Road-based line distance surveys overestimate densities of olive baboons

Abstract

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.

Influence of infrastructure, ecology, and underpass-dimensions on multi-year use of Standard Gauge Railway underpasses by mammals in Tsavo, Kenya

“…Along the infrastructure corridor which includes the SGR, food leftovers are often thrown out of cars, particularly in areas close to human habitation (Lala, pers observation). This is likely to attract baboons towards roads and their greater use of wildlife corridors near roads 99 . Moreover, baboons’ proclivity for using wildlife corridors near roads can be further explained by their use of roads as an efficient method of travel, where groups of baboons can move faster and in a more directed manner 100 .…”

Population dynamics of the Manyara monkey (Cercopithecus mitismanyaraensis) and vervet monkey (Chlorocebus pygerythrus) in Lake Manyara National Park, Tanzania

“…As field survey and analytical methods varied among sites, it is, however, difficult to compare estimates among studies. Furthermore, comparative studies on olive baboon survey methods in LMNP provide evidence that distance sampling along roads yields biased absolute population density estimates (Kiffner et al, 2022). Manyara monkey densities (average of 13.0 individuals km −2 ; 95 % CI: 10.2-16.7) for LMNP are, at least, well within the range of densities for gentle monkeys at other sites in central Africa and eastern Africa (Butynski, 1990;Thomas, 1991;Plumptre and Reynolds, 1994;Fashing and Cords, 2000;Hall et al, 2003;Uehara, 2003;Fashing et al, 2012;McLester et al, 2019).…”

“…Before providing further interpretations of our data for conservation assessments, a word of caution is appropriate. As our density estimates are based on road surveys (which may not represent the entire study area; Kiffner et al, 2022) and as both monkey species showed distinct distribution patterns (which are not accounted for when extrapolating densities from the area covered by the transect to the study area), the actual population density of the surveyed species may differ from our estimates. Potential design-based bias probably does not affect temporal trends, but the non-random distribution of transects can substantially affect absolute density estimates (Beaver et al, 2014;Kiffner et al, 2017).…”

“…In addition, competition with the abundant and widely distributed vervet monkey (Fig. 1b) and olive baboon (Kiffner et al, 2022) might influence their distribution. Specific patterns of primate co-occurrences in LMNP are known (i.e.…”

Quantifying reliability and data deficiency in global vertebrate population trends using the Living Planet Index

“…We chose a normal distribution for ϕ t because we assumed there to be an equal chance of underestimating or overestimating population abundance. The LPI uses a mix of survey types and estimation methods and there does not seem to be conclusive evidence of whether one type of bias is dominant (e.g., Johansson et al, 2020; Kiffner et al, 2022; Lubow & Ransom, 2016; Manning & Goldberg, 2010).…”