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Predation shapes communities through consumptive and non‐consumptive effects. In the latter case, prey respond to perceived predation risk through proactive or reactive risk management strategies occurring at different spatial and temporal scales. The predator–prey space race and landscape of fear concepts are useful to better understand how predation risk affects prey behavioral decisions and distribution. We assessed predation risk effects in a terrestrial Arctic community, where the arctic fox is the main predator of ground‐nesting birds. Using high‐frequency GPS data, we estimated a predator activity landscape corresponding to fox space use patterns and validated with an artificial prey experiment that this predator activity landscape correlated with the predation risk landscape. We then investigated the effects of the fox activity landscape on multiple prey species, by assessing the anti‐predator behavior of a main prey (snow goose) actively searched for by foxes, and the nest distribution of several incidental prey species. We first found that snow geese showed a stronger level of nest defense in areas highly used by foxes, possibly responding with a reactive strategy to variation in predation risk. Then, nests of incidental prey reproducing in habitats easily accessed by foxes had a lower probability of occurrence in areas highly used by foxes, suggesting these birds may use a proactive risk management strategy by shifting their distribution away from risky areas. For incidental prey species nesting in microhabitat refuges difficult to access by foxes, probability of nest occurrence was independent of predation risk in the surrounding area, as they avoid risk at a finer spatial scale. By tracking all individuals of the dominant predator species in our study area, we demonstrated the value of using predator space use patterns to infer spatial variation in predation risk. Overall, we highlight the diversity of risk management strategies in prey sharing a common predator, hence refining our understanding of the mechanisms driving species distribution and community structure.

This study introduces a novel population-based metaheuristic algorithm called secretary bird optimization algorithm (SBOA), inspired by the survival behavior of secretary birds in their natural environment. Survival for secretary birds involves continuous hunting for prey and evading pursuit from predators. This information is crucial for proposing a new metaheuristic algorithm that utilizes the survival abilities of secretary birds to address real-world optimization problems. The algorithm's exploration phase simulates secretary birds hunting snakes, while the exploitation phase models their escape from predators. During this phase, secretary birds observe the environment and choose the most suitable way to reach a secure refuge. These two phases are iteratively repeated, subject to termination criteria, to find the optimal solution to the optimization problem. To validate the performance of SBOA, experiments were conducted to assess convergence speed, convergence behavior, and other relevant aspects. Furthermore, we compared SBOA with 15 advanced algorithms using the CEC-2017 and CEC-2022 benchmark suites. All test results consistently demonstrated the outstanding performance of SBOA in terms of solution quality, convergence speed, and stability. Lastly, SBOA was employed to tackle 12 constrained engineering design problems and perform three-dimensional path planning for Unmanned Aerial Vehicles. The results demonstrate that, compared to contrasted optimizers, the proposed SBOA can find better solutions at a faster pace, showcasing its significant potential in addressing real-world optimization problems.

Predators respond to the increase of prey by aggregation in space or foraging more often. However, foraging habitat suitability limits predators’ responses. For nocturnal insectivorous bats, artificial light at night (ALAN) can trigger insect prey aggregation. It is not clear how ALAN might affect predator-prey relationships in the urban setting, where urban bats could have adapted to the city, and novel spatial complexity introduced by man-made objects might alter foraging habitat suitability. We strategically selected sites to represent different levels of ALAN and spatial complexity. We recorded bat commuting and foraging activities and collected aerial insects to examine how ALAN and spatial complexity affected bat-insect relationships. We found that insect biomass was positively correlated with ALAN, but was not affected by spatial complexity. Large-sized big brown bats and hoary bats positively responded to change of prey in open sites whereas small-sized eastern red bats and silver-haired bats positively responded in cluttered sites, suggesting that the impact of ALAN could vary when ALAN is coupled with urban spatial complexity. Our study demonstrates that foraging habitat suitability can alter which species might benefit from ALAN. Predator-prey relationships in cities are complex, but general ecological principles still apply in novel urban ecosystems.

Current conceptual metacommunity models predict that the consequences of local selective pressures on community structure increase with spatial isolation when species favored by local conditions also have higher dispersal rates. This appears to be the case of freshwater insects in the presence of fish. The introduction of predatory fish can produce trophic cascades in freshwater habitats because fish tend to prey upon intermediate predatory taxa, such as predatory insects, indirectly benefiting herbivores and detritivores. Similarly, spatial isolation can limit dispersal and colonization rates of predatory insects more strongly than of herbivores and detritivores, thus generating similar cascading effects. Here we tested the hypothesis that the effect of introduced predatory fish on insect community structure increases with spatial isolation by conducting a field experiment in artificial ponds that manipulated the presence/absence of fish (the redbreast tilapia) at three different distances from a source wetland. Our results showed that fish have direct negative effects on the abundance of predatory insects but probably have variable net effects on the abundance of herbivores and detritivores because the direct negative effects of predation by fish may offset indirect positive ones. Spatial isolation also resulted in indirect positive effects on the abundance of herbivores and detritivores but this effect was stronger in the absence rather than in the presence of fish so that insect communities diverged more strongly between fish and fishless ponds at higher spatial isolation. We argue that an important additional mechanism, ignored in our initial hypothesis, was that as spatial isolation increases fish predation pressure upon herbivores and detritivores increases due to the relative scarcity of predatory insects, thus dampening the positive effect that spatial isolation confers to lower trophic levels. Our results highlight the importance of considering interspecific variation in dispersal and multiple trophic levels to better understand the processes generating community and metacommunity patterns.

Camouflage is a widespread and well-studied anti-predator strategy, yet identifying which patterns provide optimal protection in any given scenario remains challenging. Besides the virtually limitless combinations of colours and patterns available to prey, selection for camouflage strategies will depend on complex interactions between prey appearance, background properties and predator traits, across repeated encounters between co-evolving predators and prey. Experiments in artificial evolution, pairing psychophysics detection tasks with genetic algorithms, offer a promising way to tackle this complexity, but sophisticated genetic algorithms have so far been restricted to screen-based experiments. Here, we present methods to test the evolution of colour patterns on physical prey items, under selection from wild predators in the field. Our techniques expand on a recently-developed open-access pattern generation and genetic algorithm framework, modified to operate alongside artificial predation experiments. In this system, predators freely interact with prey, and the order of attack determines the survival and reproduction of prey patterns into future generations. We demonstrate the feasibility of these methods with a case study, in which free-flying birds feed on artificial prey deployed in semi-natural conditions, against backgrounds differing in three-dimensional complexity. Wild predators reliably participated in this experiment, foraging for 11 to 16 generations of artificial prey and encountering a total of 1,296 evolved prey items. Changes in prey pattern across generations indicated improvements in several metrics of similarity to the background, and greater edge disruption, although effect sizes were relatively small. Computer-based replicates of these trials, with human volunteers, highlighted the importance of starting population parameters for subsequent evolution, a key consideration when applying these methods. Ultimately, these methods provide pathways for integrating complex genetic algorithms into more naturalistic predation trials. Customisable open-access tools should facilitate application of these tools to investigate a wide range of visual pattern types in more ecologically-relevant contexts.

Mental imagery and planning are important aspects of cognitive behaviour. Being able to predict outcomes through mental simulation can increase environmental fitness and reduce uncertainty. Such predictions reduce surprise and fit with thermodynamically driven theories of brain function by attempting to reduce entropy. In the present work, the authors tested these ideas in a predator–prey scenario where agents with a limited energy budget had to maximise food intake, while avoiding a predator. Forward planning agents, with the ability to mentalise, to Actor Critic agents that do not plan beyond the current state were also compared. The authors show that the ability to mentalise has distinct advantages when in noisy, uncertain stimuli. These advantages are even more prevalent when tested in the real world on physical robots. The authors’ results highlight the importance of taking into consideration mental imagery and embodiment when constructing artificial cognitive systems.

Prey-predator interactions play a pivotal role in elucidating the evolution and adaptation of various organism’s traits. Numerous approaches have been employed to study the dynamics of prey-predator interaction systems, with agent-based methodologies gaining popularity. However, existing agent-based models are limited in their ability to handle multi-modal interactions, which are believed to be crucial for understanding living organisms. Conversely, prevailing prey-predator integration studies often rely on mathematical models and computer simulations, neglecting real-world constraints and noise. These elusive attributes, challenging to model, can lead to emergent behaviors and embodied intelligence. To bridge these gaps, our study designs and implements a prey-predator interaction scenario that incorporates visual and olfactory sensory cues not only in computer simulations but also in a real multi-robot system. Observed emergent spatial-temporal dynamics demonstrate successful transitioning of investigating prey-predator interactions from virtual simulations to the tangible world. It highlights the potential of multi-robotics approaches for studying prey-predator interactions and lays the groundwork for future investigations involving multi-modal sensory processing while considering real-world constraints.

Scientific knowledge in the field of ecology is increasingly enriched by data acquired by the general public participating in citizen science (CS) programs. Yet, doubts remain about the reliability of such data, in particular when acquired by schoolchildren. We built upon an ongoing CS program, Oak Bodyguards, to assess the ability of schoolchildren to accurately estimate the strength of biotic interactions in terrestrial ecosystems. We used standardized protocols to estimate attack rates on artificial caterpillars and insect herbivory on oak leaves. We compared estimates made by schoolchildren with estimates made by professional scientists who had been trained in predation and herbivory assessments (henceforth, trained scientists), and trained scientists’ estimates with those made by professional scientists with or without expertise (untrained) in predation or herbivory assessment. Compared with trained scientists, both schoolchildren and untrained professional scientists overestimated attack rates, but assessments made by the latter were more consistent. Schoolchildren tended to overestimate insect herbivory, as did untrained professional scientists. Raw data acquired by schoolchildren participating in CS programs therefore require several quality checks by trained professional scientists before being used. However, such data are of no less value than data collected by untrained professional scientists. CS with schoolchildren can be a valuable tool for carrying out ecological research, provided that the data itself is acquired by professional scientists from material collected by citizens.

The pink spotted lady beetle Coleomegilla maculata has been identified as a promising predator to mass rear and release into greenhouses and high tunnels to control aphids on small fruits and vegetables. This study tested the hypothesis that laboratory-reared C. maculata, without any exposure to aphids for multiple generations, could recognize, attack, and consume live aphids. The aphid adults of two species were collected from non-crop host plants (weeds) over two consecutive seasons. The time (seconds) that C. maculata adults required to recognize and partially or completely consume live, healthy adult aphids was recorded in Petri dish arenas in the laboratory. Regardless of the non-prey food source (brine shrimp egg diet, mealworm-protein-based artificial diet), C. maculata adults readily recognized aphids. Adult females were occasionally more voracious than males. One aphid species (Uroleucon erigeronense) was consumed more readily than the other aphid species (Aphis nerii). In conclusion, multigenerational rearing on non-prey foods did not affect the prey recognition behavior of C. maculata adults in the laboratory. Validating the ability of lady beetles reared on artificial diets to recognize and consume live aphids is an important protocol before augmentative releases for aphid control in greenhouses and high tunnels.

Continuous cover forestry is a silvicultural system designed to mimic natural forest dynamics and maintain the struc-ture of uneven-aged semi-natural forests. One of the key steps in this approach is to create small gaps in the canopy by logging small groups of trees or individual trees. In gap-cutting, the main goal is to determine the optimal shape and size of these gaps in order to ensure spontaneous natural regeneration of the major tree species in the canopy. Yet, it remains relatively unknown how various arthropods respond to such forestry practices. Carabid beetles (Coleoptera: Carabidae) play an important role as predators of various small invertebrates and their predators are mostly vertebrates. The interactions between carabids and their predators might change due to shifts in the distribution of patches of suitable habitat as a result of forest management. Here, the aim was to determine whether gaps in the canopy of two different sizes (small vs. large) and shapes (circular vs. elongated) can affect the predation pressure on large carabids in a Hungarian oak-hornbeam forest. Using 3D-printed decoys of the largest com-mon carabid in the area, Carabus coriaceus, placed in each of the four gap treatments and control plots, the seasonal, diurnal, and treatment-specific aspects of predation pressure was estimated. This revealed no significant effects of any of the variables included in this study, which indicates that predation pressure in undisturbed controls located in closed forests and small canopy gaps did not differ significantly. Creating gaps in the canopy by felling few trees seems to be a good strategy for maintaining the forest ecological network with minimal disruption compared clear-felling large areas.