Quick Read. Put a human runner in Singapore and a bee in a forest. Both move through space. Both use information. Both face resources, barriers, costs and changing conditions. Yet they do not experience the same operational world. The runner may organise movement around pavements, junctions, heat, shade, traffic and distance. The bee may organise movement around the hive, sunlight, visual landmarks, odours, wind, flower patches and return direction. The physical environment may be shared, but the usable habitat depends on the receiver.

Start with movement, not with the map

A conventional map begins by asking what exists in a place: roads, buildings, rivers, trees, paths and boundaries. Movement ecology begins with a different set of questions. Why is an organism moving? How can it move? What information can it use? Which external factors change the movement that is actually realised?

Ran Nathan and colleagues proposed a unifying movement-ecology framework built around four interacting components: internal state, motion capacity, navigation capacity and external factors. Internal state asks why the organism moves. Motion capacity asks how it can move. Navigation capacity asks when and where it can orient movement. External factors include the physical and biological environment. The movement path is produced through the interaction of all four, and the path then feeds back into later state and environmental conditions.

This framework is powerful because it works across very different organisms. A human jogger, a bee, a migrating bird, a dispersing seed and even a microorganism can be studied without pretending that their movement mechanisms are identical.

The Singapore runner

Imagine a person leaving home for a ten-kilometre run in Singapore. The objective city contains millions of physical details. The runner does not need most of them. The useful world is compressed into a smaller set of movement-relevant relationships:

• home and return point,
• pavements and park connectors,
• junctions and crossings,
• distance and gradient,
• shade and exposed sections,
• heat, rain and humidity,
• water and rest opportunities,
• crowding and traffic risk,
• construction or temporary closures,
• familiar landmarks and alternative routes.

Even this runner does not possess one fixed operational map. The map changes with state. A fresh runner may treat a hill as a training opportunity. The same hill can become a major cost late in the run. A route that is ideal at 6 a.m. may become unpleasant at midday. A thunderstorm can turn an open path into a bad option. Construction can remove a familiar shortcut overnight.

So the runner’s effective city is better described as:

Singapore × receiver × current state × movement capability × time.

Now replace the runner with a bee

A foraging bee leaves its hive. The physical world may contain trees, clearings, paths, buildings, water, flowers, wind, moving shadows, predators and many other objects. But the bee’s movement problem is organised differently.

• Home: where is the hive or nest?
• Direction: what celestial and visual information supports orientation?
• Route: which learned views or landmarks remain useful?
• Resource: where are rewarding flowers and how profitable are they?
• Condition: what are the wind, temperature and light doing?
• Competition: are other foragers exploiting the same patch?
• Risk: where are predators, obstacles or harmful exposures?
• Return: can the bee get home with sufficient energy and navigational information?

Research on honeybee navigation shows that bees can use different visual cues at different portions of a journey. Near the hive, local landmarks can help with precise localisation. Along a familiar route, bees can compare current visual input with learned information. Celestial cues such as the sun and polarisation pattern of the sky can provide directional information. Close to a target, short-range features can help pinpoint the destination.

The important idea is not that the bee has a human-style map. It is that its environment contains information distributed across multiple scales, and the bee can use different information when different problems become relevant.

A landmark is receiver-relative

A landmark is not simply a large object. A review of landscapes and landmarks in bee navigation argues that landmark utility depends on properties such as uniqueness, conspicuousness, stability and context. A feature that is memorable to a human may not be useful to a bee; a visual pattern humans barely notice may be highly reliable to the insect.

Landmarks also work differently by distance. Nearby features change dramatically as the animal moves around them. Distant features may remain relatively stable and support broader orientation. This gives the habitat a hierarchy: far cues can support general direction while near cues support local precision.

Distance is not the same as movement cost

Two points can be close on a map and still be poorly connected for a particular organism. A human runner may face a fence, expressway or inaccessible crossing. A bee may face strong wind, rain, a feature-poor stretch, pesticide exposure or insufficient resources to make the journey worthwhile.

This suggests an important distinction:

Geometric connectivity asks whether two places are spatially connected. Functional connectivity asks whether this receiver can use the connection under current conditions.

The shortest route is therefore not automatically the best route. Movement must be interpreted through capability, state, risk and purpose.

The habitat does some of the computational work

A city deliberately contains information that reduces human navigation effort: street names, signs, traffic lights, bridges, addresses, paths and transport networks. A forest was not designed for bee navigation, yet it still contains structured information: skyline patterns, vegetation edges, visual landmarks, odours, gradients, celestial information and resource patches.

In both cases, the agent can use external structure instead of internally reconstructing every detail of the environment. This does not make a bee and a human equivalent. Human infrastructure is culturally engineered; natural landscapes arise through ecological and geological processes. The safe comparison is functional: external information can reduce the amount of internal representation required for successful movement.

Movement changes the next observation

Movement is not only an output. It also changes what can be sensed next. A runner turns a corner and reveals a blocked path. A bee moves closer to a flower patch and gains stronger visual and chemical information. An insect flies across an edge and enters different wind, light and resource conditions.

This makes movement an information-generating process:

Perceive → move → reveal new information → update → move again.

In the language of movement ecology, the realised path feeds back into both internal and external conditions. Energy changes. Position changes. Risk changes. New cues become available. The next decision starts from a different world state.

There is no single habitat without a receiver

The word “habitat” can sound like a container: an animal lives inside a forest, wetland or city. For movement, that is not enough. The same physical place contains many overlapping operational habitats.

• A bee sees foraging patches, nest cues and flight corridors.
• An ant may experience the ground as a network of chemical, tactile and visual routes.
• A butterfly may depend on host plants, nectar sources and sunlit movement corridors.
• A mosquito may experience water containers, hosts, humidity and resting surfaces as key nodes.
• A human runner sees paths, crossings, heat, gradient and time.

The physical geography is shared. The movement topology is not.

Why the comparison matters

The runner-and-bee thought experiment prevents two common mistakes. First, it prevents us from treating a map as the environment itself. A map records selected features for a particular purpose. Second, it prevents us from treating movement as a property of the organism alone. Movement arises from a relationship between organism and world.

A more complete description is therefore:

Movement = internal state × motion capacity × navigation capacity × external world × time.

This is not a literal biological equation. It is a compact reminder that removing any one of these dimensions can produce a misleading explanation.

From movement to habitat

This article follows How an Insect Perceives Its World. The next article, Habitat as an Operational World, develops the idea that habitat is not simply an area on a map but a network of possible actions available to a receiver. After that, Landmarks, Routes, Fields and Functional Connectivity examines how graph structure and continuous environmental conditions work together.

Research sources and further reading

• Ran Nathan et al., “A movement ecology paradigm for unifying organismal movement research,” Proceedings of the National Academy of Sciences 105 (2008), 19052–19059. Open-access copy: PMC2614714.
• Thomas S. Collett, Matthew Collett and Rüdiger Wehner, research on landmark learning, route memories and path integration in insect navigation.
• Jürgen Tautz and related honeybee-navigation literature on multiple visual and celestial cues.
• “The Role of Landscapes and Landmarks in Bee Navigation: A Review,” Insects 10 (2019). Open-access copy: PMC6835465.
• Deborah M. Gordon, ecological work on collective behaviour and environment-dependent ant movement.

---

Research note: The runner-and-bee comparison is a systems analogy. It does not imply equivalent cognition. It is used to isolate a narrower principle supported by movement ecology: the realised movement path depends jointly on the organism and the external world.