Seasons of the Scientific Conference

Maybe one or more of these sound familiar?

Newbie. You’re an undergrad or a brand new grad student or something in between. There’s a big regional or national conference nearby and it costs relatively little for you to go. So you go! You spend hours poring over the program, looking for the talks that seem awesome. Except they all do. You write out a complicated schedule of talks you Must Not Miss and fill every minute of every day. You know no one — or maybe one other person, also a newbie. You dress casually because you don’t want to attract attention. Or you over-dress because you don”t want to attract attention, and then realize too late what ecologists wear to conferences. You keep busy keeping to your schedule, head down in the halls, bee-lining for the next talk on your list. The talks themselves leave you amazed and awed. Everyone is doing amazing work. Every Single Talk inspires you, as you expected them to. Ecology research is so cool and you can’t wait to dive in to do your own.

Missed chance. You finally have research to present at a national or international meeting! But you can’t go unless you find funding. And you can’t find funding. OR… there is funding, but it requires that you present at the conference. No problem, except you weren’t able to submit an abstract because life interfered. You gave birth just before the abstract-submission window and could barely function, never mind write an abstract. Or your closest friend died and you could barely function, never mind write an abstract. Or your chronic health condition flared up and you could barely function, never mind write an abstract. OR… you submitted an abstract, but you can’t actually attend the conference because you’re pregnant and on bed rest. Or you need to take care of your aging father who has taken a turn for the worse. Or you can’t afford to take your infant and you can’t afford to leave your infant behind. In the end, you don’t really mind missing the conference. After all, there were more important things to take care of. Except you really do.

First-time talk. You’re a few years into your PhD or finishing up your Masters (or maybe earlier in your degree if you did substantial undergraduate research). You’ve submitted an abstract, found funds to attend the conference, and are all ready to go. You know a bunch of people now, mostly people at your own institution, and it’s nice to run into them in the halls and to hang out at dinner. But you still spend most of your time attending talks and worrying about your own. Your own first conference talk feels weirdly anti-climactic. You’ve spent a lot of time prepping it and you’ve been worried about the follow-up questions. But in the end, the three questions are all polite and cover angles you’ve thought about. You field them without a problem. After the talk is over, no one approaches you to talk about it. It’s over and done. All the other talks you go to are good. But they’re not amazing, like you remember them being when you were a newbie. As you watch one, you’re horrified at the methods or statistics. “No, no, no,” you silently say to yourself. “You can’t do that!” You calculate that about 80% of the talks are good, but not amazing, and you include your own in that group. About 10% have serious flaws. And the other 10% you find inspiring. You wonder why ecology research has really stagnated in the past few years. And then you have a revelation: it’s not ecology research that’s changed; it’s you! You’re finally getting the hang of it, and are starting to recognize the merit and limitations of others’ research.

Unintentional networking. You’ve been to a couple conferences now and don’t feel quite so intimidated as the first times. You know what to wear. You know how things go. You prep your talk, but are more interested in what you’ll see and learn than presenting your own material. You still spend a lot of time looking through the program to find the talks you’ll like the most, but you’re starting to get a bit picky. When you arrive, you realize that your network has expanded, and that you know people from other institutions. You meet someone face-to-face who you’ve only known online. For the first time, you go out to dinner with a group that include people you haven’t yet met. You start to expand your network. On the way to a talk you really want to see, you run into someone you haven’t seen for a couple years. You’re torn, but end up skipping the talk and chatting with your friend for a half-hour. It’s a great chat. Other people pass by and you end up talking with friends of your friend, and before you know it, you’ve missed all the talks you wanted to see that afternoon, but have run into several old friends and met a dozen new ones. You go out to dinner and outline a novel research paper with one of these new friends. By the end of the conference you’ve had another revelation. This time: conferences aren’t about talks, they’re about people.

Intensive intentional networking. You’re a year or less away from defending your dissertation and you need a job! Your goal at this conference is to meet as many people as possible who might be interested in hiring you or writing a grant proposal with you. You prepped for this conference by making lists of people you want to meet and then cold-emailing them to see if you can chat with them at the conference. Every Single One who is attending says yes, because ecologists are super nice. Your schedule is packed with one-on-one meetings, and you only just start looking at the program on the flight to the conference. You’re more nervous about your meetings than your talk. Oh, man, your talk! You put down the program and write your talk on the plane. You spend the days meeting with more senior folks, trying to impress them, trying to figure out the place your research interests best overlap, and trying to figure out if they have any money. You spend your evenings catching up with friends and colleagues and trying to relax before the next day’s one-on-one meetings. When the conferences is over, you’re exhausted, but have a bunch of leads on possible jobs and grants. Plus you’ve met some great people and talked about some exciting research.

Conference regular. You’ve got your PhD in hand and a job, even if it’s temporary. You’ve been to conferences for a while now, and have a good sense of what you like best about them. You balance seeing talks you think will be inspiring with networking with old and new friends and colleagues. You’ve developed a method for picking talks that you’ll like and it works pretty well. You’ve got a talk or two to present this time, and you even organized a session. You plan ahead to meet a few new folks, and you take time to bring uncomfortable-looking students into conversations. One of them even stops you to chat about your talk in the hallways. Somehow, the same topic keeps coming up when talking with different groups of people, and you decide that a paper needs to be written on it. The conference is exciting and invigorating, and you leave with ideas for future research directions.

Do you have any to add? The “Conference gone terribly wrong”? “Selling your first book”? “Conference as an old hand”? Add your own in the comments.

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The postdoc pay cut

One beneficial thing about working out in the “real world” before starting a PhD is that you have the perspective of academia within the larger world, rather than academia as the only thing you’ve ever known. If you’ve gone from grade school to college directly on to grad school, you may not realize what a bizarre world academia is. Academia is the only place I know of where an organization makes substantial investments in its employees’ [1] I mean grad students here training and education and then as soon as they’ve shown mastery, casts them away. After graduating from college, I worked for the government. There, I was in a 3-year training program. I had classes and hands-on learning experiences. I did rotations through different offices to learn about the organization, its mission, and to develop my skills. I was paid like a regular employee, because I was seen as an investment; once I was through training, I was quite valuable to the organization.

Contrast that with graduate school. The good people of Minnesota spent more than $50,000 on my graduate education. The U.S. government upwards of $100,000. I consumed countless hours of time of senior faculty, whose time could otherwise have been spent doing research. When I defended (i.e. showed mastery), I was essentially fired, just as everyone is. My husband and I loved living in Minnesota. We would have been glad to give back to our adopted state by doing our research there, bringing in grants and using our newly developed skills to bring whatever honors to the state we could. But that was never an option. Weirdly, many states spend a lot of effort to keep their college graduates in-state. But they kick their newly minted PhDs out the door – and out of the state – as quickly as possible.

I think the most perverse part of the academic system is that postdocs actually take a pay cut compared to their pay as graduate students. Ecology graduate students frequently support themselves on teaching or research assistantships (TAs and RAs). The usual TA and RA arrangement is a “half-time” appointment; that is, an expectation of about 20 hours per week. For this work, they are typically paid from about $8,000 to $13,000 per semester, depending on location, cost of living, and institutional resources. Assuming grad students can find additional money to cover the summer months, they live on $20,000 to $34,000 per year. [2] NSF’s graduate research fellowship stipend is $34,000, matching the highest-paid TA/RAs This isn’t a lot – especially for areas with a high cost of living – but it’s usually (just) enough to live on for people with no dependents. And because the pay is for half-time work, the actual pay rate is $40,000 to $68,000 per year, which is quite reasonable for high-quality workers in their early-to-mid twenties.

What happens when ecology grad students become postdocs is something of a cruel joke. They take a huge pay cut. Now, they’re expected to work full-time. But they only get paid $40,000 to $45,000 per year with their advanced skills, knowledge, and qualifications. That’s a 33% pay cut for those with the highest grad student earnings. [3] As an example, I went from a $30,000/year grad fellowship (which substitutes for a half-time appointment, so has an actual pay rate of $60,000/year) to a $50,000/year postdoc – an excellent rate for ecology, but nevertheless a pay cut of $10,000.

Why do we as a community put up with it? I think the pay cut happens, in part, because of complacency on the part of people in power – “this is how it’s always been, so this is the way it has to be.” And in part, because economic forces: there are many people who are willing to work for low pay. And in part, because of a lack of awareness. Many new postdocs are so glad to have “more money” in absolute terms, they don’t stop to realize that they’re being cheated. Many (most?) academic ecologists (and likely scientists in some other fields) have no concept of their market value. [4] By the way, this is nothing unique to ecology; it’s just easier for me to find numbers in the field I’m most familiar with. NIH has a schedule for how much its postdocs should be paid. You can see that low pay relative to qualifications is institutionalized with this schedule. Initial postdoc stipend set around $50,000? The types of academic high-achievers who go to grad school could make this much salary immediately out of college in many urban areas.

Here’s a quick-and-easy way to figure out your own minimum value outside academia with a PhD: Go to the U.S. government’s salary schedules, choose your location, open the PDF or webpage under “Annual Rate,” and look at the value in the chart for Grade 11, Step 1.

These tables are the pay rates for U.S. government employees worldwide and they’re based on competitive rates with industry. In other words, they’re a reasonable estimate of what you should be paid based on your credentials, location, and experience. Grade 11, Step 1 is the absolute minimum you could be hired by the government with a PhD in hand. If you’ve got any additional work experience or specialized skills (e.g. statistics, coding, discipline-specific skills), you could expect higher steps and/or grades. [5] Assume a minimum of one step per year of experience. On top of that, the government has a bunch of special rates for individuals with specific specialized skills. If you could classify yourself as a “biological scientist,” “natural resource specialist,” “plant protection technician,” “soil conservationist,” “forestry technician,” “soil scientist,” “geologist,” or “oceanographer,” there’s a special (higher) rate for you.

According to these charts, my worth as a PhD-holding resident of the Boston area with 2.5 years of postdoctoral experience means that I’m worth about $15,000 more than I’m being paid. At minimum. [6] Please note that I am not complaining about my personal situation. I make the choice voluntarily to stay in this job – with my eyes wide open – for a multitude of complex reasons. My goal with this post is raise awareness of the job worth and market value of postdocs, as I believe academia as a system purposefully shrouds this information to enable exploitation of highly skilled labor.

How about you?

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Most ESA Early Career Fellows are almost mid-career

The Ecological Society of America recently announced its call for nominations for awards for 2017. I encourage you to get out there and nominate people. In particular, consider nominating folks that are historically underrepresented. [1] For the Early Career Fellows, consider nominating someone at a comprehensive university, primarily undergraduate university, or in the private sector. As an early career researcher, I feel a bit intimidated by the idea of nominating folks for the heavy-weight awards such as the Eminent Ecologist Award and MacArthur Award. But there are plenty of other ones to choose from, if you are an early career research like me.

Last year, I nominated someone as an Early Career Fellow. While that person was not named a Fellow, those who were are quite impressive. In looking over the list, I began to think that maybe I had misjudged my nomination. It’s not that the person I nominated hasn’t done awesome things, but rather those who were named as Fellows were quite a bit more senior than my nominee. If true generally, this would be a big deal for nominators. Putting together a nomination for any of the ESA awards is fairly time consuming, and so it doesn’t make a lot of sense to try to nominate someone who is almost certainly going to be out of the running.

So I dug into the data. [2] Specifically, I scoured the web for data on Early Career Fellows. Most have professional web pages. Many have CVs online. The rest have information on social media sites like LinkedIn. And my initial hunch was right. ESA states that Early Career Fellows must be non-students who are no more than eight years past their PhD degree date when they are selected. But all 27 existing Early Career Fellows were at least four years past their PhD degree date when selected, and 70% were at least seven years past their PhD degree date. [3] I am not sure why 3 Fellows were 9 years past a PhD. My guess is that the time between nomination and award announcement (6-9 months) accounts for it. Either that, or 8 years isn’t a hard cut-off. Or the awards committee doesn’t bother to verify that nominees adhere to the 8 year limit. My nominee, by contrast, had received a PhD fewer than four years earlier.


I interpret this to mean that the awards committee for Early Career Fellows looks at all nominees on an even playing field, without accounting for career length. An alternative way potential fellows might be judged is to account for time since PhD. For example, NSF committees judging applicants for the NSF Graduate Research Fellowship are supposed to take into consideration whether applicants are not yet in graduate school, are first year grad students, or are second year grad students. This is because we would expect differing levels of proposal sophistication among these groups, and it wouldn’t be fair to judge the best second year grad students against the best not-yet-grad-school applicants.

Likewise, a great researcher with just dissertation work and a year or two of postdoc experience isn’t going to be competitive with a great researcher who has an additional six years of experience. I’m not necessarily advocating that the selection committee for Early Career Fellows should take into account time since PhD. There are pros and cons of doing so. I do hope, however, that ESA leadership understands how nominees are being judged and that it feels comfortable that the judging methods align with the goals of this honor.

One thing that is clear, though, is that most Early Career Fellows are spending a sizable chunk of their 5-year honorific fellowship as mid-career ecologists. Here are the professional titles that Fellows held at the time the award was conferred:


Of the 17 Assistant Professors, I was able to calculate the number of years each Fellow had been an Assistant Professor for 16 of them. On average, Fellows had been Assistant Professors for four years when they were named Early Career Fellows (mean = 3.8, median = 4):


What this means for you as a nominator is that you should probably not bother nominating postdocs or other researchers in early temporary positions for this award. The most competitive nominees are going to be those six to eight years out from their PhD who have been in permanent positions for at least three years at the time of nomination.

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Beware this scary thing Excel can do to your data!

[1] Heh, heh. I’ve always wanted to write a clickbait title. That was fun. Excel. Love it. Hate it. Most ecologists I know use it at least a little, including me. Now I know there are plenty of people who abhor the idea of using Excel for science. But Excel is a tool, just like any other. If you were to use a screwdriver to try to hammer a nail, then my dad – who taught me to respect tools and use them for their proper purposes – would be horrified. And if you were to use Excel to manage and analyze your dataset of tens of thousands of data points, I would be horrified. You could perhaps eventually manage to struggle through. But there are better tools.

Excel is probably best for things like manual data entry, especially if you constrain the format of your cells to only allow valid entries and save in a non-proprietary format. Excel can be fine for quick exploratory analysis of small datasets: means, standard deviations, sums… that sort of thing. It’s fast at making interpretable graphs. It’s a good exploratory viewer for datasets that you get from others – most of the time.

I say most of the time because Excel tries to think for you a little too much. When you open a file that is in CSV format (the best format to store your data in most of the time), Excel converts all the values to its best guess of the format you want to view them in. This is normally fine. But when it comes to dates and times, things can go wrong. Terribly wrong. For one thing, people store their dates and times in different formats according to culture. In the US, we (weirdly) prefer the month-day-year format. In Europe (and other places), the preferred format is the more logical day-month-year. So the value 03-04-2016 is ambiguous; it could be March 4, 2016 or April 3, 2016, depending on your cultural bias. (Times can be 12-hour or 24-hour, causing other problems.)

Each version of Excel has a setting as to which way to read dates, which it originally gets from your operating system, though you can switch it manually if you want to. So if you’ve got your computer set up with US defaults, Excel will display (and save) dates in month-day-year format. If you’ve got it set up with European defaults, Excel will use day-month-year format. This can be a problem if you’re collaborating with someone who uses a different format system than you and you’re using Excel spreadsheets to share data. (Been there. Done that.)

But it’s worse than that. Excel can actually change the format of the dates in a non-Excel file (e.g. CSV file) without your permission. Don’t believe me? Try it yourself:

  1. Start with a CSV file that contains a date in a year-month-day format – the type of format we scientists prefer because it’s unambiguous across cultures. (And, if you’re a data wrangler, because any type of sorting – numeric, date-based, alphabetical – puts the dates in proper order.) You can use one of my files if you like. Make sure it is saved to your computer. excel-before
  2. Open your file in Excel. Excel will automatically reformat your dates into something it prefers.
  3. Click “Save”.
  4. Excel will prompt you with an “Are you sure?” dialog. After all, you may lose your amazing formatting, graphs, and the like if you try to save as a CSV file instead of an Excel file.
  5. Click “No” because you don’t want to save (and overwrite) your CSV file.
  6. Excel will redirect you to the “Save As” dialog. But by now, the damage has been done! Click cancel or back (depending on your version of Excel) so that you don’t save anything.
  7. Close your file. When Excel asks if you want to save it, say no.
  8. Open your CSV file with a text editor and cringe as you see that Excel has changed the format of all your dates to month-day-year (or day-month-year) without your permission. excel-after

How do you avoid this? Some suggestions:

  1. Don’t use Excel’s “Save”. Only ever use “Save As”. Of course, this only works if you’re not an obsessive saver like me who clicks Ctrl-S every few minutes without even thinking about it. [2] Once upon a time, before a developer had ever dreamed up auto-save, it was quite easy to lose huge amounts of work because you forgot to save early and often. One day an eight-year-old girl was traumatized when her home lost power, deleting a story she had spent all afternoon writing. Never again, she vowed.
  2. Store dates in a format Excel doesn’t recognize. You can use an eight-digit string, such as YYYYMMDD. So that March 4, 2016 becomes 20160304. That’s not super easy to read as a human and it can get confused with integers, so I prefer the underscored version: YYYY_MM_DD. A date might look like 2016_03_04, but Excel has no idea it’s a date and so won’t try to auto-format it. The only downside is if you need interoperability along a data management pipeline. Packages for various programming languages will almost invariably recognize YYYY-MM-DD as a date, but you’ll have to write conversion routines if you want to use underscores in your dates instead of hyphens.
  3. Never open an original copy of a file in Excel. I do this frequently, too. Simply make a copy of a CSV file and open the copy in Excel. Store your originals somewhere where you’re not tempted to open them in Excel by mistake.
  4. Explicitly tell Excel not to convert the formats on your dates and times. This is especially useful for large files. You can import your CSV file rather than opening it. If you do this, you can manually tell Excel how to read each column. So for your dates and times, tell Excel that it’s a text field instead of a date or time one. The problem with this method is that it’s tedious and there’s no way to tell Excel to remember what you did for next time or set defaults. So you’ll have to go through the tedium every time you open a file.
  5. [UPDATED] Use separate columns for month, day, and year. [Thanks to Emily McKinnon and Kara Woo (in the comments), and Kristina Riemer (on Twitter) for pointing out this simple and useful workaround!]

Or you could just not use Excel. But since you probably will, just be aware that Excel can change the format of the data in your files (without you knowing) and take precautions as needed.

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ESA Early Career Fellows are well balanced by gender

ESA announced its 2016 Early Career Fellows a few weeks ago. The program is fairly new – only in its fourth year – and its aim is to recognize the achievements and potential of excellent ecologists, broadly construed. The announcement of the 2016 cohort brings the total number of Early Career Fellows to 27. And you know what that means: a reasonable sample size for analysis and statistics! <<crowd goes wild>>

(Today, just a teaser, as I’ve got a manuscript to finish up this week before going on vacation. And I absolutely don’t work on vacation, so this manuscript’s gotta be done now.)

Let’s start out by looking at gender diversity. I was pleased to see a high representation of women Early Career Fellows this year. How has gender diversity played out over the four years of the program?

gender While we shouldn’t expect a continued increase in the proportion of women Fellows, [1] Anyone else itching to draw a trend line? 2020: 130% of ESA Early Career Fellows are women! ESA and the selection committee should be commended on its very balanced portfolio. At a total of 14 women and 13 men, that’s about as close to an even balance as you can get. I hope that this means that the efforts I’ve seen put forth in the ecological community to encourage nominators to nominate women and other underrepresented groups are paying off. (It would be interesting to know the gender balance of all nominees, but I’m not privy to that information.)

Okay, what about the institutions where Early Career Fellows are working? The description of the honor clearly states that nominees are evaluated based on contributions that “include, but are not restricted to, those that advance or apply ecological knowledge in academics, government, non-profit organizations, and the private sector.” So it seems that we should expect to see some Fellows who are not just working at R1 (or foreign equivalent) research institutions.

institution_typeWell, 80% of Fellows were at major research institutions when they got the award. Three were in the U.S. federal government, one was in U.S. state government, and one was at a non-profit. What I don’t see represented at all are comprehensive universities, primarily undergraduate universities, and the private sector. But we’re still just four years in and the sample size is still small. One question for ESA is whether a 80-20 split between major research universities and other types of institutions is a desirable balance, or whether the latter group is under-represented (perhaps based on ESA membership).

Another thing we can quickly look at is the distribution of institution locations. ESA is primarily a society for those in the United States, but it welcomes members from across the world. Early Career Fellows must be members of ESA for at least two years prior to being nominated. Here is where Early Career Fellows were geographically located when they were recognized with this award:

institution_placeI don’t have any major comment to make on this. 85% of Early Career Fellows were at US-based institutions when they became Fellows. Two were in Canada. One was in New Zealand. And one had dual affiliations in Australia and Germany.

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How and when to tell your advisor you’re pregnant (or your partner is)

I have had the experience of telling three advisors I’m having a kid — two as a grad student and one as a postdoc. And probably because I’m a bit noisy, I’ve had others ask me for advice on how to tell their advisors that they’re about to become parents. Below is my suggested game plan. You may naively expect that academic workplaces are family-friendly, as I did the first time around. While the culture is moving in that direction, there is a lot of variation among institutions and fields, and frequently no written policies for graduate students and mixed ones for postdocs. You’re likely going to have to make a lot up as you go, so the more legwork you do before birth, the less blind-sided you will be as you go through the process. Telling your advisor is a key step. Here’s how to do it:

1. Know your advisor

Will your advisor be supportive? This is the most important question to figure out an answer to before you tell. Attitudes surrounding becoming a parent – and especially becoming a mother – in academia can range from quite supportive to very negative. And you can’t assume from your advisor’s gender, age, or parent status what his or her attitude will be.

You can probably classify your advisor’s attitude as:

  • Unilaterally supportive. Your advisor recognizes his job as a mentor, and will help you any way he can to make sure you can be both an involved parent and a successful scholar.
  • Tepidly supportive. Your advisor knows she should be supportive and maybe wants to be supportive, but has reservations. These reservation may be because your scholarship reflects directly on her own or she has never mentored a grad student parent or postdoc parent before and is uncertain of how she can help.
  • Not enthusiastic. Your advisor wishes you were not going to be a parent, and may say so. She may have had a disappointing experience with a previous student or postdoc who became a parent, and may be worried about having another similar experience.
  • Hostile. Your advisor does not believe that parenthood and scholarship are compatible. He likely feels that you are “uncommitted” to your work now that you will be a parent. He may cut off funding for you, stop mentoring you, or try to hand your project to someone else.

How do you find out your advisor’s attitudes? Ask around. If you’re relatively new to the lab, ask senior grad students in your lab if they have a sense of your advisor’s attitudes. You could ask other faculty if your advisor has ever had a student or postdoc with kids and how they have reacted.

Or, if none of these strategies work, bring up the topic with your advisor yourself. You can do this long before you start the kid-begetting process. Here’s one way: if your advisor has kids, there are likely pictures on her desk. Start a conversation about them: “oh, hey, how’s Ashley doing? She’s gotta be a junior this year. Oh, gosh, are you all starting to look at colleges? Blah, blah, blah.” And then transition: “hey, have you ever had a student (or postdoc) who has had kids?” Or, if there’s a student or postdoc in the department who has kids, you can use him or her as a start-up topic of conversation: “Hey, I was just talking to Maria. Did you know she has a toddler? I wonder what that’s like, having a kid while in grad school (or as a postdoc). Have you ever had a student (or postdoc) who has had kids?” Or, if your department has a dearth of obvious parents, you can even use that as a topic starter: “I noticed that there aren’t any students (or postdocs) in the department with kids. Has this always been the case? Why do you think there aren’t any?”

2. Know your rights

In the United States, [1] If you’re not in the US, you probably have some sort of national and possibly regional laws governing your rights with regard to work and parenthood. You’ll want to look them up. your family status and your pregnancy status cannot be used to discriminate against you as an employee (i.e. teaching assistant, research assistant, postdoc employee) or as a student or as a trainee. [2] It’s far from settled law, but recent conversations I’ve had with Title IX experts lead me to believe that many postdocs are legally covered under Title IX as “trainees,” even if they aren’t technically students. That means that as a parent or parent-to-be, you shouldn’t be losing funding, getting worse assignments, or being otherwise marginalized due to your parenthood status. It also means that if you need accommodation to do your courses and/or research because you are pregnant, you are entitled to those accommodations as much as anyone with a disability is. Even if you don’t qualify for FMLA (and you likely don’t as a grad student or postdoc), if you need time to recover from birth, you can’t be kicked out of your program or fired for taking the leave you need (as established by your doctor). If you feel you’re being treated unfairly, seek out the Title IX officer at your school. (There is required to be one, but many universities haven’t come into compliance yet. So if you can’t find one, try the ombudsman’s office and see if they can help you find the right person to talk to.)

3. Know your institution and/or department’s policies

Your department or institution may have formal policies in place for grad student and/or postdoc parents. Of course, they might not. Do a web search and see what you can find. [3] Here are the written policies for parental leave for postdoc parents at a number of top ecology universities. Ask other grad student parents or postdoc parents if they know of any policies. Know that policies for grad students and postdocs are likely to be different, if they’re written down anywhere at all. Know that if you’re supported on an NSF fellowship, NSF defers to the university for parenthood policies. [4] I’m not sure how other funding agencies handle parenthood. You can always call and ask if you’re funded by NIH or EPA or another agency. Know that any policies you find on the web may not, in fact, be the true policies; make sure you get them verified by the appropriate administrative staff (for university policies) or department head (for department policies). If your university or department doesn’t have any formal written policies, then your advisor and/or department get to make up policies for you. This is why it’s important to know your rights.

4. Assess your situation

Combine what you know about your advisor, your rights, and the policies that cover you. Do you have a supportive advisor, but few rights or written policies? You may need your advisor to advocate on your behalf. Do you have a likely hostile advisor, but protective rights and policies? You may need to rely heavily on those rights and policies. Hopefully you have a reasonably supportive advisor and reasonably clear rights and policies. Whatever the case, this is the position you’re working from. Your position will affect your plan and your approach to telling your advisor.

UPDATE: Roxanne has a great comment below. If you’re a biological mom, your situation may also largely depend on the type of research you do. If you work in a lab or in the field, you may need to avoid toxic chemicals, certain types of physical activity, or you may be forbidden from accessing certain resources (e.g. ocean vessels). Roxanne highly recommends consulting with your institution’s Environmental Health and Safety department to determine what precautions will be necessary. You can do this confidentially before you meet with your advisor.

5. Have a plan, any plan

Next, you want to have a plan. The plan communicates to your advisor that you have done your homework and you have a concept of how impending parenthood is going to affect your work. For advisors who haven’t advised parent scholars before, the plan helps them get comfortable with the idea and helps them understand their role in the process. What goes in a plan? This is your best guess as to what you’re going to do in terms of your research and other work obligations as you progress through pregnancy (if you’re a biological mother) and then at birth and the first months after birth. Here are some examples of the sorts of things you might want to include:

  • I will apply for funds for an assistant to help me with field work as my pregnancy progresses
  • I will contact disability services when I am 7 months pregnant for parking and shuttle accommodations so I can get to my office in the last two months of pregnancy
  • I will take a month off after the birth of my child, as allowed by our university’s paternal leave policy
  • I am going to move up my preliminary exam two months from April to February, so that I remain on track in my grad program
  • I will arrange to set up Skype on my own computer and on a computer in our lab, so I can Skype in to lab meetings when I can’t be there in person
  • I am rearranging the order in which I do analyses on existing data and new lab work to accommodate necessary precautions on chemical exposure while pregnant
  • I will work with you to find funding so the lab work I’m doing can continue while I am on maternity leave
  • I plan to be completely offline while I am on maternity leave, so I will delegate ongoing responsibilities during this time to these named lab members

The main goal is to communicate to your advisor that you’ve thought about how your research will continue, though there may need to be changes and accommodations. You should stress to your advisor that this is a preliminary plan and that you and your advisor will necessarily need to be flexible. You may not know exactly what you will need ahead of time. Additionally, having a child is a series of lotteries and you will likely encounter unexpected events. Planning for flexibility is key.

6. Time your tell, and make your Ask(s)

Finally, it’s time to tell your advisor. You’ve got a sense of what his reaction will be. You’ve done your homework and know your rights and resources. You’ve got a plan to present. When and how do you actually tell?

How far ahead of birth to tell your advisor is a personal decision. The earlier you tell, the more time you’ll have to develop plans and contingency plans – either in collaboration with your advisor or through other resources. But I don’t know of too many people who tell their advisors before their immediate family and closest friends. In general, it’s better to tell your advisor directly, rather than having her hear through the grapevine. So plan to tell him before you tell all your peers. (Obviously if you have some close peer friends who can refrain from spreading the info, feel free to tell them first.) If you’re going to be a biological mother, you don’t have as much flexibility as biological fathers or adoptive parents; your body will likely tell by about 5 or 6 months of pregnancy, whether or not you decide to tell in words.

For targeting an actual date to tell, figure out where your advisor is in terms of her own business. If you can, try to avoid a particularly stressful time in your advisor’s life, whether that is the first weeks of a semester, the weeks before submitting a major grant proposal, or pinch time for field work. If you’ve got a good rapport with your advisor and he is likely to have a non-negative reaction, I suggest you simply schedule a meeting and tell him in person. Present your plan. Ask for advice; maybe he knows of some resources that you haven’t encountered.  If you are worried about your advisor’s reaction, it’s okay to tell her by email. In fact, it may be a good idea. An advisor who is lukewarm or hostile to the idea of advising a parent scholar will likely have a very negative initial reaction, but may come around with enough time. Present your plan in the email. Make it clear that you intend to be both a parent and a researcher. Give your advisor time to process the news before having a more extended conversation about it.

You might need to make one or more Asks, whether that’s in person or by email. What I mean by this is that you may need to ask your advisor for time, money, material resources, permission, or advocacy that will enable you to succeed as a scholar while also becoming a new parent. Your Asks should be framed in a win-win sort of way:

  • The semester I give birth, I won’t be able to be a teaching assistant. Can you help me find another source of funding so that I can continue to make progress on my graduate studies during this time? We both want me to meet the goals of the graduate program.
  • I will be on parental leave for a month, so I won’t be able to feed the lab critters every day. Can you designate someone else to take over this task during this time? We both need live critters to do our research.
  • In the first year after my child is born, I would like to have permission to work from home and attend meetings by Skype as much as feasible. This flexibility will allow me to maximize my time to make the most progress on my analysis and manuscript writing. We both want to see these manuscripts published as soon as possible.

Don’t be afraid to ask for what you need. Advisors, by definition, have a vested interest in seeing you succeed. They may not be able to give you exactly what you ask for, but all but the most hostile should be able to help you think through possible options.

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Open data, authorship, and the early career scientist

About a year ago, my coauthors and I published a huge dataset of more than a million annotated images of animals from a camera trap network in the Serengeti. The lead author, Dr. Swanson, and I are both early career scientists, and we both put a ton of time and effort into this dataset. We made the decision to publish the dataset as its own product after more than a half-dozen researchers in other fields (computer vision, citizen science, education) contacted us to ask if they could use our data. Our graduate advisor (and PI-on-paper) wondered whether this was a good idea. If we published the data, he worried, other people could take it and do the sorts of community ecology research that we were hoping to do with it.

I’ve heard this worry a lot about open data. I’ve had this worry myself as a grad student. But as far as I can tell, having made this dataset (and others) available, is that the worry about being scooped is way overblown for most ecology datasets. That doesn’t mean it can’t or doesn’t happen. But I think it’s a rare case when it does. (Can anyone point to a time it’s happened?) Instead, opening up the data has meant two great things. First, when people contact us about our data and camera trap network (which happens monthly), we can just point them to the dataset and it saves us a ton of time. Second, there are ecologists using our data in ways we never imagined, including looking at community ecology in groups of animals we don’t (small mammals, lizards versus large mammals) and investigating wildlife disease.

Open data is great!

But. (You knew there was going to be a but.) Here’s something I haven’t heard proponents of Open Science talking about much. If you publish a dataset, you pretty much lose control over authorship.

Traditionally, the way data in ecology worked (and still mostly works) is that you go through a lot of effort to create a dataset. Then you keep it. Hopefully you’re smart and you back it up and have other safeguards to make sure it doesn’t get compromised. But usually it just sits on your desktop computer somewhere. Then people find out about your data. Probably you published something. Maybe sometimes through word of mouth. And if people want to use your data, they contact you and say, “hey, I have a great idea for an analysis and paper that needs your data. Can we collaborate?” Often this is code for, “if you give me your data, I’ll give you co-authorship on the resulting publications.”

And there’s a reason for this customary tit-for-tat. Producing ecological datasets is far from trivial. It’s also nice to know who is using your data and for what. As a data-creator, you want to make sure your data is not misused. Not only do you care about the science coming out right, but because your reputation is attached to the data, a misuse reflects poorly on you, even if it’s done by someone else.

The LTER network has an explicit data policy that reads, “The Data Set has been released in the spirit of open scientific collaboration. Data Users are thus strongly encouraged to consider consultation, collaboration and/or co-authorship with the Data Set Creator.” Not too long ago this policy was on a site-by-site basis and — at least for the sites that I used data from — contacting the data creator was a requirement for publishing using existing data.

For early career researchers, there’s a super important reason for this custom of co-authorship when re-using data. Number of publications matters. It just does. If I have spent some sizeable fraction of my nascent career on developing a particular dataset, I need to get credit when that dataset is used for advancing science. And the truth is that number of publications counts way more than number of citations.

So here’s the problem: anyone can use data from our big published dataset (please do!), and they will be right and proper to simply cite it. If we hadn’t published the dataset, then people would have to contact us about collaborating and my coauthors and I could rack up more publications. Perhaps the data would be used less overall, because it’s a bit more effort to exchange a few emails than to simply download a dataset. The crucial point is that Open Data may be good for science, but it may be bad for scientists — especially early career ones. Not because the authors of open data will be scooped, but because the authors lose credit for their data relative to authors who do don’t make their data open.

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Experiments in efficiency: cooking while peer-reviewing

In computer science, laziness is a virtue. The term “lazy” is basically used as a shorthand for saying you should strive for efficiency so you don’t spend time writing code you could have avoided writing if you’d been smarter about your coding design. I’ve always generally keep an eye towards efficiency in my work, and never more so since having kids, when efficiency is the only way to be moderately successful in both work and other-than-work life. (By which I mean avoiding inefficiency, not becoming hyper-efficient, which has its own problems.)

I try to do all the standard established work efficiency things – make lists, batch tasks, delegate when I can, turn email off – and household efficiency things – make lists, consolidate shopping trips, have schedules for the kids [1] Schedules are useful for maintaining some semblance of peace and harmony in a household with kids. Or at least as much peace and harmony as you can have when your kid is in the highly-opinionated-and-completely-irrational phase, in which any of the following can produce a complete meltdown: He wants to be both eating and playing in the living room simultaneously and the laws of physics are not cooperating. The red car and the blue car both need be occupying the same volume of space and the laws of physics are not cooperating. The green car needs to be half on the table with the other half hovering in midair and the laws of physics are not cooperating. The socks will not fit over the shoes. The very large ball refuses to roll under the couch unlike its more obedient smaller cousins. The door that was closed this morning is now open. Mommy is wearing a red shirt. Why yes, kiddo #2 is turning TWO this week. How did you know?, and so forth. And I keep an eye out for efficiency tactics that are specific to my life – things that aren’t necessarily applicable to all people and so don’t make the usual Top 10 list. For example, I can write papers blog on my bus commute, whereas many people don’t have bus commutes or else get motion sick and can’t write on their commutes even if they are on a bus.

It’s never clear ahead of time which tricks will work and which will fail, so it’s kinda fun to try them. Example situation: working with a newborn asleep on lab. Trick that didn’t work for me, but may work for you: dictating to software, so that you can write while parenting. My problem: every time I talked, the baby woke up. Trick that did work for me: Getting an iPad that I could perch on the arm of my chair so that I could read and research and do email one-handed.

So last week I was working on a review, and we had a tricky childcare situation, since our usual provider was on vacation. And it was 5:00 and I absolutely positively had to stop working to make dinner so that my family wouldn’t starve [2] or at least get really cranky which sometimes feels almost as bad. But I was in the middle of my first read-through and I really, really wanted to finish, because I hate stopping things in the middle of things. I briefly considered whether I could read and chop vegetables at the same time, but of course, that’s ridiculous. And then it occurred to me that I could try having my computer read to me!

Most (all?) computers have an accessibility feature where the computer will read text. It took me less than five minutes to figure out where mine was and set it up. Still 55 minutes to cook, so I was okay. I told it to start reading in the middle of the paper I was reviewing. And then I had to take a couple minutes to figure out how to slow down – slow way down – the reading speed. Then my computer read to me while I cooked! Overall, I give the trick a lukewarm thumbs up. Here’s what I discovered:

  • I needed more volume. Cooking is loud. There’s water running, and onions sizzling, and the exhaust fan. And moreover, I was moving around the kitchen, so I wasn’t always close to my computer. Next time, I could potentially hook up my Bluetooth speakers to actually get more volume. But probably better are wireless earbuds or headphones, so the sound could stay with me as I moved around.
  • At the end of every page, the computer read me the watermark and the footer and the header of the next page. It was rather annoying, especially since the main text was usually in the middle of a sentence. And then at the beginning of every section, the computer read to me the line numbers. I stood there dumbstruck as it recited, “forty-six, forty-seven, forty-eight, … “ So several times, I had to stop cooking, run over to the computer, and move the cursor so it would skip the numbers. I can’t think of any way around these particular annoyances. If you can, let me know!
  • Cooking is a bit messy, and having to interact with my computer was cumbersome, as I had to make sure my fingers were relatively dry and free of food whenever I did so.
  • Listening to the paper slowed down my cooking. It’s true what they say about multitasking: your brain isn’t wired to do two unrelated tasks simultaneously. But it didn’t slow it down by much. Maybe an extra 5 to 10 minutes for an hour of cooking. If it was going to take me 20 minutes to finish reading the paper anyway, that’s still a few minutes saved. More importantly to me, I got to finish the paper, while also getting dinner on the table on time!
  • Relatedly, I had to pause the paper-reading a couple times to read a recipe or search for an ingredient that wasn’t where I thought it was. I definitely couldn’t do anything cooking-wise that required more than minimal attention while also paying attention to the paper.
  • Cooking while listening to the paper meant I didn’t catch all the details of the paper (maybe in part because of the volume issue). And that’s okay for a first read-through of a paper that I’m going to reread in more depth anyway. But the trick might not work for all papers.

I’m probably not going to be listening to papers while cooking very much, but it’s nice to know that I could. I think perhaps it might be a useful trick for a time when I have a lot of repetitive work to do (e.g. mounting insects) that doesn’t involve much thinking. I usually listen to podcasts or streaming radio when I do. Instead, I could listen to some of those papers in my Interesting Papers To Read directory that I never seem to get around to.

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Thoughts on my first double-blind peer review

Not too long ago I agreed to review a paper after skimming the abstract and looking up the journal. When I went to actually do the review, I saw that the journal has a double-blind policy, and so I couldn’t see the names or affiliations of the authors and they couldn’t see mine. (The latter part here is standard practice for all but the “open review” journals.)

I’ve read about double-blind review, but never actually participated as author or reviewer before, so I got a little thrill when I realized I’d be participating. In theory, I really like the concept, because there is reason to believe that unconscious bias affects how reviewers review papers. After all, unconscious bias affects pretty much everything. Unfortunately, there’s not a lot of good hard evidence for reviewer unconscious bias, mostly because this issue has only come into the general scientific awareness relatively recently, and – I’ve read – it’s hard to actually do a good study. Rather than feel like, “no need to get excited about reviewer implicit bias until there’s evidence,” I think we ought to be particularly motivated to get some really solid studies done. Because if it’s a problem, then it’s a very serious one.

My particular views on implicit bias come from realizing my own. Several years ago, I took this awareness test (choose “Gender-Science IAT” from the list to do the one I did). And I started paying attention to my own thoughts. And I realized something unsettling. In early grad school, I frequently skipped the authors section when first reading a paper, because I pretty much didn’t know who anyone was and the names were meaningless to me. Then, if it was a paper I liked, I’d note the names of the authors, so I could remember them. If the first author’s name was female, I’d be surprised – like, “oh wow! Hawkes is a woman!” Because the thing is, when I read a science paper, the default narrator’s voice in my head is male. It just is. These days, I note authors’ names before reading, and frequently enough I know the authors or at least know of them. But every once in a while, I’m still surprised by author gender – almost invariably I’ve read a paper that lists only first initials and then come to find out that the author is female later in some other way.

Okay, so this is horribly embarrassing. I mean, I consider myself to be pretty free of gender stereotypes. I’m a self-described tomboy. I’ve spent most of my life in male-dominated activities doing male gendered things. My husband and I are all in on equal parenting and householding. I know tons of accomplished female scientists and other highly respected women in male-dominated fields. So what gives? Culture. I am simply a product of my culture – just like everyone else. And so if I’ve got anti-female implicit bias, I figure pretty much everyone else does, too.

Back to double-blind review. Does implicit bias matter when reviewing? Very possibly. We don’t know for sure yet. [1] But I think that a good study will look in the math or physics or engineering fields first, where power to detect such a bias is likely higher. Even if it doesn’t matter or matter very much, the perception that it matters is still affecting where people send manuscripts. So, at the very least, it matters indirectly.

How is double blind actually conducted? I imagine there are variations on a theme at different journals. Here’s what the journal I reviewed for did:

  • It specified that the author(s) were “blinded” and didn’t provide their names or affiliations
  • Oddly, it also “blinded” the Date Submitted, but not the Total Time in Review. (shrug)
  • Within the text itself, someone at the journal had redacted some bits of text here and there and replaced it with (Removed by [journal]).

I found this curious, as I am no stranger to reading and writing words that can’t be seen by most people, and I know from first-hand experience that redacting a document is awfully time-consuming, tedious, and error-prone. It’s a task that no one enjoys. It’s expensive. And to be honest, I’m not sure how useful it is in the case of double-blind review.

I don’t know the authors of the study I reviewed. But I can easily guess the nationality of their institution – and even what part of the country they’re in. If I wanted to do a little googling, I’m pretty sure I could figure out who exactly they are. And I’ve read critiques saying that because double-blind often doesn’t really blind the reviewer to the authors’ identities, double-blind peer review is an exercise in futility.

But I’m not so sure. Let’s divide the relationships between author and reviewer into three categories. First, we have authors and reviewers who know one another personally or know one another’s work well. They may have collaborated at some point, or more likely, they just study the same sorts of things and so read one another’s papers a lot. They may meet at conferences and workshops because of their mutual interests. When a reviewer reads a paper by someone whose work (or whose lab’s work) they know, they’re likely to figure out the authors if the review is double-blind. But I’d argue that this is okay. The reviewer already has an impression of the author based on other experiences, and so implicit bias may not be an issue. [2] Proof is left as an exercise for the reader

Now let’s consider reviewers who don’t know the authors in real life, and have never even heard of them. Let’s say that, like in my case, there’s enough information in the manuscript that the reviewer could figure out the authors’ likely name(s) if they tried. My question would be: who would bother? I mean, who has the time to go sleuthing for names? [3] If you do have that time, could you maybe sign up to do a bit more reviewing instead of sleuthing? So, here double-blind works to counter implicit bias in that the reviewer still doesn’t know who the authors are, even though the blind has technically failed.

Finally, we have the straightforward case of a reviewer who doesn’t know the authors and in which it isn’t possible to tell from the manuscript who they are. In this case the blinding works, and there’s not much more to say.

Assuming that reviewers aren’t willing to go the extra mile to uncover author identities and that reviewers who can figure out who the authors are just by reading the manuscript already have an impression of the authors, making double-blind really simple might be just as good as having it be complex. The strategy would be this: Just don’t provide author names and affiliations. That’s it. Really simple to do. Really fast. Really inexpensive.

As for my review, I signed it, as I always do. [4] I think the retaliation fear is way overblown, and I’m happy to be a guinea pig. But I’m glad I got to try a blind review, as it modified my thoughts on the double-blind process.

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From the beginning: my path to ecology

Meg Duffy is collecting ecologists’ origin stories, and who doesn’t like to write about themselves? So here is my story of How I Became an Ecologist.

My story begins on the high plains of the Great Karoo in South Africa. I’d never been anywhere like it. The land is flat and dry and ruddy, dotted by unfamiliar shrubs and grasses. Off on the horizons, pastel mountains and koppies interrupt the progression from earth to sky. For someone from the forested Northeast US, the openness is a little bit invigorating, a little bit frightening. During the day, I spot a tortoise. At night, I gaze up at an unfamiliar sky and see the Southern Cross for the first time. I’m here visiting my college friend Corinna. She’s doing a Fulbright year, studying these semi-desert plants of the Karoo and the effect of drought-stress and cattle grazing on them. I barely follow the aims of her science and wonder why what seems like scientific minutiae have any importance, but I am fascinated by the landscape. While she works, I pepper her with natural history questions she can’t possibly know the answers to, because nobody does. But I don’t know that yet. She suggests that maybe I should become an ecologist.

Except, my story doesn’t really begin there. It begins across the ocean, at a community college in Maryland, where I’m attending an evening introductory biology class. I hold a bachelor’s degree in computer science, and a good-paying job in that field. But I’m unsatisfied with my day job and so have been filling my evenings and weekends with more meaningful activities. This fall, I’m going back to school to learn what I might have learned in high school, had things played out differently. My fellow students mostly have complex lives. Many are working during the day and attending college at night to earn their first degree. My lab partner works two jobs and has kids. He barely makes it through each class awake. We are reading a chapter on cell organelles, and the chapter explains that no one really know what some of the organelles do. I assume the content is a bit out-of-date and corner the teacher after class, only to have it confirmed. I’m incredulous. I’m infuriated. I’m intrigued. How is it possible that we don’t understand these bits of our own cells – this material that is in the first few chapters of an introductory biology course?

Except, that’s not the beginning either. Perhaps the beginning is when I am a child living at the edge of a small woods that I am free to explore. I learn the paths intimately, climb the trees, make pretend. I find ladies slippers and Indian pipes. I know how to walk quietly through the woods, how to spy on the occasional dog-walker or other interloper without being seen or heard. These are my woods, and I retreat to them when I am upset or sad or lonely. But I long to know more. I want to know the names of the trees, which plants are edible, the identities of the birds that I hear. But it’s the pre-Internet era, and I don’t have access to this information. My parents are both in the computer field. They don’t walk in my woods.

But maybe my story actually begins when I decide to be a computer scientist. I’d always wanted to be a scientist, I was a whiz at math, and I’d taught myself to program. Now I am holding a four-year scholarship that I can take to any college, as long as I major in computer science. The scholarship is a diversity program run by the federal government and stipulates that I work for the government for about four years upon graduation. The program has not yet been ruled unconstitutional. The scholarship means that I can go to the college of my choice, but also importantly, that there will be enough money left in the family coffers for my younger brother to go the school of his choice, too. I can’t say no, and I don’t want to. A full ride with a guaranteed job is an amazing deal.

The other beginning takes place in a three-bedroom roach-infested apartment that I share with Mike and Tim on the outskirts of Washington D.C. We live steps from the National Oceanic Atmospheric Administration (NOAA) on the border of gentrified Northwest and the not-yet-subsumed melting pot of Northeast. NOAA means nothing to me. Being childless, listless, and bored, I’m perusing the bookshelves where Mike and Tim stash their leisure reading. Tim works for an anti-hunger non-profit. Mike works for the National Academies. Both are intensely interested in land-use policy and social and environmental justice. I have grown up without any real civic education, either at home or at school. Mike and Tim take me to protests. They introduce me to civics, to international policy, to power structures, and I gobble it all up. I pick up A Sand County Almanac and Guns, Germs and Steel. I read Edward Abbey, John McPhee, Bill McKibben, Vandana Shiva. Tim and his girlfriend Erin subscribe to Bull Run Farm, which sells its vegetables through the Community Supported Agriculture (CSA) model, and they give me their leftover produce. The food is local, pesticide-free, and delicious.

But all that only really matters because I met Ilana and she asked me to cook with her. I’d met Ilana in Brown’s introductory computer science course, but it’s the only computer class she’ll ever take. Ilana is thoughtful and extrospective, a true intellectual. She will take a semester off to read books because school is interfering with her ability to learn. I love talking with her. Her food co-op needs more members and she encourages me to sign up, though I’ve never really cooked before and certainly not for 16 to 20 people. But two people cook each meal and I’m carefully paired each time with a more experienced member. We cook vegetarian kosher food with the Moosewood Cookbook as our sacred text, and I am introduced to both eating and preparing a diverse array of food. I shed my childhood pickiness and learn to appreciate real food for the first time.

Of course, everyone’s story really begins with their parents. My mother and father each had unusual upbringings, though I didn’t understand that until much later. Endlessly curious, as all children are, my mother learned to stop asking questions early on, for fear of her father abandoning her, too. My father, also endlessly curious, had to find his own answers, as the oldest of four children in a foreign country with an absentee father and a mother who had to learn the customs and language of the family’s new country. Both my parents have a fierce devotion to education. When I started primary school and they found the local school to be inadequate for me, they sold their beloved old house and moved the family to a much smaller home in a nearby wealthy town with an excellent public school system. Both the old house and the new house have woods out back.

When I was born, my mother made a promise to herself to try answer all of my questions, to never snap back “because I said so,” to never ignore my curiosity out of hand. As a parent now, I understand how hard it is to keep that sort of promise, but she did. In the era before the Internet, my mother didn’t always have all the answers. One winter, I worried about the Eastern painted turtles that wandered up into our yard from the neighboring wetland during the summers. I had just learned about warm-blooded and cold-blooded. Were the turtles all dead? They couldn’t be. But how could they survive New England winters? My mother didn’t know, so she took me to the library. We searched the kids’ books; useless. We searched the adult books, but found no answers. We asked the librarians, and learned nothing. We even wrote in to the science Q&A column of the newspaper. The question was never published. A couple years later my mom stumbled upon the answer and told it to me excitedly. She hadn’t forgotten my question; she honored my curiosity. I would find, as I grew up, that my fearlessness in asking questions would occasionally annoy people. But much more often, it would open doors.

In the beginning, as a kid, my favorite TV programs are PBS nature specials. I watch every single one I can, engrossed by animals I’ve never seen, landscapes I could never have imagined. I envy the naturalists and scientists who are profiled in these programs their adventures. But I know, as any child does who is encouraged to be reasonable, that TV personalities have unobtainable jobs. Just like the professional basketball player and the movie actress, the stars of nature specials are in a special class of not-quite-real people who somehow get to be celebrities on TV. I don’t see ‘naturalist’ or ‘ecologist’ as real jobs; I’ve never even heard of either.

It might be that my story begins in a windowless inner office of the National Security Agency. It is not long after airplanes fly into two New York office buildings, the Pentagon, and a field in Pennsylvania. It is quite a while before Edward Snowden. I like my job. I hate my job. I am doing research, which I am good at and is fun. I enjoy excelling at my job. I loathe what my efforts might be used for. I am forced to think about ethics, individual responsibility, meaning, personal fulfillment. I quit my job the day my scholarship contract is up.

It might also be that my story begins on one of the many days I sigh and walk into the Sunlab, the huge room full of Unix workstations that acts as the community center of the Brown computer science department. On this particular day, I walk in and see the phrase “Gentlemen, welcome to the Sunlab” scrawled across the announcement white board. I point out to the Sunlab Coordinator, a student whose job it is to oversee the lab, that the message is sexist. He gets defensive. “No, it’s not. It’s from a movie, don’t you know? It’s just a joke. Geez.” Fight Club has just come out, but I haven’t seen it, will never see it. Resigned, I find a computer and sit down to work. It’s just not worth the fight. I am smugly satisfied to see that the message has been erased when I finish my assignment and leave. But long term, I don’t really want to spend all my time fighting the boys’ club that is computer science. I wish I could change my major.

That same week I probably met up with Corinna to go to the soup seminar at the Urban Environmental Lab. We’ll also meet Ben, my on-and-off boyfriend who will eventually become my husband. They are both environmental science majors in a department that hosts a weekly seminar presented by an environment professional. As a proper undergraduate, the lure of free food (soup!) and the comradery of two of my closest friends is hard to resist, and I find myself at many such soup seminars, listening to ecologists and conservationists talk about the work they do. For the first time, it enters my mind that maybe it is possible to have a job studying and protecting nature. But, of course, I have my scholarship and my fixed major. I don’t think too much about “what if.”

From the start, I knew biology wasn’t for me. In seventh grade, I had my first biology class. We memorized things now long forgotten and dissected worms and frogs. The stench of formaldehyde would stay with me forever. In high school, it was clear what the hierarchy of sciences was. The lowest levels were earth science and biology. Next was chemistry. And highest was physics. I was smart and ambitious. I chose earth science over biology, then took chemistry, physics, and advanced physics. My guidance counselor protested. “If we were to require any science course, it would be biology,” he explained. I ignored him. I knew that biology was nothing but memorization, which I hated, while chemistry and physics were centered around math, which I loved. Even still, dear Mr. Flight, my earth science teacher and one of my best-ever teachers, planted the seed of environmental education. He ended each class with a Fact of the Day, such as an exposition of dead zone in the Gulf of Mexico due to nutrient run-off from Midwest agriculture. Fifteen years later, I was horrified to discover that the Grown Ups had not yet fixed this obviously terrible problem.

My new beginning, the start of the rest of my life, takes place in Wisconsin, on a small family farm near the scenic river town of Osceola. I am in the Midwest because Ben, now my fiancé, has started a geology PhD at the University of Minnesota. I am on a farm because I want to do something as different from computer work as possible. This is a CSA farm, run by the husband-wife team of Paul and Chris. We plant, cultivate, pick, pack, and deliver vegetables to the 300 subscribers who have invested in the farm activities from the outset. The farm has no nutrient runoff into the nearby river. I am enamored with organic agriculture and the CSA economic model, and think I might become a farmer. Paul has a PhD in plant biology and delivers lectures to me and the two other interns as we haul boxes of produce, pull weeks from the soil. I learn about the nitrogen cycle, about legumes and their Rhizobia. I learn about powdery mildew and crop rotations. I learn about soils and decomposition. I learn about insect pests and their natural enemies. I learn to identify plant stress at a glance, about calcium deficiency and plant competition. Despite – or perhaps because of – his PhD, Paul decries the ivory tower. He left it for a reason. University researchers, even extension researchers, are out of touch with what happens in the real world, out of touch with the needs and constraints of actual farmers, actual land managers. And despite his vast knowledge of plants biology, I drive him crazy with my incessant questions. I question his practices, his routines. He tells me that this is a business. You have to pick a method and do it, or you won’t have any vegetables to sell. There is not much time for experimentation on a small family farm.

I spend the summer placing tiny seeds into divided trays, watering, picking and pulling, hauling, sorting, building a greenhouse, learning to drive a tractor. I love working outside every day. I get up early to witness the peaceful mornings when the low light makes the eggplants and peppers and summer squash glow with vibrant colors. The palms of my hands toughen and I find a quiet reverie in weeding row after row of carrots, row after row of spinach, row after row of cilantro. The smells of basil, of tomato vine, of damp earth infuse my being and I feel for the first time in my adult life that I am really living. The work is meaningful and fulfilling. It is also hard toil, and by mid-autumn I am physically stronger than I’ve ever been, but tired. Very tired. I know this is not quite my path, but I don’t know yet what is.

I spend the next year in Minneapolis, pondering, reading, volunteering, fencing, making new friends. I want a job that is meaningful, and a job that is intellectually stimulating. I want a job in which I am not stuck behind a computer all day every day and in which I can make a difference. By now, the world of academic research is less unfamiliar. Corinna is at the University of California at Davis, finishing up an ecology PhD. Ben is in the second year of his geology PhD. Tim is about to start a geography PhD at Michigan State. I find the University of Minnesota’s conservation biology program online, and peruse its pages. I email a dozen professors affiliated with the program and ask to talk with them. About half reply and agree to meet with me. I am excited by their research, attracted by their friendliness. One of them, Craig Packer, will become one of my future dissertation advisors. I sign up for the intro undergrad ecology course through the office of continuing education The teacher for the course has good reviews in the undergrad ratings catalog. His name is David Tilman. Partway through the course, I go to his office hours and tell him that he screwed up his lecture, mistaking the prefix mega- for giga- when talking about the carbon cycle. Our conversation ends with him hiring me part-time to work on an environmental economics project. He will become my other dissertation advisor. That fall, I apply to the ecology program, and Paul writes me a letter of recommendation.

I think most people’s lives are not straight lines, one thing leading to another, but rather a skein of threads, each twisting and turning, becoming entangled with others, stopping, starting again. We crave a linear story, a simple one. And I could fit my story into a straight narrative if necessary. But the truer story is messy. I have become an ecologist. I work as an ecologist now. Who knows what the future holds.

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