From #fieldworkfail to Published Paper

Amphipods are, unfortunately, not very photogenic. But here you can see some of my study organisms swimming around in a mesocosm in the laboratory, shredding some leaf litter like it’s their business (because it is).

It can be intimidating to try to turn your research into an academic paper. I think that sometimes we have the idea that a project has to go perfectly, or reveal some really fascinating new information, in order to be worth spending the time and effort to publish.

This is the story of not that kind of project.

One of my dissertation chapters was just published in the journal Aquatic Ecology. You can read it here.

The project originated from a need to show that the results of my lab experiments were relevant to real-world situations. To start out my PhD, I had done several experiments with amphipods – small crustacean invertebrates common to central European streams – in containers, which we call mesocosms. I filled the mesocosms with water and different kinds of leaves, then added different species and combinations of amphipods. After a few weeks, I saw how much leaf litter the amphipods had eaten.

We found that there were some differences between amphipod species in how much they ate, and their preferences for different kinds of leaves based on nutrient content or toughness (that work is here). But the lab setting was quite different than real streams.

So I worked with two students from our limnoecology course (which includes both bachelors and masters students) to develop a field experiment that would test the same types of amphipod-leaf combinations in streams.

We built “cages” out of PVC pipe with 1-mm mesh over the ends. We would put amphipods and leaf litter inside the cages, zip tie them to a cement block, and place the cement block in a stream. We did this in two places in Eastern Switzerland, and with two different species of amphipod.

After two weeks, we pulled half the cement blocks and cages out. After four weeks, we pulled the other half out. Moving all those cement blocks around was pretty tough. I think of myself as strong and the two students were burly Swiss guys, but by the time we pulled the last cement block up a muddy stream bank I was ready to never do this type of experiment again.

Elvira and our two students, Marcel and Denis, with an experimental block in the stream. This was the stream with easy access; the other had a tall, steep bank that was a real haul to get in and out of.

Unfortunately, when I analyzed the data, it was clear that something had gone wrong. The data made no sense.

The control cages, with no amphipods in them, had lost more leaf litter than the ones with amphipods – which shouldn’t be the case since they only had bacteria and fungi decomposing them, whereas the amphipod cages had shredding invertebrates. And the cages we had removed after two weeks had lost more leaf litter than the ones we left in the stream for four weeks.

These are not the “results” you want to see.

We must have somewhere along the way made a mistake in labeling or putting material into cages, though I couldn’t see how. I tried to reconstruct what could have gone wrong, if labels could have gotten swapped or material misplaced. I don’t have an answer, but the data weren’t reliable. I couldn’t be sure that there was some ecological meaning behind the strange pattern. It could have just been human error.

I felt bad for the students I was working with, because it can be discouraging to do your first research project and not find any interesting results. It wasn’t the experience I wanted to have given them.

My supervisor and I agreed, with regret, that we had to redo the experiment. I was NOT HAPPY. I wasn’t mad at him, because I knew he was right, but I really didn’t want to do it. I’ve never been less excited to go do fieldwork.

But back out into the field I went with my cages and concrete blocks (and no students this time). In case we made more mistakes, we designed the experiment a bit differently. We had one really well-replicated timepoint instead of two timepoints with less replicates, and worked in one stream instead of two.

Begrudgingly, we hauled the blocks to the stream and then hauled them back out again.

Cages zip-tied to cement blocks and deployed in the stream. You can see the brown leaf litter inside the enclosure.

And then for 2 ½ years I ignored the data, until my dissertation was due, at which point I frantically analyzed it and turned it into a chapter.

The draft that I initially submitted (to the journal and in my dissertation) was not what I would call my best work. My FasterSkier colleague Gavin generously offered to do some copy-editing, and I was ashamed at how many mistakes he found. I hope he doesn’t think less of me. A fellow PhD student, Moritz, also read it for me, and had a lot of very prescient criticisms.

But through all of that and peer review, the paper improved. Even though it is not going to change the course of history, I’m glad that I put together the analyses and published it, because we found two kind of interesting things.

The first was about species differences. I had used two amphipod species in the experiment (separately, not mixed together). Per capita, one species ate a lot more/faster than the other… but that species was also twice as big as the other! So per biomass, the species had nearly identical consumption rates.

The metabolic theory of ecology is a powerful framework that explains a lot of patterns we see in the world. One of its rules is that metabolism does not scale linearly with body size (here’s a good blog post explainer of the theory and data and here’s the Wikipedia article). That is, an organism twice as big shouldn’t have twice the metabolic needs of a smaller organism. It should need some more energy, but not double.

This relates to my results because the consumption of leaf litter was directly fueling the amphipods’ metabolism. They may have gotten some energy and resources from elsewhere in the cages, but we didn’t put any plant material or other food sources in there. So we could expect to roughly substitute “consumption” for “metabolism” in this body size-metabolism relationship.

Metabolic theory was originally developed looking across all of life, from tiny organisms to elephants, so our twofold size difference among the two amphipod species isn’t that big. That makes it less surprising that the two species have the same per-biomass food consumption rates. But it’s still interesting.

The second interesting result had to do with how the two species fed when they were offered mixtures of different kinds of leaves. Some leaves are “better”, with higher nutrient contents, for example. Both species had consumed these leaves at high rates when they were offered those leaves alone, and had comparatively lower consumption rates when offered only poor-quality leaves.

In the mixtures, one species ate the “better” leaves even faster than would be expected based on the rates in single-species mixtures. That is, when offered better and worse food sources, they preferentially ate the better ones. The other species did not exhibit this preferential feeding behavior.

I thought this was mildly interesting, but I realized it was even cooler based on a comment from one of our peer reviewers. (S)he pointed out that this meant that streams inhabited by one species or the other might have different nutrient cycling patterns, if it was the species that preferentially ate all of the high-nutrient leaves, or not. We could link this to neat research by some other scientists. It was a truly helpful nudge in the peer review process.

So, while I had hated this project at one point, it’s finally published. And I think it was worth pushing through.

It was not a perfect project, but projects don’t have to be perfect for it to be worth telling their stories and sharing their data.

My #365papers Experiment in 2018

This year, based on initiatives by some other ecologists in the past, I embarked on the #365papers challenge. The idea of the challenge is that in academia, we end up skimming a lot of material in papers: we jump to the figures, or look for a specific part of the methods or one line of the results we need. Instead, this challenge urged people to read deeper. Every day, they should read a whole paper.

(Jacquelyn Gill and Meghan Duffy launched the initiative and wrote about their first years of it. But #365papers is now not just in ecology, but in other academic fields. Some of the past recaps I read were by Anne Jefferson, Joshua Drew, Elina Mäntylä, and Caitlin MacKenzie. Caitlin’s was probably the post that catalyzed m to do the challenge.)

I knew that 365 papers was too ambitious for me, and that I wouldn’t (and didn’t want to!) read on the weekends, for example. I decided to try nevertheless to read a paper every weekday in 2018, which would be 261 days total.

In the end, I clocked in at 217 papers (I read more than that, but see below for what I counted as a “paper” for this challenge) – not bad! I tweeted links to all the papers, so you can see my list via this Twitter search. I can confidently say that I have never read so many papers in a year.

In fact, I am guessing that this is more papers than I have read in their entirety (not skimming or extracting, as mentioned above), in my total career before 2018. That’s embarrassing to admit but I am guessing it’s not that unusual. (What do you think, if we’re all being honest here?)

This was a great exercise. I learned so much about writing, for one thing – there’s no better way to learn to write than to read a lot.

But the thing that was most exciting was that I read a lot more, and a lot of fun pieces. I had gotten to a place where there were so many papers that I felt I had to read for my own work, that I would just look at the pile, blanche, and put it off for later. Reading had become a chore, not something fun.

Titles_wordle

A Wordle of the paper titles. On my website it says I am a community and ecosystem ecologist, and I guess my reading choices reflect that! (I’d be interested to make a Wordle based on the abstracts, to see if there are more diverse words than the ones we choose for titles – but I didn’t make time to extract all the abstracts for that.)

That’s not a great way to do research, and luckily the challenge changed my reading status quo. If I was reading every day, I reasoned, then not every paper had to be directly related to my work as a community ecologist. There would be ample time for that, but I could also read things that simply looked interesting. And I did! I devoured Table of Contents emails from journals with glee and read about all sorts of things – evolution, the physical science of climate change, remote sensing.

These papers, despite seeming like frivolous choices, taught me a lot about science. Just because they were not about exactly what I was researching does not mean they did not inform how I think about things. This was incredibly valuable. We get stuck in our subfields, on our PhD projects, in our own little bubbles. Seeing things from a different angle is great and can catalyze new ideas or different framing of results. Things that didn’t make sense might make sense in a different light.

But I also did read lots of papers directly related to what I was working on. I think I could only do that because it no longer felt like a chore, like a big stack of paper sitting on the corner of my desk glaring at me. This challenge freed me, as strange as that sounds given the time commitment!

And finally, I tweeted each paper, and tagged the authors if possible. This helped me make some new connections and, often, learn about even more cool research. It helped me put faces to names at conferences and gave me the courage to strike up conversations. The social aspect of this challenge was fun and also probably pretty useful in the long run.

For all of the reasons I just mentioned, I would highly recommend this challenge to other academics. (It’s not just in ecology – if you look at the #365papers hashtag on Twitter, there are a lot of different people in different fields taking up the challenge.) Does 365 or 261 papers sound like too many? Set a different goal.  But make it ambitious enough that you are challenging yourself. For me, I found that making it a daily habit was key, because then it doesn’t feel like something you have to schedule (or something you can put off) – you just do it. Then sit down and read a whole paper, with focus and attention to detail. If you like it, why is that? Is the topic of interest to you? The writing good? The analyses particularly appropriate and well-explained? Is it that the visuals add a lot to the paper? Are the hypotheses (and alternative hypotheses) identified clearly, making it easier to follow? Or, if you don’t like it, why is that? Is it the science, or the presentation? What would you do differently?

One thing I didn’t nail down was how to keep notes. I read on paper, so I would highlight important or relevant bits or references to look up. But I don’t have a great system for how to transfer this to Evernote (where I keep papers’ abstracts linked to their online versions, each tagged in topic categories). In the beginning I was adding photos of each part of the paper I had highlighted to its note, but this was too time-consuming and I gave up. In the end it was like, if I had time, I would manually re-type my reading notes into Evernote, and if not, I wouldn’t. I do think the notes are valuable and important to have searchable, so this probably limits the utility of all that reading a little bit. It’s something I will think how to improve for next year. The biggest challenge is time.

In addition to reading a lot, I kept track of some minimal data about each paper I read. I’ll present that below, in a few sections:

  • Where (journals) and when the papers were published
  • Who wrote them – first authorship (gender, nationality, location)
  • A few thoughts about last authorship
  • Grades I assigned the papers when reading – potential biases (had I eaten lunch yet!?) and the three papers I thought were best at the time I read them

I plan to try this challenge again next year, and the data that I summarize will probably inform how I go about it. I’ll discuss that a little at the very end.

What Did I Count as One of My 365  261  217 Papers?

First, some methodological details. For this effort, I didn’t count drafts of papers that I was a co-author on, although that would have upped the number or papers quite a bit because I have been working on a lot of collaborative projects this year. I also didn’t count reading chapters of colleagues’ theses, or a chapter of a book draft. And I didn’t count book chapters, although I did read a few academic books, among them Dennis Chitty’s Do Lemmings Commit Suicide, Mathew Leibold & Jonathan Chase’s Metacommunity Ecology, Andy Friedland and Carol Folt’s Writing Successful Science Proposals, and a book about R Markdown. I started but haven’t finished Mark McPeek’s Evolutionary Community Ecology.

I did count manuscripts that I read for peer review.

Where The Papers Were Published

I didn’t go into this challenge with a specific idea of what I wanted to read. I find papers primarily through Table of Contents alerts, but also through Twitter, references in other papers, and searches for specific topics while I was working on my dissertation or on research proposals. This biases the papers I read to be more likely to be by people I’m already aware of or in journals I already read. Not entirely, but substantially.

We also have a “journal club” in our Altermatt group lab meeting which doesn’t function like a standard one, but instead each person is assigned one or two journals to “follow” and we rotate through each person summarizing the interesting papers in “their” journals once every few months (the cycle length depends on the number of people in the lab at a given time). That’s a good way to notice papers that might be good to read, and since we are a pretty diverse lab in terms of research topics, introduces some novelty. I think it’s a clever idea by my supervisor, Florian.

Given that I wasn’t seeking out papers in a very systematic way, I wasn’t really sure what the final balance between different journals and types of journals would be at the end of the year. The table below shows the number of papers for each of the 63 (!) journals that I read from. That’s more journals than I was expecting! (Alphabetical within each count category)

In addition, I read one preprint on BioRxiv.

I don’t necessarily think that Nature papers are the best ecology out there; that’s not why it tops the list. Seeing EcologyOikos, and Ecology Lettersas the next best-represented journals is probably a better representation of my interests.

But, I do think that Nature (and Science, which had just a few fewer papers) papers get a lot of attention and must have been chosen for a reason (am I naive there?). There are not so many of them in my field and I do try to read them to gauge what other people seem to see as the most important topics. I also read them because it exposes me to research tangential to my field or even entirely in other fields – which I wouldn’t find in ecology journals, but which are important to my overall understanding of my science.

I’m pleased that Ecology & Evolution is one of my top-read journals, because it indicates (along with the rest of the list) that I’m not only reading things for novelty/high-profile science, but also more mechanistic papers that are important to my work even if they aren’t so sexy per se. A lot of the journals pretty high up the list are just good ecology journals with a wide range of content.

There are a lot of aquatic-specific journals on the list, which reflects me trying to get background on my specific research. But there are also some plant journals on the list, either because I’m still interested in plant community ecology despite being in freshwater for the duration of my PhD, or because they are about community ecology topics that are useful to all ecology. It will be interesting to see if the aquatic journals stay well-represented when I shift to my next research project in a postdoc.

Society journals (from the Ecological Society of America, Nordic Society Oikos, British Ecological Society, and American Society of Naturalists, among others) are well represented. Thanks, scientific societies!

When The Papers Were Published

The vast, vast majority of papers I read were published very recently. Or, well, let’s be honest, because this is academic publishing: who knows when they were written? I didn’t systematically track this, but definitely noticed some were accepted months or maybe even a year before final paginated publication. And they were likely written long before that. But you get the point. As for the publication year, that’s below.

year_published

This data was not a surprise from me as a fair amount of my paper choices come from seeing journal table of contents alerts. I probably should read more older papers though.

Who Wrote the Papers: First Authors

Okay, on to the authors. Who were they? As I mentioned for journals, I didn’t systematically choose what I was reading, so I was curious what the gender and geographic breakdown of the authors would be. Since I didn’t very consciously try to read lots of papers authored by women, people of color, or people outside of North America and Europe, I guess I expected that the gender of first authors to be male-skewed, white, and from those continents. I wasn’t actively trying to counteract bias in this part of the process, so I expected to see evidence of it.

I did my best to find the gender of all first authors. Of those for which this was deducible based on homepages, Twitter profiles listing pronouns, in-person meetings at conferences, etc.,:

  • 59 first authors were women
  • 155 first authors were men
  • 2 papers had joint first authors
  • 1 paper I peer-reviewed was double-blind (authorship unknown to me)

I’m fairly troubled by this. I certainly wasn’t going out of my way to read papers by men, and I didn’t think it would be this skewed when I did a final tally. If I want to support women scientists by reading their work – and then citing it, sharing it with a colleague, contacting them about it, starting discussions, etc. – I am going to have to be a lot more deliberate. I want to learn about other women scientists’ ideas! They have a lot of great ones. I’m going to try harder in the future. Or, really, I’m going to try in the future – as mentioned, I was not intentionally reading or not reading women this past year.

I initially tried to track whether authors were people of color, but it’s just too fraught for me to infer from Googling. I don’t want to misrepresent people. But I can say that the number of authors who were POC was certainly quite low.

I did, however, take some geographic stats: where (to the best of my Googling abilities) authors originally came from, and where their primary affiliation listed on the paper was located.

For the authors for whom I could identify nationality based on websites, CVs, etc., 31 countries were represented.

FA nationality

The authors were numerically dominated by native English speakers, but those had relative geographic diversity, coming from the US, Canada, the UK, Ireland, Australia, and New Zealand (I’m not sure if English is the first language of the South African author). 15 different European nationalities were represented. There were a number of authors from Brazil, and one each from Chile, Colombia, and Ecuador, as well as Central America being represented by a Guatemalan. Maybe a surprise was that Chinese authors were underrepresented, either from Chinese institutions (see below) or those outside China; there were just five. There are many countries from which there are great scientists which are not represented in this dataset.

When it came to institutional country, the field narrowed to 24 countries plus the Isle of Man.

FA_inst

While there were 78 American first authors, 90 first authors came from American universities/institutions. In Europe, Denmark, Sweden and Switzerland gobbled up some of the institutional affiliations despite having low numbers of first authors originally from those countries (this is very consistent with my experience in those places).

(Note: it would have been really nice to make a riverplot showing how authors moved between countries, but I was too lazy to build a transition matrix. Sorry.)

This isn’t really surprising, the consolidation into fewer countries. It reflects that while small countries have great scientists, they often don’t have as many resources to have great research funding or many universities. Some places, even those with traditionally strong academic institutions, are simply going through austerity measures. I think of many Europeans I know who decided that leaving their countries – Portugal, Spain, the Baltics and Balkans, and other places – was their best bet to be able to do the research they wanted to do, and have a job. I think of others, notably a friend in Slovenia, who is staying there because he loves it, but whose opportunities are probably curtailed because of that.

I’d like to read more widely in terms of institutional location and author nationality, but it’s a bit overwhelming to make a solid plan. Reading more women is fairly straightforward. But when I think of all the places with good science but where I didn’t read a single paper, there are a lot of them. I can only read so many papers! So part of it will be recognizing that I can make an effort to read more diversely but I’m not going to solve bias in science just with my reading project. I need to make an effort that is meaningful, and then be okay with what it doesn’t accomplish.

Also, I don’t always know the gender, race, or nationality of an author before I Google them – this past year, I only did that after I read the papers. I might need to sometimes reverse that process, perhaps?

Do you have other ideas of how to tackle this? I’d love suggestions if anyone has them.

One thought is to more deliberately read from the non-North American, non-European authors in the journals I already read from. I already know I like the papers those editorial teams select. This would probably be the least amount of extra work required to diversify my reading, because I could stick to the same method of choosing papers (table of contents alerts), but execute differently on those tables of contents.

And a Bit About the Last Authors

I did not collect as detailed information about the last authors of each paper, but I did collect some. A big topic in academia is that women get fewer and fewer the higher you go in the academic hierarchy. I wondered if that was true in the papers I was reading.

There were fewer last authors because some papers were single-author. Of those that were multi-author, I filtered the dataset to look at only those where last-authorship seemed to denote seniority (based on author contribution statements, lab composition and relationships between authors, etc.) rather than being alphabetical or based on something else (on some papers with very many authors, all the senior authors were listed at the front of the author list). Of these,

  • 19 senior last authors were women
  • 105 senior last authors were men

Yikes!

That’s all one can say! Yikes!

Like the first authors, the last authors came from 31 different countries… but some different ones were represented (Venezuela, Serbia, India). They represented institutions in a few more places than the first authors, 28 different countries vs. 24 for first/single authors. I’m not sure what to make of that, especially since this is from a smaller subset of papers (since the single-author papers were removed), but obviously collaborative research and writing is alive and well.

Ratings and Favorite Papers

Right after I read each paper, I assigned it a letter grade. Looking back through my record keeping, I am less and less convinced that this is really meaningful. I think it had to do a lot with my mindset at the time, among other things. Did I just have a stressful meeting? Was I impatient to finish my reading and go home? Was I tired? Maybe I was less receptive to what I was reading. Or conversely, maybe if I was tired and a little distracted I was less likely to notice flaws in the paper. Who knows. Anyway, “B” was the grade I most frequently assigned.

grades

I didn’t keep detailed notes of why I felt different grades were merited, but I can make a few generalizations. Quite a number of the papers I gave poor grades were because I didn’t find methods to be well enough explained. I either couldn’t follow what the authors did, or maybe important statistical information wasn’t even included (or only in the supplementary information when I thought it was so essential to understanding the work that it really needed to be brought to the center). In particular this included some papers using fancy and cutting edge methods… just using those statistics or analysis techniques doesn’t make your paper magic. You still need to say what those analyses show and what they mean ecologically, and convince me that the fancy stats actually lead to a better understanding of what’s going on!

In some ways this is not authors’ faults – journals are often pressing for shorter word counts, and some don’t even publish methods in the main text, which is a total pain if you’re a reader. Also, it’s one of the biggest things I struggle with when writing – you know perfectly well what you did, and it can be hard to see that for an outsider your methods description seem incomplete. I get it! Reading papers where you don’t understand the methods is always a good cue to think about how you present your own work.

I assigned three papers grades of “A+”. Were they better than the ones I deemed “A”s? I’m not sure, but at the time, whether because of my general mood or their true brilliance, I sure thought they were great. They were:

I read a lot of other great papers too! But looking back, I can say that these were among my favorites, all for different reasons. I could go and add more papers to a “best-of” list but I’ll just leave it at that.

Recap!

Besides all the great reasons to do this challenge that I mentioned in the opening, this was pretty interesting data to delve into. I think I will try to keep doing the challenge in 2019, and I am currently thinking about how I choose which papers to read and if there are good strategies to read more diverse authors. I’m happy with the diversity of research that I read, but I would be happier if the voices describing that research were more diverse, to reflect the diversity of scientists in our world.

Do you have ideas about that? Comment below.

This was the final year of my PhD, and so in some ways a great time to do a reading challenge. It probably would have been more helpful if I had done this in the first year of my PhD, but hey, too late now. This year I wasn’t doing lab work, just writing and analyzing, so it was easy to fit in a lot of reading. It’s not good to stare at a screen writing all day, and I prefer to read on paper, so it was often a welcome break.

I don’t know what my work life will be like next year, so I will see how many papers I end up reading. It could be more, as I start a new project and need to get up to speed on a new subfield. Or it could be less as my working habits change. I’ll just do my best and adapt.

Finally, I’m thinking about whether there’s additional data I should track for next year’s challenge. Whether there is a difference between first and corresponding authors might be interesting. I’d welcome other suggestions too, but only if they don’t take much work to extract!

The marathons of 2018.

This autumn I ground away at two big goals: finishing my dissertation, and running my first trail marathon.

A number of people told me I was insane to try to do both of these things at the same time. But everyone has different ways of staying happy and maximizing what they are capable of. For me, it’s essential to have more than one thing to focus on. I have a few friends who must live like I do: they said, oh, that’s perfect!

The last few months of dissertation writing were really hard. Although I made a plan with my supervisor about how to get everything done, work didn’t really proceed according to plan. Some things took longer. Other tasks required waiting on collaborators for feedback. Sometimes I simply realized that I had no idea what was expected as a certain output. I tried to start working anyway, only to have my first attempt deemed garbage.

By contrast, my marathon training was straightforward. I won’t say it was easy, but I knew what I had to do.

***

I didn’t sign up for just any marathon; the Transruinaulta in southeastern Switzerland is mostly off-road and features 1,800 meters (~6,000 feet) of climbing, plus the corresponding 1,800 meters of descents. In order to do a race effort I felt good about, I knew I would have to take training seriously.

I bought a training plan from Uphill Athlete, a company and community run by Scott Johnston and Steve House. I have known about Scott for years through the cross-country ski community (though I have never met him), and I respect his work, experience, and philosophy so much. I knew that whatever plan I got from Uphill Athlete would deliver me well-prepared to the start line. It had been seven years since I last followed a training plan, but at last, I was ready to return to intentional, organized training. I dove in and had confidence every step of the way that I was doing the right thing.

“The right thing” involved functional strength training exercises that did more to rehab my ankle from last year’s ruptured ligaments than anything my non-skiing PT had taught me. It included interval sessions that I found I really enjoyed – a surprise, since in those last seven years I had done intervals less than a dozen times annually, and some years probably less than five times.

One week “the right thing” involved a 30-kilometer run/hike one day and a 20 k  run/hike the next day. That was hard, but I planned in advance to head to the Engadin valley for the weekend so that I the spectacular scenery would entice me out the door on Sunday when my body was already tired.

IMG_3088

Enjoying some amazing trail running/hiking around Pontresina.

And maybe the hardest week was when “the right thing” had a 30 k run scheduled on a weekday. I woke up early, took the train to Baden, and ran all the way to the office. I have to admit I wasn’t a very effective worker that day.

But even though it was often hard, I knew what I had to do. Just follow the plan. The plan will get you where you want to go.

Training for a marathon was probably the easiest thing I did this fall.

***

The trauma (there, I said it) of the last month of my dissertation has almost blotted out the months that came before, work-wise. But looking back, I can piece together what they looked like.

I want to be clear that a lot of my problems were self-inflicted. I’m a perfectionist. I hate doing less than the best I could possibly do.

I also have a strong viewpoint that data should not go un-analyzed and un-reported. It’s not good for science if we leave something in a file drawer just because it didn’t turn out to be interesting. That means that someone else will repeat our experiment in the future. And if they also leave it in a file drawer because it turns out to not be interesting, then some unsuspecting third scientist will also decide to tackle it. And so on. You get the picture.

My natural tendency to overwork myself was at some points made worse by my supervisor. Florian is a great supervisor – I would highly recommend working in his lab, and the effusive thanks I eventually wrote in the acknowledgments section of my dissertation were not exaggerations. But he knows how to get the most out of all of us. And at this point, he has known me for four years. He probably knew that if he told me he didn’t think I could do something, that would make me try that much harder to get it done.

All of which is to say that in late August when I sat down with Florian to plan the final few months, I should have been confident that my dissertation would be fine. I had already published three chapters of it as papers, which is a great position to be in. If I had wanted to, I could have coasted in to the finish, writing up one more chapter and calling it a day. Nobody would have said my dissertation wasn’t adequate.

But neither Florian nor I were interested in that option. Instead we planned out three more chapters, plus an introduction and conclusion to the dissertation. I had the data already for all of those chapters, but I still had to analyze it and I still had to do the writing.  I had until mid-November to get all of that done.

And so I made an estimate of how long everything would take. Choosing and learning the appropriate geostatistical method to upscale my survey data: would that take two days, or two weeks? Better just schedule one.

“You can write a paper in a week,” Florian said. I didn’t feel like that was true, but sure, chapter four, let’s schedule a week for the writing.

Inevitably, things didn’t go according to plan. And I also had to apply for postdoc fellowships, too, an exhausting process during which I came up with a research proposal that didn’t even strongly relate to my dissertation. Charging ahead on both of these fronts required shifting between intellectual arenas in my brain.

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So here’s a plan I didn’t end up following, like, at all… in fact, the chapters aren’t even the ones that ended up in my dissertation!

Most days I came home from work exhausted, but through early fall, I was making progress. I submitted the fourth chapter to a journal two weeks before we had planned. Things weren’t going exactly as I had thought, but the parts going better than planned seemed to be making up for the areas where I was way behind.

***

In mid-October, with one month until my dissertation was due, I took the train to southeastern Switzerland on a Friday afternoon and got ready to race the next day. I had been tapering, which felt weird. I hadn’t done any competitions I felt strongly enough about to taper for since my only other marathon run, back in 2013 in France. (That one was on the road; I trained for it, but not according to any real plan.)

My friend Annie came down to race too, and was likewise stressed by work. She had been in the field all week, hardly ideal preparation. We went to bed early, and neither of us slept well. We made some overnight oats for breakfast and found a regional bus that would take us to Ilanz, where the race would start.

In the leadup to the race, a lot of people would ask how long I thought it would take. I had no idea what to answer. Five hours? Four hours? There was all that up and down. Plus, though it was clear that the race wouldn’t have much pavement, would the balance be dirt/gravel roads, or singletrack? How technical would the terrain be? This was clearly not a race where you could pick a pace or split and just try to consistently hit it.

Instead, I made a race plan based on heart rate. I wanted to start off easy on for the first few kilometers and then get into an easy but fast groove for the first ten or so kilometers, which looked mostly flat on the course profile. I set limits for the big climbs: don’t let your heart rate go above this. If you have to walk, walk. You’re in this for the long hall and you are not going to make yourself bonk. Downhills are one of my strengths, so I wanted to run every downhill as fast as I sustainably could.

Oh, and I planned to eat as many calories as I could stuff in my face.

I more or less followed this plan. My slow start meant that people poured past me in the opening kilometers (it was an individual-start marathon, weirdly), and I ended up going a little harder than I planned – but still easy enough that I don’t think it taxed me too much. My plan had probably been too conservative.

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First 10 k: whee, this is fun!

After that, my plan worked great. On the climbs that went for kilometer after kilometer, mostly on dirt roads but sometimes on singletrack, I kept up a steady effort hovering just around my anaerobic threshold. The downhills were a blast as I flew past people. Sometimes they would pass me again as I slowed to my steady pace on the uphills, but it paid off.

We hit the high point of the course around 30 k (20 miles) into the marathon, and there was an aid station at the top. One guy who had been running around me – sometimes ahead, sometime behind – staggered over to a picnic table and sat down heavily.

“Scheisse,” he groaned.

I ran through the aid station, stopping only for a few seconds to refill a water flask. I had quite a few kilometers of gradual to steep downhill to look forward to. I hadn’t completely wrecked myself on the uphill, and I started reeling people in. I was flying, catching runners whom I had told myself not to worry about as they went past me on the last climb.

It was pretty fun until a few kilometers to go. We had all been warned that there were three steep hills just before the finish, so to save something. The first one was a reality check after those nice kilometers of downhill, and it was longer than I had guessed, but not so bad.

The second one was short and very steep. I walked. Everyone walked.

The third one: very steep. It was terrible. I mentally cursed the race organizers. I came over what I thought was the top only to see that the hill went on. I felt like I was crawling. My swagger from a few kilometers ago was long gone. But at least from here it would only get easier towards the finish.

Down the other side, around a corner and… what the hell? Another steep hill. Like, really steep, find-something-to-grab-ahold-of steep. There were two retirees by the side of the trail. The runners ahead of me swore out loud this time, and the retirees laughed at them. At us. If I wasn’t so tired I would have fixed them an evil glare as I went by.

By the time I went down the fourth of the three hills, I wasn’t even fast on the downhills anymore. There was a very, very gradual climb to the finish line, back on pavement, which should have felt fast and easy. Instead, I struggled to maintain a jog. But I got to the finish, clocking a time just under five hours.

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The organizers set up this sweet panorama so you could mug and get a cool finish line photo as if you were running on the trail, but I was so beat I didn’t even notice. Whoops!

The sun was shining as we congratulated each other and began to refuel the calories and salt we had lost. Dry clothes felt so good. Sitting down felt good. I was proud of myself – my result was not particularly great, but I had worked hard and followed a plan and, I believe, done the best race I could do on that day. I was just over a year out from a major injury, and another major victory is that I hadn’t hurt myself again. That functional strength had worked: even when I was so tired, my feet nimbly navigated the trails and my ankles stayed stable.

Most importantly, I had a ton of fun and I was already dreaming of what long trail or mountain race to sign up for next year.

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With Annie at the finish: we did it! (Photo: some older lady walking by, who we accosted…)

***

The race hadn’t been easy.

If I’m thinking about the events that cap off my grueling goals, I think my PhD defense – scheduled for January – will be much easier. I like giving presentations, and I am excited to tell my colleagues, friends, and family about what I’ve been working on. I’m sure I will be nervous, but mostly, it will be fun. I’ve been imagining that day for months and months and months.

Compared to a mountainous trail marathon? PhD defense = easy.

But if I’m thinking about the paths that lead to those days, the running was much easier. The day after my marathon, I went for a little walk in the mountains with Annie, because we were already there and the views and mountain feeling are too good to miss even when your legs are jelly.

On Monday I went back to the office, and I didn’t take another day away from my dissertation until I handed it in just over a month later.

Again: that bad, bad situation of overwork, and everything it led to, was somewhat self-inflicted. I could have told myself, look, this is crazy. You don’t even really need six chapters. Florian, I can’t do chapter six. I’m going to take the weekend off and unscramble my brain and work on giving you a great five-chapter dissertation.

But that is not what I did. I wrote for hours at a time. I revised. I formatted. I cried. I ate a lot of cookies (a lot!). I asked colleagues to read terrible drafts. I rarely went running. I kept writing. I slept badly. I complained. I became a bad friend and officemate. I resented Florian. I cried more.

What I lacked was confidence. I was trying to follow the plan we had made, but it wasn’t working. I didn’t have that feeling that if I just did what was on the schedule, everything would be fine. Most days, it felt like there was no way in the world that everything would be fine.

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You think you’re doing okay and then you start correcting your bibliography and it looks like this…

Maybe partly because my training was over and I was rarely exercising, I totally lost perspective. My dissertation seemed like the only thing in my life, in some ways, and it felt like a slow-rolling disaster. Every little setback seemed like the end of the world.

But, on November 19, I handed Florian a printed version of my dissertation.

He made some minor corrections and told me it was very nice. This was classic: he had previously told me that he expected he would make a lot of corrections and there was no way I’d be able to turn it in the next day. But by saying that, he had ensured that I would ruin myself attempting to give him a nearly perfect dissertation.

I made those small corrections, and on November 20, I submitted my dissertation to the University of Zurich. It was anticlimactic. I uploaded a PDF to the online interface, and then walked some paperwork over to the Faculty of Science. The woman at the desk who accepted my registration for a PhD defense didn’t even say congratulations. Nobody had come along to give me a high five or hug, because I hadn’t asked them to.

Instead I went home and, much like after my marathon, lay on the couch. I sank into the leather cushions and felt like maybe I could stay there forever.

***

Recovery began the next day.

If there’s anything that being an athlete has taught me, it is that recovery is important. It’s not something I’m particularly good at, and it’s also something that I didn’t really value for much of my “serious” athletic career. I was interested in too many other things – when I didn’t have to train, I filled that time with something else. I’m pretty sure I would have been a lot faster if I had just taken a nap.

But now I’m some combination of older and wiser, and my body is older, and my brain is older. They need recovery and I fully believe in its value.

I took almost a week off from work, and now I’m back. I’m able to enjoy going to the office again. I’m able to get excited about reading papers, another thing that I almost completely neglected while I was writing. Many of the projects I am working on now, in this time between my dissertation and defense, are collaborative, and that feels great to get back to, too.

And in the back of my mind I can say that no matter what else happened in 2018 – the political, the personal, the stupid stress I put myself under – I accomplished my two big goals. That feels pretty good.

beginnings.

Every time I talk to my mother (hi mom!) she asks me something like, “so what is your usual day like?” I’m the  first one in my family to go to a research-based graduate program in the sciences – my cousin Jess is in med school and my uncles got PhDs in history and economics, but the routine of those lives are very different. There’s a certain amount of mystery and allure about what happens when you are a graduate student, besides of course my mother’s general curiosity about what I’m doing with my life. I’m not going to class, so what is it that I’m doing?

Apparently I'm a professional now. Headshot for the institute website www.eawag.ch.

Apparently I’m a professional now. Headshot for the institute website http://www.eawag.ch.

But there’s not a real answer. Days both fly by and drag past. There isn’t really so much to distinguish them from one another at this point – I haven’t started fieldwork or labwork for real. The main thing is that Fridays are filled with group meetings, department meetings, and seminars. Sometimes other days are, too. Those days it can feel like you get nothing done and are running around from one thing to the next all day. Other days it can feel like you get nothing done and are just reading all day. No matter what kind of day it is, it’s hard to measure progress or have any tangible outcome of what you’ve done.

For me, the biggest change is to have a community, a structure, obligations, meetings. For more than the last year, I worked pretty independently. In Davos at SLF, we were a tiny department and had a short meeting once a week. That was it, other than checking in with co-workers whenever it was convenient just by popping my head into their office, or taking out my earbuds and striking up a conversation across my desk.

In Sweden, my supervisor was on paternity leave and only came into the office a few days a week. I didn’t have a real office – he offered me a place in the computer lab – so I worked in the library, which was a considerably nicer place, or from home. I checked in with him in his office a few times a week, but other than that it was up to me to make my own schedule.

No matter where you are in academia, there’s some flexibility in scheduling. People keep their own hours. Night owls hunch over their computers deep into the night; early birds cycle to work and have pumped out a few pages of writing or analysis before the rest of us even arrive. I don’t have to keep a timesheet, clock in and out, or tell anyone my schedule.

But compared to Davos and Gotland, it’s jarring to be back in an environment where people more or less arrive at 8 and leave at 5, taking a regular lunch break all together in the cafeteria. Where there are meetings and seminars and journal clubs that you will be shamed if you don’t go to. Where if you decide to leave early and spend the rest of the afternoon reading that book from the comfort of your sofa at home, probably there was some important obligation that you will have totally forgotten about and subsequently miss.

This is, of course, real life. I don’t dislike it. In fact, I do like it. I like our coffee breaks, our lunches, having other people. I can chat with the postdocs; I can turn my chair around and ask my fellow PhD student, Roman, how to go through the maze-like University matriculation process. Once a week I have a scheduled meeting with my supervisor Florian. We spend an hour or two talking about my project, ranging from experimental details to theory.

On Thursday, the ECO department had its annual Christmas party. A few wonderful people dressed the old teaching lab up with streamers, a disco ball, and other decoration. The department purchased more beer and wine than the 60 of us could possibly drink; they hired a pizza truck to park outside (I was initially alarmed to see an actual firewood-fired pizza oven in the back of a truck, because it just seems dangerous, but on second thought it’s no more crazy than a usual food truck) and make us pizzas to order. The rest of us brought salads and desserts; three student’s DJ’ed and everyone, from students to lab techs to the administrative staff, danced. It was great fun. It’s really nice to be part of a department with such a sense of community.

The hardest thing is that I have to try to get my daily run in before work, which is challenging when it doesn’t get light until after 7. I struggle to pry myself out of bed. But I shouldn’t complain. Millions of people manage to go running in the dark before work, why is it so hard for me?

The second hardest thing is that these meetings with Florian never have a concrete outcome. Embarking on a PhD in Switzerland is different than in the U.S. because I only have three years to finish. That means that right off the bat, there is a certain sense of urgency to figure out what I’m doing and get started. But at the same time, mistakes can’t be made. Things have to be carefully planned, connected to theory. We have to make sure we have good questions that we are answering, that we’re not just collecting data willy-nilly. It’s a fine balance between making decisions and taking more time.

It can feel frustrating, but I think that is what a PhD, and indeed research itself, is all about. Still though, it is easy to feel jealous of Roman, who is six months ahead of me and already busy with labwork, PCR’s, and weeklong trips to other labs to learn new techniques. I’m still figuring out what it is I have to learn and it can feel like everyone around me is leaving me behind as they move on with their projects.

None of that really answers the question of what I do all day. What I do all day is very different than what I will be doing in three months; in some ways it isn’t very representative of what PhD life is like.

But maybe it answers what I feel all day. I feel giddy if I make a GIS map; I feel sleepy if I read too many chapters of a book on ecological theory; I feel excited when I listen to a seminar about some cool research someone in my department is doing; I feel overwhelmed when I think about how to try to link all the pieces of my project together. I feel responsible for some important, long-term decision when I go to buy hip-waders for my stream work, even though actually this is probably the least-important decision I will make in the whole project.

And this combination of excitement, stress, and confusion is probably what will characterize my life for the next three years. One of the best things I am doing now is looking at the people around me and trying to glean information about how they manage their days, their projects, their home lives, their expectations. Luckily, I have a great set of mentors to learn from.

on top of the world!

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I’m in Davos, and I’m on top of the world! Okay, not quite literally, I’m not on top of the biggest mountain here and the mountains here certainly aren’t the biggest in Switzerland. But I’m on top of something, and I can see quite far, and thankgodI’mbackinthemountains.

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But also… I feel emotionally like I’m on top of the world. I have an exciting announcement: I’ve been accepted to do a PhD at Eawag, the Swiss Federal Institute of Aquatic Science and Technology. I will be working in the lab of Dr. Florian Altermatt, which I’m really looking forward to. My project on biodiversity and ecosystem functioning using a meta-ecosystem framework will be fun and challenging. I’ll have to learn a lot! Already, I know that I will need to learn to identify and work with amphipods, small crustaceans which will serve as our main study taxa, and how to set up mesocosm experiments. There’s also talk of using stable isotopes to track carbon and other fluxes through ecosystems, which I’m excited to tackle. I was at Eawag on Thursday for a visit and interview, and I think that it will be great group to work with. A lot of smart people but all really friendly and, most importantly, everyone seemed very happy. That’s something important when you are deciding whether to make a 3-year commitment!

I’m really relieved to have my future worked out a little bit and to think that I won’t be unemployed once I finish my masters. I’m looking forward to settling down in one place for 3 years – I want to continue traveling and having adventures, but I haven’t felt like I have had a home base to come back to in my time in Europe so far, so that will be a very welcome change. I can have a few more belongings than fit into one suitcase, and hopefully my road bike too. I never realized how much I would look forward to a little bit of stability.

And, I’m excited to be at Eawag for a few more reasons. It is a very amazing research institute, highly respected and covering all aspects of freshwater research, not only ecology but also more applied things. For instance, on the news page you can find, in close proximity, an announcement of Dr. Altermatt getting the big grant which will fund my project; “Combining the best of both toilet worlds“; “Cocktail of pesticides in Swiss rivers“; and a notice about extending the wastewater treatment plant. I think that working in a place which has multiple fields of focus will be a great opportunity and hopefully make my research more dynamic. It’s great to think of being able to check ideas with people looking at other aspects of river ecosystems. And, because of their focus on sustainability, the main building is the amazing Forum Chriesbach which is built from a lot of prototype materials, harvests rainwater for the bathrooms, and is so energy-efficient that it doesn’t have a heating or cooling system!!

Finally, my degree will be through University of Zurich, which is also pretty cool. While I was in town for the interview I stayed with my friend Timothée and visited the campus and his lab. There is a lot of very cool research going on there, and in general, Zurich is an amazing academic environment. There’s also ETH Zurich, the Swiss university, and the two institutions collaborate on seminars and courses. It is going to be a very stimulating few years.

So, I have a lot of joy in my life right now. For the weekend, I’m focusing on tying up some loose ends and spending a bit of time in the mountains which I have missed so dearly.

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