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Costs for switching partners reduce network dynamics but not cooperative behaviour
No full textSocial networks represent the structuring of interactions between group members. Above all, many interactions are profoundly cooperative in humans and other animals. In accordance with this natural observation, theoretical work demonstrates that certain network structures favour the evolution of cooperation. Yet, recent experimental evidence suggests that static networks do not enhance cooperative behaviour in humans. By contrast, dynamic networks do foster cooperation. However, costs associated with dynamism such as time or resource investments in finding and establishing new partnerships have been neglected so far. Here, we show that human participants are much less likely to break links when costs arise for building new links. Especially, when costs were high, the network was nearly static. Surprisingly, cooperation levels in Prisoner's Dilemma games were not affected by reduced dynamism in social networks. We conclude that the mere potential to quit collaborations is sufficient in humans to reach high levels of cooperative behaviour. Effects of self-structuring processes or assortment on the network played a minor role: participants simply adjusted their cooperative behaviour in response to the threats of losing a partner or of being expelled.German Initiative of Excellence of the German Science Foundation (DFG
Patch depletion, niche structuring and the evolution of co-operative foraging
Full text linkAbstract Background Many animals live in groups. One proposed reason is that grouping allows cooperative food finding. Group foraging models suggest that grouping could increase food finding rates, but that such group processes could be evolutionarily unstable. These models assume discrete food patches which are fully detectable. However, often animals may only be able to perceive local parts of larger-scale environmental patterns. We therefore use a spatial individual-based model where food patches are aggregates of food items beyond the scale of individual perception. We then study the evolution of foraging and grouping behavior in environments with different resource distributions. Results Our results show that grouping can evolve to increase food intake rates. Two kinds of grouping evolve: traveling pairs and opportunistic grouping, where individuals only aggregate when feeding. Grouping evolves because it allows individuals to better sense and deplete patches. Such enhanced patch depletion is particularly apparent on fragmented and partially depleted patches, which are especially difficult for solitary foragers to deplete. Solitary foragers often leave a patch prematurely because a whole patch cannot be observed directly. In groups, individuals that are still eating allow other individuals that inadvertently leave the patch, to return and continue feeding. For this information sharing a grouping tendency is sufficient and observing whether a neighbor is eating is not necessary. Grouping therefore leads to a release from individual sensing constraints and a shift in niche specialization, allowing individuals to better exploit partially depleted patches. Conclusions The evolved group foraging can be seen as cooperative in the sense that it leads to a mutually-beneficial synergy: together individuals can achieve more than on their own. This cooperation exists as a group-level process generated by the interaction between grouping and the environment. Thus we reveal how such a synergy can originate in evolution as a side-effect of grouping via multi-level selection. Here there is no cooperative dilemma as individuals cannot avoid producing information for their neighbors. This scenario may be a useful starting point for studying the evolution of further social and cooperative complexity.</p
Local orientation and the evolution of foraging: changes in decision making can eliminate evolutionary trade-offs.
Full text linkInformation processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or "recognize patterns" in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is "staying in patches". In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape
The economic interaction between climate change mitigation, climate migration, and poverty
Full text linkMitigation of anthropogenic climate change takes place against the backdrop of poor countries being most affected by climate change impacts; climate-induced migration is expected to increase in the future. However, the interaction between mitigation, climate migration and poverty has not been investigated explicitly. Here, we represent simultaneous poverty- and climate-induced migration in a laboratory setting, within the collective-risk social dilemma that arises from attempts to avert dangerous climate change. The relatively rich participants try to prevent migration by the relatively poor but in the long run these attempts are unsuccessful because of free-riding among the rich. The rich are willing to increase their effort at averting dangerous climate change when the poor are hit by a climate extreme event exacerbating their poverty. Conversely, the poor are willing to compensate some weaker effort by the rich, as long as the effort by the rich lies above a threshold emerging within the experiment
Co-evolution of behaviour and social network structure promotes human cooperation
No full textP>The ubiquity of cooperation in nature is puzzling because cooperators can be exploited by defectors. Recent theoretical work shows that if dynamic networks define interactions between individuals, cooperation is favoured by natural selection. To address this, we compare cooperative behaviour in multiple but independent repeated games between participants in static and dynamic networks. In the latter, participants could break their links after each social interaction. As predicted, we find higher levels of cooperation in dynamic networks. Through biased link breaking (i.e. to defectors) participants affected their social environment. We show that this link-breaking behaviour leads to substantial network clustering and we find primarily cooperators within these clusters. This assortment is remarkable because it occurred on top of behavioural assortment through direct reciprocity and beyond the perception of participants, and represents a self-organized pattern. Our results highlight the importance of the interaction between ecological context and selective pressures on cooperation
Consistent Strategy Updating in Spatial and Non-Spatial Behavioral Experiments Does Not Promote Cooperation in Social Networks
Full text linkThe presence of costly cooperation between otherwise selfish actors is not trivial. A prominent mechanism that promotes cooperation is spatial population structure. However, recent experiments with human subjects report substantially lower level of cooperation then predicted by theoretical models. We analyze the data of such an experiment in which a total of 400 players play a Prisoner's Dilemma on a 4 x 4 square lattice in two treatments, either interacting via a fixed square lattice (15 independent groups) or with a population structure changing after each interaction (10 independent groups). We analyze the statistics of individual decisions and infer in which way they can be matched with the typical models of evolutionary game theorists. We find no difference in the strategy updating between the two treatments. However, the strategy updates are distinct from the most popular models which lead to the promotion of cooperation as shown by computer simulations of the strategy updating. This suggests that the promotion of cooperation by population structure is not as straightforward in humans as often envisioned in theoretical models.This work has funding by the German Initiative of Excellence of the German Science Foundation (DFG). J.G.'s work was supported in part by The Ministerio de Ciencia e Innovacion (MICINN) (Spain) through grants PRODIEVO, MOSAICO, FPI, EEBB, and by Comunidad de Madrid (Spain) through grant MODELICO-CM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Publicad
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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