The value of spatial experience and group size for ant colonies in direct competition.

Animals often search for food more efficiently with experience. However, the contribution of experience to foraging success under direct competition has rarely been examined. Here we used colonies of an individually foraging desert ant to investigate the value of spatial experience. First, we trained worker groups of equal numbers to solve either a complex or a simple maze. We then tested pairs of both groups against one another in reaching a food reward. This task required solving the same complex maze that one of the groups had been trained in, to determine which group would exploit better the food reward. The worker groups previously trained in the complex mazes reached the food reward faster and more of these workers fed on the food than those trained in simple mazes, but only in the intermediate size group. To determine the relative importance of group size versus spatial experience in exploiting food patches, we then tested smaller trained worker groups against larger untrained ones. The larger groups outcompeted the smaller ones, despite the latter's advantage of spatial experience. The contribution of spatial experience, as found here, appears to be small, and depends on group size: an advantage of a few workers of the untrained group over the trained group negates its benefits.

Non-spatial information on the presence of food elevates search intensity in ant workers, leading to faster maze solving in a process parallel to spatial learning.

Experience can lead to faster exploitation of food patches through spatial learning or other parallel processes. Past studies have indicated that hungry animals either search more intensively for food or learn better how to detect it. However, fewer studies have examined the contribution of non-spatial information on the presence of food nearby to maze solving, as a parallel process to spatial learning. We exposed Cataglyphis niger ant workers to a food reward and then let them search for food in a maze. The information that food existed nearby, even without spatial information, led to faster maze solving compared to a control group that was not exposed to the food prior to the experiment. Faster solving is probably achieved by a higher number of workers entering the maze, following the information that food is present nearby. In a second experiment, we allowed the ants to make successive searches in the maze, followed by removing them after they had returned to the nest and interacted with their naïve nestmates. This procedure led to a maze-solving time in-between that displayed when removing the workers immediately after they had reached the food and preventing their return to the colony, and that of no removal. The workers that interacted upon returning to the nest might have transferred to naïve workers information, unrelated to spatial learning, that food existed nearby, and driven them to commence searching. Spatial learning, or an increase in the correct movements leading to the food reward relative to those leading to dead-ends, was only evident when the same workers were allowed to search again in the same maze. However, both non-spatial information on the presence of food that elevated search intensity and spatial learning led to faster maze solving.

Wormlions prefer both fine and deep sand but only deep sand leads to better performance.

Wormlions are small fly larvae that dig pits in loose soil to trap their prey. Similar to other trap-building predators, like spiders and antlions, they depend on the habitat structure for successful trap construction and prey catch. We examined whether sites at which wormlions are present differ in sand depth and particle size from nearby sites, at which wormlions are absent. Next, in the laboratory we manipulated both sand depth and type (fine vs. coarse) to determine their joint effect on microhabitat preference, the size of the constructed pit, wormlion movement, and their latency to respond to prey. We expected better performance by wormlions in fine and deep sand, and the sand in wormlions' natural sites to be finer and deeper. However, in only partial agreement with our expectations, wormlion sites featured finer sand but not deeper sand. In the laboratory, wormlions preferred both fine and deep sand, and moved more in shallow and coarse sand, which we interpret as an attempt to relocate away from unfavorable conditions. However, only deep sand led to larger pits being constructed and to a faster response to prey. The preference for fine sand could, therefore, be related to other benefits that sand provides. Finally, body mass was a dominant factor, interacting with the preference for both deep and fine sand: deep over shallow sand was more favored by large wormlions and fine over coarse sand by smaller ones. Our results suggest that several factors should be incorporated when studying microhabitat selection.

The effect of maze complexity on maze-solving time in a desert ant.

One neglected aspect of research on foraging behavior is that of the effect of obstacles that increase habitat complexity on foraging efficiency. Here, we explored how long it takes individually foraging desert ant workers (Cataglyphis niger) to reach a food reward in a maze, and examined whether maze complexity affects maze-solving time (the time elapsed till the first worker reached the food reward). The test mazes differed in their complexity level, or the relative number of correct paths leading to the food reward, vs. wrong paths leading to dead-ends. Maze-solving time steeply increased with maze complexity, but was unaffected by colony size, despite the positive correlation between colony size and the number of workers that searched for food. The number of workers observed feeding on the food reward 10 min after its discovery decreased with complexity level but not colony size. We compared our experimental results to three simulation models, applying different search methods, ranked them according to their fit to the data and found the self-avoiding random search to fit the best. We suggest possible reasons for the model deviations from the observational findings. Our data emphasize the necessity to refer to habitat complexity when studying foraging behavior.