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  1. Free, publicly-accessible full text available May 1, 2023
  2. 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.
  3. 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 nestmore »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.

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  4. Abstract Observations have shown that tropical convection is influenced by fluctuations in temperature and moisture in the lower free troposphere (LFT; 600–850 hPa), as well as moist enthalpy (ME) fluctuations beneath the 850 hPa level, referred to as the deep boundary layer (DBL; 850–1000 hPa). A framework is developed that consolidates these three quantities within the context of the buoyancy of an entraining plume. A “plume buoyancy equation” is derived based on a relaxed version of the weak temperature gradient (WTG) approximation. Analysis of this equation using quantities derived from the Dynamics of the Madden–Julian Oscillation (DYNAMO) sounding array data reveals that processes occurring within the DBL and the LFT contribute nearly equally to the evolution of plume buoyancy, indicating that processes that occur in both layers are critical to the evolution of tropical convection. Adiabatic motions play an important role in the evolution of buoyancy both at the daily and longer time scales and are comparable in magnitude to horizontal moisture advection and vertical moist static energy advection by convection. The plume buoyancy equation may explain convective coupling at short time scales in both temperature and moisture fluctuations and can be used to complement the commonly used moist staticmore »energy budget, which emphasizes the slower evolution of the convective envelope in tropical motion systems.« less
  5. Abstract

    Recent advances in phylogenomics allow for the use of large amounts of genetic information in phylogenetic inference. Ideally, the increased resolution and accuracy of such inferences facilitate improved understanding of macroevolutionary processes. Here, we integrate ultraconserved elements (UCEs) with fossil and biogeographic range data to explore diversification and geographic range evolution in the diverse turtle ant genus Cephalotes Latreille, 1802 (Hymenoptera: Formicidae). We focus on the potential role of the uplift of the Panamanian land bridge and the putative ephemeral GAARlandia land bridge linking South America and the Antilles in shaping evolution in this group. Our phylogenetic analyses provide new resolution to the backbone of the turtle ant phylogeny. We further found that most geographic range shifts between South America and Central America regions were temporally consistent with the development of the Panamanian land bridge, while we did not find support for the GAARlandia land bridge. Additionally, we did not infer any shifts in diversification rates associated with our focal land bridges, or any other historical events (we inferred a single diversification rate regime across the genus). Our findings highlight the impact of the Panamanian land bridge for Cephalotes geographic range evolution as well as the influence of taxonomicmore »sampling on macroevolutionary inferences.

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  6. Hurricane Matthew locally generated more than 400 mm of rainfall on 8–9 October 2016 over the eastern Carolinas and Virginia as it transitioned into an extratropical cyclone. The heaviest precipitation occurred along a swath situated up to 100–200 km inland from the coast and collocated with enhanced low-tropospheric frontogenesis. Analyses from version 3 of the Rapid Refresh (RAPv3) model indicate that rapid frontogenesis occurred over eastern North and South Carolina and Virginia on 8 October, largely over a 12-h time period between 1200 UTC 8 October and 0000 UTC 9 October. The heaviest rainfall in Matthew occurred when and where spiral rainbands intersected the near-surface front, which promoted the lift of conditionally unstable, moist air. Parallel to the spiral rainbands, conditionally unstable low-tropospheric warm, moist oceanic air was advected inland, and the instability was apparently released as the warm air mass rose over the front. Precipitation in the spiral rainbands intensified on 9 October as the temperature gradient along the near-surface front rapidly increased. Unlike in Hurricane Floyd over the mid-Atlantic states, rainfall totals within the spiral rainbands of Matthew as they approached the near-surface front evidently were not enhanced by release of conditional symmetric instability. However, conditional symmetric instabilitymore »release in the midtroposphere may have enhanced rainfall 200 km northwest of the near-surface front. Finally, although weak cold-air damming occurred prior to heavy rainfall, damming dissipated prior to frontogenesis and did not impact rainfall totals.

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  7. Realistically representing the multiscale interactions between moisture and tropical convection remains an ongoing challenge for weather prediction and climate models. In this study, we revisit the relationship between precipitation and column saturation fraction (CSF) by investigating their tendencies in CSF–precipitation space using satellite and radar observations, as well as reanalysis. A well-known, roughly exponential increase in precipitation occurs as CSF increases above a “critical point,” which acts as an attractor in CSF–precipitation space. Each movement away from and subsequent return toward the attractor results in a small net change of the coupled system, causing it to evolve in a cyclical fashion around the attractor. This cyclical evolution is characterized by shallow and convective precipitation progressively moistening the environment and strengthening convection, stratiform precipitation progressively weakening convection, and drying in the nonprecipitating and lightly precipitation regime. This behavior is evident across a range of spatiotemporal scales, suggesting that shortcomings in model representation of the joint evolution of convection and large-scale moisture will negatively impact a broad range of spatiotemporal scales. Novel process-level diagnostics indicate that several models, all implementing versions of the Zhang–McFarlane deep convective parameterization, exhibit unrealistic coupling between column moisture and convection.