Female post-copulatory behavior in a group of olive baboons (Papio anubis) infected by Treponema pallidum

Host-Parasite Coevolution in Primates

Organisms adapt to their environment through evolutionary processes. Environments consist of abiotic factors, but also of other organisms. In many cases, two or more species interact over generations and adapt in a reciprocal way to evolutionary changes in the respective other species. Such coevolutionary processes are found in mutualistic and antagonistic systems, such as predator-prey and host-parasite (including pathogens) relationships. Coevolution often results in an "arms race" between pathogens and hosts and can significantly affect the virulence of pathogens and thus the severity of infectious diseases, a process that we are currently witnessing with SARS-CoV-2. Furthermore, it can lead to co-speciation, resulting in congruent phylogenies of, e.g., the host and parasite. Monkeys and other primates are no exception. They are hosts to a large number of pathogens that have shaped not only the primate immune system but also various ecological and behavioral adaptions. These pathogens can cause severe diseases and most likely also infect multiple primate species, including humans. Here, we briefly review general aspects of the coevolutionary process in its strict sense and highlight the value of cophylogenetic analyses as an indicator for coevolution.

Road-based line distance surveys overestimate densities of olive baboons

Estimating population density and population dynamics is essential for understanding primate ecology and relies on robust methods. While distance sampling theory provides a robust framework for estimating animal abundance, implementing a constrained, non-systematic transect design could bias density estimates. Here, we assessed potential bias associated with line distance sampling surveys along roads based on a case study with olive baboons (Papio anubis) in Lake Manyara National Park (Tanzania). This was achieved by comparing density estimates of olive baboons derived from road transect surveys with density estimates derived from estimating the maximum number of social groups (via sleeping site counts) and multiplying this metric with the estimated average size of social groups. From 2011 to 2019, we counted olive baboons along road transects, estimated survey-specific densities in a distance sampling framework, and assessed temporal population trends. Based on the fitted half-normal detection function, the mean density was 132.5 baboons km^-2 (95% CI: 110.4–159.2), however, detection models did not fit well due to heaping of sightings on and near the transects. Density estimates were associated with relatively wide confidence intervals that were mostly caused by encounter rate variance. Based on a generalized additive model, baboon densities were greater during the rainy seasons compared to the dry seasons but did not show marked annual trends. Compared to estimates derived from the alternative method (sleeping site survey), distance sampling along road transects overestimated the abundance of baboons more than threefold. Possibly, this overestimation was caused by the preferred use of roads by baboons. While being a frequently used technique (due to its relative ease of implementation compared to spatially randomized survey techniques), inferring population density of baboons (and possibly other species) based on road transects should be treated with caution. Beyond these methodological concerns and considering only the most conservative estimates, baboon densities in LMNP are among the highest across their geographic distribution range.