Who is doing interesting system-based research? And what is a model system anyway?

I will be organizing the American Society of Naturalists’ Vice Presidential Symposium next year, and think it would be fun to have the symposium focus on insights gained from system-based research. (Related: my old post on the merits of system-based research.) My thinking is to combine people who are working on well-established model systems (e.g., three spine sticklebacks, Arabidopsis, E. coli) with those working on more recently established systems (nascent model systems?). I’d like to include work that spans the breadth of the society (so, ecology, evolutionary biology, and behavior). I also want the symposium to feature the work of early career scientists. That’s where you come in! Tell me who you think is doing really interesting and exciting system-based research. I’m especially interested in hearing about early career folks, and am super duper interested in learning about early career folks who’ve done work to establish new model systems.

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Am I frantically juggling when I should be letting things go off the edge of a cliff?

When I started my first faculty position at Georgia Tech, I felt like I was juggling as fast as I could; every time it felt like I was starting to get a hang of things, a new ball would get tossed in. I mentioned this at some point to someone there who said: the key is to remember that some balls are glass and some are rubber.

I was thinking about that juggling metaphor again recently because I was involved in a discussion with other faculty about how we all have too much to do. There was some discussion of the root causes of this, including a major decline in administrative support and more expectations. Obviously those are huge issues that are worthy of much more thought and systemic solutions. But there was also a discussion of what we can do individually in the short term as we all struggle with this. At some point, someone said something to the effect of, “you need to accept that you are never going to be able to do it all, and you have to accept that some things are just going to go off the edge of the cliff”.

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Guest post: Strategies for helping your research reach a wider audience

Note from Meghan:  This is a guest post from Richard B. Primack and Caitlin McDonough MacKenzie; Richard has written guest posts for us before, including one on using a professional editor. This guest post is on a topic that I get asked about regularly when I travel for seminar trips, so I suspect it will be of interest to readers. I’ve added some thoughts of my own throughout the post below.

 

As scientists, we love our research and want to share our findings far and wide. As ecologists and conservation biologists, we especially hope that our findings affect policy, management, or everyday stewardship. And funding agencies remind us that we must ensure our research has broader impacts that benefit society, beyond just publishing scientific papers. But how do we effectively communicate our research? Here, we share some tips about how researchers can communicate research to the media, and reach audiences beyond peer-reviewed journal readers. We use examples from a recent paper of ours published with co-authors.

Make your research exciting—identify your hook. In our recent paper, Phenological mismatch with trees reduces wildflower carbon budgets, published in Ecology Letters, we emphasized that we are building on the observations of Henry David Thoreau; Thoreau was the “hook” that we use to attract much of the interest in our research.

Make the message easy to understand—tell a story. We wrote a press release that told a story about our research and highlighted key points in non-technical language and without jargon. Even though Richard’s academic home of Boston University does not generally issue press releases about scientific papers, our summary helped reporters quickly understand our work, its significance, and potential angles that could interest readers or listeners.

(From Meghan: if you’re having a hard time finding your hook or story, there are some great resources. Randy Olsen’s And, But, Therefore structure is great, and laid out in detail in his book, Houston, We Have a Narrative. The Aurbach et al. “half life” activity (described here) is also a helpful way to find your message.)

Provide informative, high-quality photos. We take many photos to illustrate our research and the key results. Sometimes these photos are carefully staged to illustrate the research process or results. Reporters are more likely to write a story if excellent photos are available.

A man wearing a baseball cap is crouched down in a field. In one hand, he is holding a field notebook. The other hand is reaching out towards a plant with yellow flowers.

Having good photos, such as this carefully arranged shot of Primack working in the field, helps to create media interest.

(From Meghan: these are so important, and often people forget to take them! I agree that carefully staged photos are valuable. Getting videos is very helpful, too, including for reporters to use as “B roll”. I recently shared various short snippets with a reporter—I was glad to have them, but also wished I had more! Another example of how videos can be helpful comes from this recent story by some of my colleagues at Michigan, which went viral because a student on the trip, Maggie Grundler, thought to pull out her phone and capture a quick video of a very cool interaction.)

Reach out to the media and be responsive.  We emailed our press release and eye-catching photos to contacts in the media. One of them liked the story and wrote an article about our work for the Boston Globe. He was writing the article on tight deadline, so we promptly answered his numerous questions.

(From Meghan: A couple of things related to this: first, reporters are often working on much, much tighter deadlines than we are used to—they might need to file the story by the end of the day they contact you. So, you need to be quick about responding to them, but it also helps to give them as much lead time as possible. Second, reporters generally will not share their story with you ahead of time for you to review. It’s very different than working with a university press officer!)

One thing can lead to another. The Boston Globe writer pitched the story to National Public Radio, and he will interview us for a radio program in April.

(From Meghan: One thing can lead to another….or not, or maybe it does but with a big delay. One of the things I didn’t really appreciate when I first started doing more science communication is that you can spend a lot of time talking to a reporter and it can end up going nowhere. [example 1, example 2] It can be really frustrating! If anyone has advice on how to make this less likely, I’d love to hear it!)

Get with social media. Caitlin tweeted about the article, creating buzz in the twittersphere. We wrote a short summary of our paper for our lab blog—essentially a shorter, more conversational version of the press release—with links to a pdf of our article. Our lab blog has been viewed around 100,000 times in 6 years, so we estimate that this will be 500 views of this story, a nice complement to the Twitter buzz.

Publish on-line. To generate publicity within our Boston University community, we wrote an article for BU Research, using the press release as a starting point. This article further widened the audience who will hear about the research, with relatively little additional effort on our part.

Leverage institutional networks.  The other co-authors of our paper reached out to their universities and media contacts, sharing our press release. The paper received added coverage in institutional publications and websites of the University of Maine and the Carnegie Museum of Natural History.

(From Meghan: another reason this can be useful: one press officer might not be interested or might not have the time, but someone else’s might.)

Send out pdfs.  We emailed a pdf of our paper to 100 colleagues in our field, along with a very short email summarizing the key points of the article, again pulling from the same basic story in the press release and blog and Twitter posts.

Each paper and project are different, but hopefully this post has given you some ideas of things to try.

Other resources:

Compass – https://www.compassscicomm.org

The Op Ed Project – https://www.theopedproject.org/pitching

Cahill Jr, J. F., Lyons, D., & Karst, J. (2011). Finding the “pitch” in ecological writing. The Bulletin of the Ecological Society of America92(2), 196-205.

Merkle, B. G. (2018). Tips for Communicating Your Science with the Press: Approaching Journalists. Bulletin of the Ecological Society of America99(4), 1-4.

First cut results of poll on manuscript rejections: we deal with a lot of rejection

I recently did a poll asking readers about their experiences with manuscript rejections. This was based on thinking about different submission strategies, including wondering about what the “right” amount of rejection is. In this post, I lay out the big picture results, and then end by asking about what further analyses you’re interested in.

There are lots of figures below, but here’s my summary of the key results:

  • respondents to this poll reported a lower acceptance rate at the first journal to which they submitted a manuscript (48.4%) than in the recent Paine & Fox survey (64.8%). They had vastly more respondents (over 12,000!!!), so I trust their number more; other potential factors that might also contribute are discussed below.
  • it’s not uncommon for people to need to submit a paper to 3 or more journals before it’s accepted.
  • it’s surprisingly common (at least to me) for people to take the “aim high, then drop if rejected” strategy
  • people are submitting to stretch journals pretty often—and sometimes it pays off
  • there’s a decent amount of uncertainty in terms of how well a manuscript fits a particular journal (on the part of authors, reviewers, and/or editors). This suggests that the concluding advice of Paine & Fox (“We therefore recommend that authors reduce publication delays by choosing journals appropriate to the significance of their research.”) is sometimes easier said than done.
  • people aren’t totally giving up on manuscripts as often as I might have thought they might (but this might be explained by the demographics of the poll respondents)

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If your field experiment has few replicates (and it probably does), intersperse your treatments rather than randomizing them

The last experiment I did as a graduate student was one where I wanted to experimentally test the effect of predation on parasitism. To do this, I set up large (5,000 L) whole water column enclosures (more commonly called “bags”) in a local lake. These are really labor intensive, meaning I could only have about 10 experimental units. I decided to use a replicated regression design, with two replicates of each of five predation levels. These were going to be arranged in two spatial blocks (linear “rafts” of bags), each with one replicate of each predation level treatment.

left picture shows two objects in the distance in a lake; the most obvious thing about them is fencing at the surface; the left picture shows a close up of one of them where you can see five individual bag enclosures

Left: two experimental rafts; right: a close up of one of the rafts, showing the five different bag enclosures

As I got ready to set up the experiment, my advisor asked me how I was going to decide how to arrange the bags. I confidently replied that I was going to randomize them within each block. I mean, that’s obviously how you should assign treatments for an experiment, right? My advisor then asked what I would do if I ended up with the two lowest predation treatments at one end and the two highest predation treatments at the other end of the raft. I paused, and then said something like, “Um, I guess I’d re-randomize?”

This taught me an important experimental design lesson: interspersing treatments is more important than randomizing them. This is especially true when there are relatively small numbers of experimental units*, which is often the case for field experiments. In this case, randomly assigning things is likely to lead to clustering of treatments in a way that could be problematic.

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Building confidence, building resilience, and building CVs

When I was at the biology19 meetings recently, someone said something to me that I can’t stop thinking about: a student’s first manuscript should get sent to a journal where it will be accepted without much of a struggle; the second submission should be more of a struggle, but should get accepted at the first journal to which it was submitted; the third should go somewhere where it gets rejected. The person who said this, Hanna Kokko, acknowledged this was somewhat tongue-in-cheek, and that many factors will end up influencing where someone submits a given manuscript; her real approach is to respect the first author’s own wishes, after a discussion of the pros and cons of different options. But her tongue-in-cheek recommendation is motivated by the recognition that rejections can be a huge hit to one’s confidence, especially when someone is just starting out. I’ve seen (and personally experienced) the enormous confidence hit that can come from serial rejections of a manuscript, again, especially when one is just starting out. So, trying to figure out a strategy to reduce the potential for a big ego blow (while learning to deal with rejection too—but not before one has succeeded twice) makes a lot of sense to me.

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In which my ink runs out and I realize there are lots of things that are interesting and important, and I cannot do them all

Last Monday, I faced a post-travel inbox filled with emails that needed replies. Some of them were invitations for things that would take up my time, but that seemed interesting or important or valuable or all three. And, then, of course, there were all the other things I needed to do as part of my job – editing manuscripts, writing letters of recommendation, sending emails to get people access to the lab, analyzing data, etc. And it was also the day where my post on seeing a therapist appeared, which led to lots of interactions on social media, via text, and through email. All of that led me to revisit a question that I am constantly asking myself, and that I surely will never stop asking myself: how should I spend my work time?

I couldn’t get this out of my head, and, as I walked to daycare, I realized that there are three questions I should consider as I evaluate whether to do something:

  • Is it officially part of my job?
  • Am I particularly good at it?
  • Do I enjoy doing it?

I thought about how, ideally, I should try to prioritize things where the answer would be “yes” for all three. And I thought about how I spend a lot of time on things where the answer to all three of those questions is “no”.

When I got to daycare, I knew I wanted to think about this more, and was worried I would forget it. So, I pulled out my notebook in the daycare lobby, propped it on top of the stroller, and drew this:

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When did you realize you work on climate change?

Some ecologists start their careers planning to study climate change, and others make a decision to pivot towards that line of research. But something I find fascinating is that there are ecologists, myself included, who didn’t necessarily set out to study climate change, but who are accidental climate change biologists. To give just one example: if you work on a time series on natural populations, communities, or ecosystems that extends more than a few years, chances are you’ve found that climate change is now a part of what you’re studying.

I’ve thought about this over the years as projects we work on that started out as basic research into host-parasite interactions end up relating to climate change. Some links are obvious—wanting to understand how temperature influences host-parasite interactions leads pretty naturally to thinking about how climate change will influence host-parasite interactions. Some links are less obvious—for example, we wondered whether the light environment might be influencing when and where we saw parasite outbreaks. As I recall, our initial interest in this was not related to climate change. But lakes are getting browner, in part due climate change, so any work we do on how lake light levels influence disease naturally links with climate change. And we now have some data on host-parasite interactions in lakes that spans 1-2 decades. Once you’re into decadal time scales, you have to consider the impact of climate change on what you’re seeing.

I’ve also thought about this in terms of some projects I didn’t work on. When I started grad school, one of the projects I was thinking of working on related to what was going on under the ice in lakes in winter, and how things like snow cover influenced that. So, when I saw news articles about a new study showing that there will be an “extensive loss of lake ice…within the next generation”, I thought back to those grad school plans to work on lake ice & snow cover. My recollection is that my interest in that project was mainly wanting to understand the basic biology of lakes, but clearly it would have ended up being a study of climate change if I’d pursued it.

Based on conversations with colleagues, I know I’m not alone in coming to realize that I am an accidental climate change biologist.

So, I’m curious: for my fellow accidental climate change scientists, when did you realize you were studying climate change?

Comparison of ways of visualizing individual-level Likert data: line plots and heat maps and mosaic plots, oh my!

Last week, I wrote a post where I talked about how my training in evolutionary ecology led me to try reaction norms (that is, paired line plots) for plotting paired Likert data. I had already tried a few other options, but didn’t include them in that post, and I got some feedback on that post that gave me more ideas. There was also a request for code on how to actually generate those plots. So, this post shows four different ways of visualizing individual-level responses to paired Likert-scale questions (paired line plots, dot plots, mosaic plots, and heat maps). It does that for two different comparisons, leading me to the conclusion that the type of plot that works best will depend on your data. I’d love to hear which ones you think work best — there are polls where you can vote for your favorite! And, if you’re working on similar data and want to see code, there’s an associated Github repo, but it comes with the disclaimer that my code is good enough, but definitely not elegant.

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I couldn’t make it in academia without my invisible support network

I recently got some good work news. (Hooray!) When I heard, one of the first things I did was text a group of friends who are also academics. They have become an essential source of support for me. I wanted to tell them the good news, yes, but I also wanted to thank them. I had almost given up on this thing over the summer—I wasn’t sure it was worth the time I was investing in it, and thought it didn’t stand much of a chance. They told me it was worth it and gave me the encouragement to go forward with it. So, without them, this good thing may well not have happened.

And that’s just one example of a time when I benefitted from my invisible support network. Both in Atlanta and here in Michigan, I’ve benefitted immensely from this behind-the-scenes support. These networks help with specific situations: Is it worth applying for this thing? What do I do about this tricky work situation? I think this behavior by person X seems not okay—am I being overly sensitive? What do you think of the wording on this really important email—is it too strong? Did I screw up when I did Y? I can’t decide between A & B—can you help me think them through? There’s also the general venting and commiserating and celebrating and checking in on each other. These support networks aren’t visible to outsiders, but they feel essential to my ability to do what I do.

It’s possible that the title of this post is an overstatement—maybe I could make it without my behind-the-scenes support networks?—but I’m really, really glad I don’t have to. I don’t want people who will agree with everything I say, but I do want people who I know will be supportive, even if they’re challenging me.

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