Triadic awareness predicts partner choice in male–infant–male interactions in Barbary macaques

Social knowledge beyond one’s direct relationships is a key to successful maneuvering of the social world. Individuals gather information on the quality of social relationships between their group companions, which has been termed triadic awareness. Evidence of the use of triadic awareness in natural contexts is limited mainly to conflict management. Here we investigated triadic awareness in wild Barbary macaques (Macaca sylvanus) in the context of bridging interactions defined as male-infant-male interactions whereby a male (actor) presents an infant to another male (receiver) in order to initiate an affiliative interaction with that male. Analyses based on 1,263 hours of focal observations on ten infants of one wild social group in Morocco supported the hypothesis that males use their knowledge of the relationship between infants and other adult males when choosing a male as a partner for bridging interactions. Specifically, (i) the number of bridging interactions among initiator-infant-receiver triads was affected by the strength of the infant-receiver relationship and (ii) when two males were available as bridging partners, a male was more likely to be chosen as the receiver the stronger his social relationship with the infant in comparison to the other available male was. This demonstrates that non-human primates establish triadic awareness also of temporarily rather dynamic infant-male relationships and use it in naturally occurring affiliative context. Our results contribute to the discussion about the mechanism underlying the acquisition of triadic awareness and the benefits of its usage and lend support to hypotheses linking social complexity to the evolution of complex cognition

LOTVS: a global collection of permanent vegetation plots

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time-series monitored for at least 6 years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology

LOTVS: a global collection of permanent vegetation plots

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time-series monitored for at least 6 years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology