This past weekend I went on a camping trip to New York with a few others to celebrate the joint birthdays of myself and another friend. It was a great weekend of many camp fires, little technology, and general acceptance of camp funk from the camp fires and lack of technology. Brings me back to field seasons.
Camping just outside Buffalo, we felt a little obligated to make the quick trip north to Niagara Falls. Walking around, I was asked several times whether fish could make the journey down the nearly 170-foot fall and survive. The answer is yes, absolutely! (Turtles can too, but this isn’t a turtle blog.) Generally speaking, as long as fish are falling in water (as opposed to falling through the air and hitting water at the bottom), they probability of surviving the fall is high.
But, what about getting back up? It goes without saying that a trip down a fall as large as Niagara is a one-way journey. But, smaller falls can potentially be traversed by fish moving in both directions. This is especially true in salmonids (including trout), which are natural-born high jumpers and are able to leap several feet into the air if they can get a good “running” start.
What makes a waterfall navigable by upstream migrants isn’t so cut and dry. A fall that is a straight drop is not going to be passable by even the most agile fish. But, smaller falls and falls made-up of a series of small step-downs can often be traversed. And, somewhat ironically, the ability of fish to navigate a waterfall increases with higher stream flows. Flooding increases water velocity in the center of the channel, which can give fish the extra boost of swimming speed needed to jump higher and further. High flows also cause streams to spill over onto the banks where it is normally dry, and fish seeking refuge in these temporary habitats often find new, easier routes, up waterfalls.
So, how do we determine if a fall is navigable? Genetics! Specifically, we can look at the results from a program called STRUCTURE.
STRUCTURE output can easily become difficult to understand. But, in short, you feed the genetic data from individual fish into the program, and it produces a diagram that shows you the most likely population assignment for each fish. You can then use the output to answer questions about where a fish was likely born, how connected populations are, and/or the extent an identified barrier (such as a waterfall) blocks fish movement.
I find it best to think about STRUCTURE output with an example. STRUCTURE analyses can be performed on any organism, and the below example is from a paper on the plant, creeping fig. The authors’ sampled 17 populations, and STRUCTURE determined that there were only two genetically unique populations (as represented by the red and green colors). The number of sampled populations is much higher than the number of genetically distinct populations because there is a high degree of population connectivity and movement of individuals among populations prevents genetic isolation.
If you look at the STRUCTURE diagram, you can see that there is a line for each individual, and each line is a stacked bar chart that is color-coded by the probability the individual assigns to each population. So, an individual with high assignment to the red population is represented by a solid red bar, and an individual with high assignment to the green population will be represented by a solid green bar. Bars that are of various degrees of both red and green represent individuals that have ancestors from both populations. For example, if an individual has a parent from each population, then they show up as 50% red and 50% green.
Big picture, the more isolated a population, the higher the probability that individuals will be from a single genetic population. As a result, isolated populations show up as solid blocks of color in STRUCTURE. Populations that are more open have individuals that have lower assignment probabilities to many genetic populations, and they appear as blocks of mixed color in STRUCTURE.
Now, let’s put this information to work using two examples from brook trout in Loyalsock Creek. The first is a fairly sizeable waterfall on Weed Creek. Normally when sampling for population genetics I don’t go above a known movement barrier. I know it is likely to separate a population, even if just a little, and so I would technically be sampling two populations instead of one. But, at this site, for reason that don’t matter, I decided to collect 40 fish downstream of the falls and ten from above. The STRUCTURE diagram looks like this.
Can you guess what’s going on? (Hint: there’s three genetic populations in this diagram, and the fish caught upstream of the waterfall are on the right).
If you guessed that fish weren’t moving upstream of this fall, then you’d be correct. The solid block of green on the right represents fish upstream of the fall, and they are all assigning with high probability to the “green” population.
Downstream of the fall, things are a little more interesting and a lot more confusing. We see several fish with high assignment to the “green” population, which probably represents fish that recently dropped down the falls. As you can see, there’s quite a few fish that make the journey down the falls and survive. There’s also several fish that are represented as mostly red or mostly blue. One of those colors probably represents the genetics of the resident fish of Weed Creek who living downstream of the falls. The other is probably fish that are moving in from another tributary. Which color is which is uncertain with the data at hand.
Lastly, we see fish that are combination of any two colors, or, in some cases, all three colors. This represents individuals that were spawned from some combination of fish dropping downstream, moving from outside of Weed Creek, and/or fish living downstream of the falls in Weed Creek. This is what it looks like to have a genetically diverse population!
Now, let’s look at another example for comparison. This time, I’ve chosen two different streams, separated by no known barriers, and quite literally a stone’s throw away from one another. Before scrolling down, take a second to think about what you might expect the STRUCTURE diagram to look like.
Not what you were expecting, huh? One stream is almost entirely genetically distinct and shows up as a nearly solid blue box. The other stream has a little more diversity, with two genetic populations nearly equally represented by green and red. But, more strikingly, we see almost no fish from the other site, the “blue” site, finding their way into this stream.
What’s going on here? I’m not sure. But, what this genetics data highlights is that movement barriers aren’t always so obvious. Sure, waterfalls, bridge crossings, and dry channels decrease movement. But, sometimes we can’t always see the barrier, and it may not be a physical barrier but could be driven by some sort of behavior. In the examples here, there was more movement downstream of a fairly large waterfall than there was in an open channel. But, now that we’ve uncovered this hidden barrier, we can start looking a little more closely and potentially find a way to reconnect these two populations.