables were you examining (the axes)
    •  Why is the graph important?
      • What is the relationship that the graph is showing?
        • The title of the slide could be used to state what the result is
    • You’ve spent a lot of time making these graphs and analyzing them - so you know them very well, but your audience doesn’t yet. Take time to walk them through the graphs.
    •  If you’re showing several graphs in sequence, make sure to note if the axes are changing
      •  If the graphs are very similar it might be helpful to have a break between slides or to use an animation.
  •  Don’t show too many stats
    •  Just state the p-values and which stats were used
  • Avoid tables if possible
    •  Summarize all the information in an easy to follow figure
    •  If you can’t avoid using a table make it as appealing as possible
      •   Highlight key parts or add arrows to show trends if they exist

Discussion (20%)

Now start bringing everything back together. Your audience may have gotten lost during your results section, so now is the time to refocus them so that they can see the big picture.
Generally for the discussion, you want to:
  • Restate your hypotheses
  • Restate you main results
  • Describe how you could improve your study
  • Describe the next steps for your work and the field in general

In the end you’ll want to describe the broader implications of your work and give the audience a take home message so that they know that your work is bettering the field in some way.  

Acknowledgements (5%)

Don’t forget to thank everyone who has helped you through this whole process! This includes your supervisor, people who helped you with data analysis or revising your paper, or all the volunteers you helped you conduct your field work or lab work. You’ll also want to acknowledge your institution as well as anyone who provided funding to your project.

General tips

Here’s a quick list of tips to use throughout your presentation:
  • Use large text font
    • Don’t be flashy, make sure it’s easy to read
  • Don’t put too much text on a slide
    • This distracts the audience
  •  Don’t put any important point (text or an image) at the bottom 1/3rd of a slide
    • Depending on the room you are presenting in it may be very hard for the audience to see it
    • In general, try and keep everything within the top 2/3rd of the slide
  • Don’t put too many animations on a slide
    • This can be very distracting for the audience
  • Don’t read off your slides
    •  Use presenter view if you can’t memorize everything
  • Including outlines
    •  Not necessary in a short talk, but could be helpful in a longer talk
  • If you run out of time
    • Panic on the inside not the outside!
    • Acknowledge that you’re running out of time and start wrapping things up
      • Start talking about the broad implications of your work and maybe future directions you plan to take
      • If you have more slides, skip over them but tell the audience what you were planning on showing. If they ask questions about what you were going to show you can go back to those slides
  • Don’t talk too fast!
    • Everyone gets nervous! Take a deep breath and calm yourself down, the calmer you are the easier it is for your audience to follow you

Monday, March 9, 2015

In praise of difficult questions.

There were a lot of people at my graduate institution who weren’t afraid to ask probing, thoughtful, difficult questions. They asked them seemingly without any concern about making the recipient feel bad, although students were more likely to receive kinder versions, and they asked them at departmental talks, committee meetings, student seminars, and at faculty interviews. I’ll admit there were times when this made me uncomfortable, and it certainly contributed no small amount of anxiety before giving talks there (and I’m sure I’m not the only person who felt that way).

These days I find myself missing those tough questions, not because I enjoy confrontation per se, but because they made an important contribution to my education.

To be clear, bullying questions or competitive questioning meant to highlight the questioner’s intelligence are a waste of time (e.g. two minutes of talking about your research followed by "what do you think about that?"). Critical thinking, while one of the most important aspects of a post-graduate education, can't be taught. But tough questions and questioners model critical thinking for students in the most direct way. Being at the front of the room talking does not automatically grant expert status: the speaker's ideas must be clear and robust to debate. 

Difficult questions benefit a speaker too - they are the clearest demonstration that the audience has engaged with their work. The most useful talks are those in which the questions are thought provoking for both the speaker and the audience. 

And finally, it can be refreshing when a questioner holds a person to actually answering the question. Science is built on debate and some times disagreement. Hard questions made me feel that the people asking them were expressing a preference for good science, even if the cost was some discomfort or social unease. And that feels like an important thing to express.

Friday, March 6, 2015

Distilling an ocean of theory and adding a few of your own drops

I recently completed my PhD qualifying exam at the University of Toronto-Scarborough for the Department of Physical and Environmental Science. Prior to going through the process the exam took on a sort of “black box” quality where I’d seen colleagues pass through unscathed but the depth of questioning that took place during the oral examination remained unclear. So I thought it might be of some value to comment on my experience with the process.

The format of these exams is fairly variable across departments and between institutions with some requiring the production of several essays in a short period of time, some based on an extensive readings list, some formatted as a proposal defense and others including some or all of these components. My exam took the form of a proposal defense which required submitting a 9000-word proposal outlining the theoretical framework & justifications for my research questions, hypotheses, objectives, methodologies, preliminary results, discussion and thoughts on the significance of the work, a 25-minute presentation of this proposal followed by an oral examination that lasted about an hour and 30 minutes. These exams are typically meant to be taken at the early stages of one’s PhD, but it seems that they often get kicked further down the road, as was the case with mine which I completed half way into my 3rd year of a 5 year program. This had its advantages and disadvantages where further progress allowed presentation and discussion of some interesting findings and a clearer picture of what my thesis is going to look like, but also came with the colossal challenge of organizing everything into what seemed like a miniscule 25-minute presentation. This was probably the most challenging academic exercise I have faced.

I finalized my presentation a few days before my exam, and felt that it had a nice balance between theory and my contributions, but this only after “throwing away” 100+ slides in the 2 weeks leading up to the exam… And while that might sound like a total waste of time, it actually forced me to distill what seemed like an “ocean of theory” to the essential elements that grounded my work. Further, developing slides that can visually communicate complex theory is a great form of study that can serve you well during the oral exam; even if you can’t show the slides you will know the material. Also, I can’t overstate the importance of peer and supervisory assistance here. I was extremely lucky to have my presentation lovingly torn to shreds by my lab mates. This can be a terrifying process as we know that imposter syndrome is alive and well in academia ( Yet, we of course survive these practice talks and our presentations benefit greatly.

Once I was happy with the content and flow of my talk I decided to inject a little humour by photoshopping some images and spattering in a couple silly animations. This was probably some kind of self-defense mechanism where I was hoping that by putting a smile on the face of an examiner I might be able to ease my own nerves and the general tension that goes along with a comprehensive exam. Of course, whether this succeeds or not will depend on the demeanor of your examiners, your delivery and probably the general quality of the rest of the presentation. In my case, I found that the humour worked and offered a nice lull in the tension. I highly recommend trying this, once you’ve nailed down the meat of the talk of course. Beyond attempts at humour, you should know the talk. You shouldn’t be reading off any notes and should only read out points on the slide that are essential theory items or specific research questions, hypotheses or findings. There will be an upcoming blog post on presentation tips, so I’ll stop there… Just remember that in this exam, your presentation sets the tone. It is your opportunity to articulate your comprehension of the subject and the novelty of your work.

The written component of the proposal, on the other hand, can seem to be propelled by a perpetual motion machine generating an endless sprawl of “conceptual axes”, “synthetic approaches” and “novel perspectives” about your thesis topic. Here, you can definitely produce a fairly comprehensive picture of the subject and your perspectives but you’ll still have to tug the reigns so as not to irritate your readers with a bloated document. If you find yourself delving into the linkages between your thesis and systems theory, and you’re not in physics, odds are you’ve gone too far. Everything in your written proposal is essentially fair-game for the oral examination, so don’t let it disappear from your desktop once you’ve submitted it. You will most certainly get questions about the methods you’ve proposed or have employed, and you will need to be able to justify your choices and situate your studies within the literature.

The oral examination will surely be one of the most unnerving experiences of your academic life, but you can minimize your unease by continually drawing those links between your thesis and the literature in the weeks leading up to the exam. I found the oral exam to be a very fair process where I was tested on the biophysical interactions that I was examining, the measures that I used, and the conceptual links between my thesis components and the trends in the literature. Now, my thesis is fairly atypical in that it takes a multi-disciplinary approach to a larger topic, and this definitely generated some questions about the linkages between the various components. But beyond that challenge I think any questions about the “grand scheme” of your thesis can be addressed by highlighting those initial motivations that you included in your application to your program. In my application, I was required to write a page about why interdisciplinary perspectives are essential in the field of environmental science, and I was able to pull from that motivation to answer these kinds of questions. Odds are that your initial reasons for engaging with a certain research topic will ground a lot of your answers during the oral examination. One question that I didn’t anticipate was essentially “where do you see yourself in 10 years”?  I think in our PhD’s we can easily get tunnel vision and forget that there is an end to the process at which point we’ll move on to something new. So don’t forget about that light at the end of the tunnel during the exam. Think about your future aspirations and how far you’ve come since you became fascinated with your topic. Your examiners want to feel that engagement and passion. And you will get questions about the theory that are right in your wheelhouse, so take advantage when they appear and highlight both your understanding of the unanswered questions and how your work is not just adding to the complexity but is helping to bridge those gaps.

In the end, after all the late nights of writing, pecking at bowls of nuts (because cooking takes too long) and re-arranging your presentation slides for the 100th time, you’ll most likely find that this process has probably been the most constructive thing that you’ve ever been a part of.

Wednesday, March 4, 2015

Graduate students- employees, scholars, or something in between?

Graduate school has always required that students balance research, classwork, and teaching activities (perhaps with some time for complaining). Though many aspects of graduate school are unchanged, there can be a tension between grad students and their employers driven by a shift in both these groups’ expectations, and the complex nature of STEM graduate school.

This is illustrated well by the current strikes of teaching assistants (primarily graduate students) at University of Toronto and York University – both major Canadian institutions. [And even more extreme cases exist]. The union at U of T has become a defacto union for graduate student issues as well, and the primary sticking point appears to be graduate student stipends, which are far below the poverty line. The students there are striking as teaching assistants (so research work can continue) but their main issue is a holistic “graduate student” issue.

Supposing the components of graduate school have remained similar over the years, why might tension be increasing between what graduate students and faculty/departments expect? Partly because so many other things have changed-–the economy, the workforce, cultural expectations. I think that in the past, it was easier to consider graduate school as a place of passion and intellectual curiosity, where one would make a lousy salary, but consider it “worth it”.  Today, the cost-benefit analysis for getting a PhD is considerably less positive – it takes longer to get a PhD, on average, and the payoff in terms of obtaining a faculty or other job, makes this less clear. The cost of education, particularly in the US, is immense: the possibility of student loan debt from 4-8 years of postgraduate education is fairly unpalatable.

From Nature.
As the realities change, so too do the expectations. That on its own would be the source of some tension. But the dual nature of graduate school compounds the tensions since it is difficult for graduate students, faculty, and department heads to evaluate what reasonable expectations are for things such as pay, hours, vacation time. For most students, graduate school has aspects of both a clear job (usually teaching duties—running labs, marking tests and assignments, sometimes lecture duties) and a clear studentship (class work, appraisal exams, all culminating in a defense). It also includes research, done in a lab or the field, which may vary between being a job (doing tasks primarily for the PI, monitoring undergrads, ordering supplies) and an intense learning experience. Employment involves contracts with expectations and restrictions, set hours and wages; being a student lacks the same expectations but is often associated with greater freedom and personal growth. The extent to which faculty and graduate students see the position as “student” or as “job” may well differ.

The interaction of economic realities with the duality of graduate school is an important issue. Should graduate school be considered the start of one's working life? If so, is it equivalent to an entry-level position? After all, TAs do a lot of grunt work -- marking, marking, and more marking, run simple labs and tutoring sessions -- and many universities hire undergraduates to do similar tasks. On the other hand, graduate students are also high-achievers doing complicated analyses for research, and have reasonably high education levels. Graduate school may come with opportunity costs  - peers with similar educations tend to have jobs and retirement funds. In contrast, the pure academic path usually means you will live frugally for many years before your first "real" position (and you may be in your 30s or later before you get it).

There may be some generational changes as well. It is suggested that Millenials/Generation Y have different priorities than previous generations: they strongly desire fulfilment from their work, but also competitive compensation and job flexibility (e.g.). The downsides of graduate school are greater and perhaps more obvious to this generation: if it is a job, it is poorly paid and entry-level, if it is a studentship, it comes with an opportunity cost. But how to evaluate it when it is both? It is undeniably easier to go through graduate school for those who don't have to deal with the dualities - such as through having a fellowship that allows a student to do research and classes only. Most people are still in graduate school for the same reasons as they always have been - love of science and learning. That hasn't changed. But the meaning of graduate school itself may well have changed. There is no one or easy solution to the issue. But no doubt a recognition by both sides of the realities of being a graduate student (and a supervisor) and honest communication about expectations on both sides (and sometimes, perhaps a little pressure) would go far. 

The real truth about graduate school according to the Simpsons...

**I just want to note that this is inspired by--but not addressing--the U of Toronto situation, and any comments that simply want to debate specific circumstances in particular universities will be deleted...
Larger discussion of the general issue always welcome.

Friday, February 27, 2015

Going natural: biological control of insect pests

*Guest post by Sheena Fry

Damage caused by agriculture pests is one of the most important factors of crop yield reduction (Cramer, 1967; Oerke et al., 1994) and can cause billions of dollars worth of damage each year (e.g. in Brazil, insect pests cause up to US$ 17.7 billon year-1 of damage, Oliveira et al., 2014). Due to its economic impact, controlling pest populations is a priority for agricultural scientists. Chemical control is the primary method of pest management due to its relatively low costs and high effectiveness (Cooper and Dobson, 2007). Despite the widespread use of chemical controls, the health and environmental risks associated with their use are well known (Pimentel et al. 1992; Pimentel, 2005). The risks associated with pesticide use, as well as the evolution of pesticide resistance, has lead to a surge in interest in the use of biological control for pest management over the past 50 years.

The most important decision to be made in a biological control program is which biological control agent to use against a pest. Success rates for biological control of insects are low, with only 24-35% resulting in the establishment of the introduced species (Hall and Ehler 1979, van Lentern, 1983) and only 16% resulting in complete control of pest species (Hall et al., 1980). What determines the success of colonization and establishment is a key question in biological control research and must be answered in order to make predictions about establishment and success of introduced species. In 1965, Debach attempted to identify characteristics of successful colonizers but found that neither success nor failure could be explained by the presence or absence of a common characteristic. Over the past 50 years, several attempts have been made to list characteristics of successful invaders (e.g. Murdoch et al., 1985) and while they seem logical, there are too many exceptions for them to be used as a reliable indicator of a species’ potential to colonize and establish in a new area. DeBach saw “no possibility of predicting the fate of a purposely colonized imported entomophagous insect” and at present it remains an elusive goal (Fischbein and Corley, 2015).
Paul Debach 1914-1992

The environmental and health risks associated with chemical controls of insects (see references above) are not an issue when using biological controls. In addition to this, successfully established biological control species will be able to maintain stable populations without the need for additional investment by humans (unlike chemical controls, which must be applied each season). Despite the obvious benefits of biological control, there are also risks associated with the use of insects in biological control, such as the risk to non-targeted species (Simberloff and Stiling, 1996) or host switching. In order to make decisions about biological control we need to understand the evolution of introduced species in new environments, which can increase the efficiency of biological control (through post-colonization adaptation) or can increase the risk to non-targeted species. “The Genetics of Colonizing Species” (1965) brought together evolutionary biologists and ecologists (theoretical and applied) to discuss the evolution of introduced species. In DeBach’s chapter, he focused on colonizing entomophagous insects and, using biological control case studies, looked at the relative influence of pre- and post colonization adaptation, a key question in evolutionary biology. One such case study was the introduction of a parasitoid wasp (Comperiella bifasciata Howard, Figure 1), which was introduced to control a citrus pest, the California red scale (Aonidiella aurantii Maskell). The parasitoid wasp was released throughout southern California but initially was only able to establish at one location. It slowly spread and increased in abundance and, by 1957 was found at various locations throughout southern California. DeBach interpreted the poor initial establishment of the parasite followed by intense colonization as an indication that genetic adaptation had occurred.

Figure 1. A female parasitic wasp (Comperiella bifasciata Howard) infesting a California red scale (Aonidiella aurantii Maskell), from Forester et al. (1995).

Fifty years have passed since the publication of “The Genetics of Colonizing Species” (1965) and understanding the relative effects of pre- and post-colonization adaptation has remained an important issue. Phillips and colleagues (2008) examined the relative effects of genetic drift and selection in the frequencies of two asexually reproducing, genetically distinct parasitoid biotypes. This South American parasitoid wasp (Micrictonus hyperidae Loan, Figure 2) was introduced as a biological control for a pasture pest (Listronotus bonariensis Kuschel, Figure 2) in New Zealand in 1992. Phillips and colleagues recorded the relative frequencies of each biotype over a 10-year period and found that changes in biotype frequency were consistent with strong directional selection, favouring one of the parasitoid biotypes. This resulted in parasitoid populations being better adapted to New Zealand conditions than those originally released. 

Figure 2. A female parasitic wasp (Micrictonus hyperidae Loan, right) infesting a South American weevil (Listronotus bonariensis Kuschel, left). © Copyright AgResearch

There have been significant advance in the tools (statistical and molecular) available for the study of post-colonization success and adaptation since the publication of “The Genetics of Colonizing Species” (1965). These tools allow for better understanding of the post-colonization process of introduced species but, despite these advances, there has been little progress towards being able to predict the success of introduced species.

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