ECOP-MS03

The complex adaptive dynamics of honeybee societies

Monday, June 14 at 5:45pm (PDT)
Tuesday, June 15 at 01:45am (BST)
Tuesday, June 15 09:45am (KST)

SMB2021 Follow Monday (Tuesday) during the "MS03" time block.

Note: this minisymposia has multiple sessions. The second session is MS02-ECOP (click here).

Jun Chen (Arizona State University, USA), Yun Kang (Arizona State University, USA), Gabriela Zuloaga (Arizona State University, USA)

Description:

Social insect colonies are complex adaptive systems where collective behavior emerging from local interactions determines group survival in dynamic environments, which include parasites, epidemics, seasonality and human behavior. Honeybees are ideal model organisms to study how social systems adapt to complex environmental changes since both group and individual features can be experimentally measured and manipulated. They also play an irreplaceable role in ecology, agriculture and economy through, for example, pollination and honey production. Our session will discuss how honeybee colonies maintain their health and social organization while adapting to the dynamic environmental factors. This mini-symposia will bring together a group of distinguished applied mathematicians and biologists who have great expertise in applying experimental approaches, mathematical models and theory to focus on complex adaptive systems in dynamic environments. It will provide an effective platform for presenting and discussing current research as well as generating connections and promoting collaboration in an interdisciplinary group of researchers across different universities and career stages.

Adrian Fisher II

(Arizona State University, School of Life Sciences, United States)

"A widely-used mito-toxic fungicide negatively affects honey bee (Apis mellifera) health"

The honey bee (Apis mellifera) is an essential contributor to crop pollination in the United States. However, honey bees, and other pollinators, have been undergoing population declines for poorly understood reasons. Pollinators may frequently encounter fungicides in foraging environments as they are applied to crop plants during bloom. To assess the impact of the fungicide Pristine® (25.2% boscalid, 12.8% pyraclostrobin) we partially tested the hypothesis that Pristine® negatively affects protein digestion or absorbance. Field colonies were maintained for 13 months with pollen containing four concentrations of Pristine®, bracketing concentrations measured in pollen collected by bees while foraging on fungicide-sprayed almond trees We found that Pristine® negatively affects colony growth and winter survival. Additionally, we observed several individual outcomes including early foraging, elevated rates of pollen foraging and consumption, and reduced longevity. Pristine® consumption also lowered hemolymph protein levels, and this effect increased with bee age. Together, these findings support the hypothesis that fungicides such as Pristine® negatively impact honey bee health at least partly by impairing protein balance. This research was supported by USDA 2017-68004-26322.

Yixiang Wu

(Middle Tennessee State University, United States)

"An Environmental Model of Honey Bee Colony Collapse Due to Pesticide Contamination"

We develop a model of honey bee colony collapse based on the contamination of forager bees in environmental regions contaminated with pesticides. An important feature of the model is the daily homing capacity each day of foragers bees. The model consists of difference equations describing the daily homing of uncontaminated and contaminated forager bees, with an increased homing failure of contaminated bees. The model quantifies colony collapse in terms of the fraction of contaminated bees subject to this increased homing failure. If the fraction is sufficiently high, then the hive falls below a viability threshold population size that leads to rapid disintegration. If the fraction is sufficiently low, then the hive can rise above the viability threshold and attain a stable population level.

Mary R Myerscough

(School of Mathematics and Statistics University of Sydney, Australia)

"Modelling the role of temperature stress in honeybee colony collapse."

Honey bees raise their brood (bee larvae and pupae) inside the hive, ideally at a temperature of between 34 and 36 degrees Celsius. If the brood experiences lower temperatures then it will develop into sub-standard adult bees. These low quality adults will have an impact on the hive as they will less effective workers. Previous modelling work has strongly suggested that effective foraging and, in particular, the prevention of premature death of foragers is crucial for hive health and survival. In this talk we will examine the effect of temperature stress on hive populations, using a delay-differential equation model that includes the effect on adult bees of poor temperature regulation when they were pupae. We show that the equilibrium of these equations has two fold bifurcations. The right most fold bifurcation produces hive collapse in the model. We show that increasing temperature stress makes the hive more prone to collapse if it experiences increased rates of premature forager death.

M. Gabriela Navas-Zuloaga

(School of Human Evolution and Social Change, Arizona State University, United States)

"From Individual Phenotypes to Collective Behavior in Honeybee Foragers: A Mathematical Model"

Recent studies have shown that discrete heritable attention phenotypes in individual honey-bee foragers drive their foraging behavior, thus affecting colony fitness. In particular, individual and collective preference for familiar or novel resources is dependent on the relative presence of high and low attention individuals in the colony. Previous models of honey-bee foraging have not included this phenotype-dependent preference. In order to understand how colony-level preferential exploitation of novel and familiar resources emerges from the interactions between individuals with different preferences and levels of influence, I developed an ordinary differential equation model of self-organized foraging based on the different phenotypes. The model reproduces the observed increased foraging activity in colonies with higher proportions of high-attention foragers, as well as the preference for familiar sources in such colonies. It also provides mechanistic support for the empirical hypothesis that individual preference, amplified by efficient communication, is sufficient to produce collective preference at the observed levels in different colonies. The model contributes to understanding the role of individual cognitive variation in regulating the collective trade-off between exploring for new resources and exploiting known ones.

Hosted by SMB2021 Follow

Virtual conference of the Society for Mathematical Biology, 2021.