Philippa Kaur

Study site and experimental setup
Our experiment was conducted at the La Hampa field station of the Spanish National Research Council (CSIC) in Seville, Spain (37°16′58.8″ N, 6°03′58.4″ W), 72 m above sea level. The climate is Mediterranean, with mild, wet winters and hot, dry summers. Soils are loamy with pH = 7.74, C/N = 8.70 and organic matter = 1.16% (0–10-cm depth). Precipitation totaled 532 mm during the experiment (September 2014–August 2015), similar to the 50-y average. We used ten common annual plants, which naturally co-occur at the study site, for the experiment. These species cover a wide phylogenetic and functional range and include members of six of the most abundant families in the Mediterranean grasslands of southern Spain (Table 1). Seeds were provided by a local supplier (Semillas silvestres S.L.) from populations located near to our study site. Our experiments were located within an 800 m2 area, which had been previously cleared of all vegetation and which was fenced to prevent mammal herbivory. Landscape fabric was placed between plots to prevent growth of weeds.
Theoretical background for quantifying niche and fitness differences
Here we summarize the approach developed in ref. 38 to quantify the stabilizing effect of niche differences and average fitness differences between any pair of species. Both these measures are derived from mathematical models that capture the dynamics of competing annual plant populations with a seed bank19,39. This approach has been used in the past to accurately predict competitive outcomes between annual plant species38. Population growth is described as:

$$frac{{N_{i,t ,+, 1}}}{{N_{i,t}}},=,left( {1,-,g_i} right)s_i,+,frac{{lambda _ig_i}}{{1,+,alpha _{ii}g_iN_{i,t},+,{mathrm{{Sigma}}}_{j = 1}^{mathrm{S}}alpha _{ij}g_jN_{j,t}}},$$
(1)

Where ({textstyle{{N_{i,t + 1}} over {N_{i,t}}}}) is the per capita population growth rate, and Ni,t is the number of individuals (seeds) of species i before germination in the fall of year t. Changes in per capita growth rates depend on the sum of two terms. The first describes the proportion of seeds that do not germinate (1 − gi) but survive in the seed soil bank (si). The second term describes how much the per germinant fecundity, in the absence of competition (λi), is reduced by the germinated density of conspecific (giNi,t) and various heterospecific (left( {{mathrm{{Sigma}}}_{j = 1}^{mathrm{S}}g_jN_{j,t}} right)) neighbors. These neighbor densities are modified by the interaction coefficients describing the per capita effect of species j on species i (αij) and species i on itself (αii).
Following earlier studies14,38, we define niche differences (1 − ρ) for this model of population dynamics between competing species as:

$$1,-,rho,=,1,-,sqrt {frac{{alpha _{ij}}}{{alpha _{jj}}}frac{{alpha _{ji}}}{{alpha _{ii}}}} .$$
(2)

The stabilizing niche differences reflect the degree to which intraspecific competition exceeds interspecific competition. 1 − ρ is 1 when individuals only compete with conspecifics (i.e., there is no interspecific competition) and it is 0 when individuals compete equally with conspecifics and heterospecifics (i.e., intra and interspecific competition are equal). Niche differences between plant species can arise for instance from differences in light harvesting strategies29,37,38,39, or in soil resource use and shared mutualisms40.
The average fitness differences between a pair of competitors is ({textstyle{{kappa _j} over {kappa _i}}})38, and its expression is the following:

$$frac{{kappa _j}}{{kappa _i}},=,frac{{eta _j,-,1}}{{eta _i,-,1}}sqrt {frac{{alpha _{ij}}}{{alpha _{ji}}}frac{{alpha _{ii}}}{{alpha _{jj}}}} .$$
(3)

The species with the higher value of ({textstyle{{kappa _j} over {kappa _i}}}) (either species i or species j) is the competitive dominant, and in the absence of niche differences excludes the inferior competitor. This expression shows that ({textstyle{{kappa _j} over {kappa _i}}}) combines two fitness components, the “demographic ratio” (left( {{textstyle{{eta _j – 1} over {eta _i – 1}}}} right)) and the “competitive response ratio” (left( {sqrt {{textstyle{{alpha _{ij}} over {alpha _{ji}}}}{textstyle{{alpha _{ii}} over {alpha _{jj}}}}} } right)). The demographic ratio is a density independent term and describes the degree to which species j has higher annual seed production, per seed lost from the seed bank due to death or germination, than species i

$$eta _j,=,frac{{lambda _jg_j}}{{1,-,left( {1,-,g_j} right)s_j}}.$$

The competitive response ratio is a density-dependent term, which describes the degree to which species i is more sensitive to both intra and interspecific competition than species j. Note that the same interaction coefficients defining niche differences are also involved in describing the competitive response ratio, although their arrangement is different. Because of this interdependence, a change in interaction coefficients (( {alpha _{ji}^prime s} )) simultaneously changes both stabilizing niche differences and average fitness differences21.
With niche differences stabilizing coexistence and average fitness differences promoting competitive exclusion, the condition for coexistence (mutual invasibility) is expressed as14,38:

$$rho, More

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A total of 96 subjects in 8 12-person sessions, split across two treatments, interacted as avatars in 35 90-s periods (representing days; 75 s of day (including 5 s of dusk) and 15 s of night). Their goal was to earn as many points as possible, which were converted into US Dollars (at a 1:1 ratio) at the end of the experiment. Avatars were numbered and color coded so that individuals could identify one another. During the day, avatars could earn points that were directly converted into cash earnings by foraging for one of two types of food (“fruit” and “grass”; see below for details) and participating in a generic social interaction that was a proxy for beneficial social engagement. Fruit was high value but replenished slowly (never within the same day), and was always scarce, whereas grass was low value but infinitely renewable, that is, it was continuously available at the site it appeared at each day. The social interaction was labeled “health” for the participants but hereafter we refer to it as “grooming”, for it represents all directional social interactions that provide a direct benefit to one other avatar at a time. Because grooming was equally important to earning points in both conditions, it was not useful for measuring differences in sociality between the two. At night, remaining stationary in nests (all extant apes exhibit such nesting behavior) increased points. (See the supplementary online material for our precise language. For example, we did not use the words grooming, chimpanzee, or bonobo.)
In both conditions, the world was a rectangle with two “groves” of trees, one in the north and one in the south, which was designed to make it costly for avatars to congregate around a single supply of fruit, as apes in the naturally occurring world must search out fruit from dispersed groves. The amount of fruit was equally distributed between northern and southern trees, and grass was randomly distributed throughout the world so that there was no caloric incentive to prefer one area of the world over another. Fruit trees remained in the same location, but flowered and bore fruit in a cyclical pattern. Fruit was thus not available on each tree each period, but avatars could predict that it would be available in a day or two based on the flowering. Moreover, once a fruit was eaten in a given period, it was no longer available. Avatars could not guard fruit or exclude others from a tree. The location of grass changed each day as well, so subjects could not obtain enough food without moving, but within a day the grass continuously renewed and multiple individuals could feed on the same patch at the same time. The aggregate amount of food was held constant between Chimpanzee and Bonobo conditions. There was three times as much fruit per day (120 vs 40 pieces) in the Chimpanzee treatment vs the Bonobo treatment, but it took three times as long to forage on grass in the Chimpanzee treatment. Note that this was not meant to reflect naturally occurring handling times, but provided a way to incentivize different food choices while keeping the rate of food consumption the same across conditions.
Randomizing the location of the grass around the world and having trees fruit at different times made the problem of forming and maintaining groups nontrivial. In other words, before conducting the experiment we did not know if our design choices would induce any grouping behavior. The virtual environment was sufficiently large relative to avatar speed that it took 22% of the day to walk between the two groves of trees. Consistent with foraging in a forested environment, subjects could not see the entire world, but only a limited range around them. A map in the upper left corner of the screen displayed their location as well as the location of the trees (but not whether they were fruiting), which was designed to be a proxy of the mental maps apes have of their environment40. Subjects could call to one another over a greater distance and tell from what direction others’ calls emanated.
Finally, subjects, at a severe potential cost to themselves, could also individually attack a lone outsider, explicitly termed a “pirate”, who ate the fruit, but not less valuable grass. If one avatar attacked the pirate, the avatar incurred a significant cost and the pirate continued eating fruit. Subsequently, any avatar within the viewing window received a message indicating the outcome of two simultaneous attacks. If two avatars attacked the pirate, neither incurred a cost, and the outsider would leave for the rest of the day only to return the next day. Likewise, nearby avatars then received a message explaining three simultaneous attacks: if three or more group members attacked the pirate, it was “killed” and did not return in future days, although unannounced to the participants, there were a total of three pirates in each world; if all three were killed, no additional pirates appeared. Note that we intentionally made a solo attack extremely costly because solo attacks are not reported in the wild. However, we did not disallow solo attacks because one of our goals was to see whether such behavior emerged endogenously. In addition, this approach required minimal instruction and no explicit rules restricting behavior. This latter point was extremely important, as our goal was to see how people would explore the space and what decisions they would make without instruction, which could bias their subsequent decisions. An online video (https://www.youtube.com/watch?v=i0o_9nf2wwc) illustrates the subjects’ tasks in the virtual world and provides the experimental context.
Given that events during the day occurred in real time at the discretion of the participants, and may depend on idiosyncratic social temperaments, a daily pattern of the events was ex ante unpredictable. Our first result establishes the consistency of behaviors across four different sessions of a treatment in response to the biological imperatives we induced in the experiment. In Figs. 1 and 2, we report the total number of grooming, grass foraging, and fruit foraging events over the course of a day (summed over all 35 days) for each session in the Chimpanzee and Bonobo treatments, respectively.
Figure 1

Grooming and foraging over the course of the day in the Chimpanzee treatment, summed over 35 days.

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Figure 2

Grooming and foraging over the course of the day in the Bonobo treatment, summed over 35 days.

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Global differences
The results in Figs. 1 and 2 indicate a consistency with which the sessions replicated a daily pattern in the two different ecological environments. Such consistency in an experiment with a relatively unstructured decision space indicates that we have created an environment in which the participants responded to the incentives we presented. In other words, we appear to have designed an experiment such that rewards of the experiment (the money they earned for their choices) were high enough to maintain the attention of the participants, i.e., “the reward structure dominates any subjective costs (or values) associated with participation in the activities of an experiment” (41, p. 934).
One key design goal of our virtual environment was that the virtual worlds contained the same amount of total food even though the treatment conditions varied the amount of the fruit and processing time for grass. This goal was achieved; the average, maximum, and minimum earnings for all participants were very similar for the Bonobo and Chimpanzee treatments—respectively, US$15.98 (s.d. = $9.23) vs. US$16.29 (s.d. = $8.00), US$27.87 vs. $27.53, US$3.00 vs. US$2.85—indicating that the environments, by design, were indeed equally challenging for the participants. There was no significant difference in average session earnings (Mann–Whitney U4,4 = 8  > critical value = 0, α = 0.05, two-tailed test). Nonetheless, we observed differences between the treatments (see Figs. 1 and 2). The hominoids in the Chimpanzee treatment spent the earliest part of the day (15 s) foraging for fruit, followed by a slow sustained increase in grass foraging and a variable, but a flat rate of grooming. In the Bonobo treatment, hominoids quickly increased their grass foraging over the first half of the day (40 s) and then spent the rest of the daylight time (35 s) grooming. Consistent with the different ecological inducements, Bonobo hominoids spent very little time foraging for fruit as compared to their Chimpanzee counterparts, and Chimpanzee hominoids spent much less time foraging for grass. While there were subtle differences in the patterns of daily events within a treatment (some social groups groomed more than others as compared to other sessions in the same treatment condition), the data in Figs. 1 and 2 visually indicate that Chimpanzee sessions were more similar to each other than they were to Bonobo sessions and vice versa.
The nesting locations of the avatars indicated with whom the avatars concluded their day’s activities and with whom they began the next day; this was our measure of social affiliation since it earned no points for social partners (like grooming did) and was therefore a measure of subjects’ endogenous affiliation choices. If all 12 avatars decided to nest, there were 12C2 = 66 combinations of unique distances between the avatars. To quantify the avatars’ proximity to one another at the end of a day, we summed the unique distances between all avatars who chose to nest. As some avatars occasionally decided not to nest (and instead stood in place or walked around), we divided the sum by the actual number of nest combinations for that day to ensure the distance measure was comparable across days. (For example, if only 10 avatars nested in a day, there are only 10C2 = 45 distances between 10 avatars that day). Figure 3 illustrates the nesting proximity of avatars by day, with sessions represented by dashed lines and treatment averages across all sessions represented by solid lines (orange for Chimpanzee, blue for Bonobo). Lower numbers indicate closer nesting proximity within the session. The trendline for the Bonobo average is decreasing (− 40.6 pixels/day) at a statistically significant rate (p-value  More