Home range, sleeping site use, and band fissioning in hamadryas baboons: Improved estimates using GPS collars

Abstract

Variation in spatial and temporal distribution of resources drives animal movement patterns. Links between ecology and behavior are particularly salient for the multilevel society of hamadryas baboons, in which social units cleave and coalesce over time in response to ecological factors. Here, we used data from GPS collars to estimate home range size and assess temporal patterns of sleeping site use in a band of hamadryas baboons in Awash National Park, Ethiopia. We used GPS data derived from 2 to 3 collared baboons over three 8-12-month collaring intervals to estimate annual and monthly home ranges using kernel density estimators (KDEs) and minimum convex polygons (MCPs). The 95% KDE home range was 64.11 km² for Collaring Interval I (July 2015-March 2016), 85.52 km² for Collaring Interval II (October 2016-October 2017), 76.43 km² for Collaring Interval III (July 2018-May 2019), and 75.25 km² across all three collaring intervals. MCP home ranges were 103.46 km² for Collaring Interval I, 97.90 km² for Collaring Interval II, 105.22 km² for Collaring Interval III, and 129.33 km² overall. Ninety-five percent KDE home range sizes did not differ across months, nor correlate with temperature or precipitation, but monthly MCP home ranges increased with monthly precipitation. Our data also revealed a southward home range shift over time and seven previously unknown sleeping sites, three of which were used more often during the wet season. Band cohesion was highest during dry months and lowest during wet months, with fissioning occurring more frequently at higher temperatures. One pair of collared individuals from Collaring Interval III spent 95% of nights together, suggesting they were members of the same clan. Our results both suggest that previous studies have underestimated the home range size of hamadryas baboons and highlight the benefits of remote data collection.

Keywords: fission fusion; home range size; movement patterns; remote sensing; spatial ecology.

Figure 1

(a) Sleeping cliffs used by a band of hamadryas baboons (Papio hamadryas) in Awash National Park, Ethiopia, over three collaring intervals from 2015 to 2019. Cliffs A–D (diamonds) had been identified as sleeping sites before this study, while cliffs E–K (circles) were discovered as sleeping sites using data from this study. The scale bar is 10 km in every panel. (b) Annual home range estimate (95% KDE; transparent yellow) and core area estimate (50% KDE; solid yellow with border) for Collaring Interval I (2015–2016). (c) Annual (95% KDE; transparent blue) and core area estimate (50% KDE; solid blue with border) for Collaring Interval II (2016–2017). (d) Annual (95% KDE; transparent purple) and core area estimate (50% KDE; solid pink with border) for Collaring Interval III (2018–2019). KDE, kernel density estimator

Figure 2

Monthly home range estimates (95% KDE, km²) for a band of hamadryas baboons (Papio hamadryas) over three collaring intervals from 2015 to 2019. KDE, kernel density estimator

Figure 3

Monthly home range estimates (95% KDE, km²; solid line) and “core area” estimates (50% KDE, km²; dashed line) for a band of hamadryas baboons (Papio hamadryas) over three collaring intervals from 2015 to 2019. ^†Months with less than 2 weeks of data. KDE, kernel density estimator

Figure 4

Seasonal variation in use of each sleeping cliff by a band of hamadryas baboons. (a) Monthly use of Cliff A (Filoha) over time, compared to Cliffs E–I, showing a greater use of Cliff A during drier months and a decrease in use of Cliff A over time. (b) Monthly use of Cliffs E, F, and H (the southerly cliffs), showing increased use during and following months with higher total monthly precipitation and increased use over time. ^†Months with less than 2 weeks of data

Figure 5

Monthly rates of band cohesion in hamadryas baboons as a function of average monthly minimum temperature. Band cohesion decreases significantly, that is, band fissioning into clans increases, as average minimum temperature increases, with warmer months, such as June, July, and August, having the lowest cohesiveness