Drawing showing experimental setup for the delayed partner arrival experiment.

<p>Subject is presented with the duo platform which can only be pulled in when the partner arrives at the apparatus.</p

Keas Perform Similarly to Chimpanzees and Elephants when Solving Collaborative Tasks

<div><p>Cooperation between individuals is one of the defining features of our species. While other animals, such as chimpanzees, elephants, coral trout and rooks also exhibit cooperative behaviours, it is not clear if they think about cooperation in the same way as humans do. In this study we presented the kea, a parrot endemic to New Zealand, with a series of tasks designed to assess cooperative cognition. We found that keas were capable of working together, even when they had to wait for their partner for up to 65 seconds. The keas also waited for a partner only when a partner was actually needed to gain food. This is the first demonstration that any non-human animal can wait for over a minute for a cooperative partner, and the first conclusive evidence that any bird species can successful track when a cooperative partner is required, and when not. The keas did not attend to whether their partner could actually access the apparatus themselves, which may have been due to issues with task demands, but one kea did show a clear preference for working together with other individuals, rather than alone. This preference has been shown to be present in humans but absent in chimpanzees. Together these results provide the first evidence that a bird species can perform at a similar level to chimpanzees and elephants across a range of collaborative tasks. This raises the possibility that aspects of the cooperative cognition seen in the primate lineage have evolved convergently in birds.</p></div

Drawing showing experimental setup for the simultaneous release experiment.

<p>Subject is presented with the duo platform which can only be pulled in with the help of a partner.</p

Performance of the keas across Experiments 2–5.

<p>Trials (errors) show the total number of trials needed and errors made to reach criterion on the training stage of the delay experiment (Experiment 2). Randomized delay 0–65 secs and 26–65 secs show the number of successful trials keas completed at test in Experiment 2, both for all trials, and for trials longer than keas had previously experienced during training. Solo-Duo indicates the number of successful trials in Experiment 3, No Rope shows the same for Experiment 4, Prosocial Motivation shows the same for (Experiment 5 p < 0.05). Neo completed 40 trials of Experiment 5 because he was tested with two different kea.</p

ESM Data on condition order, exchanges, abandoned trials and refusals from Kea show no evidence of inequity aversion

It has been suggested that inequity aversion is a mechanism that evolved in humans to maximize the pay-offs from engaging in cooperative tasks and to foster long-term cooperative relationships between unrelated individuals. In support of this, evidence of inequity aversion in nonhuman animals has typically been found in species that, like humans, live in complex social groups and demonstrate cooperative behaviours. We examined inequity aversion in the kea (<i>Nestor notabilis</i>), which lives in social groups but does not appear to demonstrate wild cooperative behaviours, using a classic token exchange paradigm. We compared the number of successful exchanges and the number of abandoned trials in each condition and found no evidence of an aversion to inequitable outcomes when there was a difference between reward quality or working effort required between actor and partner. We also found no evidence of inequity aversion when the subject received no reward while their partner received a low value reward

Histogram of the estimated age of the Austronesian language family calculated using a conservative set of calibration points.

<p>The light blue bar shows the age range predicted by the pulse-pause scenario (5,000 to 6,000 years BP), and the gray bar shows that predicted by the slow-boat scenario (13,000 to 17,000 years BP). The mean age estimate for Proto-Austronesian is 5,117 BP.</p

Workflows for automatic cognate detection.

<p>In LingPy, cognate detection is treated as a hierarchical clustering task. After distances or similarities between word pairs have been determined (A), a hierarchical clustering algorithm is applied to the matrix and terminates when a certain threshold is reached (B). Similarity networks start from a graph-representation of the similarity or distance matrix (C). In a first step, edges whose score exceeds a certain threshold are removed from the graph (D). In a second step, state-of-the-art algorithms for community detection are used to partition the graph into groups of cognate words (E).</p

Individual test results (B-Cubed F-Scores).

<p>The figure shows the individual results of all algorithms based on B-Cubed F-Scores for each of the datasets. Results marked by a red triangle point to the worst result for a given subset, and results marked by a yellow star point to the best result. Apart from Uralic, our new Infomap approach always performs best, while the Turchin approach performs worst in four out of six tests.</p

General results of the test analysis.

<p>General results of the test analysis.</p

Recent approaches to cognate detection.

<p>A plus “+” indicates that the algorithm meets the requirement, a minus “-” indicates that its failure. ML (multilingual) refers to the ability of an algorithm to identify cognate words across more than two languages at the same time. RQ (requirements) refers to additional requirements apart from the raw word list data, such as needing reference phylogenies or extensive training data. FA (free availability) means that the method has a useable public implementation.</p