Fossils and molecular data are two independent sources of information that should in principle provide consistent inferences of when evolutionary lineages diverged. Here we use an alternative approach to genetic inference of species split times in recent human and ape evolution that is independent of the fossil record. We first use genetic parentage information on a large number of wild chimpanzees and mountain gorillas to directly infer their average generation times. We then compare these generation time estimates with those of humans and apply recent estimates of the human mutation rate per generation to derive estimates of split times of great apes and humans that are independent of fossil calibration. We date the human-chimpanzee split to at least 7-8 million years and the population split between Neanderthals and modern humans to 400,000-800,000 y ago. This suggests that molecular divergence dates may not be in conflict with the attribution of 6-to 7-million-y-old fossils to the human lineage and 400,000-yold fossils to the Neanderthal lineage.hominin | molecular dating | primate | speciation O ver 40 y ago, Sarich and Wilson used immunological data to propose that humans and African great apes diverged only about 5 million y ago, some three to four times more recently than had been assumed on the basis of the fossil record (1). Although contentious at the time (e.g., ref. 2), this divergence has since been repeatedly estimated from DNA sequence data at 4-6 million years ago (Ma) (3-8). However, this estimate is incompatible with the attribution of fossils older than 6 Ma to the human lineage. Although the assignment of fossils such as the ∼6 Ma Orrorin (9) and the 6-7 Ma Sahelanthropus (10) to the human lineage remains controversial (11), it is also possible that the divergence dates inferred from DNA sequence data are too recent.The total amount of sequence differences observed today between two evolutionary lineages can be expressed as the sum of two values: the sequence differences that accumulated since gene flow ceased between the lineages ("split time") and the sequence differences that correspond to the diversity in the common ancestor of both lineages. The extent of variation in the ancestral species may be estimated from the variance of DNA sequence differences observed across different parts of the genome between the species today, which will be larger the greater the level of variation in the ancestral population. By subtracting this value from the total amount of sequence differences, the sequence differences accumulated since the split can be estimated. The rate at which DNA sequence differences accumulate in the genome ("mutation rate") is needed to then convert DNA sequence differences into split times.In prior research, mutation rates have been calculated using species split times estimated from the fossil record as calibration points. For calculating split times between present-day humans and great apes, calibration points that assume DNA sequence differences between humans and orangutans...

Large‐scale genomic studies of wild animal populations are often limited by access to high‐quality DNA. Although noninvasive samples, such as faeces, can be readily collected, DNA from the sample producers is usually present in low quantities, fragmented, and contaminated by microorganism and dietary DNAs. Hybridization capture can help to overcome these impediments by increasing the proportion of subject DNA prior to high‐throughput sequencing. Here we evaluate a key design variable for hybridization capture, the number of rounds of capture, by testing whether one or two rounds are most appropriate, given varying sample quality (as measured by the ratios of subject to total DNA). We used a set of 1,780 quality‐assessed wild chimpanzee (Pan troglodytes schweinfurthii) faecal samples and chose 110 samples of varying quality for exome capture and sequencing. We used multiple regression to assess the effects of the ratio of subject to total DNA (sample quality), rounds of capture and sequencing effort on the number of unique exome reads sequenced. We not only show that one round of capture is preferable when the proportion of subject DNA in a sample is above ~2%–3%, but also explore various types of bias introduced by capture, and develop a model that predicts the sequencing effort necessary for a desired data yield from samples of a given quality. Thus, our results provide a useful guide and pave a methodological way forward for researchers wishing to plan similar hybridization capture studies.

It has been proposed that human cooperation is unique among animals for its scale and complexity, its altruistic nature and its occurrence among large groups of individuals that are not closely related or are even strangers. One potential solution to this puzzle is that the unique aspects of human cooperation evolved as a result of high levels of lethal competition (i.e. warfare) between genetically differentiated groups. Although between-group migration would seem to make this scenario unlikely, the plausibility of the between-group competition model has recently been supported by analyses using estimates of genetic differentiation derived from contemporary human groups hypothesized to be representative of those that existed during the time period when human cooperation evolved. Here, we examine levels of between-group genetic differentiation in a large sample of contemporary human groups selected to overcome some of the problems with earlier estimates, and compare them with those of chimpanzees. We find that our estimates of between-group genetic differentiation in contemporary humans are lower than those used in previous tests, and not higher than those of chimpanzees. Because levels of between-group competition in contemporary humans and chimpanzees are also similar, these findings suggest that the identification of other factors that differ between chimpanzees and humans may be needed to provide a compelling explanation of why humans, but not chimpanzees, display the unique features of human cooperation.

Genetic capture‐recapture (CR) estimates of population size have potential for aiding the conservation and management of rare or elusive animals. To date, few studies have explored the performance of genetic CR estimates by implementing them in a population of known size. We evaluated the accuracy and precision of genetic CR estimates by genotyping fecal samples collected opportunistically over the territory of a well‐studied group of approximately 190 previously identified and genotyped eastern chimpanzees (Pan troglodytes schweinfurthii) in Kibale National Park, Uganda. We compared the performance of genetic CR estimates based on 3‐month and 3‐year sampling periods to explore the impact of lengthened sample periods, which are expected to increase accuracy and precision of estimates but also increase the chances of violating population closure assumptions. We compared the effects of using spatial and non‐spatial models and equal or heterogeneous detection probabilities upon estimates. Over the 3‐year period, we detected 54% of the group members and produced population size estimates with more accuracy and narrower confidence intervals than the 3‐month sampling period. The population remained effectively closed over the 3 years and detection heterogeneity was linked to age but not sex. Non‐spatial methods estimated group size more accurately than spatially explicit methods, which had a stronger tendency to underestimate population size. This study suggests that genetic CR may produce accurate and precise population size estimates if substantial effort is allocated to sample collection and genotyping. © 2016 The Wildlife Society.

Behavioral flexibility, the ability to change behavior when circumstances change based on learning from previous experience, is thought to play an important role in a species’ ability to successfully adapt to new environments and expand its geographic range. However, it is possible that causal cognition, the ability to understand relationships beyond their statistical covariations, could play a significant role in rapid range expansions by allowing one to learn faster by making better predictions about outcomes and by exerting more control over events. We aim to determine whether great-tailed grackles (Quiscalus mexicanus), a species that is rapidly expanding its geographic range, use causal inference and whether this ability relates to their behavioral flexibility (flexibility measured in these individuals by Logan et al. 2019: reversal learning of a color discrimination and solution switching on a puzzle box). We found that grackles showed no evidence of making causal inferences when given the opportunity to intervene on observed events using a touchscreen apparatus, and that performance on the causal cognition task did not correlate with behavioral flexibility measures. This could indicate that causal cognition is not implicated as a key factor involved in a rapid geographic range expansion, though we suggest further exploration of this hypothesis using larger sample sizes and multiple test paradigms before considering this a robust conclusion.