feedback loop

Guest blog post by Dominik Lammers

Models help us ask a deceptively simple question: if the world works in a particular way, what should we expect to happen?

For honey bee colonies, answering that question is difficult. A colony’s development depends on food, weather, disease, the surrounding landscape, and the behaviour of thousands of individual bees. These influences do not act separately. They affect one another, sometimes in ways that are hard to isolate even in carefully designed experiments.

In a recent study with Fabrice Requier, Andreas Focks, and Jürgen Groeneveld, we explored one of these connections using BEEHAVE, a computer model of a honey bee colony. We developed an exploratory extension called BEEHAVE-PPE, asking whether seasonal colony development could arise from links between pollen, brood pheromones, egg laying, and temperature, rather than following a seasonal egg-laying pattern specified in advance.

Table of Contents

A starting point that made BEEHAVE useful
A feedback loop inside the hive
Letting seasonal dynamics emerge
Learning from where the model fails
The data needed to go further
Why this matters for future stressor research

The result is not a finished replacement for the original model. It is a hypothesis about processes inside the hive: one that can produce plausible colony dynamics, while also making clear where scientific understanding remains incomplete.

A starting point that made BEEHAVE useful

Wooden beehive boxes for beekeeping and honey collecting in blooming canola field. Credit to stevanovicigor via Envato.

BEEHAVE has been used to investigate how food availability, weather, parasites, pesticides, and beekeeping practices can affect honey bee colonies. It links processes inside the hive with conditions in the surrounding landscape, allowing researchers to explore combinations of stressors that would be difficult to study directly in real colonies.

To give a simulated colony a realistic seasonal trajectory, the original BEEHAVE uses an annual curve that determines how many eggs the queen lays on each day of the year. This was an effective modelling choice. It allowed the colony to develop in a broadly realistic way under typical Central European conditions and made it possible to investigate many other questions.

At the same time, this relationship shapes much of the simulated colony’s development. The queen follows a known seasonal pattern, while real colonies are likely to adjust reproduction in response to conditions inside and outside the hive.

I was interested in what would happen if that central pattern was no longer specified in advance. That became less like removing a single line from a model and more like beginning a journey. Each change exposed a new problem: without the fixed curve, what would initiate colony growth? What would prevent it from continuing indefinitely? What processes might connect the colony’s nutritional state to its reproduction?

For me, this was both a creative and an intellectual task. It involved imagining possible biological explanations, searching the literature for evidence that could support them, and translating those ideas into code. BEEHAVE-PPE emerged from that process.

A feedback loop inside the hive

The resulting model is built around three linked ideas.

Conceptual overview of the relationships between stored pollen and egg-laying in BEEHAVE and the new version, BEEHAVE-PPE. Major differences are indicated in red. Credit to Lammers et al., 2026.

First, the amount of pollen stored in the colony influences the queen’s egg laying. Pollen is the main protein source for feeding brood, so a colony with more available pollen can plausibly support more reproduction.

Second, larvae produce brood pheromones: chemical signals that can influence the behaviour of worker bees.

Third, brood pheromones can encourage workers to collect more pollen rather than nectar. This helps replenish pollen stores and can support further egg laying.

Together, these processes create a feedback loop:

pollen availability -> egg laying -> brood pheromones -> pollen collection -> pollen availability

Temperature affects this loop. In BEEHAVE-PPE, warmer conditions increase the assumed degradation of brood pheromone. This weakens the signal encouraging pollen collection and can slow colony growth.

In one sense, temperature fulfills a role similar to the original seasonal egg-laying curve: it helps shape when growth slows and when a colony reaches its annual peak. But it does so differently. Rather than instructing the queen to lay a certain number of eggs on a particular date, it represents an environmental condition that can differ between places and years. This opens the possibility that the same underlying model could respond differently under different temperature regimes, provided that its temperature relationships can eventually be tested and calibrated.

Letting seasonal dynamics emerge

Bees Entering Hive on Wooden Frame. Credit to NaturesCharm via Envato.

Under the average weather conditions used in this study, BEEHAVE-PPE produced plausible seasonal colony dynamics. The simulated colonies grew in spring, reached a population peak in early summer, and declined afterwards. The number of adult bees in the simulated colonies followed the broad timing and shape of the French monitoring data used to calibrate the new module.

The model did not prove that real colonies work through precisely this mechanism. It cannot do that. A model can show that a proposed explanation is capable of generating an observed pattern; it cannot establish, by itself, that the explanation is the only or exact one used in nature.

What BEEHAVE-PPE does show is that the seasonal development of a colony need not be prescribed as a curve from the outset. A plausible combination of pollen availability, brood signalling, worker behaviour, and temperature can generate it.

That changes the role of the model. Instead of only reproducing a known seasonal pattern, it asks what biological connections could be responsible for that pattern.

Learning from where the model fails

bees on honeycomb — Bees on honeycomb. Credit to Kohanova via Envato.

The model also revealed a clear limitation. It produced plausible dynamics under averaged weather conditions, but it was vulnerable to prolonged periods in which bees could not collect pollen.

In the simulation, a long interruption weakens the feedback loop. Less pollen leads to reduced egg laying; fewer larvae produce less brood pheromone; and the weaker pheromone signal reduces the incentive to collect pollen when conditions improve. The colony can become trapped in a low-pollen, low-brood state.

This is unlikely to be the complete story in real colonies. Colonies can buffer difficult periods through stored resources and changes in brood and worker management. BEEHAVE already contains potentially relevant processes, including brood cannibalism and worker self-metabolism, but these are not yet represented in sufficient nutritional detail to support recovery within the new feedback loop.

That result gives the next steps a clearer direction. Rather than simply knowing that the model behaves unrealistically after sustained poor weather, we can identify the chain of events that causes it. This points to promising improvements, including better representation of nutrient reserves, resource recovery through brood cannibalism, and the colony processes that help it restart reproduction after a difficult period.

The data needed to go further

Honey bees flying into wooden beehive. Credit to cookelma via Envato.

Developing and testing a model depends on data. The French dataset used in this study, covering 250 colonies, was especially valuable because it provided an unusually broad picture of seasonal colony development under comparable climatic conditions. It made it possible to see not just how one colony behaved, but what a larger set of colonies broadly did over a season.

This kind of baseline information is more limited than it may seem. For several important aspects of honey bee colony development, some of the most detailed observations still trace back to research from decades ago. We have valuable knowledge about individual processes, but less information showing how pollen availability, egg laying, brood development, worker behaviour, temperature, and population size change together over time.

New long-term observation approaches, including continuously monitored colonies, could help fill this gap. Targeted measurements of these linked processes would make it possible to test not only whether BEEHAVE-PPE produces realistic patterns, but whether it does so for the right biological reasons.

Why this matters for future stressor research

BEEHAVE is often used to explore how poor forage, adverse weather, parasites, pesticides, and beekeeping practices may affect colony development. In the original model, these pressures act on a colony whose broad reproductive trajectory is already set by the annual egg-laying pattern.

Honey Bee on flower. Credit to IciakPhotos via Envato.

BEEHAVE-PPE changes that relationship. Because egg laying, brood production, pollen collection, and colony strength can influence one another, a stressor can affect more than one isolated part of the model. A shortage of pollen, for example, may not only reduce food available on a particular day. It may also reduce reproduction, alter brood signals, change later foraging behaviour, and affect the colony’s capacity to recover.

The current version may respond too strongly when the feedback loop is interrupted. But if these dynamics can be stabilised and supported by stronger empirical evidence, future versions could give a more complete picture of how stressors interact. They could help investigate when the effects of a stressor are amplified by the colony’s internal state, which combinations are most damaging, and where a colony’s natural buffering mechanisms provide protection.

This is particularly relevant as weather patterns, flowering times, forage availability, and temperature change together. BEEHAVE-PPE is not yet a forecasting tool for climate change or colony risk. It is a first step from an imposed seasonal pattern toward interacting biological mechanisms.

Its main value is that it makes both a plausible explanation and its remaining gaps visible. That is one of the strengths of models: they do not only tell us what we can predict. They show us what we still need to understand before prediction becomes possible.

Original source:

Lammers D, Requier F, Focks A, Groeneveld J (2026) Food for thought: could the queen’s egg-laying rate in the BEEHAVE honey bee model emerge from the effects of brood pheromones, weather conditions, and pollen availability? Individual-based Ecology 2: e185721. https://doi.org/10.3897/ibe.2.185721

Every year on May 20th, the world celebrates World Bee Day, a date chosen to honour Anton Janša, an 18th-century pioneer of modern beekeeping who was born on this day in Slovenia, a country where beekeeping has been a cherished tradition for centuries. This year’s theme, “Bee Together for People and the Planet,” puts the spotlight on the partnership between humans and bees, and how collaboration, tradition, and innovation can help secure a sustainable future for both.

At Pensoft, we’re marking the occasion by shining a light on a threat that often goes unnoticed: the destabilisation of pollination networks. As ecosystems change and pathogens spread, sometimes carried by the very pollinators we rely on, the delicate web of relationships between plants and their pollinators is under pressure. Understanding bees and other pollinators as potential carriers of invasive plant diseases is becoming an increasingly important piece of the conservation puzzle.

Surprising Interaction

Apis mellifera and myrtle rust fungus invasional mutualism — Apis mellifera on leaves with myrtle rust. Photo credit to Geoff S Pegg.

New research published in NeoBiota has found that the Western honey bee – an introduced species to Australia – and the devastating, invasive plant fungus known as myrtle rust (Austropuccinia psidii) may have formed a mutually beneficial relationship known as an “invasional mutualism.”

Myrtle rust is notorious for devastating ecologically and culturally significant native plants in the Myrtaceae family, putting 17% of Australia’s endemic vegetation at risk. While rust fungi generally rely strictly on wind to spread, researchers discovered that bees may actively forage on the bright yellow fungus spores, packing them into their pollen baskets and carrying them back to the hive just as they would regular pollen.

Researcher taking samples from a beehive. Photo credit to Caroline Hauxwell.
Beehive in the forest. Photo credit to Caroline Hauxwell.

Through a series of experiments, the team made three significant findings. Firstly, the rust spores proved to be quite nutritious. They contained over 22% protein and all 10 essential amino acids, meeting the threshold required for bee colonies to survive. In fact, the fungus matched the nutritional quality of high-value floral pollen, like willow pollen.

In laboratory feeding trials, larvae raised on a diet of myrtle rust spores grew up perfectly healthy, developing at the same speed and reaching similar body weights as bees raised on a traditional high-quality pollen diet. As the researchers explain:

These findings suggest that spore foraging may not be an aberration, but a viable foraging strategy for honey bees.

And perhaps the most alarming discovery is that the myrtle rust spores remain viable and capable of causing new plant infections for at least nine days inside a beehive which could pose significant biosecurity risks

A Devastating Ecological Feedback Loop

Beehive samples taking — Taking samples from a beehive. Photo credit to Caroline Hauxwell.

This discovery challenges the assumption that invasive species always act independently, and it carries major environmental consequences. As myrtle rust kills off keystone taxa in the Myrtaceae family, such as eucalypts, paperbarks, and other ecologically and culturally significant species, particularly in Australia, fewer flowers and less pollen become available for bees to forage on. Beyond the direct biodiversity loss, as the fungus kills these plants, fewer flowers and less pollen are available for the bees.

Under such conditions, bees may increasingly turn to alternative protein sources, such as fungal urediniospores,
the researchers explain.

This could set off a devastating ecological feedback loop.

“Over time, this dynamic may destabilise plant-pollinator networks and forest regeneration, particularly in regions with high Myrtaceae endemism.” They add: “While generalist foragers like A. mellifera may buffer their colony health by switching to spores or non-Myrtaceae pollen sources, the long-term ecological cost could be substantial, especially for specialist pollinators that lack such flexibility.“

The risks extend beyond ecosystems. Because spores remain viable inside a hive for over a week, commercial beehives – regularly transported across the country over three to seven days to pollinate crops – now represent a significant pathway for human-assisted spread of the pathogen.

As the lead author, Sacchi Shin-Clayton (University of Cambridge) emphasises:

Apis mellifera is an introduced species used as a commercial pollination agent worldwide, and shifting honey bee colonies between agricultural sites to boost pollination has become a standard practice. This reliance on honey bee colonies and shifting between multiple sites is quite concerning, given the demonstrated interaction between A. mellifera and myrtle rust, and its longevity within colonies.

Despite this, current biosecurity strategies for managing myrtle rust do not account for the movement of commercial beehives, leaving a critical gap in disease management approaches.

We propose that honey bees be explicitly considered in both epidemiological models and the formulation of management and containment strategies,
the researchers urge.

Recognising pollinators as potential vectors of invasive plant pathogens is an essential next step – one that could prove critical for protecting Australia’s vulnerable native forests.

This World Bee Day is a timely reminder that our relationship with bees is more complex than it might seem. Protecting them and the ecosystems they move through will require us to understand that complexity better.

Original source:

Shin-Clayton S, Mortensen AN, Beggs JR, Buxton MN, Hauxwell C, Bateson MF, Jochym M, Pegg GS, Pattemore DE (2026) Honey bees as potential vectors of the invasive rust pathogen Austropuccinia psidii: nutritional mutualism and implications for pathogen spread. NeoBiota 106: 75-90. https://doi.org/10.3897/neobiota.106.169027

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Tag: feedback loop

A honey bee colony does not follow a calendar. Should its model?