Unknown

Dataset Information

0

Alarm communication networks as a driver of community structure in African savannah herbivores.


ABSTRACT: Social information networks have the potential to shape the spatial structure of ecological communities by promoting the formation of mixed-species groups. However, what actually drives social affinity between species in the wild will depend on the characteristics of the species available to group. Here we first present an agent-based model that predicts trait-related survival benefits from mixed-species group formation in a multi-species community and we then test the model predictions in a community-wide field study of African savannah herbivores using multi-layered network analysis. We reveal benefits from information transfer about predators as a key determinant of mixed-species group formation, and that dilution benefits alone are not enough to explain patterns in interspecific sociality. The findings highlight the limitations of classical ecological approaches focusing only on direct trophic interactions when analysing community structure and suggest that declines in species occupying central social network positions, such as key informants, can have significant repercussions throughout communities.

SUBMITTER: Meise K 

PROVIDER: S-EPMC6973068 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

altmetric image

Publications

Alarm communication networks as a driver of community structure in African savannah herbivores.

Meise Kristine K   Franks Daniel W DW   Bro-Jørgensen Jakob J  

Ecology letters 20191127 2


Social information networks have the potential to shape the spatial structure of ecological communities by promoting the formation of mixed-species groups. However, what actually drives social affinity between species in the wild will depend on the characteristics of the species available to group. Here we first present an agent-based model that predicts trait-related survival benefits from mixed-species group formation in a multi-species community and we then test the model predictions in a com  ...[more]

Similar Datasets

| S-EPMC6053937 | biostudies-literature
| S-EPMC6710573 | biostudies-literature
| S-EPMC4978872 | biostudies-literature
| S-EPMC8216902 | biostudies-literature
| S-EPMC4027387 | biostudies-literature
| S-EPMC4650178 | biostudies-literature
| S-EPMC5990837 | biostudies-literature
| S-EPMC7532184 | biostudies-literature
| S-EPMC1863470 | biostudies-literature
| S-EPMC6772172 | biostudies-literature