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Abstract Biological transportation networks must balance competing functional priorities. The self-organizing mechanisms used to generate such networks have inspired scalable algorithms to construct and maintain low-cost and efficient human-designed transport networks. The pheromone-based trail networks of ants have been especially valuable in this regard. Here, we use turtle ants as our focal system: In contrast to the ant species usually used as models for self-organized networks, these ants live in a spatially constrained arboreal environment where both nesting options and connecting pathways are limited. Thus, they must solve a distinct set of challenges which resemble those faced by human transport engineers constrained by existing infrastructure. Here, we ask how a turtle ant colony’s choice of which nests to include in a network may be influenced by their potential to create connections to other nests. In laboratory experiments withCephalotes variansandCephalotes texanus, we show that nest choice is influenced by spatial constraints, but in unexpected ways. Under one spatial configuration, colonies preferentially occupied more connected nest sites; however, under another spatial configuration, this preference disappeared. Comparing the results of these experiments to an agent-based model, we demonstrate that this apparently idiosyncratic relationship between nest connectivity and nest choice can emerge without nest preferences via a combination of self-reinforcing random movement along constrained pathways and density-dependent aggregation at nests. While this mechanism does not consistently lead to the de-novo construction of low-cost, efficient transport networks, it may be an effective way to expand a network, when coupled with processes of pruning and restructuring. 

Understanding how resource limitation and biotic interactions interact across spatial scales is fundamental to explaining the structure of ecological communities. However, empirical studies addressing this issue are often hindered by logistical constraints, especially at local scales. Here, we use a highly tractable arboreal ant study system to explore the interactive effects of resource availability and competition on community structure across three local scales: an individual tree, the nest network created by each colony and the individual ant nest. On individual trees, the ant assemblages are primarily shaped by availability of dead wood, a critical nesting resource. The nest networks within a tree are constrained by the availability of nesting resources but also influenced by the co-occurring species. Within individual nests, the distribution of adult ants is only affected by distance to interspecific competitors. These findings demonstrate that resource limitation exerts the strongest effects on diversity at higher levels of local ecological organization, transitioning to a stronger effect of species interactions at finer scales. Collectively, these results highlight that the process exerting the strongest influence on community structure is highly dependent on the scale at which we examine the community, with shifts occurring even across fine-grained local scales. 

Biological systems are typically dependent on transportation networks for the efficient distribution of resources and information. Revealing the decentralized mechanisms underlying the generative process of these networks is key in our global understanding of their functions and is of interest to design, manage and improve human transport systems. Ants are a particularly interesting taxon to address these issues because some species build multi-sink multi-source transport networks analogous to human ones. Here, by combining empirical field data and modelling at several scales of description, we show that pre-existing mechanisms of recruitment with positive feedback involved in foraging can account for the structure of complex ant transport networks. Specifically, we find that emergent group-level properties of these empirical networks, such as robustness, efficiency and cost, can arise from models built on simple individual-level behaviour addressing a quality-distance trade-off by the means of pheromone trails. Our work represents a first step in developing a theory for the generation of effective multi-source multi-sink transport networks based on combining exploration and positive reinforcement of best sources.