A fundamental question in nutritional biology is how distributed systems maintain an optimal supply of multiple nutrients essential for life and reproduction. In the case of animals, the nutritional requirements of the cells within the body are coordinated by the brain in neural and chemical dialogue with sensory systems and peripheral organs. At the level of an insect society, the requirements for the entire colony are met by the foraging efforts of a minority of workers responding to cues emanating from the brood. Both examples involve components specialized to deal with nutrient supply and demand (brains and peripheral organs, foragers and brood). However, some of the most species-rich, largest, and ecologically significant heterotrophic organisms on earth, such as the vast mycelial networks of fungi, comprise distributed networks without specialized centers: How do these organisms coordinate the search for multiple nutrients? We address this question in the acellular slime mold Physarum polycephalum and show that this extraordinary organism can make complex nutritional decisions, despite lacking a coordination center and comprising only a single vast multinucleate cell. We show that a single slime mold is able to grow to contact patches of different nutrient quality in the precise proportions necessary to compose an optimal diet. That such organisms have the capacity to maintain the balance of carbon-and nitrogen-based nutrients by selective foraging has considerable implications not only for our understanding of nutrient balancing in distributed systems but for the functional ecology of soils, nutrient cycling, and carbon sequestration. acellular slime mold | complexity | geometrical framework | nutrition | Physarum polycephalum P lasmodia of Physarum polycephalum are single multinucleate cells extending up to hundreds of square centimeters. Cytoplasm streams rhythmically back and forth through a network of tubular elements, circulating nutrients and chemical signals and forming pseudopods that allow the organism to navigate around and respond to its environment. Plasmodia are distributed information processors, which, for example, can find the shortest route through a maze to locate food (1), anticipate the timing of periodic events (2), and solve multiobjective foraging problems (3).Under adequate nutrition, P. polycephalum plasmodia are completely sedentary and grow steadily (4, 5), but on nonnutrient substrates, they migrate a few centimeters per hour (6), directed by external stimuli, including gradients of nutrients such as sugars and proteins (7-12). When two or more identical food sources are presented at various positions to a starved plasmodium, it optimizes the shape of the network to facilitate effective absorption of nutrients (1), and plasmodia select the higher concentration patch of two patches differing in nutrient concentration (3). Can it solve complex nutrient balancing problems by altering its growth form and movement to maintain an optimal ratio of macronutrients in the face of variati...
Spatial memory enhances an organism's navigational ability. Memory typically resides within the brain, but what if an organism has no brain? We show that the brainless slime mold Physarum polycephalum constructs a form of spatial memory by avoiding areas it has previously explored. This mechanism allows the slime mold to solve the U-shaped trap problem-a classic test of autonomous navigational ability commonly used in robotics-requiring the slime mold to reach a chemoattractive goal behind a U-shaped barrier. Drawn into the trap, the organism must rely on other methods than gradient-following to escape and reach the goal. Our data show that spatial memory enhances the organism's ability to navigate in complex environments. We provide a unique demonstration of a spatial memory system in a nonneuronal organism, supporting the theory that an externalized spatial memory may be the functional precursor to the internal memory of higher organisms. extracellular slime | protist | reactive navigation | amoeboid organism
Most models of animal foraging and consumer choice assume that individuals make choices based on the absolute value of items and are therefore 'economically rational'. However, frequent violations of rationality by animals, including humans, suggest that animals use comparative valuation rules. Are comparative valuation strategies a consequence of the way brains process information, or are they an intrinsic feature of biological decision-making? Here, we examine the principles of rationality in an organism with radically different information-processing mechanisms: the brainless, unicellular, slime mould Physarum polycephalum. We offered P. polycephalum amoebas a choice between food options that varied in food quality and light exposure (P. polycephalum is photophobic). The use of an absolute valuation rule will lead to two properties: transitivity and independence of irrelevant alternatives (IIA). Transitivity is satisfied if preferences have a consistent, linear ordering, while IIA states that a decision maker's preference for an item should not change if the choice set is expanded. A violation of either of these principles suggests the use of comparative rather than absolute valuation rules. Physarum polycephalum satisfied transitivity by having linear preference rankings. However, P. polycephalum's preference for a focal alternative increased when a third, inferior quality option was added to the choice set, thus violating IIA and suggesting the use of a comparative valuation process. The discovery of comparative valuation rules in a unicellular organism suggests that comparative valuation rules are ubiquitous, if not universal, among biological decision makers.
With increasing worldwide pressure on bee pollinator populations and an increase in insecticide resistance amongst pest insects, there is a growing need for diversification of pollinator and pest control systems. Syrphid flies (Diptera: Syrphidae) contribute ecosystem services to agroecosystems through their supporting roles as crop pollinators and predators of pests. Adult syrphids are important pollinators with high floral visitation rates and pollen carrying capacity, while predatory syrphid larvae are natural biological control agents, reducing aphid populations in both field and laboratory conditions. The present challenge is to determine whether syrphid flies have the potential for application as pollinators and in integrated pest management schemes as biological control agents. Currently, there are gaps in research that are hindering the use of syrphids as dual service providers. Such gaps include a lack of knowledge of syrphid floral preferences, the role and viability of adult syrphids as pollinators in natural and agro-ecological pollinator networks, and the predatory efficiency of larvae in field and glasshouse conditions. By reviewing relevant literature, we demonstrate syrphid flies have the potential to be used as pollinators and biological control agents.
The “social brain hypothesis” posits that the cognitive demands of sociality have driven the evolution of substantially enlarged brains in primates and some other mammals. Whether such reasoning can apply to all social animals is an open question. Here we examine the evolutionary relationships between sociality, cognition, and brain size in insects, a taxonomic group characterized by an extreme sophistication of social behaviors and relatively simple nervous systems. We discuss the application of the social brain hypothesis in this group, based on comparative studies of brain volumes across species exhibiting various levels of social complexity. We illustrate how some of the major behavioral innovations of social insects may in fact require little information-processing and minor adjustments of neural circuitry, thus potentially selecting for more specialized rather than bigger brains. We argue that future work aiming to understand how animal behavior, cognition, and brains are shaped by the environment (including social interactions) should focus on brain functions and identify neural circuitry correlates of social tasks, not only brain sizes.
Many biological systems use extensive networks for the transport of resources and information. Ants are no exception. How do biological systems achieve efficient transportation networks in the absence of centralized control and without global knowledge of the environment? Here, we address this question by studying the formation and properties of inter-nest transportation networks in the Argentine ant (Linepithema humile). We find that the formation of inter-nest networks depends on the number of ants involved in the construction process. When the number of ants is sufficient and networks do form, they tend to have short total length but a low level of robustness. These networks are topologically similar to either minimum spanning trees or Steiner networks. The process of network formation involves an initial construction of multiple links followed by a pruning process that reduces the number of trails. Our study thus illuminates the conditions under and the process by which minimal biological transport networks can be constructed.
Several recent studies hint at shared patterns in decision-making between taxonomically distant organisms, yet few studies demonstrate and dissect mechanisms of decision-making in simpler organisms. We examine decision-making in the unicellular slime mould Physarum polycephalum using a classical decision problem adapted from human and animal decision-making studies: the two-armed bandit problem. This problem has previously only been used to study organisms with brains, yet here we demonstrate that a brainless unicellular organism compares the relative qualities of multiple options, integrates over repeated samplings to perform well in random environments, and combines information on reward frequency and magnitude in order to make correct and adaptive decisions. We extend our inquiry by using Bayesian model selection to determine the most likely algorithm used by the cell when making decisions. We deduce that this algorithm centres around a tendency to exploit environments in proportion to their reward experienced through past sampling. The algorithm is intermediate in computational complexity between simple, reactionary heuristics and calculation-intensive optimal performance algorithms, yet it has very good relative performance. Our study provides insight into ancestral mechanisms of decision-making and suggests that fundamental principles of decision-making, information processing and even cognition are shared among diverse biological systems.
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