Reproductive activities are often associated with conspicuous morphology or behaviour that could be exploited by predators. Individuals can therefore face a trade-off between reproduction and predation risk. Here we use simple models to explore population-dynamical consequences of such a trade-off for populations subject to a mate-finding Allee effect and an Allee effect due to predation. We present our results in the light of populations that belong to endangered species or pests and study their viability and resilience. We distinguish several qualitative scenarios characterized by the shape and strength of the trade-off and, in particular, identify conditions for which the populations survive or go extinct. Reproduction can be so costly that the population always goes extinct. In other cases, the population goes extinct only over a certain range of low, intermediate or high levels of reproductive activities. Moreover, we show that predator removal (e.g. in an attempt to save an endangered prey species) has the least effect on populations with low cost of reproduction in terms of predation and, conversely, predator addition (e.g. to eradicate a pest) is most effective for populations with high predation cost of reproduction. Our results indicate that a detailed knowledge of the trade-off can be crucial in applications: for some trade-off shapes, only intermediate levels of reproductive activities might guarantee population survival, while they can lead to extinction for others. We therefore suggest that the fate of populations subject to the two antagonistic Allee effects should be evaluated on a case-by-case basis. Although the literature offers no quantitative data on possible trade-off shapes in any taxa, indirect evidence suggests that the trade-off and both Allee effects can occur simultaneously, e.g. in the golden egg bug Phyllomorpha laciniata.

• MeSH
• biologické modely * MeSH
• ekosystém MeSH
• hodnocení rizik MeSH
• kompetitivní chování fyziologie   MeSH
• predátorské chování fyziologie   MeSH
• rizikové faktory MeSH
• rozmnožování fyziologie   MeSH
• sexuální chování zvířat fyziologie   MeSH
• zvířata MeSH
• Check Tag
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The research presented in this manuscript proposes a novel Harris Hawks optimization algorithm with practical application for evolving convolutional neural network architecture to classify various grades of brain tumor using magnetic resonance imaging. The proposed improved Harris Hawks optimization method, which belongs to the group of swarm intelligence metaheuristics, further improves the exploration and exploitation abilities of the basic algorithm by incorporating a chaotic population initialization and local search, along with a replacement strategy based on the quasi-reflection-based learning procedure. The proposed method was first evaluated on 10 recent CEC2019 benchmarks and the achieved results are compared with the ones generated by the basic algorithm, as well as with results of other state-of-the-art approaches that were tested under the same experimental conditions. In subsequent empirical research, the proposed method was adapted and applied for a practical challenge of convolutional neural network design. The evolved network structures were validated against two datasets that contain images of a healthy brain and brain with tumors. The first dataset comprises well-known IXI and cancer imagining archive images, while the second dataset consists of axial T1-weighted brain tumor images, as proposed in one recently published study in the Q1 journal. After performing data augmentation, the first dataset encompasses 8.000 healthy and 8.000 brain tumor images with grades I, II, III, and IV and the second dataset includes 4.908 images with Glioma, Meningioma, and Pituitary, with 1.636 images belonging to each tumor class. The swarm intelligence-driven convolutional neural network approach was evaluated and compared to other, similar methods and achieved a superior performance. The obtained accuracy was over 95% in all conducted experiments. Based on the established results, it is reasonable to conclude that the proposed approach could be used to develop networks that can assist doctors in diagnostics and help in the early detection of brain tumors.

• Klíčová slova
• Harris Hawks optimization, chaotic, classification, convolutional neural networks, exploitation–exploration trade-off, quasi-reflection-based learning, swarm intelligence,
• MeSH
• algoritmy MeSH
• Falconiformes * MeSH
• meningeální nádory * MeSH
• nádory mozku * diagnostické zobrazování   MeSH
• neuronové sítě MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH

The search for mates is often accompanied with conspicuous behaviour or morphology that can be exploited by predators. Here we explore the evolutionary consequences of a trade-off that arises naturally between mate acquisition and risk of predation and study evolution of the rate at which male prey search for mates in a population subject to a mate-finding Allee effect and exposed to either generalist or specialist predators. Since we show that the mate search rate determines the strength of the mate-finding Allee effect, we can alternatively view this as evolution of the mate-finding Allee effect in prey. We contrast two different life histories and find that, predominantly, male prey either evolve towards the maximal mate search rate yielding the weakest possible mate-finding Allee effect (thus showing no adaptive response in mating behaviour to predation risk) or evolutionary bi-stability occurs. In the latter case, males evolve a relatively low mate search rate (hence a relatively strong mate-finding Allee effect, interpreted as an adaptive response of male prey to predation) when initially slow or the maximal mate search rate when initially fast. Disruptive selection does not occur in populations exposed to generalist predators but is possible when predators are specialists. The dimorphic phase, in which fast and conspicuous male prey coexist with slow and cryptic ones, is however but a transient in evolutionary dynamics as one branch goes extinct while the other evolves towards the maximal mate search rate.

• Klíčová slova
• Adaptive dynamics, Evolutionary branching, Life history trade-off, Mating behaviour, Predator-prey dynamics,
• MeSH
• algoritmy MeSH
• biologická evoluce * MeSH
• biologické modely MeSH
• kompetitivní chování fyziologie   MeSH
• predátorské chování fyziologie   MeSH
• rozmnožování fyziologie   MeSH
• sexuální chování zvířat fyziologie   MeSH
• zvířata MeSH
• Check Tag
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH