Course admin

(a) Mating territory

- defend mating stations

- e.g. prairie grouse

- attract or control access to mates

(b) Breeding territory

- mating and rearing

- feed outside territory

(c) Feeding territory

- defense of food resource only

- difficult to demonstrate

(d) Multipurpose

-most common

- provides all necessary requisites for survival and reproduction

(2) PARTICIPATION LEVEL

(A) Individual

- feeding/mating

(B) Pair

- usually breeding/multipurpose

- occupied by both sexes and offspring - defense by male or both

(C) Group

- mammals (monkeys, lions)

- occupied by group - Kin

- defense by any member of the group.

STRUCTURE OF TERRITORIES

(1) Boundaries & Size

- not fixed

- territory can vary in size and shape over a season

- Size affected by

(1) species specificity

(2) function of territory

(3) body size of animal (positive correl)

(4) food habits (predators - larger territ)

(5) age

(6) population density (negative corr)

(7) predator pressure (negative corr)

(8) food abundance (negative corr)

- but territory - compared to only certain minimum size

- rel. to owners readiness to fight

(2) Advertising Boundaries

- territory advertisement

- form of threat beh.

- low I

Modalities

(A) visual - prominent display

- can use - landmarks

- specific movements

- body posture

(B) acoustic - vocalize at edge of territory

- recognition

(C) olfactory - scent marking

- can mark with

(a) metabolic by products (feces, urine, saliva)

(b) specialized secretions

- cutaneous scent glands

(D) electric

- some mormyrid fish

but whether a territory or not, decided by scent, song etc

- proximate questions

Why have certain rules evolved in each

- need to go back 40 yrs

Brown (1964)

- idea of economic defendability

- annual - spend time & in defence

if benefit > alternate behav.

- affected by resource distributed in space & time

(1) space e.g. ants

- Weaver ant - food source - insects in veg.

- uniform distribution over space

- stable over time

defend large 3-D

- several nests of 1 colony distribute through territory

- Harvester ant - food patchy (seeds on ground)

- stable over time

- 1 nest - defended

- traits to new food sources

- Honey ant - food - termites under

- patchy in space & time

not fixed territory - defend resource

economics of territory defense

- if benefits increase

- optimum territory size - lower

- if costs increase

- optimum territory size - lower

Currency

- meaningless to talk about territory optimality

- without defining what is meant by ‘optimal’

i.e. - need to know ‘currency’

- max net C intake

- max net nutrient intake

- minimize daily variation

currency can vary over season or life and affect where animal lives on curve

e.g. if animal wants to put on for a migration - exist at max.

e.g. if animal ‘wants’ to maintain constant weight by minimizing costs

- exist at minimum

other currencies

- decrease chance of predator

- number of mates that can be attracted

- time scale - variable - case-by-case

Look at a couple of case studies of territory economics

(1) humming bird

- breed in NW of N. Amer.

- migrate to winter grounds - Mexico

- migration

- series of flights between alpine meadows

- set up feeding territories

- gain weight

some conclusions and observations

(1) track

day 1 - 25 flowers in meadow - no birds

day 7 - 3200 flowers in meadow - 15 territ.

(2) individuals make adjustment for flower density

- 100 fold variation

(3) if adjust territory to maintain a constant resource level

- expect a straight line on a log-log plot of territory size and flow density

- also - there is experimental evidence

- if remove flowers - birds incr. territory size to compensate

(4) also found (a bit of a lesson on currency)

- not just defend a constant number of flowers but adjust for flower quality

e.g. Indian paint brush - nectar vol = X

Columbine - vol = 4X

- here - case of territoriality which closely agrees with prediction

Pied wagtails

Territory owner

- patrol sides of streams looking for insects washed up on shore

- cropped resource at “profitable” removal time

- non-territory owner - flocks

- individuals try to get into territory

- very unprofitable

- feeding on depleted areas

- but didn’t adjus;t territory to match food supply

- instead - adjusted to abundance by

(1) change beh. to intruders

(2) varying amount of time on territory

how

(1) low food abund.

- fed elsewhere but returned to defend from intruders

(2) intermediate food

- all day on territory

- evict intruder

(3) high food level

- share territory with one other

- usually juvenile or female

- cost - share food

- benefit - share defense

(if food dropped - satellite evicted)

(4) very high food

- no attempt to defend

- feeding ratio not affected by others.

Predation Foraging & Prey

- all animals - acquire food for

all are either predator or prey

- role can change

want to look at 3 aspects of this in next 3 lectures

(1) decisions made by animals on acquiring food

(2) behaviour employed in collecting food

- including social organization

(3) antipredator techniques

Decisions

when looking at how an animal should go about being a predator

Biologist - look at OPTIMALITY THEORY

Optimality models

- predict what an animal should do (course of action) under a specific set of conditions to maximize its fitness

- compare predicted to expected

3 parts

(1) decisions - strategies available to the animal - that it can choose

e.g. eat food a or food b

(2) Currently (already talked about this)

- criterion upon which decision is made

- might want to maximize intake

- choice of current

- great eff. on outcome of model

(3) Constraints

- limits of the animal

- structure

- energetic

Final consideration

- can’t expect models to be perfectly optimized

- haven’t considered all possible

Foraging Models

- what are the rules for animals finding food

Two major types of models

(1) diet selection or prey models

(2) patch models

Diet selection models

- ideas about this first were considered

-when it became obvious that

- predators were not eating food just as it was available

e.g. owls - searching for and eating rodents - in N.J.

- voles - 5% of found

- 70% of diet

- obviously not being eaten in proportion to abundance

Therefore need to look at other parameters

therefore might do something like the following

Scenario: (predator) forager looking for food

- finds 1 prey at a time

decision: should it eat the prey it finds or continue searching

currency: rate of intake

- maximize

constraints: prey need to be processes (handled) - handling time

: can’t handle and search at same time

To model this

say there are 2 prey types 1 & 2

- provide different amounts of

i = energy in any prey type

1 = energy in prey 1

2 = energy in prey 2

and hi = handling time for any prey type

h1 & h2

if want to maximize intake

can consider profitability

- ratio of intake: handling time

i = profitability of prey

hi

if define prey, as most profitable the

1 2

____ > ____

h1 h2

- complicate matters

- each prey has to be found

and so.. have to work in a search time (which costs )

S1 & S2

Final assumption

- predator knows all this

Now imagine a searching animal has found prey item

QUESTION: TO EAT OR NOT TO EAT

- eat or continue searching

- If prey 1 - it’s easy

- eat prey - won’t find anything better

but if it finds prey 2?

- eat less profitable prey or keep searching

decide by comparing

Gain from eating prey 2 =

Gain from searching for & eating prey =

should eat prey 2 if

Now have testable predictions

(1) decision to eat prey 2 - based in part on search time for 1 (if 1 is

(2) search time for prey 2 - not important

(3) predator should switch instantly between prey - eat most profitable

- some experiments have been done testing this general conclusion

- found that part 3 did not hold up

- didn’t switch between prey clearly - ate mixture

What else would affect this kind of model?

(1) have chosen right currency?

- maybe they’re minimizing search time

- maybe they’re making complex judgments re food quality

e.g. deer - Berteaux et al, ‘98)

- offer artificial food - 4 kinds

- high/low in protein

- high/low in

- choose high calorie, low protein

(2) models assume that probability of finding a prey item its density

- not always true

Tinbergen (another one!) - birds & caterpillars

- shows that birds don’t forage density alone

- Why? - develop a “SEARCH IMAGE”

- improve ability to detect a particular kind of prey

- a kind of central filter

A second kind of model - PATCH MODEL

- This model deals with the notion that prey are not scattered randomly - but are changed

into patches

tide pool

fruit trees

seed pods

now have a different set of problems for foragers

- how long does an animal stay in a patch before moving on?

- factors in decision

(1) richness of patches

(2) distance between patches

In 1976 Charnov - proposed Marginal Value Theorem

- gain drops with time

now - add in travel time between patches

e.g. long travel time when animal not feeding

e.g. 2 - short travel time

is there any experimental work on this?

Birds - aviary - compared travel time & time in patch

- from above model

- as time in travel increases time in patch should increase

found the following

Some modifications on this theme

(1) Central Place Foraging

- this applies to animals that carry food to a location for storage or feeding others

- nesting birds

- insects in colonies

- problem here - several factors

(1) time in patch

(2) food quality

(3) load size

Animals can judge this

e.g. Davoren & Burger (1999) Anim. Beh.

- rhinoceros auklet

- marine bird in B.C.

- when foraging for themselves

ate smaller
- presumably

- don’t want to make trip to next with small fish

- carry largest possible load

(2) Second Modification

RISK SENSITIVE FORAGING

- so far have assumed some average level of prey in patch

- not always true

- over time - both have same mean but in second - can win big or lose big

riskier (in a gambling sense)

If a predator can distinguish these two kinds of patches - risk sensitive

Those that prefer variable patch - risk-prone

That prefer stable patch - risk

Let’s leave models for a bit

ask more generally - how do animals go about acquiring food

- some very imaginative ways

(1) Modify food supply

e.g. limpets - use mucous trail

solitary limpets - return to ‘home’ depression in rock

- leave mucous trail

(1) traps algae

(2) stimulates algal growth

(2) Trap Building

ant lions

(3) Aggressive Mimicry

- fireflies - Photuris X female - post-mating won’t respond to own spp.

- will flush in response to Photuris Y male - eat him

- complicated matters

- male of Y: will mimic X

soon female Y will respond

- another mating

(4) Tool use

Final Pt. on Predators

- Foraging & Social Beh.

- forager can benefit greatly from cooperation with members of species

- thought to be on eof the major factors in the evolution of social behaviour

Most studied

- mammalian carnivores

2 general kinds

(1) stalk & rush

- Lions

- sneak very close to prey and then attack

- benefits - can take larger prey than single lions

(2) Cruisers

- e.g. wild dogs

- pursue prey for long distances

- use tag-team approach to tire prey

- allows group to take larger prey than a single animal could

But for all of this - predators (even in groups) are not all that successful

Mech (1970)

- recorded 131 of moose encountering wolves

- of these - 6 resulted in moose being killed

DEFENSE AGAINST PREDATORS

Can divide strategies into two types

(1) INDIVIDUAL

(2) GROUP

INDIVIDUAL

(1) Escape and freezing

- escape - presupposes proximity to nest/burrow or some hide

- familiarity with escape routes

- freezing - often associated with cryptic colour

(2) Deception

appear to be something you’re not

- e.g. false advertising

(1) resemble

- inanimate obj

- e.g. Lepedopterous - twigs, bark

(2) Descriptive colour

- brightly coloured reef fish

- hard to tell where or what the fish is

- eyespots - on tail

- fresh

- often bright colour associated with

- we’ll talk about some of this

vis a vis - communication

Toxicity & Aposematism

- wide range of noxious substances

- after associated with warning or aposematic colours

- skunks

- why colour? - enable predator to quickly

- one of fastest learning models is avoidance

Mimicry

- resemble unpalatable species

Batesian mimicry - monarch-

- another kind of mimicry

- several unpalatable species look similar

- Mullerian mimicry

- gives predators fewer types of prey to avoid

Group on Social STrategies

- want to talk about these as part of Social beh.

SOCIAL BEHAVIOUR

Want to examine some of the mechanisms by which social behaviour may have come about.

- first attempt (also says something about levels at which selection operates)

1962 - V.C.Wynne Edwards

Animal dispersion in relation to social behaviour

Control Thesis

- Animals tend to avoid over exploitation of their habitats

- do so by reproductive restraint

- many animals are capable of producing more offspring than they do

e.g. - subordinates - no reprod.

- delay age of first breeding

- infanticide

- reproductive restraint

- of social behaviour

- much of social behaviour

- epidiectic display

Therefore anything that animals did in groups or as a group

- epidiectic

- allowed members of a group to be informed of local abundance

engage in reproductive restraint

- sparked great debate

- can interpret ‘epidiectic’ display more parsimoniously

e.g. English swift

- 2 eggs/clutch

but can lay 3-4/clutch

W-E interpretation

- courtship display - allow census of local population

therefore females lay few than she is capable

but

if look more closely

- at fledging success

clutch size % fledging S/nest

2 82 1.64

3 45 1.35

therefore laying fewer eggs helps individual not group

W-E recognized problem with his theory vis a vis genetics

- if have gene A - promotes altruism

a - promotes selfishness max. reprod.

- A can’t spread

- carries automatic selection against itself

This is difficult to explain

W-E Mech - Group Selection

- reproductive restraint can evolve theoretically if

benefit of group of altruism

> reprod. advantage of being selfish

- but no one could conceive of a system in which this inequality holds

Why - criteria are v. rarely met

Criteria

(1) differentiate reprod. of group

> diff reprod. of individuals in group

(2) little genetic X between group

- no immigration or emigration

- argument is that these criteria are never met

one e.g. - cited as evidence of group selection

Australia - rabbit/myxoma virus

Facts (1) ‘group’ - viruses in one rabbit

(2) over time - virus has become less virulent

(3) virulence = lethality = f (reprod. rate)

(4) transmission by mosquito

therefore p (infection) and lifespan of rabbit

virulent form high reprod lower probability of transmission

(selfish)

less virulent lower reprod lower probability of transmission

form (altruistic)

group selectionist argument

- less virulent - restrained reprod.

therefore individual sacrifice for group survival

- more virulent - higher individual success

therefore individual selfishness

group extinction (no transmission)

- individual selectionist

- look at all components of fitness

ask if high ‘r’ x low transmission < lower ‘r’ x high transmission

How do we approach this now?

- standard - Cost vs benefit used to answer question - Why life in groups?

(A) protection from physical factors

e.g. butterfly larvae - aggregate

- have less variable range of body temp. wrt. ambient

- explains aggreg. - not social beh.

(B) Protection against predators

- this is the #1 benefit

how?

(1) Encounter effect

- grouped animals are more difficult to find

one study with colonial spiders (Vetz)

- found that not only was this true but that the expectation that as colony size increased encounter rate would too - was not

(2) Selection effect

- once a predator has encountered a group - group size should benefit individuals

- since each animal’s chance of being taken

- drops with increased size

Theory that puts these points together to show how groups form

Hamilton - Geometry for the Selfish Herd

- imagine a circular lily pond

- colony of frogs

+

water snake

- snake - preys on frogs one at a time

- at same time of day

- just before snake appears

- frogs climb onto rim of pond

- snake appears & will go for

nearest frog

- suppose frogs - given opportunity to move

how should they move

Hamilton - defined - domain of danger

- frog should move between frogs

- if all frogs are obeying these rules

- aggregation

- indeed - all models tested (various rules about jumping)

- aggregation

(C) mate searching

- easier to find mates

(D) Locating food

- foraging success

- cooperative hunting

(E) Resource defense

- obvious for spp. like baboons

- but even something like colonial bryozoan

- less likely to be overgrown by competition if in larger colony

(F) Division of labour

- esp. in Caste spp. - bees, ants, wasps,termites

(G) Aiding (or getting help) from relatives

- if help another individual

- needs to be Km or be reciprocal

(H) Modifying Environment

- spp. that build Structures

(2) Costs of Group Living

(1) Increased competition

- reflected in increased aggressive interaction

e.g. prairie dog colonies

# aggressive acts/individual

- increase with group size

(2) Increased chance of disease and parasites

e.g. in cliff swallow nests

(3) Interference with reproduction

- several kinds of reproduction increase with increased group size

- infanticide

- mating interference

It’s plan that group living has costs and benefits

- some are understandable

- aggregation for warmth

- being in a group if dilution effect works

but why behave (apparently) altruistically?

e.g. - warn about predator - calling attention to oneself

- raising another animal’s offspring

Theoretical Bases

Hamilton - most situations of mutual help - relatives

- Kin selection

divided fitness into two types

(1) direct - fitness gained through reproduction

(2) indirect - fitness gained through reproduction of related individuals

direct + indirect = INCLUSIVE FITNESS

Kin selection - is how your inclusive fitness is

first have to know the coefficient of relatedness between 2 individuals

r = probab. that two individuals possess the same allele due to common ancestry

e.g. Parent/offspring - 1/2

Full sibling - 1/2

half siblings - 1/4

cousins - 1/8

Aunt Uncle/Niece Nephew - 1/4

Grant parent/grandchild - 1/4

how is this used to understand altruism?

Hamilton’s rule says:

altruistic trait will spread if

B/C > 1/r

b = benefit to recipient of altruists help

c - cost to altruist

r = coeff. of relatedness

are there examples of this

Florida Scrub Jay

- large groups of all purpose territories

- breeding pairs

- 1/2 have helpers (1-6 that remain for 1-5 years)

- helpers - feed, defend territory, fight predators

- most are adult offspring of breeding pair

Benefits - to breeding pair

without helpers - 1.62 young/nest

with helpers - 2.20 young/nest

( of number of helpers)

Benefits to helper

- RS of pairs with 1 helper -1.94/nest

therefore helper success = 1.94 - 1.62 = .32 x 1/2 (relatedness) = .16

Novice breeders - 1.02/nest x 1/2 = .51

therefore RS as novice breeder is 3x higher than as a helper

Why help?

other fitness components come into it

e.g. study showed that being a novice breeder was risky

found that

(1) survival for those on home territory

- higher

(2) incr. chances for territory by taking over home territory or budding off it.

What about animals that are unrelated?

This is called RECIPROCITY

- do something now in anticipation of receiving a benefit later

The theory behind this is game theory

mathematical (‘Beautiful Mind’)

Prisoners Dilemma

Scenario - 2 prisoners - caught and jailed for a petty crime

- but suspected of having committed a more serious crime

- questioned separately

each prisoner (player) has a choice

- cooperate - deny all knowledge of more serious crime