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Dickson, C. C.

Publications and source records attributed to Dickson, C. C..

2 recordsLinked to original sources

Demographic, behavioral, and ecological data from a long-term field study of wild baboons in Amboseli, Kenya

Long-term data sets on individually recognized animals and their environments are critical to understanding animal behavior, evolution, and ecology. However, they are resource- and time-intensive and seldom made publicly available. The Amboseli Baboon Research Project (ABRP) is one of the longest-running studies of a wild mammal population in the world and has collected extensive data on the baboon population of the Amboseli ecosystem in Kenya since 1971. Here, we describe four ABRP data sets newly available to the evolutionary biology, behavioral ecology, and primatology communities: (1) the sizes and demographic compositions of 21 social groups from 1971-2023; (2) the activity budgets of adult females and immatures from 1984-2023; (3) behavioral data on diet for adult females and immatures from 1984-2023; and (4) weather data, including precipitation from 1976-2023 and temperature from 1976-2022. Data are aggregated annually and monthly to enable cross-data set analyses. These data offer a rare longitudinal perspective on behavioral and ecological change in a wild mammal population.

animal behavior and cognition↗

When is microbial strain sharing evidence for transmission?

In humans and other social animals, social partners have more similar microbiomes than expected by chance, suggesting that social contact transfers microorganisms. Yet, social microbiome transmission can be difficult to identify based on compositional data alone. To overcome this challenge, recent studies have used information about microbial strain sharing (i.e., the shared presence of highly similar microbial sequences) to infer transmission. However, the degree to which strain sharing is influenced by shared traits and environments among social partners, rather than transmission per se, is not well understood. Here, we first use a fecal microbiota transplant dataset to show that strain sharing can recapitulate true transmission networks under ideal settings when donor-recipient pairs are unambiguous and recipients are sampled shortly after transmission. In contrast, in gut metagenomes from a wild baboon population, we find that demographic and environmental factors can override signals of strain sharing among social partners. We conclude that strain-level analyses provide useful information about microbiome similarity, but other facets of study design, especially longitudinal sampling and careful consideration of host characteristics, are essential for inferring the underlying mechanisms.

microbiology↗