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Factors Determining Fish Catch in Indonesian Fishing Villages

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Factors Determining Fish Catch in Indonesian Fishing Villages The data is a subset from a survey of saltwater fishermen in the Minahasa region of Northern Sulawesi ... – PowerPoint PPT presentation

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Title: Factors Determining Fish Catch in Indonesian Fishing Villages


1
Factors Determining Fish Catch in Indonesian
Fishing Villages
  • The data is a subset from a survey of saltwater
    fishermen in the Minahasa region of Northern
    Sulawesi, Indonesia (source of data Professor
    Randall Kramer, Duke University)
  • Data includes the following variables
  • Average Catch (in Kg/trip)
  • Type of Gear Used (nets, hook line, etc)
  • Boat ownership
  • Type of boat used (canoe, sail, etc)
  • Daily fishing habits
  • Education level
  • Family Size

2
Research Questions
  • Which of the factors studied has an effect on the
    fishermens catch size?
  • 2) Can we recommend a policy based on this data
    which will reduce overall catch?

3
Data Collection Method
  • Systematic sampling from random lists of
    fishermen was used in order to select individuals
    for the survey. A two-stage cluster sampling
    method was used first by sub-districts and second
    by villages within selected sub-districts.
  • Raw data was obtained from government statistics
    on population and occupation from 1997 and from
    village chief records (March 1999-June 1999).
  • 6 coastal sub-districts (3 from the East and 3
    from the West) were randomly selected out of a
    total of 17 (6 of these were excluded due to
    having less than 5 fishermen). 30 (18) of the
    coastal villages within the selected
    sub-districts were randomly selected for a survey
    using a random number generator.

4
Data Collection Method
  • A target of 600 completed interviews was set in
    order to allow sufficient degrees of freedom for
    various econometric analyses. The numbers of
    interviews needed for each village was determined
    (based on the fishermen population size), and the
    interviewers acquired a list of all fishermen
    living in the village. They randomly selected
    fishermen to interview until they had exhausted
    the quota for the village.
  • Fishermen in those sub-districts of the Minahasa
    region which had over 5 of the working male
    population primarily engaged in saltwater fishing
    had the same probability of being interviewed.

5
  • Analysis of Data Catch vs. Family Size

Hypothesis Testing Let ?1 be the median fish
catch for small family sizeLet ?2 be the median
fish catch for medium family sizeLet ?3 be the
median fish catch for large family size Ho ?1
?2 ?3 HA not all ?i are equal Statistical
tests were run using log transformed data
Categories The original data contained
discrete ordered variables (1 through 9 members
per household) and was pooled into three
categorical groups because of low sample sizes
prior to pooling. Test Assumptions (One-Way
ANOVA)The three groups had relatively equal
variances after log transformations and were
close to normally distributed.
Results There is insufficient evidence to
suggest a difference in the median fish catch
between the small, medium and large family groups
(two-sided p-value of 0.788, one-way analysis of
variance F-test).
6
Analysis of Data Catch vs. Boat Ownership
Hypothesis Testing Let ?0 be the median fish
catch for non boat-ownersLet ?1 be the median
fish catch for boat-owners Ho ?0 ?1 HA ?0 ?
?1 Statistical tests were run using log
transformed data Categories The original data
contained the discrete categorical variables
shown and was not changed. Test Assumptions
(Welchs 2 Sample t-test)Due to unequal
variances after log transformations, a Welchs
Modified t-test was used. The samples were
close to being normally distributed after
transformation.
4 outliers from same village
Summary Statistics (log data)
Results There is insufficient evidence to
suggest a difference in the median fish catch
between the boat owners group and non boat-owners
(two-sided p-value of 0.115, Welch two-sample
t-test).
7
Analysis of Data Catch vs. Boat Type
Hypothesis Testing Let ?1 be the median fish
catch for canoe usersLet ?2 be the median fish
catch for sail boat usersLet ?3 be the median
fish catch for motor boat users Ho ?1 ?2 ?3
HA not all ?i are equal Statistical tests
were run using log transformed data Categories
The original data contained discrete categorical
variables and was not changed. Test Assumptions
(One-Way ANOVA)Given that the sample size in
the group with motor boats is much smaller than
the other two groups, we assumed that its
variance would have been larger had the sample
size been larger. Normality assumptions were met.
Results There is insufficient evidence to
suggest a difference in the median fish catch
between the groups with the three different boat
types (two-sided p-value of 0.053, one-way
analysis of variance F-test).
8
Analysis of Data Catch vs. Education Level
Hypothesis Testing Let ?1 be the median fish
catch for group 1Let ?2 be the median fish catch
for group 2Let ?3 be the median fish catch for
group 3 Ho ?1 ?2 ?3 HA not all ?i are
equal Statistical tests were run using log
transformed data Categories The original data
contained four discrete categorical variables.
The primary and no education variables were
pooled due to a low sample size in the latter.
Test Assumptions (One-Way ANOVA)Given that the
sample sizes in the secondary and high school
education groups were much smaller than the other
two groups, we assumed that their variances would
have been larger had the sample size been larger.
Normality assumptions were met.
Results There is insufficient evidence to
suggest a difference in the median fish catch
between the groups with primary or no education,
secondary and high school education (two-sided
p-value of 0.315, one-way analysis of variance
F-test)
9
Analysis of Data Catch vs. Daily Fishing Habits
Hypothesis Testing Let ?0 be the median fish
catch for non-daily fishermenLet ?1 be the
median fish catch for daily fishermen Ho ?0 ?1
HA ?0 ? ?1 Statistical tests were run using
log transformed data Categories The original
data contained the discrete categorical variables
shown and was not changed. Test Assumptions (2
Sample t-test)The three groups had relatively
equal variances and were close to being normally
distributed after log transformations.
3 outliers from same village (Borgo)
4 outliers from same village (Borgo)
Results There is insufficient evidence to
suggest a difference in the median fish catch
between the group that fishes on a daily basis
and the one that does not (two-sided p-value of
0.59, two-sample t-test).
10
Analysis of Data Catch vs. Gear Type
Hypothesis Testing (K-W Rank Sum Test) Let ?0
be the median fish catch for non daily
fishersLet ?1 be the median fish catch for
daily fishers Ho ?1 ?2 ?3 HA not all ?i
are equal Statistical tests were run using log
transformed data Categories The original data
contained six different types of fishing gear.
The four net types were combined into a single
group due to low sample size in some of the net
subgroups (see next slide). Test AssumptionsDue
to unequal variance in the net group, the
Kruskal-Wallis Rank Sum Test was used. The
Tukey-Kramer pairwise comparison test was run to
determine the difference.
One outlier from Village Sapa
Outliers from village Borgo
Results There is sufficient evidence to suggest
a difference in the median fish catch between at
least two of the three different gear type groups
(two-sided p-value of 0.0002, Kruskal-Wallis Rank
Sum Test). The group with the net gear type had
a median fish catch which was 1.23 to 7.21
kg/trip higher than the spear-fishing group (95
confidence interval,Tukey-Kramer multiple
comparison).
11
Analysis of Data Catch vs. Gear Type
Outlier from village Borgo
Net group consisted of 4 different sub-groups
shown above. Small sample sizes suggested the
need for pooling.
12
Further Analysis of Gear Data
Left Count Table for Gear Type and Average
Catch. Nets seem to account for the majority of
catches in the higher average catch categories,
while Hook and Line fishing accounts for the
majority of counts in the low (0-30) average
catch group.
Above Data in Net group of fishing gear was
comprised of 4 different types of fishing nets.
The data was combined into a single group due to
small sample size in some groups, as seen in the
table to the left. (Note the relative high
abundance of counts for Fly Fishing Net catch
in the 30-50 kg/trip the 50-80 kg/trip
categories.)
13
Further Analysis of Gear Data
  • Using count tables to compare all groups to gear
    type, the following was determined
  • The majority of fishermen using nets also
  • Have a medium-sized family (3-5)
  • Low level of education (Primary only)
  • Use a canoe
  • Fish daily
  • Own their own boat
  • NOTE Above statements are casual observations
    (not statistical conclusions) from count tables.
    No inferences about the general population can be
    made as a statistical test was not possible for
    these comparisons because of low observations
    (lt5) in some groups.

14
Unique Features of Data
  • Types of variables The data consisted of one
    continuous variable (the response variable
    average fish catch) and six categorical
    variables. Some categorical variables were
    created while others were original.
  • Outliers All outliers were identified
    throughout the study and had the following
    characteristics all were from the village Borgo
    and did not own boats while one of them (average
    catch 340 Kg/trip) was from the village Sapa
    and owned a boat. It has been suggested that
    fishermen from Borgo are a part of larger
    commercial operations, which may partake in
    multi-day fishing trips.

15
  • Shortcomings of the Experimental Design
  • Is This Sample Representative of the Larger
    Population? There are doubts as to whether the
    survey sample is representative of the population
    at large as only 6 out of 17 coastal
    sub-districts were selected and from these only
    30 of the coastal villages were sampled. Small
    sample sizes also accounted for difficulty in
    making inferences about the larger population of
    fishermen.
  • Accuracy of Preliminary Data? The method used by
    interviewers to acquire the lists of fishermen
    currently living in coastal villages could be
    subject to inaccuracies. Government statistics
    proved to be outdated when compared with actual
    observations. The local team members, therefore,
    resorted to gathering this information by asking
    village chiefs or their staff the names of the
    fishermen currently living in each village.
    There is no guarantee that these figures were
    accurate or that the chiefs were honest when
    sharing this information.
  • Accuracy of Survey Methods? Fishermen who
    completed surveys were not guaranteed anonymity
    and this may have influenced the answers they
    provided. Interviewers contacted the fishermen
    they selected from their lists (through
    systematic random sampling) and then asked them
    to complete the survey on the spot. There is no
    indication as to how many fishermen refused to
    fill out the survey or how many were unavailable
    to do so, although the target of 600 completed
    surveys was reached.

16
Conclusions
  • Statistical conclusions
  • The analysis failed to provide evidence of a
    significant effect on fish catch by all of the
    variables studied with the exception of gear
    type.
  • The only statistical difference found was that
    fishermen using nets showed a significantly
    higher catch than spear-fishermen.
  • The effect of the other variables on gear type
    could not be determined due to small sample sizes
    and the limited scope of statistical tools
    available for this analysis.
  • Implications
  • There is not enough evidence based on this study
    to make any policy recommendations, although
    obtaining larger sample sizes may provide
    valuable insight into fishery management
    strategies. Future studies should focus on
    determining the effects of the different gear
    types on average fish catch.
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