Dive In: Iron from the seafloor to the surface

This is the first post in a new series called Dive Into Science.  Here I’ll be explaining results from recent scientific papers in oceanography.  Dive Into Science gives you a glimpse of current research in an easy to read format that everyone can understand.  To read more about oceanography, just use the Dive Into Science tag.

Today’s article is “Estimating the benthic efflux of dissolved iron on the Ross Sea continental shelf” by C.M. Marsay et al, published in Geophysical Research Letters, 2014.

This paper is all about iron supply from the seafloor to the surface ocean.  Specifically, in the Ross Sea, Antarctica, a place of extreme weather that’s difficult to travel to and observe.

I’ve mentioned the importance of iron in the ocean before, and even talked about how it is measured, but let’s do a quick recap.  Iron is known as a “micronutrient”.  Phytoplankton need iron to carry out their biological processes; to grow and reproduce.  However, unlike other nutrients such as nitrogen, phosphorus, and carbon, iron is only needed in extremely small quantities.  Such small quantities, in fact, that it took oceanographers awhile to discover that iron was even used at all!

In most oceanic habitats, there is enough background iron that it doesn’t really make a difference to the phytoplankton – they are more concerned about their main nutrients.  However, in certain locations, like the Southern Ocean, there are areas that are iron-limited, such as the Ross Sea.  Here, we see tons of nutrients in the surface waters, but no phytoplankton, because they are missing the iron they need.

The Ross Sea, Antarctica.  Shown with important landmarks, and the ship track for the cruise this data was collected on.

During spring time in the Ross Sea, which occurs in December in the Southern Hemisphere, the sea ice melts and the phytoplankton get enough sunlight to grow.  They multiply quickly during this “spring bloom” period, then die off as the iron runs out.  The iron in the surface ocean during springtime has either been mixed up from the bottom waters over the winter, or has been added from sea ice melting.

The authors of this paper are specifically investigating the iron that starts at the seafloor, often from the sediments on the bottom, and mixes upward to eventually reach the surface.  To do this, they took a series of measurements during a cruise of concentrations of dissolved iron in the water at various locations and depths in the Ross Sea.  Using these measurements, they can see how much iron is near the seafloor, and how quickly it depletes towards the surface.

Graph of how iron concentration changes with height above the seafloor in the Ross Sea.  Adapted from Marsay et al 2014.

Then, they combined these measurements with results from a regional ocean circulation model.  This model shows how the water moves and can give researchers a good idea of how long it takes to mix water upwards, and how much is mixed upwards.

So, if water at the bottom has a certain amount of iron in it, and is mixed upward at a certain rate, you can calculate how much iron from the bottom gets to the surface.  This calculation was the main purpose of this paper; to put a number on the flux of iron from near the seafloor.

Comparing this number with how much iron is used up in the surface showed that only about 1/10th actually made it from seafloor to surface.  The rest, even though it was mixed upwards as calculated, was probably exported from this area to other regions offshore by currents.

As a scientist, this paper holds two important results for the community.  The data that was collected was the first time detailed near-bottom sampling of dissolved iron was carried out in this area.  Then, the main result of the paper is the amount of iron that traveled from the seafloor to the surface.  In order to understand the iron-limited system in the Ross Sea, we need to know all the sources and sinks of iron: where does it come from, and where does it leave, and by how much?  This paper put a number on one of those sources, and estimated that a large portion of that source is exported before it reaches the surface.

This is a good example of how science progresses.  A cruise in early 2012 took water samples that were analyzed in a laboratory to produce dissolved iron data.  That data was then examined for patterns and explanations, combined with other available data (in this case model results), and published 2.5 years after the cruise.  The time it took from beginning to end is very reasonable for science, especially when you consider that the scientist is working on other projects and publications at the same time, perhaps even teaching classes, and the data is being used for other research.

Questions or thoughts about this new research?  I’ll also take suggested topics for future article reviews.

Working on a Collaborative Project

Over the past several years, I’ve had some excellent first hand experience with large collaborations.  You know, the projects where there are PIs (that’s Principal Investigators for you non-science people) from multiple institutions.  They are all interested in their own little slice of the project, yet they still need to work together to answer larger questions.
And so the endless conference calls begin…
It’s really not that bad.  No, seriously.  It takes a lot of time to be a part of a larger group, time you could have spent doing your own work.  But then you pool the results of the joint effort to answer large, over-arching questions.  And it is amazing.
Instead of being stuck in your own niche, you branch out and grow.  Sure, you can still write the technical papers that only the handful of people in your sub-sub-sub-sub-field will understand and actually read.  But you also help write the synthesis papers that makes the work you’ve done useful to answer a bigger question.
Here are some of my reflections on the process of working as part of a large collaborative project and what I’ve learned from it:
You start to think about multi-disciplinary approaches.  For most projects, the important results aren’t what some individual researcher happened to find.  The results that really matter are the synthesis of different types of data from different sub-fields to understand a larger system or process.  When you work on a large project, you still consider what advances you can make, but you also think a lot about how what you do can help someone else.  As the project progresses, you learn a lot more than you ever cared to know about other sub-fields.  This changes the way you think, and when you move on to new ideas and new projects in the future, you will already have an idea of how your work can help answer questions in a different field.  Right now, the most important results in earth sciences are coming from areas where multiple sub-fields intersect.
Prioritizing your work becomes more important.  Once you start working for a group, you have essentially two separate goals.  One is to finish your own work in a timely manner (so you can publish, graduate, move on…).  The other is to provide the support other project members need to do their work.  For me, prioritizing the proper goal was a matter of trial and error.  In some cases, maybe when a paper in review needs more data from you to get it published, it is clear the project work must come first.  But then there are also times when the project work isn’t as important, and you can put it off to pursue your own work.  The right answer to which should you prioritize seems to be mostly based on specific situation.  Just keep a good handle on deadlines and expectations.  And notice you aren’t the only one on the project who isn’t doing as much as they could be.
Do not make unrealistic claims about how fast you can work.  Projects often require status updates and future plans to be given to the group.  And this is fine.  Just don’t say you will finish such and such a stage by next month.  As soon as those words are out of your mouth, your equipment will break, or your computer will crash, and you’ll be left making excuses.  Unless you are directly asked for a time when a certain part will be completed, don’t offer any sort of information on timing.  Just report what you’ve done and outline what you plan to do next.  In the event that you are asked for a timeline, consider a worst-case scenario to finish a task, then double that amount of time.  Finishing something early always looks better than finishing it late, and the only difference is what you say at the beginning.
It is possible to herd cats gracefully.  Scientists are like cats.  Independent, intelligent, and impossible to herd without some incentive or bribery.  And even then, it’s a toss up if they will go where you want them to.  So when you get a roomful of scientists, who each lead their own lab group, and specify one to be the leader for the project, it turns into an exercise on herding cats.  I’ve heard of projects where this effort does not go well.  The key to herding cats gracefully seems to be a healthy dose of respect all around, and a guiding leader.  If the head scientist on the project can guide discussions in the right direction, bring up important issues, and keep people on task, but NOT make decisions for everyone, it works well.  You end up with a group making joint decisions after discussions and consideration from everyone.  The best leader in this case is one who oils the gears of a machine rather than trying to drive it a certain direction.
Conference calls are the best way to stay in touch, and the bane of your existence.  Most projects use conference calls to stay in touch and provide updates on a weekly or monthly basis.  Rather than playing email tag, or traveling to the same location, it’s a great way to check in, advance plans, and get feedback about important issues.  At the same time, conference calls can be a huge time sink.  It is unlikely that, unless you are the project leader, you will be interested in more than half of the call.  It takes time to hash things out, and during an hour long call, you may be bored and un-involved for most of it.  But beware of multi-tasking!  As soon as you stop paying complete attention, someone will ask you for details only you know about, and the only part of the question you will hear is your name.
You reap the benefits of co-authorship and exposure and your network expands.  When working on a larger project, you end up spending a good amount of time with the other project members.  By getting to know them, you are expanding your professional network, and increasing your exposure.  When you work on papers with them as a co-author, you become the expert they know.  They, like you, may not often work with many people in other fields.  Now that they know you, you are their go-to person for any questions related to your field.  If you do your work well, they may refer their other colleagues to you as well, and this can open up opportunities for other projects and collaborations in your future.
Overall, I found that working with a large project is very beneficial for me.  The extra time and work commitment is more than compensated for by the papers, connections, and exposure that comes from working with a large multi-disciplinary group.
So, what about you?  Have you had any experiences working on large projects?  Would you want to be a part of one in the future?

Alternate Careers

I’ve never been much of one to have a career plan.  I studied what I found interesting in school.  I’m one of the lucky ones though – I’ve been considered smart enough to be allowed to just keep on learning.  Thus I avoid all encounters with the dreaded job market.

This isn’t really the best strategy though.  Sure, it feels easy to slide through life and grad school this way, but that’s because this is the path of least resistance.  Think about it.  You are only exposed to people (professors) who finished that career path one way.  In terms of statistics, it is most certainly NOT a random sample.

The issue is that there are way more PhDs awarded than there are academic positions for them above the postdoc level.  A good portion of graduate students will not end up following a path similar to that of their mentors and advisors.  There’s a good chance that could be you.  So, have you thought about what you can do outside of academia?

First, let’s get over the term “alternate career”.  Sure, if you want to do a search on the subject, that’s probably the best phrase to use.  But it implies that a career in academia is the “right” end to a graduate school start, and all other choices are second-best.  This stigma is still present, especially among older faculty members, but it no longer makes sense.  In a society focused on work-life balance, your career choice is no longer a strict indicator of your intelligence.  Never feel like choosing an non-academic career path is a step down.

Now that your head is in the right place, you need to figure out your options.  This will depend on your field, and also on what degree you end up with.  And any extra experience you may have.  It’s not always obvious at first what you can do with a grad school degree besides academic work.

The first option that typically comes to mind, at least in the sciences, is science writing or outreach.  You can also consider a job in industry.  Almost every science-based field has a corresponding industry, but it may not be clear at first.  I found some of the best information in library books and by signing up for job boards and email lists.  Another option is to consult a career counselor – and there’s a good chance your university offers a service like this.

In the end, it’s up to you to choose the career that best fits your skills and lifestyle.  The first step in this direction is to know what your options are.  So don’t be taken in by thinking academia is the only path.  Find people who have done something different with the same background.  After you know what’s out there, you’ll be able to make much better career decisions.