Ecology Test 1

Front 1

Destructive sampling

Back 1

killing a large amount of species to open up there guts and see what they eat

Front 2

Gross energy returns

Back 2

E, what animals want to maximize

Front 3

Handling time

Back 3

h, time it takes to pursue, handle and swallow food

Front 4

Profitabilites

Back 4

E(gross energy returns)/h(handling time)

Front 5

Encounter rate

Back 5

λ, how available the item is

Front 6

Search time

Back 6

Ts , total time searching for food

Front 7

Optimal foraging model

Back 7

Understand conditions when it is best for an animal to eat both items, or pass up a poorer item and continue searching for a better one

Front 8

Expected energy reward equation

Back 8

E = Ts(λ1E1+λ2E2)

Front 9

Total time requried for foraging

Back 9

T = Ts + Ts(λ1E1+λ2E2)

Front 10

Net energy gain per unit time

Back 10

E(1,2) / T(1,2)

Front 11

Optimal foraging predictions 1 and 2

Back 11

1) at greater abundance animals will be more selective, 2) an item should be incledued in the diet based on the abundance of the better item, not considering abundance of worse item

Front 12

Exploitative resource depression

Back 12

Animal depletes food supply

Front 13

Behaviorial resource depression

Back 13

Animal scares food away

Front 14

Compression hypothesis

Back 14

Invading species (predators) will result in a drop of patches from an animals routine. Basically, don’t want to go where they will get eaten

Front 15

Home range

Back 15

Where an animal normally frequesnts (every animal has one)

Front 16

Territory

Back 16

A defended area, exclusive of other individuals

Front 17

Feeding territories

Back 17

Defended exclusively for food

Front 18

Nesting territories

Back 18

Small area around nest to protect aggs and young

Front 19

Multi-purpose territories

Back 19

Defender sleeps, courts mates, breeds, nests, and feeds offspring

Front 20

Relative threats hypothesis

Back 20

The intensity of an owners response to a threat depends on what it stands to lose in fights with neighbors and strangers

Front 21

The food hypothesis

Back 21

Animals assess resource availability directly and defend areas containing sufficient quantity of food

Front 22

The intruder hypothesis

Back 22

Animals defend as large an area as they can, but this is contrained by competition and neighbors

Front 23

Lincoln Index

Back 23

(number of marked individuals, M)/(total number of individuals, N) = (number of recaptured individuals, m)/(total number captured in second visit) N = nM/m

Front 24

Survivorship

Back 24

lx = number alive at age x / number alive at birth = nx / n0

Front 25

Mortality

Back 25

mx = number of deaths during an age class / number of individuals alive at the start of the age class = (nx− nx+1) / nx

Front 26

Survival rate

Back 26

Sx = nx+1 / nx = 1 − mx

Front 27

Future life expectancy

Back 27

ex = Tx / nx , how many more years an individual should live on average

Front 28

Average alive during an age class

Back 28

Lx = (nx + nx+1) / 2

Front 29

Sum of average alive during an age class

Back 29

Tx = Σ (from x=i to ∞) Lx

Front 30

Three Types of Survivorship Curves

Back 30

Type 1 = low juvenile mortality, high adult mortality, ex) humans, Type II = constant rate of death, diagnol plot, ex) birds and lizards, Type III = high juvenile mortality, low adult mortality, ex) fish and insects

Front 31

Fecundity

Back 31

bx, Fecundity is the number of offspring produced by each breeding female

Front 32

Realized fecundity

Back 32

lxbx, The survivorship at each age class multiplied by the fecundity

Front 33

Net reproductive rate

Back 33

R0, is the average number of offspring produced by an individual in the population. Thus it is the sum of realized fecundity over all ages: R0 = Σlxbx (x=age i to ∞)

Front 34

Population

Back 34

N, where N0 is initial population and Nt is population at a given time

Front 35

Geometric model of population growth

Back 35

Nt = N0 R0t , gives us the size of population at time t in the future but not how fast the population is growing. R0 can be substitued with λ, Nt = N0λt

Front 36

Geometric rate of increase

Back 36

λ = Nt+1 / Nt ,estimates the rate at which our population is growing

Front 37

Instantaneous rate of increase

Back 37

r, r=birth rate (b) − death rate (d)

Front 38

Exponential growth model

Back 38

dN/dt = rN, where r, the per capita rate of increase, is constant and N, the size of a population, is the variable. Can be rewritten in computational form: Nt = N0 ert

Front 39

Density dependent vs. independent factors

Back 39

Dependent factors are limits on resources such as food and places to live. Independent factors are are hard to predict such as temperature, enviornmental catastrophes, etc.

Front 40

Carrying capacity

Back 40

K, the upper limit to population growth

Front 41

Logistical growth model

Back 41

dN/dt = r0 N(1−(N/k)) , where 1− (N/k) measures how empty the enviornment is