Madec, C. | Search bioRxiv

bioRxiv2026

Capacity of oil palm (Elaeis guineensis Jacquin) male inflorescences to host Elaeidobius kamerunicus Faust (Coleoptera: Curculionidae: Derelominae). Comparison between two cultivars in northern Sumatra

During the 1980's, Elaeidobius kamerunicus, one of the oil palm pollinator species in Africa, was successfully introduced in Indonesia from Cameroon to improve oil palm production and reduce assisted pollination. It is now well known that E. kamerunicus completes its entire life cycle on the anthesis of the male inflorescences. However, for a long time, oil palm breeding programs have favoured the development of female inflorescences for production purposes, to the detriment of male inflorescences. The objective of our study was to explore the interactions between the weevil population, at immature stages, and male inflorescences, produced by two different cultivars (a super-male (SM) cultivar and a highly female and productive experimental cultivar (EXP) of five years old) during anthesis and post-anthesis stages. Morphological characteristics of spikelets of inflorescences were also studied and compared. We analysed field and laboratory data, collected in North Sumatra (Indonesia) from April to June 2019. The mean number of spikelets is lower in EXP palms (126{+/-}16) than in SM palms (213{+/-}15). There are more abnormal spikelets in SM palms (126{+/-}77 and 100{+/-}73 for SM-SD and SM-DD cultivars, respectively), than in EXP palms (33{+/-}23). However, all these differences do not affect either male inflorescences number of flowers or their carrying capacity that contributes to E. kamerunicus development. The number of male flowers per inflorescences is almost the same for both materials, and about 10% of flowers were occupied by E. kamerunicus immature stages. Despite noticeable morphological differences, no major differences were found between male inflorescences of EXP and SM cultivars. We will discuss our results from pollination point of view.

plant biology↗

bioRxiv2020

Deep Neural Network and field experiments reveal how transparent wing windows reduce detectability in butterflies

Lepidoptera - a group of insects in which wing transparency has arisen multiple times - exhibit much variation in the size and position of transparent wing zones. However, little is known as to how this variability affects detectability. Here, we test how the size and position of transparent elements affect predation of artificial moths by wild birds in the field. We also test whether deep neural networks (DNNs) might be a reasonable proxy for live predators, as this would enable one to rapidly test a larger range of hypotheses than is possible with live animals. We compare our field results with results from six different DNN architectures (AlexNet, VGG-16, VGG-19, ResNet-18, SqueezeNet, and GoogLeNet). Our field experiment demonstrated the effectiveness of transparent elements touching wing borders at reducing detectability, but showed no effect of transparent element size. DNN simulations only partly matched field results, as larger transparent elements were also harder for DNNs to detect. The lack of consistency between wild predators and DNNs responses raises questions about what both experiments were effectively testing, what is perceived by each predator type, and whether DNNs can be considered to be effective models for testing hypotheses about animal perception and cognition.

evolutionary biology↗