Insect Diet

International audienc

Traveling Salesman

International audienceThe traveling salesman problem is the task of determining an optimal path through several points and return to the starting point

Nutrition

International audienc

Insect Diet

International audienceInsect diet refers to the food usually eaten by an insect for growth, tissue maintenance, and reproduction, as well as the energy necessary to maintain these functions

Automated monitoring of bee behaviour using connected hives: towards a computational apidology

International audienceA major difficulty in studying the behaviour of social insects, such as bees, is to collect quantitative data on large numbers of individuals and over long periods of time, in sometimes dark and not easily accessible nests. Over the past decade, connected hives equipped with large sets of sensors to monitor real-time data about bee colony health and environmental conditions have been increasingly used in fundamental research, precision beekeeping and outreach programs. Here, we argue that combining these connected hive systems with automated movement tracking devices to obtain long-term data about the behaviour of bees inside and outside the hive can lead to major breakthroughs by helping discover new behaviours and compare data across labs and species. First, we describe the main sensors and hive parameters commonly used in connected hives used for honey bee and bumblebee colonies. Next, we discuss how developing more integrated systems connecting bees, hives and their environment, will help ask novel fundamental questions on bee behaviour and ecology

Analysis of temporal patterns in animal movement networks

We implemented our method in R. We provide the codes and the bumblebee and black kite datasets in Dryad Digital Repository https://doi.org/10.5061/dryad.47d7wm390 (Pasquaretta et al., 2015). The roe deer dataset was obtained from MOVEBANK (Wikelski & Kays, 2020). Animal Identifier: Sandro (M06), from Cagnacci et al. (2011) (https://www.movebank.org/). The wolf dataset was obtained from MOVEBANK (Wikelski & Kays, 2020), Animal identifier: Zimzik, from Kaczensky et al. (2006) (https://www.movebank.org/).International audience1. Understanding how animal movements change across space and time is a fundamental question in ecology. While classical analyses of trajectories give insightful descriptors of spatial patterns, a satisfying method for assessing the temporal succession of such patterns is lacking.2. Network analyses are increasingly used to capture properties of complex animal trajectories in simple graphical metrics. Here, building on this approach, we introduce a method that incorporates time into movement network analyses based on temporal sequences of network motifs.3. We illustrate our method using four example trajectories (bumblebee, black kite, roe deer, wolf) collected with different technologies (harmonic radar, platform terminal transmitter, global positioning system). First, we transformed each trajectory into a spatial network by defining the animal's coordinates as nodes and movements in between as edges. Second, we extracted temporal sequences of network motifs from each movement network and compared the resulting behavioural profiles to topological features of the original trajectory. Finally, we compared each sequence of motifs with simulated Brownian and Lévy random motions to statistically determine differences between trajectories and classical movement models.4. Our analysis of the temporal sequences of network motifs in individual movement networks revealed successions of spatial patterns corresponding to changes in behavioural modes that can be attributed to specific spatio‐temporal events of each animal trajectory. Future applications of our method to multi‐layered movement and social network analysis yield considerable promises for extending the study of complex movement patterns at the population level

A theoretical exploration of dietary collective medication in social insects

International audienceAnimals often alter their food choices following a pathogen infection in order to increase immune function and combat the infection. Whether social animals that collect food for their brood or nestmates adjust their nutrient intake to the infection states of their social partners is virtually unexplored. Here we develop an individual-based model of nutritional geometry to examine the impact of collective nutrient balancing on pathogen spread in a social insect colony. The model simulates a hypothetical social insect colony infected by a horizontally transmitted parasite. Simulation experiments suggest that collective nutrition, by which foragers adjust their nutrient intake to simultaneously address their own nutritional needs as well as those of their infected nestmates, is an efficient social immunity mechanism to limit contamination when immune responses are short. Impaired foraging in infected workers can favour colony resilience when pathogen transmission rate is low (by reducing contacts with the few infected foragers) or trigger colony collapse when transmission rate is fast (by depleting the entire pool of foragers). Our theoretical examination of dietary collective medication in social insects suggests a new possible mechanism by which colonies can defend themselves against pathogens and provides a conceptual framework for experimental investigations of the nutritional immunology of social animals