Research is hard.

It’s a simple statement, but I can guarantee that every professor, post-doc, and graduate student would agree that research, while rewarding and ultimately worthwhile, is nevertheless a difficult thing to do. Every type of biologist faces their own unique set of challenges: the biological modeler may struggle endlessly with programming code, the molecular biologist may spend months troubleshooting an experiment, and the ecologist may watch helplessly as a severe storm decimates their study species. Catastrophes befall all scientists, but there are ways to prevent and mitigate the effects of bad luck. Here are a couple of challenges I faced during my research and how I dealt (or wish I dealt) with them:

Rule #1) You can never be too prepared.

Before my first field season in Chile I spent a lot of time thinking about how I was going to collect my data, and I ended up writing several drafts of equipment lists. In the end, I brought down some equipment that ended up being unnecessary (for example, I brought 10 radio trap transmitters, these nifty gadgets send out a signal when the trap door shuts. While it was great in theory, it didn’t work well in the field because birds would get caught in the traps and cause false alarms, and also 10 transmitters wasn’t very helpful when I was  generally using 100 traps at a time). But, I also ended up bringing some equipment that really saved the day, like a hand-crank centrifuge that I was able to use when we stayed in a cabin without electricity in Parque Nacional Fray Jorge. The conclusion is that it’s best to bring more things than you think you’ll need (as long as you stay within your luggage limit).

But being prepared is more than just bringing the right equipment- it’s also about reading everything you can and communicating with your collaborators and other, more experienced researchers. Grant writing was actually a great way to prepare for this- by thoroughly reading the literature and getting feedback from my mentors, I was able to iron out some of the more theoretical aspects of my projects.

Rule #2) Don’t put all your eggs in one basket

There’s always the chance that an experiment will completely and utterly fail, so it’s a good idea to have multiple projects so you’ll be able to come home with something. During my first field season in Chile, it became apparent that my main project would require another year of field work, which meant that I would have to secure more funding. In addition to this uncertainty, my main project was also ambitious and risky. So, to make sure that my first field season (which was five months long) wasn’t wasted, I also pursued two, additional projects. In the end, I completed one of these side projects during my first field season and was able to publish a manuscript, so even if things hadn’t worked out with my main project, I would have at least gotten something out of my time in Chile.

Rule #3) Make contingency plans

No matter how much you prepare and no matter how familiar you are with your study system, key events may still not go according to plan. For example, this year I’m doing a laboratory experiment that examines the effect of stress on the quality and quantity of maternal care. The easiest way to do this experiment would have been to catch pregnant degus in the field and bring them into the lab where they could then give birth. However, transference to captivity is stressful, and I didn’t want pre-natal stress (stress while the mothers are still pregnant) to affect the pups. I could have also caught pregnant females very close to parturition, so then there wouldn’t be much time for the mother’s stress to affect the pups in utero, but then the disadvantage would be that females would still be adjusting to captivity after they gave birth and maybe this would affect maternal care.  So, I instead caught females a year before the experiment and then mated them in the lab. However, I knew that my degus might have a low fertility rate, so I made a plan in case this happened (another thing would have been to collect more animals than I needed, but this wasn’t possible logistically because of space limits. Also, it would have cost a lot more money to buy more terrariums, food, and animal care. And it also has ethical problems- you don’t want to use an unnecessary number of animals).

 

So what happened? Unfortunately, only 40% of my degus got pregnant, so I went according to my contingency plan and trapped some very pregnant degus in the field and brought them into the lab. While this wasn’t the ideal situation, I will at least be able to compare my lab-mated degus with the field-mated degus. In the end, I think it will work out, and the important thing is that I planned for this and made sure that I had the time and resources to trap these additional degus. And because the current experiment isn’t totally ideal, I’ve decided to collect some additional data to take advantage of the new group of degus (some of these wild degus, due to individual differences, will be “more stressed” than others, so I’m measuring the mother’s CORT levels to see if they correspond with the amount of maternal care they give to their pups).

Rule #4) Be realistic

Don’t try to take on more than you can manage, and if things get too busy or crazy, figure out if there’s some project aspect you can drop, delay, or share with a collaborator. I’ve had chances to collect additional data or even add projects to my current research, but I’ve sometimes passed up these opportunities so I could spend more time writing papers and grants, sleeping (this is actually really important because I had to safely drive a truck at 5:00am almost every day last season), and having fun. Before I go to Chile my advisor always says “Be safe, work hard, and make sure to have some fun,” so I try to do those three things in that order.

Rule #5) Be flexible

As I explained in Rule #3, not everything goes to plan. But oftentimes an experiment can be salvaged by altering data collection methods or changing the number of treatment groups or controlled variables. Working in the field means you can’t control everything, and this is especially true when you work with wild animals because they can leave your study area, get eaten, or refuse to be recaptured. Being a successful field researcher means you have to know when to make compromises- if you compromise too much your data may lose a lot of significance, but if you refuse to compromise you may end up with no usable data at all.

Rule #6) Always, always, always back up your data.

I’ve always strictly adhered to this rule, and it really saved my bacon when my computer completely and utterly died two days after arriving in Chile this year (screw you, Apple). Luckily, I had just backed up my data on my portable, external hard drive so I was able to easily move my files to my new laptop (I now have a Lenovo which I really like except for the Spanish keyboard). When I’m collecting data, I back up my computer at least once a week, and I also try to make sure that my data is stored in at least two separate places. I’ll also occasionally email my data spreadsheets to my advisor and collaborators, just in case. And finally, I make sure to record all my data in a lab or field notebook, and I always try to enter these data into my computer within a day of collection. For field notebooks, I highly recommend Rite-in-the-Rain notebooks which are tough, waterproof, and are used by field biologists everywhere.

Rule #7) Accept defeat gracefully and with humor

This may be the hardest rule to follow, but if you can manage to keep a positive outlook and not get overly stressed when everything goes to hell, then you’ll be a happier, healthier researcher. Every researcher, at some time in their career, will have a project that will totally fail. The best thing to do is to salvage what you can or go to one of your back-up plans, but if all else fails, then it’s best to just move on and plan for future experiments. I’ve only spent a few years in academia, but from what I have seen so far, I think that the most successful researchers are those that are resilient and optimistic. To be a successful researcher you have to accept that failures will occur, because if you give up after one or two failures, then you’ll never get a grant funded or a paper accepted.

While these seven rules are not exhaustive, they do provide a good, general philosophy for any scientist working in the field. If any readers have some additional advice, please feel free to send me your comments and I’ll post them on this blog!