Results are in!

Hello everyone!

We hope this Lab Note finds all of you generous backers (and readers) staying safe and healthy! We last updated you in 2020 on our progress in the lab, different obstacles we faced (e.g. the pandemic), and some preliminary results.

Well, we’re excited to announce that all the lab work is finally wrapped up, all the analyses of the sequences is done and the full results are now in. We’ve completed the basic exploration of the samples – that is, how they are distributed between the different hyena clans we study in the Ngorongoro Crater, how many we have for each year, sex, age, social rank category, and the total number of detections for the prey species. Next will come the process of understanding the finer-scale trends and differences in prey selection over time relative to the Ngorongoro Crater prey census data. A HUGE thanks once again to all of you for your support, interest, and positive feedback during this study.

In total, we have 378 samples from 256 different hyenas to work with, with a temporal range from 1996 to 2019! All 8 of the resident Crater hyena clans are represented and there is a near 50-50 split in terms of the number of samples from the six peripheral clans that reside closest to the human settlements on the Crater highlands (187) and samples from the two central clans that are surrounded by other Crater clans (191) which will make for an interesting comparison.

 

Distribution of samples based on Ngorongoro Crater hyena clans and clan categories.

We detected 21 different prey species and among those prey species, some sure stand out. For example, we found a few detections of lion DNA in some of our samples – a sign of possible scavenging on lion carcasses or predation on lion cubs. We’ve also had a few detections of rodent DNA in our samples, which is something that tends to go undetected during our daily behavioral follows of hyenas. We also faced a challenge: we were unable to distinguish between wildebeest and kongoni DNA due to a lack of base pair differences between the species in the 12S region of the mitochondrial genome. Due to this ambiguity, we dug a bit further by re-running the 36 highest-quality samples in our data set that contained either wildebeest or kongoni DNA (or both). But this time, we focused on the larger 16S region where there were sufficient base pair differences to distinguish between the species. As it turns out, all of the samples unambiguously contained wildebeest and did not contain kongoni! This makes sense, because wildebeest are far more abundant in the Crater than kongoni are and are therefore much more available as prey to the hyenas.

 

A kongoni (left) and a wildebeest (right). Image sources: Arjun Dheer (left) and Wikimedia Commons (right).

There are already plenty more detailed, interesting trends we’ve noticed among these samples, but we’ll have to save those spoilers for later!