Barnacle eggs and mangroves
Research complications in Panama
As Dr. Jesus Pineda leapt off the side of the boat, knife in hand, I had the analogous scientific feeling of “Toto, I have a feeling we’re not in Kansas anymore.” I was out of my depth — literally — since the tide had come in and the water was several meters deep. But let me back up and tell you how I, a graduate student who prefers pixels to petri dishes and MATLAB to measuring, ended up on a boat with a renowned scientist jumping overboard.
It was January, and I was with a group of five other graduate students on a tiny island off the west coast of Panama. We were there to learn about how tropical ecology is studied and get some hands-on practice learning about the corals and mangroves there. As a theoretical ecologist, I had some noble thoughts about how useful it would be for me to understand field ecology, the difficulties of collecting data, sources of variability, and so on; I was looking forward to getting my hands dirty and feet wet.
Each of us was expected to come up with a small research project, and several days in, I had my heart set on understanding the timing of reproduction in barnacles living on mangrove trees. These barnacles are strange, compared to the ones we see on Cape Cod; they live up really high. Well, really high relative to my eye level, so about one and a half meters up. The tides in Panama are pretty extreme, so these barnacles spend quite a lot of time out of the water. We had this idea that they probably link their release of larvae to the tides, so they go out when the water level is maximal and can return in a high tidal cycle so they can settle up high as well. Scrape some barnacles off some trees, dissect them, look for eggs, do some statistics. No problem.
The first day, we were delayed after some other sampling, so we hit the mangroves at high tide rather than low, and the trees I wanted to sample were mostly underwater. It was then that our instructor abandoned ship to get the samples. I put on a brave face and tried to sound unfazed as I called out which trees to sample from my detailed plan. However, the complications with sampling in the field weren’t over, as I had hoped, but rather just beginning.
Back in the lab, I had to learn how to dissect barnacles and what the difference between a fully developed egg, an egg with eyes and guts, and random orange goo was. (It’s not easy! All of these things looked a little like orange goo to my untrained eye, and some barnacles had goo that appeared unrelated to eggs at all.) Then, we discovered that there might be some strong spatial autocorrelation in reproduction. Basically, if I had scraped off ten barnacles in a cluster, they seemed to be either all non-reproductive or all reproductive; this would complicate our analysis, because a sample of 100 barnacles in ten patches might be effectively only ten samples. However, I hadn’t learned my lesson yet about how complicated this was, and my thought was, “Easy-peasy! I’ll come up with a new sampling scheme to test for under versus over-dispersion!”
Standing out in the mangroves trying to enact my spiffy new sampling scheme was another story. I wanted to collect discrete chunks of barnacles, but knobs on the bark prevented me from getting contiguous clumps. The fact that the branches were circular complicated how I could sample; different species were sometimes intermixed; some trees had already been sampled so intensively I couldn’t collect more. In addition, it was really hot out.
I hope you are feeling as overwhelmed reading this as I felt. There were so many scales of variability and so many factors to consider. This was coupled with the fact that we had the worst type of uncertainty — unknown unknowns. We didn’t know if inter or intra-tree variability was high. We didn’t know how old barnacles were. We didn’t know what the pre-cursor for eggs looked like. We didn’t know how large their radius of fertilization was, or if they tend to self-fertilize.
Seeing first-hand hand how complicated ecology can get reminded me of the importance of why we make models — to try to simplify processes and understand how components interact. But it also reminded me how much we don’t know and how hard it is to figure it out; biology is complicated! On the flip side, I guess that guarantees I’ll still have something to research sixty years down the road.