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The evolutionary maintenance of Lévy flight foraging

In heterotrophs, incuding animals, survival depends on the net energy gained through foraging. The expectation, then, is that natural selection results in adaptations for efficient foraging that optimize the balance of searching costs and rewards. Lévy flight foraging has been proposed as an optimal foraging solution. The hypothesis states, if no information about resource locations are available, and the locations are re-visitable, then selection will result in adaptations for Lévy flight foraging, a type of random walk. It has been argued that Levy-like foraging behaviour may simply reflect how resources are distributed, but empirical and theoretical research suggests that this behaviour is intrinsic or innate. However, this research does not address evolutionary mechanisms, and lacks ecological breadth. We extend the current theoretical framework by including evolutionary ecological contexts. We treat an organism’s random walk as a heritable trait, and explore ecological contexts such as population size, lifespan, carrying capacity, searching costs, reproductive strategies, and different distributions of food. Our evolutionary simulations overwhelmingly resulted in selection for Lévy-like foraging, regardless of the distribution of food, and evidences Lévy flight foraging as a bet-hedging strategy. Thus, here we provide some of the first evidence for the evolutionary maintenance of Lévy flight foraging.

Citation: Campeau W, Simons AM, Stevens B (2022) The evolutionary maintenance of Lévy flight foraging. PLoS Comput Biol 18: e1009490. https://doi.org/10.1371/journal.pcbi.

Editor: Marcos Gomes Eleuterio da Luz, Universidade Federal do Parana, BRAZIL.

Scientists find new quantum behavior in unusual superconducting material

Researchers at Rice University and collaborating institutions have discovered direct evidence of active flat electronic bands in a kagome superconductor. This breakthrough could pave the way for new methods to design quantum materials—including superconductors, topological insulators and spin-based electronics—that could power future electronics and computing technologies.

Moving up in the world: Rare catfish species filmed climbing waterfalls

Nature often puts on incredible displays. A recent example caught on camera shows thousands of bumblebee catfish (Rhyacoglanis paranensis) climbing waterfalls in southern Brazil. This is the first time the species has been observed in such a large group and climbing, according to a study published in the Journal of Fish Biology describing the spectacle.

Environmental Military Police from Mato Grosso do Sul State spotted the catfish scaling slippery rocks between one and four meters high behind waterfalls on the Aquidauana River. The sighting occurred in November 2024 at the beginning of the rainy season, and a week later, a team of Brazilian scientists arrived to document the event.

They observed that the catfish’s climbing behavior depended on the time of day. During the hot afternoons, the fish sheltered under rocks and in shaded areas. They began climbing in the early evening as the sun was setting. The researchers also studied how the fish are able to climb. They keep their paired fins wide open and use lateral and caudal movements to push themselves forward. Scientists believe this is also aided by a suction mechanism that helps them stick to flat surfaces.

Human embryo implantation recorded in real time for the first time

Researchers at the Institute for Bioengineering of Catalonia (IBEC) in collaboration with the Dexeus University Hospital have captured unparalleled images of a human embryo implanting. This is the first time that the process has been recorded in real time and in 3D.

Intergalactic experiment: Researchers hunt for mysterious dark matter particle with clever new trick

Physicists from the University of Copenhagen have begun using the gigantic magnetic fields of galaxy clusters to observe distant black holes in their search for an elusive particle that has stumped scientists for decades.

Complex deep learning models are no better at understanding genetic perturbation than simple baseline ones, study finds

Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this prowess extend to other fields of biology as well?

Using Grover’s algorithm to efficiently prepare collective quantum states in optical cavities

The reliable engineering of quantum states, particularly those involving several particles, is central to the development of various quantum technologies, including quantum computers, sensors and communication systems. These collective quantum states include so-called Dicke and Greenberger-Horne-Zeilinger (GHZ) states, multipartite entangled states that can be leveraged to collect precise measurements, to correct errors made by quantum computers and to enable communication between remote devices leveraging quantum mechanical effects.

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