Lab Exam 2 Flashcards
Frequently used to estimate fish, aquatic inverts, and occasionally small mammal populations
delury method (removal sampling)
Estimates derived are of number present at the beginning of study
Delury method (removal sampling)
This method can be used only when uniform capture efforts are possible
Delury Method (removal sampling)
what does the DeLury or Removal method rely on?
- successive removal of members of a population
- the catch per unit effort (Ct) decreasing linearly as the total catch (Kt) increases
- should be a negative linear correlation between catch per unit effort and cumulative catch
Assumptions for removal method
- a constant proportion of N is captured with each unit of effort
- catchability stays the same during the sampling period
- the population is closed
- the investigator’s removal of animals is the only major source of mortality in the population during the entire study
Ct
(catch/unit effort) (y)
Kt
(Cumulative catch) (x)
takes advantage of the fact that as a population of finite size is harvested, the number of animals captured per unit effort in successive attempts will decrease in proportion to the number of animals previously harvested
delury’s method (removal)
examines the potential relationship between two variables in nature - the dependent variable and the independent variable
regression analysis
if one wants to see if there is any relationship between catch per unit effort and cumulative catch (after a series of catch attempts)
regression analysis
catch/unit effort
dependent variable
cumulative catch
independent variable
the mathematical equation for a straight line
Y = bX - a
Y
dependent variable
X
independent variable
b
slope of the line
a
Y-intercept (value of Y when X=0)
the value of the slope (b) may be positive, which represents a ________ between two variables
positive correlation
when the slope is negative
there is a negative relationship between the dependent and independent variables
uniquely defined by its y-intercept (a) and its slope (b)
regression line
such a line may be fitted through existing data points showing the strength of the relationship between the dependent and independent variables
regression line
SP
sum of the cross products of the deviations of X and Y from their means
SSx
Sum of the squares of the X (independent) data points
Y-intercept =
mean of y data - slope (mean x data)
this method is more applicable to game populations in which one sex is being exclusively removed
Ratio/Dichotomy Method
relies on being able to recognize distinct subgroups within the population
Lincoln-Peterson index and Ratio/Dichotomy Method
Reliance is generally on natural vs. artificial recognition features
ratio/dichotomy method
based on the change in the ratio of two different types of individuals in a population, after some of one or both of the subgroups have been either added to or removed from the original population
ratio/dichotomy method
data required for the ratio method:
- the ratio of the two types before addition or removal
- the ratio of the two types after addition or removal
- the number of each type of individual added or subtracted
major assumptions of the ratio method
- no recruitment or mortality occurs between the two samplings
- adding/removing individuals from the population will not influence the subsequent behavior and/or distribution of the remaining individuals
N1
total number of individuals in the original population
X (ratio method)
the number of one of the two types added or subtracted (indicated by sign)
Y (ratio method)
the number of the other type added or subtracted
P1
the ratio of X in the first sampling
P2
the ratio of X in the second sampling (after addition or removal)
three procedures for obtaining the age structure of a population
- by examining a cohort throughout its lifetime
- by examining all age classes at a particular moment in time
- by knowing the age at death for members of a population
By examining a cohort throughout its life time
cohort or dynamic life table
By examining all age classes at a particular moment
in time ….. the “snap-shot” approach
time specific
By knowing the age at death for members of a population
by examining skulls or animals at check stations
age class data may be collected in a variety of ways:
- counting rings on horns, scales, tooth development
- observing plumage in birds, growth rings on woody plants
- looking at developmental stages of insects and other inverts
column one
age groups
column two (x)
age cohort or age interval
column three (lx or nx)
number of individuals alive at the beginning of the study
column four (Lx)
the number of individuals alive at the middle of age class x
Lx formula
(lx) + (lx + 1) / 2
or
lx = 2Lx - (lx + 1)
column five (dx)
number of individuals in the population that die during interval x
formula for dx
dx = lx - lx+1
column six (qx)
probability of dying during age interval x
formula for qx
dx/lx
column seven (sx)
probability of surviving through age interval x
formula for sx
sx = 1 - qx
column eight (Tx)
number of time units left for all individuals to live from age x onward
formula for Tx
Tx = Lx + (Tx + 1)
column nine (ex)
age-specific life expectancy
formula for ex
ex = Tx/lx
basic introduction to capture/recapture
the lincoln-peterson method
N (lincoln peterson)
number of individuals in population
M (lincoln peterson)
number of marked individuals from first capture effort
C (lincoln peterson)
number of individuals captured in second capture effort
R (lincoln peterson)
number of individuals recaptured in second capture effort
M/N =
R/C
N/M =
C/R
N =
MC/R
To reduce bias: bailey modification
M(C+1)/R+1
Standard Error associated with N
square root of: M^2(C+1)(C-R)/(R+1)^2(R+2)
what assumptions are made when undertaking such mark/recapture effort
- Populations are closed
- No significant mortality of marked individuals
- Marked individuals become randomly distributed in the population.
- There is no recruitment into the size class being studied during entire study.
- There is no loss of marks/tags.
- The method of sampling is not selective with respect to marked vs. unmarked individuals
How large of a number should M be
M should be large enough so that MC is equal to 4 times a crude estimate of N
MC = 4N
Schnabel Modification of the Lincoln-Peterson Index
N = sum(CsumM)/sumR
or
sum(C+1)sumM)/sum(R+1)
