Chapter 4: Estimating Vital Rates Flashcards

1
Q

non-invasive capture and mark methods: sources of error

A
  • genotypic error
  • shadow effect
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

genotypic error

A

two or more individuals that share the same genetic ID or physical markings are counted as same individuals

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

genotypic error example

A

increased number of loci

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

shadow effect

A

same individual counted as multiple individuals in analyses

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

shadow effect example

A

hair cells of two individuals are amplified together, creating a ‘new’ individual

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

SCR - Spatial Capture Recapture Methods

A
  • new class of sophisticated closed CMR methods
  • incorporates spatial information of captures to estimate location and number of animal home ranges
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

SCR example

A
  • R packages
  • Bayesian approaches
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

open population models

A
  • some caught, other dead or gone
  • additions or losses are of interest
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

additions

A
  • birth
  • immigration
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

losses

A
  • death
  • emigration
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Jolly Seber Abundance

A

Ni = Mi* ni / mi

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Mi

A

estimate of number of marked animals alive in the population right before occasion i

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

how is abundance estimated

A

with closed-population models within each primary period

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

how gains and losses are estimated across the primary period

A

using open-population models

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

open population models examples

A
  • survival
  • recruitment
  • emigration
  • immigration
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

factors of survival estimation

A
  • known fate
  • CMR
  • band recovery/return
17
Q

known fate

A

all animals can be relocated

18
Q

CMR (Cormack-Jolly-Seber)

A

only survivors are recorded

19
Q

band recovery/return

A
  • only deaths are recorded
  • marked alive, bands returned via harvest
20
Q

known fate models

A

S = x/n

21
Q

S

A

survival

22
Q

x

A

number of surviving animals

23
Q

n

A

total number of sampled animals

24
Q

Kaplan Meier Methods

A

S(t) = pi [1- (# of deaths at time i=di/ # at risk at time i=ri)]

25
Q

Kaplan-Meier Methods accommodates…

A
  • multiple intervals of sampling
  • right censoring of animals with unknown fate
  • staggered entry of new animals
26
Q

assumptions of Known-Fate survival methods

A
  • marked animals are representative of the population
  • the mark/sensor does not affect survival
  • censoring is unrelated to their fate
  • survival times are independent for the different animals
27
Q

survival estimation allows for:

A

estimating the effects of different variables

28
Q

measuring reproduction: proportion breeding

A
  • observation
  • non-invasive genetic markers
  • hormone assays
29
Q

non-invasive genetic markers example

A

paternity/maternity

30
Q

factor to tell how many babies per mom

A
  • natality
  • fecundity
  • average reproduction contribution
31
Q

natality

A

average number of live offspring per female that reproduces

32
Q

examples of natality

A
  • litter size
  • clutch size
33
Q

fecundity

A

average number of offspring born per individual of a given age in one time step

34
Q

average reproduction contribution

A

product of fecundity and either the survival of young to be counted the next year or the survival of parents to have the young

35
Q

sex ratios

A
  • ratio of males to females
  • varies through different lineages
36
Q

sex ratio driving factors

A
  • temperature
  • food availability
  • males often have a lower survival
37
Q

sex ratio driving factors: temperature

A
  • climate change
  • styrofoam boxes
38
Q

food availability

A

sex allocation theory

39
Q

sex ratio driving factors: males often have a lower survival

A
  • more risky behaviors
  • high susceptibility to disease and parasites
  • X linked genetic problems