Data from: Choice in a floral marketplace: the role of complexity in bumble bee decision-making

Animals have evolved in complex, heterogeneous environments. Thus, decision-making behavior is likely affected by a diversity of co-occurring community-level traits. Here, we investigate how three co-occurring traits of floral communities - the number of flower types, reliability that flowers are associated with a reward, and signal complexity of flowers - affect bumble bee (Bombus impatiens) decision-making. We used arrays of artificial flowers in a full factorial experimental design to assess floral selectivity (preference and constancy), foraging efficiency, and decision latency in foraging bumble bees. We find that our environmental traits uniquely affect each of these behavioral variables, revealing the intricate, yet biologically significant ways that co-occurring environmental traits can affect behavior. Floral selectivity, but not foraging efficiency, is increased by a greater number of choices. Decision latency is greatest when bees are inexperienced foraging in environments with high choice number. Collectively taken, we argue that these results suggest a cost to deciding among many choices, which promotes choice fidelity when many options are present. We suggest that these results have implications for theory on decision-making and selection in biological markets, while demonstrating the importance of studying interactions between naturally co-occurring traits

Data from: Influence of pre-existing preference for color on sampling and tracking behavior in bumblebees

Animals reduce uncertainty in their lifetime by using information to guide decision making. Information available can be inherited from the past or gathered from the present. Therefore, animals must balance inherited biases with new information that may be in conflict with those potential biases. In our study, we set up color pairings such that an arbitrarily chosen focal color, human-orange, would result in an inherent bias in comparison to three other colors tested resulting in equal, medium, and strong preference differences. We chose color pairings through a series of preferences tests across 8 colonies of bumblebees. We subsequently used these pairings with rewards that varied in quality (good or bad states) and consistency (steady and fluctuating) in order to investigate how inherited biases affect the foraging choices of bumblebees when new information is gathered. We found that the pre-existing color biases within our bees were only maintained when the reward associated with those colors was steady, even if paired with mediocre sugar concentrations. When maintained, we observed that other aspects of bee choice also reflected this bias, including increased sampling for the preferred color and an increased likelihood of choosing that color in a subsequent choice. Thus, environmental change and reward differences interact with the level of pre-existing bias to determine whether inherited information is more heavily weighted than newly gathered information, and even a strong pre-existing bias can be quickly erased with experience under some conditions

Why some memories do not last a lifetime: dynamic long-term retrieval in changing environments

Memory is a fundamental component of learning, a process by which individuals alter their behavior through experience. Although memory most likely has explicit costs such as synaptic maintenance and metabolic demands, there are also implicit costs to memory, in particular, the use of information that is no longer appropriate or is incorrect. Specifically, the period of retrievability for memories, or "memory window," should be sensitive to the rate of environmental change of information stored in memory. Much empirical data suggest that memory length--this period of retrievability--changes with both the age and state of the individual. Here, we use a dynamic programming approach to examine how optimal memory retrieval might change within the lifetime of the individual learner. We find that optimal memory length varies with both age and state (e.g., energy reserves) of the organism and that features of the environment determine how this change in memory occurs. In our model, retrieval decreases as the environment becomes unreliable but roughly increases with the cost of living. Cost of living interacts with the state of the organism: with high cost of living, an organism in a very poor state should have a long memory length, but an organism in a very good state with low costs of living should have a short memory length. Finally, we find there are circumstances where it is optimal for memory retrieval to decline toward the end of the lifetime. Because this framework does not incorporate inevitable degradation of neural mechanisms, this result implies that memory loss with age might actually be adaptive. Copyright 2009, Oxford University Press.

The discounting-by-interruptions hypothesis: model and experiment

Experimental animals often prefer small but immediate rewards even when larger-delayed rewards provide a higher rate of intake. This impulsivity has important implications for models of foraging and cooperation. Behavioral ecologists have hypothesized that animals discount delayed rewards because delay imposes a collection risk. According to this long-standing hypothesis, delay reduces value because an interruption that occurs while an animal is waiting may prevent it from collecting the delayed reward. Although there have been many experimental demonstrations of animal preferences for immediacy, none have included any interruptions. This paper develops a simple model of discounting by interruptions and then tests this model experimentally. The model considers the effects of interruption rate and duration on choice behavior. The experiment tests the effects of interruptions on the choice behavior of captive blue jays (Cyanocitta cristata) using a factorial design that manipulates the rate and duration of interruptions. The results do not support the discounting-by-interruptions hypothesis. This represents one of several lines of evidence suggesting that investigators should seek alternative explanations of the animal impulsivity. Copyright 2008, Oxford University Press.

Components of change in the evolution of learning and unlearned preference

Several phenomena in animal learning seem to call for evolutionary explanations, such as patterns of what animals learn and do not learn. While several models consider how evolution should influence learning, we have very little data testing these models. Theorists agree that environmental change is a central factor in the evolution of learning. We describe a mathematical model and an experiment, testing two components of change: reliability of experience and predictability of the best action. Using replicate populations of Drosophila we varied statistical patterns of change across 30 generations. Our results provide the first experimental demonstration that some types of environmental change favour learning while others select against it, giving the first experimental support for a more nuanced interpretation of the selective factors influencing the evolution of learning

Teaching animal behavior online: A primer for the pandemic and beyond

Behavior courses face numerous challenges when moving to an online environment, as has been made necessary by the COVID- 19 pandemic. These challenges occur largely because behavior courses, like most organismal biology courses, often stress experiential learning through laboratories that involve live animals, as well as a lecture component that emphasizes formative assessment, discussion, and critical thinking. Although online behavior courses may be remote, they can still be interactive and social, and designed with inclusive pedagogy. Here, we discuss some of the key decisions that instructors should consider, provide recommendations, and point out new opportunities for student learning that stem directly from the move to online instruction. Specific topics include challenges related to generating an inclusive and engaging online learning environment, synchronous versus asynchronous formats, assignments that enhance student learning, testing format and execution, grade schemes, design of laboratory experiences including opportunities for community science, design of synthetic student projects, and workload balance for students and instructors. We designed this primer both for animal behavior instructors who need to quickly transition to online teaching in the midst of a pandemic, and for those facing such transitions in upcoming terms. Much of the manuscript’s content should also be of general interest and value to instructors from all areas of organismal biology who are attempting to quickly transition to online teaching.Teaching behavior online presents both challenges and opportunities. In this comprehensive guide, we offer suggestions for the design and implementation of online behavior courses. For all aspects of these courses, including lectures, discussions and labs, we emphasize a backwards- design approach and the importance of flexibility, inclusivity, equity, and accessibility. We also offer recommendations for delivery mode, specific course components, and resources for additional support.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163792/1/eth13096_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163792/2/eth13096.pd