Animal Behaviors

Proximate versus ultimate cause

Proximate cause: immediate underlying mechanism

Ultimate cause: evolutionary context, how the behavior increased fitness 

What is the concept of nature versus nurture (AKA innate versus learned)

• Nature V Nurture 

  • Nature 

    • Genetic basis, inherited, animal is born with it, most all of population exhibits the phenotype, innate behaviors 

      • BORN WITH (NOT BECAUSE OF EXPERIENCES) 

  • Nurture 

    • Based on environmental influences, experiences during lifetime change individuals behavior, learned behaviors 

      • LEARNED/AFFECTED OVER TIME/EXPERIENCES 

  • ** some behaviors are a combination of nature AND nurture, capacity to learn does have genetic basis 

Proximte (HOW)

• Sensory input (stimulus) → NS

  • Sensory organs, sensory cells 

• NS coordinates physiological and/or motor response 

  • May involve release of hormones (chemical signal molecules) 

  • Contraction versus relaxation of muscles 

  • Morphological adaptations may be selected for related behavior 

    • Ex: sexual selection for certain mating behaviors may lead to sexual dimorphism, etc

  • Nature versus nurture

Ultimate causes (WHY)

• Understand the behavior in the CONTEXT of evolution 

  • Get resources (food, water, territory,)

  • Avoid danger (predator, poison,) 

  • Find a mate 

  • Maintain homeostasis 

  • Conserve energy and resources 

Innate behaviors

born with it (behavior), NOT learned lifetime, developmentally “fixed”

• often related to genetics —> NOT impacted by life

  • EX: Fixed action pattern (difference in appearance because of sex)

    • Fixed action pattern: SEQUENCE of unlearned (innate) acts linked to simple environmental cue (“sign stimulus”), once initiated the behavior goes until competition, UNCHANGABLE behavior (cannot be unlearned during individuals lifetime)

Fixed action pattern

SEQUENCE of unlearned (innate) acts linked to simple environmental cue (“sign stimulus”), once initiated the behavior goes until competition, UNCHANGABLE behavior (cannot be unlearned during individuals lifetime)

What are the two types of orientation behaviors?

Kinesis: indirect orientation

Taxis: direct orientation

Kinesis

Kinesis: indirect orientation, 

• When the stimulus is absent: HIGH rate of random movement and/or rate of turning in absences of stimulus 

  • Increase chance of finding food, higher change will randomly move into area w/ food, then respond with negative kinesis

• When the stimulus is PRESENT: DECREASED rate of random movement and/or turning, movement may completely stop

  • On average animals end up spending more time near the stimulus

Taxis

Taxis:”direct orientation”

• Direct movement towards (+) or away (-) from stimulus 

• Point A to point B → oriented intentionally to or away from stimulus 

  • EX: Photosynthesis, a plant will move TOWARDS light

Biological Rythms

Biological Rhythms: behavioral and physiological response that exhibit time periodicity 

• Controlled by a combination of genetics (rhythm or clock genes exhibit an inherent timed cyclical gene expression) and environment (environmental cues calibrate the “clock” shifting the timing of the cyclical expression backwards or forwards,

  • Ex: lunar cycles, circadian rhythm

Intraspecific versus interspecific

Intraspecific/conspecific: same species

Interspecific: Different species

Examplesof stimuli/signals

Pheromones, visual, auditory, tactile (touch)

Learned behaviors

Specific experiences during the lifetime of the individual that modify the behavior (AKA “nurture”, involves formation of memories that involve changes in neuron-neuron connectivities, still has a genetic component (nature) in that the organism has the capability to make memories 

• EX: Associative learning

Associative learning

An EXAMPLE of learned behaviors

Associative learning: Learning to associate two aspects of the environment with each other 

• EX: learning that two events happen together like classical conditioning

Classical conditions

Example of associtaive learning

• Learning to associate a new/neutral stimulus with an existing involuntary behavior

  • EX: Pavlov’s dog

Imprinting

• Establishment of long-lasting behavioral response to a particular individual object 

  • Particular individual object → learned, based on experience, “nurture” 

• Can only be learned during a sensitive time period early in life then irreversible 

  • Sensitive time period → pre-determined by genetics, “nature”

Habituation

• With repeated exposure to the same stimulus an animal ceases to respond to the stimulus

• Simple form of learning 

  • Ex: gill withdrawal behavior in sea slugs, keep poking = stop withdrawing the gills

    • Evolutionary advantage to this learning → conserving energy and resources, allows response to new/more significant stimuli 

Spatial Learning

• Animals learn where objects are in relation to each other

• Navigation cues remembered 

  • Ex: sun, moon, etc acting as geographical markers

Cognition

• Ability of nervous system to acquire knowledge and understanding through thought, experience, and sensory input 

• Most complex form of learning 

• EX: problem solving, social learning 

Foraging behavior

Foraging behavior: behaviors related to searching for, recognizing, capturing and eating specific foods

• Optimal foraging model: foraging behaviors determined by the cost of obtaining food versus the benefits of nutrition 

Agonistic behavior

Agonistic behavior: Ritualistic antagonistic behaviors, -/- intraspecific interactions threatens/aggression/submission often due to competition for resources or mates

Cooperative behavior

Cooperative behavior: +/+ intraspecific behaviors, many evolutionary advantages (ex: better access to resources, mates, parental care, better defense) 

Altruism

Altruism: Sacrifice individual fitness to increase the fitness of others in the population, explained by concept of inclusive fitness 

• With respect to YOUR genes passed to the next generation, if relatedness coefficient x number of offspring left to the next generation is GREATER THAN the cost to individual for behavior and/or risk of death = altruism is favored 

  • BASICALLY: you want to increase the passing on of your genes so you want to protect the pack (which shares your genes)

Plant Tropism (4)

Directional growth (may be observed as bending towards or away from a stimulus), proximate cause is differences in cell length during growth (w/ v w/o stimulus)

• Phototropism: stems and leaves grow TOWARDS the light (positive phototropism) versus roots grow AWAY from light (negative phototropism) 

• Gravitropism: stimulus is earth's gravitational pull, stems and leaves grow upwards (positive gravitropism) or roots grow away/downwards (negative gravitropism) 

• Thigmotropism: Stimulus is touch/pressure (towards = positive, away = negative) EX: vines which grow towards touch (positive) 

• Gnostic (sudden) movements:  sudden movements 

Circadian Rythm (in plants)

• Plants also have circadian rhythms

  • Photoreceptors sense photoperiod, day v night length is measured, regulation of daily and seasonal responses 

Plant responses to herbivory (example)

• Constitutive: trait is expressed at a constant level 

• Induced: trait “turned on” or increased in response to the stimulus 

• SOS response 

•  Touch or injury to plan causes an SOS signal molecular synthesis and release, the SOS signal molecule induces herbivory defense mechanisms in injured plants AND in neighbor plants (plant communication)

  • An example of PHENOTYPICAL PLASTICITY 

  • EX: activation of chemical defences, activation of building of physical defence structures 

    • EX: Plants communicate with each other through symbiotic fungal networks

Herbivory

the ecological interaction where an animal (herbivore) feeds on living plant material, like leaves, fruits, roots, or seeds

Sexual selection for certain mating behaviors…….

may lead to sexual dimorphism

Kinesis

“Idirect orientation”

No food/stimulus = lots of crazy movment (randome movment)

—> basically looking for the food

• increase chance of finding food

  • higher chance will randomly move into

  area w/ food, then respond with

  negative kinesis

Food/stimulus = chemical signal molecules are recieved as input, decreased rate of random movement/turning, OR movement could completley stop

• on average, animals end up spending

  more time near the stimulus

Taxis

“Direct orientation”, like taking a taxi from point a to point b

• DIRECTED movement towards (+) or away from (-) stimulus

  • Ex: photosynthesis where an organism moves towards the light/sun

  • Survival: Directed movement (taxis) towards food, mates, or favorable conditions (e.g., light, chemicals) improves fitness.

    Predator Avoidance: Moving away from chemical signals of predators (negative chemotaxis) increases survival.

    Finding Resources: Positive chemotaxis guides organisms like E. coli toward nutrients.

Animal communication examples (HOW)

Types of stimuli/signals include

• pheromones

• chemical signal molecules (hormones) secreted outside body

that affect the behavior of another individual

• individual 1 ➜ individual 2

• visual

• auditory

• tactile (touch)

Animals communicate………

• courship/attraction of mates

• communication of geographical location

• social order

• territorial marking

Population versus sample

Population: ALL individuals or obersvations possible

Sample: used to represent/test population, a smaller finite amount that you can do an experiemnt on

** Ideally the sample is a true representation of the ENTIRE population

Descriptive statistics

Describe a sample or population, includes measures of central tedency AND measures of variability

3 Examples of measures ot central tendency

Mode

The mode is the value that occurs most frequently in a sample data set. If no value is repeated, there is no mode for that data set.

Median

The median is the middle value that separates the greater and lesser halves of a sample data set.

Mean

• Calculated by summing the values of the individual

measurements in a data set (x1 + x2 + x3 ... + xn) and then dividing by the number of individual measurements or sample size (n).

• The “true mean” is the mean of the entire population, the mean of the sample is referred to as the “sample mean”.

—> Ideally, the sample mean accurately and precisely estimates the true mean.

Normal Distribution

• tendency in many samples individual measurments cluster symmetrically around the mean

  • some can fall behind the mean, some can fall higher than the mean but most fall around the mean

• when graphed = displays “normal distribution”/”bell curve”

• When a data set exhibits a normal distribution, statistical measures such as standard deviation

  and standard error of the sample mean can be applied.

The area under the histogram curve represents the total #

of observations.

• This area under the normal distribution curve can be

divided into +4 quartiles and -4 quartiles flanking the

mean.

• For SD, this corresponds to mean +/- 4 SD units (Fig. 2).

Note the 4th quartiles (+4, -4) are often not shown in

normal distribution graphs.

• Variation or scatter around the mean can be reported as

mean +/- SD units. Interpretations are as follows:

o ~68.2% of observations fall within mean +/- 1 SD unit

o ~95% of observations fall within mean +/- 2 SD units

o ~99.7% of observations fall within mean +/- 3 SD units

o ~100% of observations fall within mean +/- 4 SD units

Range

Largest observed value - Smallest observed value

Variance

• Variance is a measure of the psread of the data in a sample

• used to calculte SD

• To calculate…

1. Find the deviation of each individual value from the mean.

2. Square each deviation.

3. Find the sum of the squared deviations.

4. Divide the sum of the squared deviations by (n-1), where n is the number of individuals in the data set or the sample size.

VARIANCE IS MEASURED IN SQUARE UNITS OF THE ORIGINAL DATA!

Standard Deviation (SD)

SD, represented by “s”, is a statistical measure that indicates how far from the sample mean the individual observations in a data set ypically are (i.e. the mean of the deviations from the mean).

• SD reflects average variation from the sample mean and does not take sample size into account.

• SD is calculated by taking the square root of the variance for a data set.

The units of SD are the same as the units used for original data.

Standard Error of the Sample Mean (SE or SEM)

• SE is a statistical estimate of how precisely the sample mean estimates the true mean of the population.

• SE takes into account both SD (scatter) and sample size.

• To calculate SE: divide SD by the square root of the number of individuals in the sample (n).

• The larger the sample size = the better the sample mean estimates the true mean. This is reflected in the SE calculation since, as the sample size (and hence denominator) increases, SE decreases, indicating less uncertainty about the sample mean being representative of the true mean.

• Since SE does take sample size into account, it is often preferable to report SE as opposed to SD.

• By definition, the SE will always be smaller than the SD.

Similar to SD, the units for SE are the same as the units used for the original data.

Confidence Interval (CI) and the “68.2-95-99.7 rule of thumb”

Often, we want to know how confident we can be that the

true mean of the population falls within a certain range

around the sample mean.

• SE can be used to calculate the CI. Often SE is directly used

as a good estimation of CI.

• The “68.2-95-99.7 rule of thumb” applies for CI.

o mean +/- 2 SE units estimates the 95% CI

• The 95% confidence interval is the interval in which you

can be 95% certain the true mean of the population falls.

• The CI tells you how precisely your sample mean represents

the true mean of the population.

Null hypothesis v alternative hypothesis v research hypothesis

Null: predicts NUMERICAL data base on known porbabbilities, may state the IV has NO Effect on the DV

Alternative: Different from Null, may state IV does have a certain effect on DV

Research Hypothesis: your prediction, may be the same as the null or an letnertaive hypothesis

• BE SUPER SPECIFIC

Steps to calculate the chi square value

To calculate the Chi-square value, you find the difference between your Observed (O) data and Expected (E) data for each category, square that difference, divide by the Expected value, and then sum these results across all categories, using the formula \(\sum \frac{(O-E)^{2}}{E}\) to get your final statistic, which indicates how much your actual results differ from what you'd expect.

What are degrees of freedom

#categories - 1

What is p-value

measures the strength against the null hypothesis

• smaller p value means stronger evidence AGAINST null hypotheisis

• in science… p > 0.05 is taken as acceptable deviation from the expected result

  • 5% porbbility tht the difference between expected and observes id due to chance

  • p<0.05 the DIFFERENCE betweeen observed and expected data is SIGNFICANT

  • p > 0.05 the DIFFERENCE between observed and expected data is NOT SIGNIFICANT

When stating final conclusion (with chi square/null hypothesis)…

• state p-value cut off being used

• stste degree of freedom AND critical x² for it

• state wether the calculated x² is greater or less athen the critical value for the experiemtn AND state what it means

• Caclaulte chi square is LESS than critical value = the difference between observed and expected is not expermient, FAILL TO REJECT

• Caclulated X² value is GREATER than or equal to the critical x² value - the difference between observed and expected is SIGNIFICANT, REJECT null hypotheiss, consider an alternative hypothesis

Less than (or equal to) critical value -

More than critical value -

NO SIGNFIICANT DIFFERENCED BETWEEN O AND E = ACCEPT NULL

SIGNIFICANT DIFFERENCE BETWEEN OBSERVED AND EXPECTED = REJECT NULL