Developing evolutionary anthropology in local ecosystems

The traditional regional focus of evolutionary anthropology-typically defined as places where hominin fossils, nonhuman primates, and non-western populations reside-forms the basis of much evolutionary anthropological research. Using the highly biodiverse temperate region of Appalachia as an example, we suggest that evolutionary anthropologists have much to gain by stepping outside of this traditional geographic area. Being purposely provocative, we argue that evolutionary anthropologists might also benefit from conducting research in Appalachia and other temperate ecosystems. We briefly discuss multiple areas of study-including studies of seed dispersal, functional redundancy, convergent evolution, human behavioral ecology, and conservation-and how they can be considered within the purview of integrative and evolutionary anthropology. We also highlight broader impacts to higher education that evolutionary anthropologists can help promote by working in local ecosystems.

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.