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Social organizations:

• Solitary

• Pairs

• Family groups

• Herds/Flocks

• Complex societies

Complex societies/Eusociality, social organisation

• The highest level of social organization

• Overlapping generations within a colony of adults

• Division of labour into a caste system:

  • Single reproductive female (queen)

  • Sterile workers

  • Drones (male)

  • Soldiers

• Cooperative care of brood

Costs and benefits of living in a group

Costs:

• Greater conspicuousness

  • Easier to see a big group of animals

• Competition

  • Food sharing

  • Dominance disputes

• Disease transmission

• Reduced reproductive fitness

  • Infidelity

  • Inbreeding

  • Infanticide

Benefits:

• Reduced predation risks

  • “Many eyes” effect

  • Confusion by blending in

• Information sharing

• More reliable access to mate

• Increased success in accessing food

  • Ability to take down larger pray

  • Ability to mob larger predators of kills

• Shared rearing of offspring

• Energy conservation

  • I.e. huddling together

The selfish herd

• A theory based on the assumption that predation risk is not evenly distributed across positions within a group

• Individuals within a population attempt to reduce their predation risk by putting other conspecifics between themselves and predators

Edge effect

• Higher exposure to predation risk at the edge of a group

• Creates competition for good positions

• Consider motivation vs. risk (e.g. hunger)

• Part of the selfish herd theory

• Position is affected by: social status, age, health, food motivation, reproductive status

Domain of danger

A key element in the theory is the domain of danger, the area of ground in which every point is nearer to a particular individual than to any other individual

Social networks

• Animal social networks are descriptions of social structures

• Networks consist of nodes connected by edges

• Consists of nodes and edges

Centrality, social networks

A measure of an individual’s structural importance in a group based on its network position

Degree centrality, social networks

• Based on the number of direct edges an animal has

• An animal with more edges (degree node) will have more influence on those around it and possibly on the whole network (e.g. disease transmission)

Direct edges, social networks

A focal individuals immediate connections

Indirect edges, social networks

A focal individuals connections with individuals through other individuals

Bridges, social networks

Some individuals (nodes) serve as bridges in or between networks (node B)

Dominance

• A social relationship reducing conflicts

• Determines priority access to contested resources

  • mating opportunities, food, shelter

• Not a personality trait, rank can change

• Only applicable within a species

Signals and dominance

• Can provide information about rank or fighting ability and helps in the establishment of dominance hierarchies

• Can signal dominance, individual identity and fighting ability

A few examples of how rank is earned:

• Signals

• Age (birds born in succession)

• Inherited rank

Affiliative

Relating to forming social and emotional relationships with others, or to the feeling of wanting to form these relationships

Tit for tat

• Cooperate on the first move, then copy what the opponent did on the last move

• Works because defection is punished immediately, but can also be forgiven if the defector corrects

• Cooperation between non-relatives can be favoured when individuals are likely to interact again

• Conditional cooperation that tracks a partner's recent behaviour

Kin selection

• When natural selection favours a trait due to its positive effects on fitness of an individual’s relatives even when this process comes with a cost to the individual’s own fitness

• Helping behaviour is favoured by selection whenever the relatedness-weighted benefit exceeds the cost to the helper (Hamilton’s rule)

• Kin selection explains how altruism evolves because relatives share a portion of the same genes

• Example: Ground squirrels emit loud warning calls to alert others of approaching predators. This behaviour puts the caller at a higher personal risk of being spotted by the predator, but it saves nearby family members.

Cooperative breeding

• When an individual, a helper, foregoes its own reproduction to help raise the young of others. Most often the helper is related to the young

• Why help?

  • Kin selection

  • Habitat saturation/fragmentation

  • Reliable food supply

  • Succession for breeding opportunity

• Cooperative breeders are disproportionately found in regions with high climatic variability and unpredictability – adaptive strategy

Hamilton’s rule

r × B > C

• r relatedness of helper to recipient

• B fitness benefit gained by the recipient

• C fitness cost to helper

Different kinds of eyes

• Pupils

  • Can be round and expanded

    • e.g. humans, birds

    • 180 degree visual field with mostly overlap/depth perception

  • Narrow —> round

    • e.g. cats, dogs

    • Better at adjusting their size

    • Broader visual field with more narrow overlap

  • Horizontal

    • e.g. horses, goats, sheep

    • Very broad visual field (almost 360 degrees)

      • Horses still have 65-80 degree frontal overlap, just like canids.

    • Additional “white fingers” that stick out/forwards of the eye to block sunlight (the shade from this can be visible)

  • “Dots”

    • Very small dots turning into covering the entire iris (basically)

    • e.g. gecko, tarsier

Mammal eye

• Cornea

• Lens

• Iris

• Ciliary muscle

• Zonule

How does the mammalian eye work?

Ciliary muscle is a “circle” around the iris, “attached” through the zonule.

• When the ciliary muscle contracts, the zonule become relaxed and the lens becomes rounded to focus on close objects

• When the ciliary muscle relaxes, the zonule taut and flattens the lens to focus on more distant objects

Fish eye

• Spherical Gradient Lens

  • (Lens doesn’t change in shape ?)

• (Retractor/Protractor Lens in some species)

Reptile eye

• Bony ossicle

• Brucke’s muscle

Bird eye

• Bony ossicle

• Brucke’s muscle

• Crampton’s muscle

How do reptile/avian eyes work?

Active changing of the lens, actively pressing to change the shape

In birds, you have the additional Crampton’s muscle to change the size of the cornea

• Diving birds also use it as a surface for water (?)

Amphibian eye

• Protractor lentis

How does light reach the retina?

Light must go through all layers of cells before reaching the photoreceptors

• Light might “change”/reflect throughout this journey

Cones vs rods

Cones see colours and are more “angular” in shape ( > )

Rods are bigger and more light sensitive, have more pigment, and are rod shaped ( ニI )

Explain eyesight (?)

Light must go through all layers of cells before reaching the photoreceptors

• Light might “change”/reflect throughout this journey

When light is absorbed, there is a hyperpolarization

• (not depolarisation as in other processes)

• In the relaxed state, you have a lot of neurotransmitters. When light is absorbed, you get less neurotransmitters.

• “It is only the outer segment that is light sensitive, A larger outer segment can absorb more light

Ganglion cells

Ganglion cells are the last step before the signals are sent to the brain.

• When densely packed, there are less photoreceptors

• = think of them as pixels. When they are smaller (and more) we can see finer details

• Packed areas of ganglion cells is called the fovea

Fovea

Where the ganglion cells are the most packed

• in humans, this area only consists of cones (not rods)

• Horses, wolves, hares etc have rods as well in their fovea

• Most birds have 2 fovea in each eye (other species only have 1)

Correlation between domestication and vision in dogs ?

• Dogs with more “wolf-shaped” nose have a broader area of ganglion cells

• In pugs (and other dogs with flatter noses), they have a very small but very “good”/Intense? spot — just like humans    

  • This spot is called “area centralis”

• Similar pattern in horses

Spatial resolution

• Measure of how closely lines can be resolved in an image

  • (e.g. black-white stripes. One black-white is one cycle. Measured as “cycles per degree (at a certain distance)”)

    • dvs how many degrees could one’s eye detect?

• Is sacrificed in dim light

  • Spatial resolution becomes worse in darker environments

Temporal resolution

• “shutter time”

• Photoreceptors can only code information up to a certain temporal frequency

• Cones are generally better than rods to discriminate fast movements.

• Imagine a fan:

  • With short shutter time, you can see each individual blade

  • With long shutter time, you see it all as a blur

• Sacrificed in dim light

Explain how color vision works

• Colour requires two or more cone types

• The reflected light from a surface enters the cones and the brain considers which type of cone absorbed the most amount of light, compare them, and then the brain makes us perceive a certain colour based on the cones that absorbed the light.

• An absorbed photon has no “identity”, it’s just what cone absorbed it

  • Colour is just a hallucination

Ancestral cone photopigments

Most animals have the four ancestral cone photopigments

As mammals, we lost two of these four due to the nocturnal history from the dinosaur ages and whatnot

• Primates have created a new third one 30 million years ago (unrelated to the four ancestral ones) to experience red colour

Neutral point

Dichromatic visioned mammals have a so-called “neutral point” where they cannot discriminate grey shades from a green-blue shade at 480nm.

Ways to improve night vision in dim light

• Enlarge pupils

• Enlarge eyes

• Short focal length

  • Shorter distance = less “disturbance” —> clearer image

• Summation in space and time

  • Can extend visual range down to intensities 100 000 dimmer than provided by optics itself

Discuss colour vision in dim lights

Horses, despite having large eyes + tapetum lucidum, they cannot distinguish colours in darkness due to their vision being mostly based on rods.

Nocturnal helmet geckos can see colours in dim light when we can’t.

Several bees and hawkmoths can see colours at night.

Decline effect

• Effect sizes shrink systematically in follow-up studies

• Early studies of a phenomenon report large, striking effect sizes. Follow-up studies tend to report smaller effects. Over many replications, estimates regress toward the true (usually smaller) value. This is the expected consequence of publication bias plus small initial sample sizes.

• Currently the field has many studies on similar questions but few close replications. This makes it difficult to separate methodological variation from true biological variation.

P-Hacking is:

• Collecting data, or conducting statistical analyses, until a non-significant result becomes significant

• Driven by the pressure to produce positive findings rather than by the data or the research question

How p-hacking occurs:

• Stopping data collection to early

  • Ending data collection the moment p < 0.05 is reached, before pre-specified sample size

• Collecting data until the p-value is significant

  • Conducting multiple experiments; reporting only the one that worked.

• Cherry-picking outcomes

  • Measuring many variables but only reporting those that reach significance.

• Tweaking the data

  • Post-hoc decisions on outlier removal or data transformation to achieve significance

• Doing multiple comparisons without corrections

  • Performing many tests without correcting for family-wise error rate

Type I errors

Untrue significant results (false positive)

Type II errors

Untrue non-significant results (false negative)

HARKing is:

• When a hypothesis is invented after the data collection and results, and presented as if it was pre-formulated

• Makes a chance finding look like a prior prediction

• You’re pretending to have tested for something that was just a chance finding

Why is HARKing problematic?

• Inflates false-positive

  • p = 0.05 means there is a 5% probability that your results occurred by pure random chance. If you run 20 independent tests at α = 0.05 and report the best one as a "prediction," your actual false positive rate is closer to 1 − 0.95²⁰ ≈ 64%, not 5%

• Results cannot be replicated

  • Because results are post-hoc justified they are unlikely to replicate in a study with new data. Entire research fields can be based on non-replicable results. Researchers will spend time and money trying to replicate findings that cannot be replicated.

• Invisible in publications

  • Readers cannot detect HARKing from the published paper alone. Peer review cannot catch HARKing without access to study logs

Publication bias

Positive findings are far more likely to be reported than null or negative results - regardless of scientific value

File-drawer effect

• Direct consequence of publication bias

• Null results are not written up, submitted or published

How can you detect publication bias?

• Using a funnel plot

  • A funnel plot is a scatterplot used in meta-analyses to visually detect publication bias. It plots individual study effect sizes against a measure of precision (like standard error)

• No Publication Bias: The plot resembles an inverted, symmetrical funnel. The larger studies cluster tightly near the center, while smaller studies spread out equally on both sides. This indicates that all studies, regardless of their positive or negative results, had an equal chance of being published.

• Publication Bias: The plot is assymetrical. This usually means that small studies with negative, nonsignificant, or unfavourable results were left unpublished (the "file drawer effect"), while small studies with positive, statistically significant results made it to publication.

Types of replication

• Close replication

• Conceptual replication

Both types of replications are needed but close replications are rare. Currently the field has many studies on similar questions but few close replications. This makes it difficult to separate methodological variation from true biological variation.

Close replication

• Repeats the original study using the same species, setting, protocol and sample size

• Rare

Conceptual replication

Tests the same hypothesis with a different design

How can we improve the reporting in academia

• Pre-registration of hypotheses

  • Register hypotheses, design, sample size, and analysis plan on repositories before collecting data. Eliminates HARKing and reduces p-hacking.

• A Priori Power Analysis

  • Calculate minimum N needed to reliably detect an effect of the expected magnitude before starting. Prevents underpowered studies, which inflate effect sizes and produce unreliable results.

• Open Data & Materials

  • Raw data, analysis scripts, and methods should be provided with the paper. The environmental confound in Hare et al. (2002) would have been easier to detect if the full protocol had been openly accessible.

• Replication Studies

  • Actively conduct and publish close replication studies using the same species, same protocol, but from independent labs. Laskowski et al. (2026) describe a dedicated journal section for exactly this.

• Report All Results

  • Report null results, failed conditions, and unexpected findings, not only p<0.05 outcomes. Reduces the filedrawer effect. Krause et al. (2018) explicitly name this as a priority for the animal pointing literature.

A good research question…

• Uses defined terminology

• Can be answered by your study

• Clarifies what you would measure, in which species, at what age, or under what conditions

• Can be falsified

“The first and most consequential decision in any study is choosing the right question at the right level of explanation. Tinbergen's framework provides guidance.”

Tinbergen's Four Questions (short)

• Mechanism

  • How does it work?

• Development

  • How does it develop?

• Function

  • What is it for?

• Evolution

  • How did it evolve?

All four questions matter

• No single question sufficiently describes the complexity of animal behaviour

• Proximate and ultimate explanations are complementary - not competing

• A behaviour’s function (e.g., to find a mate) is fundamentally different from its mechanism (i.e. the hormones that trigger it)

• Animals are not static organisms - they develop over time and are constantly influenced by the environment. A single mechanistic rule cannot adequately capture why animals behave the way they do.

Innate behaviours

behaviours that are not changed by learning

Tinbergen's Four Questions: Mechanism

• Causation

• What underlying mechanism causes the behaviour?

• Which stimuli elicit the behavioural response?

• A mechanistic question asks what internal states and external stimuli produce the behaviour. It can be addressed by measuring hormones, neural activity, or the stimuli that trigger responses.

Tinbergen's Four Questions: Development

• Ontogeny

• How does the behaviour change with age?

• Is development of the behaviour affected by environmental factors?

• A developmental question asks how behaviour presents across the lifetime. It can be addressed by comparing individuals at different developmental stages or with different early experiences.

Tinbergen's Four Questions: Function

• Adaptive value

• What is the (current) function of the behaviour?

• How does the behaviour affect survival and reproduction?

• A functional question asks what the behaviour does for the animal. What is its effect on survival and reproduction? It can be addressed by estimation of fitness.

Tinbergen's Four Questions: Evolution

• Phylogeny

• How did the behaviour evolve?

• Which species share the behaviour, and did it evolve once or multiple times?

• An evolutionary question asks where a behaviour came from, which species share it, and whether similarities reflect shared ancestry or independent evolution. It can be addressed by comparing genetic expression, phylogenetic analyses etc.

Ultimate vs proximate explanations

Ultimate

• Function & Evolution

• “Why”

  • Why does the organism do is?

  • Why did it evolve?

Proximate

• Mechanism & Development

• “How”

  • How does it work?

  • How did it develop?

Hypothesis vs prediction

Hypothesis: A proposed explanation for an observed behaviour. A hypothesis should always state WHY.

Prediction: What you would observe in your data if your hypothesis is true. States WHAT the results will look like.

• One hypothesis can generate multiple predictions

• One prediction can be consistent with multiple hypotheses

• If a prediction fails the hypothesis is challenged

• If a prediction succeeds the hypothesis is supported, but not proven - other hypotheses may make the same prediction (i.e. there may be other explanations for the behaviour you observe)

Example:

Observation: Male long-tailed widowbirds have tails far longer than needed for flight. We suspect this might be driven by female choice (a behaviour driving sexual selection).

Hypothesis: Tail length evolved through female choice with females preferring longer-tailed males, and this preference drives exaggeration of the trait over evolutionary time.

Two predictions: 1. Males with experimentally elongated tails will attract more females than controls. This prediction supports the hypothesis. But are there any alternative explanations? 2. Tail length will not correlate with territory size. This prediction rules out that females prefer resources, not tails.

Use the lecture slides for Research Questions to practice writing good hypotheses and predictions

Motivation and decision making

Different motivations can strongly affect decision making

What can affect motivation

Motivation fluctuates through time and life history stages

• Hormones

• Age

• Biological sex

• Time of day

• Season

• Climate

Homeostasis

• The maintenance of a stable state of internal physical and chemical conditions within narrow optimal ranges by living organisms

• Involves many things, including: o Blood pH o Core temperature o Blood glucose and oxygen levels

How is homeostasis maintained?

• Homeostasis maintains stability through negative feedback

• The behavioural response is reactive – it occurs as a reaction to a deviation from homeostasis

Allostasis

• Stability through change

• Process by which animals actively adjust their internal state to meet predictable and unpredictable demands

• Allostatic parameters allows for dynamic shifts in parameters to match needs to eventually return to homeostasis

• Examples of allostastic adjustments:

  • The increase in heart rate and blood pressure during physical activity

  • Elevation glucocorticoids before a breeding season

• Why this matters in the context of motivation: not every rise in a hormone or a drive reflects a deficit being corrected — some reflect anticipation of a demand

Allostasis and motivation

STABLE STATE vs ADAPATBILITY

• Homeostasis: Fixed set points within a narrow range

• Allostasis: Dynamic set points that can adapt to changing demands

• Allostatic responses can be predictive, i.e. changes occur before deviation from a set point occurs

• Example: You watch a movie and anticipate that a scene will be scary – your pulse goes up

Allostatic load

• The cumulative cost to the body of allostasis

• All animals experience acute daily and seasonal stressors that they need to cope with. However, when stressors are repeated too often, there can be “wear and tear” across multiple somatic systems, which can lead to chronic stress

  • Can lead to an altered set point

Measuring motivation

• The cost and animals is able to pay to gain access to a resource can tell us about its motivation for this specific resource

  • Preference tests with costs

    • Can measure:

      • How flexible the animal is in its motivation for this resource

      • Resource value

      • Maximum cost paid to get to the resource

Displacement activities

• A normal behavioural pattern that appears out of its usual context

• Expressed when motivations compete, or a motivated act is hindered

• Ex: redirected behaviour, intention movements & ambivalence

Redirected behaviour

The correct behaviour is directed at the wrong object

Intention movements

Suboptimal or fractions of the correct behaviour

Ambivalence

Combination of intention movements from both conflicting motivational systems (e.g. approach and retreat)

Stereotypic behaviour

Repetitive, functionless and often damaging behavioural pattern

• Stereotypic behaviour is most often a response to chronic stress, frustration or an inability to continued perform natural behaviours

• Stereotypic behaviour is not necessarily a displacement activity but a repeated state of motivational conflict can lead to the development of stereotypic behaviours as a coping mechanism

• Even if an animal is taken out of the situation in which it is not thriving the stereotypic behaviour often persists

Judgement vs decision making

Early decisions can modify subsequent judgments, which in turn can modify subsequent decisions

How to differentiate between lack of judgement and decision not to act in a behaviour study?

Potential solution – add additional measures to your set up:

• Physiology

• Neurology

• More behaviours

State-dependent decision making

• Energy reserves affect the decisions made by educated predators foraging on defended prey

• Higher motivation leads to more risk taking

Aposematism

An advertising defence strategy where an animal uses bright colours, bold patterns, distinctive sounds, or strong smells to warn predators that it’s toxic, venomous, or tastes bad

Designing a study with motivation in mind

• Separate motivational strength from loaded or andromorphic terms

  • “worked hard for it” is not the same as motivation

• Control for and report deprivation/energy state before testing

  • it confounds tests involving food

• Some animals are just less food motivated

  • will this influence your test?

• Watch for general activity and arousal masquerading as a specific motivational or decision effect

  • Is your focal animal affected by the test situation itself? Something secondary in its environment? Or internally not related to your research question?

• Watch for displacement activities being mistaken for the trait you are actually measuring

Ethogram

• A written inventory of behaviours in a species’ repertoire

• Can be partial or complete depending on the research question

• Should be based on pilot observations

Classifying behaviours in an ethogram

• Descriptive/Structural: “Nose is pressed or close to the ground (less than 10 cm) with jaw muscles moving”

  • Can sometimes be too exclusive and detailed

• Functional: “Feeding”

  • Can sometimes be too broad

Behavioural categories for an ethogram

In order to quantify behaviour we have to divide them into categories. These categories should be:

• Mutually exclusive

  • There can be no overlap between behaviours. Each observation fits only one category

• Objective

  • Describe what you see, not what you think it means

• Reliably measurable

  • Can a stranger use the ethogram without instructions?

• States vs Events

  • Distinguish between behaviours with duration (states) and instantaneous behaviours (events)

Events

• Classification of behaviours

• Relatively short duration

• Typically low variance in duration

• Usually measured in frequency of occurrences

Common pitfalls when making an ethogram

• Anthropomorphism

• Categories that are too broad

• Categories that are too narrow

  • Unnecessary detail makes coding impossible in real time.

• Overlap between categories

• Assuming universality

  • Always validate your ethogram for your specific species and context – even across populations of the same species behaviours might differ.