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OCR for page 31
2
Current Situation and Problems
in Effort and Catch Estimation
This chapter highlights the complex nature of monitoring fishing
effort and catches within the recreational fishing sector, discusses the
data collection and estimation challenges posed by this complexity, and
focuses on issues associated with the implementation of existing surveys.
At present, there is a patchwork of methods and systems of data
collection for recreational fishing throughout the United States, primarily
as a result of historical anomalies and different regional and state
management approaches. However, basic similarities in the methods
used by component programs do exist because a two-phased process1 is
generally needed to arrive at an estimate of the essential parameter, total
catch, based on information about effort and catch per unit effort
(CPUE). Survey programs must also consider design characteristics
needed to address the requirements for information on indices of relative
population abundance, biological sampling of fish species, and related
parameters concerning economics and angler attitudes.
The common feature of catch estimation by surveys discussed in this
report is that estimates of total catch for each subcomponent (i.e., the
design-based spatial and temporal strata, or the post-data collection
strata, defined by species, primary fishing area, and type of catch) are
obtained by multiplying together the estimates of effort and CPUE
gathered from two separate surveys. Total catch is estimated in this way
1Note that the committee is not referring to a nested survey process here but
instead is using two-phase to indicate the use of two different surveys, one to
estimate CPUE and the other to estimate effort.
31
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32 REVIEW OF RECREATIONAL FISHERIES SURVEY METHODS
because of concern that nonsampling errors would invalidate direct
estimates of total catch derived from data of either a dockside or
telephone survey alone. (See Figure 2.1 for sources of error in survey
estimates.) While a telephone survey might theoretically provide access
to all anglers, anglers contacted in this manner may provide poor
estimates of catch because they would be required to identify species
caught or to recall the size or number of fish landed for fishing trips that
may have occurred weeks or even months before being contacted.
Similarly, reliance on dock-side intercept surveys alone is susceptible to
problems of incomplete spatial sampling frames (see Box 2.1 for a
discussion about sampling frames) wherein undercoverage bias results
from the difficulties of accessing private fishing sites. In addition, poor
precision of intercept surveys can result from financial constraints on the
number of interviews that can be conducted, particularly to reach sites
that are more remote or to sample dispersed but low-use sites adequately.
Therefore, the Marine Recreational Fisheries Statistics Survey (MRFSS)
uses a hybrid approach in which dockside intercept surveys are used to
estimate CPUE and conduct biological sampling, and catch and
telephone interviews are used to estimate effort. The results of the two
surveys are combined to yield an estimate of total catch. The result of
using these complementary strategies for assessing effort and CPUE and
for obtaining biological information is that the estimation procedure is
more complex than for many other demographic surveys since it requires
two separate sampling operations. Additionally, numerous adjustments
and extrapolations arise because the sample frames on which the surveys
are based are incomplete or unrepresentative of the entire population.
Evidence throughout this chapter will show the fundamental
problems associated with the overall national MRFSS program and with
some of the component state surveys. These problems are variations on
several common elements. There are potentially large biases in the
sample estimates, and neither their magnitude nor impact can be
measured using the current data. These biases are due to the following
reasons:
· The sample frames for both catch rate estimation and for effort
estimation are incomplete, contain errors, or both.
· Fidelity to sampling protocols used in both effort estimation
interviews and access-point intercept surveys is not monitored
adequately.
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SITUATION AND PROBLEMS IN EFFORT AND CATCH ESTIMATION 33
FIGURE 2.1 Sources of error in survey estimates (Groves et al., 2004;
reprinted with permission from John Wiley & Sons, Inc.).
· Assumptions of unknown validity are used in the expansion of
estimates over the nonsampled segments of the angler popu-
lation.
Other potential biases within the sampling design can be estimated using
the existing data, but these analyses have not been conducted.
Inefficiencies arising from overcoverage in the list frame for effort
estimation result in low precision of estimates and higher cost than
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34 REVIEW OF RECREATIONAL FISHERIES SURVEY METHODS
Box 2.1
Area Versus List Frames and Their Use in Angler Surveys
Frame: A sampling frame is a collection of units from which a sample will
be drawn. The frame is ideally identical to the population (a complete
frame) about which one wishes to learn, but typically, the frame is a
subset of the population (an incomplete frame). If the frame is different
from the population in any way, bias can be introduced if the value of a
parameter for the frame is not the same as the value of that parameter
for the population. Two standard frame types are list frames and area
frames. Coverage errors arise from errors in elements of the frame, more
commonly in list frames, and will lead to bias in estimates based on
sampling of the frame. Overcoverage can arise when frame references
exist but do not provide access to sample elements (e.g., licenses
without addresses, incorrect telephone numbers, households with
telephones but no anglers). Undercoverage arises when some
population units exist but are not linked to the frame and therefore have
no probability of being sampled (e.g., fishing licenses sold that are not
recorded in the list frame).
List frame: A list of information that provides direct access to sample
units. Through its random digit dialing (RDD) sample, the MRFSS uses a
list frame of all working landline telephone numbers in coastal counties.
This frame suffers from overcoverage since not all households contain
anglers, undercoverage since some anglers do not live in coastal
counties or live in coastal counties but have no landline telephones, and
duplications since some anglers live in households with more than one
working landline. Similarly, the For-Hire Survey uses a list frame of
charter boat operators or licenses that may be incomplete. The access-
point intercept survey used within the MRFSS and component programs
is also an incomplete list frame. Even though the intercept sample sites
may be geo-referenced, they are chosen from a master list of
documented access sites (e.g., boat ramps, docks, piers) and therefore
are not an area frame. Typically, the access site frame will not list all
sites, resulting in undercoverage.
Area frame: In the context of site access, an area frame would be a
coastline map that could be sampled in portions, and each portion would
be searched for access sites. An area frame provides indirect access to
sampling sites; access is indirect because the geographic areas must be
selected first and the direct access to sample units achieved through a
second-stage sampling process. Currently, area frames are not used in
the MRFSS.
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SITUATION AND PROBLEMS IN EFFORT AND CATCH ESTIMATION 35
would be required if the list frame coincided with the angler population.
Moreover, the data needs for management and analysis have changed
since the inception of the program, including the following:
· Management decisions require data on finer temporal and spatial
scales.
· Recreational fishing data are now required for use in stock
assessments, sometimes as the sole data concerning stock status.
· Managing recreational catch and retention has become a primary
activity for fisheries management as recreational removals have
supplanted commercial removals for many species and areas.
Finally, the expertise and personnel needed to evaluate and improve the
survey design and execution continually are lacking, and methods used
to collect and analyze recreational fisheries data have not incorporated
evolving statistical methodology or new innovations and technologies
that would improve statistical efficiency and reduce costs.
A number of regional surveys have been developed in recent years
with the aim of addressing some of these problems. However, with such
a wide range of surveys conducted, it is beyond the committee's ability
to analyze all of their individual problems and potential solutions.
Consequently, the issues raised in this chapter tend to focus on the
MRFSS and the For-Hire Survey, but in most instances, these same
issues are also common to the regional surveys. The issues and
characteristics described here are not intended to be inclusive; rather they
are meant to illustrate the general nature of the sampling situations and
resultant problems.
BIAS AND PRECISION
As with all surveys, minimizing bias and maximizing precision of
estimators of important parameters are the goals of the recreational
fishing survey program. The problem with achieving these goals is that
the nature of recreational fishing does not allow for data to be collected
for all anglers. Ideally, representative samples that allow unbiased
estimation of the catch by the total angler population should be collected.
However, resource limitations, survey design characteristics, sample
frame errors, and restricted access to anglers in some modes may result
in nonrepresentative sampling of the angler population. Therefore,
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36 REVIEW OF RECREATIONAL FISHERIES SURVEY METHODS
adjustments, or expansions, in the estimation process are employed to
account for the lack of information for some anglers. These adjustments
require assumptions about the behavior of the unobserved anglers that
are of unknown validity. Furthermore, the data do not exist to test the
validity of these assumptions or to determine whether they result in large
biases. Not knowing whether the adjustments introduce bias, and not
being able to test for this bias, creates uncertainty about the quality of the
estimates.
Variation in an estimate among years is a source of major debate for
recreational fishing surveys--especially where fluctuations in estimates
result in equivalent fluctuations in regulations for subsequent years. It
may be the case that these fluctuations are real, but they also may be
artificial. They may result from low precision in the estimate (which can
be corrected by increasing the sample size or sampling efficiency) so that
the estimate may be unbiased but may vary from the true parameter value
in any given period because of expected variation. It is currently difficult
to assess if this is the problem because standard errors may be estimated
incorrectly.
Recreational fishing provides formidable challenges in estimating
catch, effort, and economic expenditures by anglers, either regionally or
nationally, due to the diversity of fishing sites and modes available to
anglers. Recreational fishing can be an individual or group pursuit. It can
be based on shore or on water and can be conducted on private boats or
through a commercial for-hire vessel. Angler trips can originate from
private residences that border fishing waters or involve travel over
thousands of miles to a departure site, with additional travel on water to
the fishing grounds. Effort can range from only minutes of active fishing
for anything caught or for a favorite species to multiple-day trips
involving multiple targets; often, trips can cover the entire 24-hour
period. Furthermore, the target species for anglers may be varied and
may include species entirely allocated to recreational fisheries, as well as
those from mixed recreational and commercial fisheries.
The difficulties of covering all fishing modes, access points, and
duration of fishing has led to several additional surveys that complement
the basic MRFSS approach. Yet, even these additional surveys are
unable to measure all essential strata, leading to assumptions about
unsampled fishing behavior. Below is a brief description of the different
angler modes that highlights survey and estimation procedures that are
used and how bias or imprecision may be introduced into estimates of
effort, CPUE, and the resulting total catch. The issues discussed are not
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SITUATION AND PROBLEMS IN EFFORT AND CATCH ESTIMATION 37
intended to be exhaustive for all surveys or even for a single survey but
are intended to emphasize the issues that are described below.
Private or Independent Fishing
Shore-based
Shore-based fishing refers to fishing directly from the shoreline (e.g.,
beaches, banks, headlands) or from artificial structures, such as docks,
jetties, piers, bridges, breakwaters, and causeways. This is the most
difficult sampling environment because of private property issues and
because of a virtually unlimited number of small access points. Anglers
who participate in fisheries from public or commercial property can be
intercepted by onsite samplers and can be included in CPUE estimation;
however, the extensive amount of publicly available property and
structures makes attaining an efficient probability-based sample chal-
lenging. Also, some shore-based anglers are not accessible through the
public access-point frame used for estimating CPUE because they fish
from private property. An angler fishing from a private residence might
never be subject to an intercept interview, and therefore, his or her data
never could contribute to CPUE estimate. Instead, his or her CPUE
would be assumed to be the same as for anglers fishing and sampled
though other modes. However, in order to expand the estimates based on
sampled anglers to this unsampled portion, the assumption must be made
that the species composition and catch rates of these anglers is the same
as for the sampled anglers. This is assumed to be true, but data to test this
assumption have not been collected. These anglers can be included in
estimation of effort through the telephone frame. However, a consistent
definition or duration of "angler trip" between shore-based and
waterborne fishing is elusive.
Effort for this shore-based private fishing is measured through the
MRFSS random digit dialing (RDD) survey, but only for anglers who
live in coastal counties. Anglers who reside beyond this area, but who
fish from shore in the survey area, are excluded from the sampling frame.
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38 REVIEW OF RECREATIONAL FISHERIES SURVEY METHODS
Residential Boat Ramps and Docks
Similar to shore-based anglers fishing from private property,
waterborne anglers who launch from private residential property are not
normally subject to access-point intercept sampling because samplers do
not have access to private residential property. If CPUE for these anglers
is the same as for those launching from public access sites, then no bias
is introduced from this undercoverage. It seems possible, however, that
the experience and knowledge of the local area among anglers in this
mode may cause the two groups to differ in CPUE. The effort within
coastal households for this mode can be estimated through the MRFSS
RDD survey.
Publicly Owned and Commercially Available Boat Ramps and
Moorage
This mode is similar to the use of public structures for shore-based
anglers in that use of public facilities for boat launching or moorage
provides the opportunity to conduct intercept sampling of waterborne
anglers. However, sampling this subpopulation of anglers still can be
problematic if there are a great many launching sites. The large number
of sites and the limited survey budgets and time may result in a tendency
to exclude many small sites from the list of sites chosen for sampler
coverage. There may also be issues associated with the timing of angler
presence at these sites; the intercept sample design must account for any
such temporal stratification. Effort for local anglers (those residing in the
selected RDD calling area) using this mode will be estimated through the
MRFSS RDD survey, but effort for nonlocal anglers will not.
For-Hire Fishing
When anglers go with a guide, charter fishing on boats with crew, or
on head boat trips, their participation and removals are estimated through
a different framework than that used for private anglers. However,
anglers who rent boats for independent, nonguided fishing are captured
by the current MRFSS sampling approaches; these waterborne anglers
are treated similarly to the private boat anglers discussed above.
Head boats, charters, and guided boats are commercial enterprises,
require registration, can be listed, and thus constitute a smaller and more
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SITUATION AND PROBLEMS IN EFFORT AND CATCH ESTIMATION 39
efficient list sampling frame than that of the population of independent
anglers. (Only some states have lists based on saltwater fishing licenses.)
Effort in the For-Hire Survey, which measures number of boat trips,
number of anglers, and areas fished, is determined from boat directory
telephone surveys instead of RDD employed in the MRFSS. Because the
list frame is complete, assuming that the directory is kept up to date, the
potential bias associated with not collecting effort data from noncoastal
county anglers is not an issue as it is with the MRFSS. Catch rate,
however, may still be collected though dockside interviews, which share
the same sampling issues associated with this type of sampling
(discussed later in the chapter). In addition to these general problems,
there are specific issues associated with the dockside interview for head
boats. Each angler's data are likely to be highly correlated. This results in
cluster effects that, if not accounted for, can have a significant impact on
both the bias and the standard error calculation for the final estimates
(see Chapter 3). (Cluster effects also should be expected for nonguided
boat anglers, although probably to a lesser degree than for head boats.) In
addition, biological sampling of these catches should account for cluster
effects, and stock assessment analysts using these data also must be
aware of these potential effects.
The for-hire sector can provide an additional unique opportunity for
recreational catch and effort sampling because records of angler
participation generally are kept by for-hire companies. These records
provide two capabilities: direct estimation of fishing effort (and,
frequently, catch) and a source of validation for estimates obtained
through alternate sampling methods, such as remote-access sampling of
anglers based on a different sampling frame. Records of client
participation are kept to varying levels of resolution. In the case of guide
boats, records normally are associated with individual anglers. For
example, guide boats taking anglers for high-prestige species, like tarpon
or bonefish, may involve considerable expenditures, and records for an
individual angler might have historical and future value for the guide.
For head boat and charter boat fishing, records of fishing effort by
anglers may or may not be accompanied by removal data at the
individual level.
Validation of charter boat records is recognized as an important
component and source of error information for the estimation process.
Access-point intercept samplers have noted inconsistencies between
charter boat logbook records and observed presence and absence
information on vessels at their normal home port. It is important to create
a rigorous and objective sampling protocol for validations of this type.
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40 REVIEW OF RECREATIONAL FISHERIES SURVEY METHODS
Similarly, validation of angler participation also must accompany the
use of charter boat data. It is important that charter boat anglers be
included in alternate estimations of fishing effort, such as remote-access
sampling, so that a validation of charter boat records can be achieved. It
also is important, of course, that care be taken not to count anglers twice
(i.e., once in contacting them individually and once through the for-hire
survey).
The implementation of the Party Charter Survey (For-Hire Survey)
in California has improved the estimates of effort and therefore catch by
this sector. The ability to define the sampling list frame through a
directory of commercial enterprises also has improved the efficiency of
sampling these anglers over what had been achieved previously in the
MRFSS. In addition, more timely data are provided because a percentage
of the vessels within the directory are sampled each week instead of
waiting two months, as with the MRFSS. Additional improvements that
can be made for this sector are discussed in Chapter 3.
Tournaments are special cases that might have some potential use for
assessing biases and for providing information for some species.
Although angler catch and effort often are well documented, they do not
represent typical angler activities and often focus on highly migratory
species, which often are not included in the MRFSS.
Night Fishing
In some areas, night fishing is common and creates unique chal-
lenges to estimation of catch rates and, to a lesser degree, fishing effort.
Effort for night fishing can be estimated through the telephone survey in
the same way as for other modes of fishing. However, estimation of
catch rate for this mode is highly problematic because, while anglers
participating in this mode may be accessed, in theory, through an
existing frame, they are inaccessible because samplers normally do not
intercept anglers at night. Therefore, a secondary temporal stratification
within the access site sampling frame is required to estimate catch rate by
this fishing mode. Such a program has been implemented in the
Mississippi Shore Night Fishing Survey. Another method of obtaining
angler-supplied night-catch information is to add some questions to the
telephone survey; although, this will create additional complexities. In
many cases, night-fishing catch will have to be ignored.
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SITUATION AND PROBLEMS IN EFFORT AND CATCH ESTIMATION 41
Spatial and Temporal Issues of Sampling Coverage
In most cases, CPUE is achieved via intercept sampling at access
points. Access points are given different probabilities of selection into
the sample, with sites weighted and chosen based on expected angler
activity. The set of selection probabilities are referred to as the pressure
matrix. This sample design is selected to improve the efficiency of the
CPUE estimate and seems likely to do so if the pressure matrix effort
estimates are accurate. While the MRFSS and its derivatives have
attempted to keep the pressure matrix relevant to current effort
distribution, the methods used to update the pressure matrix are not
consistent across regions. In addition, the selection probabilities are not
used in the estimation process, which will lead to bias in the estimators,
except in unusual circumstances. This is discussed in more detail in a
later section.
A source of potential bias in the estimate of effort is due to the
proportion of private anglers who are not part of the sampling frame.
Effort estimation is based on telephone sampling of residents of coastal
counties, and many private anglers do not reside in these counties. An
adjustment based on information obtained in the intercept sample is
attempted, but this will be adequate only under special circumstances.
(Again, this is discussed in more detail in a later section.) This mismatch
of the frames for estimating catch rate and effort results in a decreased
capability for validation of fishing effort estimation through comparison
of estimates from the two frames.
The temporal stratification of the current MRFSS is based on two-
month sampling periods, or waves. However, the timeliness of the
estimation from each wave varies by region. In most regions, the lack of
timeliness is not important because species' harvests are not managed in-
season. However, for several major species on both coasts and in the
Gulf of Mexico, in-season estimation is a key component of man-
agement. The timeframe for estimation through the MRFSS process
(because it takes a long time to accumulate enough fishing households to
have an adequate sample size) does not address management require-
ments consistently, in part due to the inefficient telephone sampling
frame for estimating fishing effort.
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46 REVIEW OF RECREATIONAL FISHERIES SURVEY METHODS
followed, the laws of probability will provide estimators with known
properties.
Currently, the onsite intercepts for all recreational surveys are
assumed to be a random sample. However, the collection of intercept
data has been tailored to the kinds of access sites that are present in a
particular region, and interviewers frequently are allowed to make
judgments about where, when, and which units to sample. This means
that these samples may not be true probability (random) samples.
Generally, the leeway afforded to onsite samplers is an attempt to reduce
costs by reducing the time it takes to gather the target number of
samples. This is problematic because such sampling is, in essence, a
quota sample,2 rather than a probability sample in which all anglers have
a known probability of being intercepted. This deviation from a
probability sampling protocol has an unknown impact on estimates of
both CPUE and effort.
Besides the deviations from sampling protocol that are explicitly
allowed, there may be other instances in which interviewers stray from
instructions on sample selection. There is no regular interviewer
monitoring program included in the sampling protocol, as is common in
most survey operations. Indeed, it would be difficult to use the most
common types of interviewer quality control programs in the intercept
survey setting because they are based on a reinterview of a sample of
respondents. The result of this problem is that it is not known, nor is
there an easy way to determine, how much interviewer error affects the
quality of the data gathered through the intercept survey. Making the
development of a reinterview program especially difficult is the fact that
intercept interviews are conducted by a wide range of people. Several
states either have their own intercept surveys or have taken over the
conduct of this portion of the MRFSS, but still others rely on contractors
to complete the surveys. With multiple organizations involved, it is
difficult to specify and monitor adherence to a common sampling
protocol across survey efforts.
2A quota sample defines groups of people who are deemed important to reach,
based on information about the target population. Quotas are set for each group
based on the group's relative size in the population. Quota samples are not
random samples, and their use can lead to bias if anglers who are difficult to
reach differ from those who are easy to reach. In addition, the precision of
estimates cannot be calculated (Pollock et al., 1994).
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SITUATION AND PROBLEMS IN EFFORT AND CATCH ESTIMATION 47
Variance Estimation
Standard error is an important indicator of the quality of an estima-
tor, and yet, correctly estimating standard error may be the most difficult
part of the estimation process. The sample design and estimator form for
the MRFSS are nonstandard, so correct assessment of variance is
challenging. There appear to be some problems with variance estimation
as it is carried out currently. Addition of variances across subpopulations
to obtain valid estimates of variance for aggregates requires that the
estimators within each subpopulation be independent. For some subpop-
ulation aggregates, this will be valid. For example, for strata representing
time periods, it seems a reasonable assumption since both intercept and
telephone samples are drawn independently in different time periods.
(However, for sparse subpopulations, information from past time periods
are imputed, which would invalidate this method.) For aggregations over
post-strata, such as catch type (e.g., removals consisting of catch
available for inspection [A] and catch unavailable for inspection because
it is filleted, discarded dead, or refused for inspection [B1]), this is
unlikely to be valid since the same sampling units are used to obtain each
type of data. There is information in the data that would allow this
correction to be attempted; in other words, it is possible to calculate
correlations from the sample, and the variance estimation method could
be changed to account for the correlation.
Estimating Mortality
The issue of catch and release of both target and nontarget species
requires much greater attention and estimation of associated mortality
rates than has occurred to date. Currently, catch released alive (B2)
usually is not incorporated into the catch estimates used for quota
monitoring because there is no verification of the catch and it ostensibly
is released alive, although Oregon and Washington do apply hooking
mortality rates to discards in ocean boat fisheries that vary by species and
other factors. However, this assumption ignores the high hooking
mortality rate associated with some fisheries, especially for those species
with swimbladders that are caught at significant depths, such as rockfish
or grouper. In some instances, mortality on released fish may represent
the major mortality factor in total removals. For example, several species
of west coast rockfish are under severe restrictions of total allowable
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48 REVIEW OF RECREATIONAL FISHERIES SURVEY METHODS
catch, and the recreational fishery (both retained and released) is the
primary source of removals.
Measuring the release of species is problematic because it relies on
angler recall (in the absence of onboard observers) and angler knowledge
of species. Estimates of size are even more difficult to collect and most
likely are overestimated due to prestige bias or are subject to rounding
errors. Better methods to estimate the number of released fish are
needed. Some of the specific issues related to catch-and-release fisheries
include (1) released catch cannot be inspected in an onsite survey, unlike
the kept catch; (2) rounding errors are common; (3) exaggeration or
under reporting due to memory problems are possible; (4) species
identification errors may occur; and (5) the size and age distribution may
be different compared to kept fish. All of these errors can be serious.
Observers in boat-based recreational fisheries can be used to obtain
direct estimates of fish release numbers. However, releases are likely to
be different if observers are present.
Research on released fish mortality estimation from cage studies and
tagging studies is needed to help estimate the contribution of the
auxiliary information collected about the depth from which fish were
caught. However, cage experiments would provide only a minimum
estimate of mortality and reflect only "physiological" mortality rather
than the "ecological" mortality that would be measured through tagging
studies.
NEW DEMANDS ON RECREATIONAL FISHING DATA
This committee identified a number of areas in which designers of
sampling programs, data collectors, and users of recreational fisheries
data appear to have incomplete communication, mismatched criteria, or
other miscommunications. In most instances, these issues have arisen
because the current uses of recreational fisheries data were not
anticipated in the design of the MRFSS. Current users require data with
higher resolution--spatially, temporally, and taxonomically--than the
current MRFSS design can deliver.
Two of the major recurring issues facing recreational surveys are
adequate spatial and temporal resolution. These needs are driven
primarily by the type of management applied in each area. Management
tactics have changed since the inception of the MRFSS and continue to
change as more stocks are monitored and managed. Survey designs now
require greater coverage and more detail to estimate harvest and effort
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SITUATION AND PROBLEMS IN EFFORT AND CATCH ESTIMATION 49
for national and interstate management (Henry, 2002; Lyle et al., 2002;
Pollock, 2002).
In addition, recreational data are now used for many stock
assessments. For stocks that now have low catches from the commercial
sector, recreational fishing data may be the primary data on which stock
assessments are based. In addition, topographic and other differences
between the coasts in various regions also affect demands on sampling
design. For example, the rocky coasts of the Pacific Northwest, with their
rough seas, provide far fewer potential access points for boats than the
sandy coasts and calmer waters of Florida and the Gulf of Mexico. The
application of recreational data to finer management scales and their use
in assessments have highlighted potential issues with the bias and
precision of current survey methods that previously were less important.
However, if these uses of the data are to continue, changes in the survey
methods are required to provide the needed information.
Spatial and Temporal Resolution in Catch and Effort Estimation
Currently, many fisheries are monitored at the state level, which is a
finer stratification than intended originally for the data collected. In order
to provide state estimates with reasonable precision, many states have
increased their sample size, either by adding additional sampling by state
personnel or by asking the MRFSS contractor to complete more calls and
onsite intercepts. These actions, taken on the whole, seem to result in
more precise estimates of total catch within these smaller areas. In
addition, these measures appear to have increased angler confidence
because increasing sample size is a straightforward premise that non-
survey scientists can understand. In some cases, it also presents the state
as taking a proactive approach that is appreciated by anglers--the states
are no longer just saying that the data are not good enough to manage,
they are actually doing something about it. Of course, additional samples
require more money, but if quotas are to be allocated and monitored by
each state, these additional samples are necessary.
There are numerous other methods that can be used to increase
precision on smaller scales than are employed in other national surveys.
However, these methods generally have not been explored for their
application to recreational fishing surveys. Some of these methods are
discussed in Chapter 3. However, data gathering on smaller scales will
only be useful if the data collection methods are not biased and the
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50 REVIEW OF RECREATIONAL FISHERIES SURVEY METHODS
assumptions made about extrapolations and imputations are valid, as dis-
cussed in the previous section.
The temporal scale of data collection also continues to be pushed to a
finer level of resolution than originally intended. Within the MRFSS,
effort sampling is conducted in two-month waves. Checking the data and
completing the final estimates takes another two months, meaning that
catch estimates are not released until at least four months following the
actual fishing effort. This lack of timeliness raises many issues for man-
agers.
Obviously, this time lag does not allow in-season management,
which is why different surveys have been implemented in states wanting
to manage in-season, such as California, Washington, and Oregon. These
states have reworked the fundamental components of the MRFSS--the
intercept survey and the telephone survey--in order to compile more
timely data. The most fundamental change is the implementation of an
angler registry so that the sampling frame used to determine effort is
more defined and efficient than that of RDD of the MRFSS. Finer
spatial-scale management also has required larger sample sizes for each
sampling wave to ensure sufficient precision of resultant estimates.
Even with annual management, data timeliness is an issue. Often, the
data from the previous year have not been analyzed completely until the
following season is under way. This can result in adjustments to the total
allowable catch once the season has begun. While this is not truly in-
season management, the effects can be similar if the adjustments to the
current year mean that fewer fish can be taken or if the season has to
close earlier than expected. These situations are difficult for anglers and
operators of for-hire vessels to deal with. For example, fishing trips can
be planned many months to a year in advance; yet, there may be no
guarantee the fishery will still be open for future planned trips. This
uncertainty is perceived to be a much larger problem in recreational
fisheries than in commercial fisheries because anglers can be infrequent
users. The time it takes to collect, verify, and calculate fishing effort and
catch using conventional survey approaches is too lengthy, even for
annual management, if stability in the yearly total allowable catch is
desired.
Use of Data for Stock Assessments
A large mismatch appears to exist between recreational sampling
programs and the stock assessment scientists using them. The MRFSS
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SITUATION AND PROBLEMS IN EFFORT AND CATCH ESTIMATION 51
and even some of the newer surveys were not designed to gather data for
stock assessments; yet, the estimates of total catch and the biological data
collected during the intercept survey are often used in assessments.
Assessment scientists using these data generally do not have a clear
understanding of the data collection process, or the data collection
process may not be executed in the manner assumed by the scientist. The
implications of this mismatch between those collecting and those using
the data are profound. The lack of continuity in intercept samplers,
differences in sampling methods applied to different modes of fishing
(e.g., shore-based and boat-based private anglers or those using various
for-hire vessels), differences in sample element definition, lack of
incorporation of design elements in the estimation process (e.g.,
weighting of spatial or temporal sampling strata), lack of consistency (or
accuracy) in species designation among fishing or sampling modes, and
the inability to combine information based on different sampling modes
all compromise the inclusion of these data in the assessment process.
Data from different sampling modes may have unknown statistical
properties because the data collection emerges from the implementation
of general designs that are adapted to suit local circumstances. Scientists
using these data may assume that their statistical properties are known
and estimable. (More specific problems associated with recreational
fisheries data and their incorporation into stock assessments [e.g., the
difficulty of measuring which, if any, species are being targeted] are
discussed in Chapter 4.)
A common knowledge base among anglers, data collectors, and data
users is required if surveys are to fulfill current data needs. This is not to
say that all anglers must have a complete knowledge base of species, but
the intercept samplers and the anglers must categorize catch to a jointly
understood level. This is particularly important for taxonomic stratifi-
cation of data. Stock assessment scientists must be able to employ data
with confidence that species designations are applied accurately and
consistently in the sampling process or with knowledge that higher
groupings of taxonomic categories are used.
INCORPORATING NEW IDEAS AND TESTING OLD ONES
Surveys designed for monitoring long-term status of populations
have considerable inertia and are resistant to change. In part, this resis-
tance is appropriate if the data provided by the surveys are to be
consistent and useful over long periods. Major design changes can break
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52 REVIEW OF RECREATIONAL FISHERIES SURVEY METHODS
the continuity of data and render them unusable for population moni-
toring unless the new and old surveys are run in parallel for some years
during the change. In addition, the original design objective for a given
survey may continue to be relevant, in spite of subsequent objectives that
may be of equal or greater priority than the original. Resistance to
change also arises because of the fixed commitment of resources (human
and material) to existing designs.
The MRFSS has made some changes to accommodate better
estimation of some fishing modes (e.g., For-Hire Survey of charter
boats). However, the fundamental aspects of the two-phased survey have
not evolved significantly since the inception of the program. Different
survey designs exist that could possibly improve the quality of the
collected data; yet, few new approaches have been undertaken by the
MRFSS or the state surveys. Indeed, several previous reviews have
offered suggestions for improvements, but most of these, including
several from a previous report by the National Research Council (2000),
have not been implemented, perhaps due to a lack of staff and additional
funding.
While several external reviews of the MRFSS or portions of it have
been conducted (Essig and Holliday, 1991; Guthrie et al., 1991), there is
presently no internal process of user feedback on evaluation and
modification of the design within the MRFSS. Some users of recreational
data have initiated dialogue with the survey project managers to address
specific design issues, but the need exists for a structural feedback
process. The rapid evolution of uses of and needs for data from recre-
ational fisheries underscores the requirement for ongoing evaluation by
survey managers.
OUTREACH
The committee heard from numerous groups and individuals
expressing a lack of confidence in the estimates produced by several of
the recreational surveys. While this is not a problem with the survey
methodology per se, increasing understanding and confidence in the
programs can be as essential as improving the data itself. The credibility
gap arises from several causes, including a belief that alternate data
sources are more credible; criticism of the temporal, spatial, group, or
taxonomic stratification of the intercept sampling; lack of understanding
of statistical methodology; or recognition that the existing sampling
frames do not describe the angler population adequately.
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SITUATION AND PROBLEMS IN EFFORT AND CATCH ESTIMATION 53
In addition to dialogue on design issues, survey managers also need
to advise data users on constraints to some uses, as well as on funda-
mental features of the data collection system. The websites for the
MRFSS and the regional data programs (National Oceanic and
Atmospheric Administration, 2005b) are information rich and provide
general background for the average angler. In addition, in recent years,
the MRFSS personnel have begun to conduct regular meetings with users
to review results of sampling waves. However, the committee heard of a
number of instances where users extracted sections of data histories but
were unaware of the data characteristics, the methods of compilation, or
the fundamental nature of sampling estimation versus census. These
observations indicate that while the program has undertaken some
outreach activities with users, misconceptions and lack of clarity on data
characteristics continue to exist. Further, the lack of user understanding
of the design basis of the survey clearly has created some lack of trust
even in the underlying data. Considerably greater outreach effort appears
necessary but with the recognition that user distrust may not be
overcome completely.
CONCLUSIONS AND RECOMMENDATIONS
The designs, sampling strategies, and collection methods of
recreational fishing surveys do not provide adequate data for
management and policy decisions. Unknown biases in the estimators
from these surveys arise from reliance on unverified assumptions.
Unless these assumptions are tested and the degree and direction of
bias reliably estimated, the extent to which the biases affect final
estimates will remain unknown. The statistical properties associated
with data collected through different survey techniques differ and
often are unknown. The current estimators of error associated with
various survey products are likely to be biased and too low. It is
necessary at a minimum to determine how those differences affect
survey results that use differing methods. It is impossible to assess the
adequacy of recreational fishing surveys, particularly those associated
with the MRFSS, when potential biases exist. Identifying and eliminating
the sources of bias or estimating and correcting for the degree of bias is a
fundamental requirement for the provision of reliable estimates from the
MRFSS.
The statistical properties of various sampling, data-collection,
and data-analysis methods should be determined. Assumptions
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54 REVIEW OF RECREATIONAL FISHERIES SURVEY METHODS
should be examined and verified so that biases can be properly
evaluated. The complexity of the recreational fishing surveys makes
them susceptible to many forms of bias. Unfortunately, it is difficult to
avoid this complexity due to the diverse nature of recreational fishing.
However, it is important to eliminate sources of bias or appropriately
adjust for them when bias is unavoidable. Biases can be addressed
through expanding the sampling frame to better represent the population,
through experiments used to derive the appropriate correction factors,
and through better training and monitoring programs aimed at improving
the quality of data sampling. All of these approaches are discussed in the
following chapters.
Some of what is viewed as bias by the public can be the result of
variance of the mean estimate, arising from inadequate sample size or
other sampling errors. While reduction in variance often can be achieved
by increasing sample size, improving the statistical efficiency through
appropriate choice of estimators and careful implementation of sampling
protocols can also be useful. Improved precision commonly is achieved
by increasing sample size, and improvements can be gained for estimates
derived from recreational fishing surveys through just such an approach.
However, gains in statistical efficiency also may be achieved by
considering alternate estimators that make better use of the information
available and by identifying and implementing mechanisms that improve
the effectiveness of the sampling procedure, as for example through the
creation of a complete sampling frame of anglers. Improvement will
come not only as a result of greater precision but also in terms of reduced
sampling effort and cost.
Greater demands on recreational fishing data from both the science
and the management sectors are being made. Management decisions
are often made at finer spatial and temporal scales than they were
earlier, the mix of recreational and commercial fishing has changed
for many areas and species, and stock-assessment models now make
greater use of data from recreational fisheries. Reallocation of harvest
from commercial to recreational sectors has increased the need to gather
stock assessment information in greater detail from recreational fisheries
sources. As managers use recreational data on finer spatial and temporal
scales, issues of precision and bias become more pronounced. Existing
spatial and temporal sampling strata may be of too coarse a resolution to
generate estimates that are adequate for the management requirements.
The MRFSS is in need of additional financial resources so that
technical and practical expertise can be added to assist in a major
overhaul of the design, implementation, and analysis of data from
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SITUATION AND PROBLEMS IN EFFORT AND CATCH ESTIMATION 55
the MRFSS. The goals and objectives of fisheries managers, as well as
the different surveys, are evolving constantly. There has been progress in
survey programs directed to some targeted fisheries with the
implementation of new, tailored surveys; yet, additional improvement is
required. There have been several reviews of the national program in the
last 10 years, but a more fluid, continuous review and feedback would
allow for evolution of the program to meet emerging needs. In addition,
as statistical theory and sampling technologies improve, it is essential
that the managers of these regional or national monitoring programs have
greater access to expertise in statistical analysis and sampling design. It
appears that the implementation of new survey methods is hampered by
the inertia of existing surveys and that even when a need for change is
identified, a lack of resources, staff time, and expertise may prohibit
implementation of such changes. Development of new survey methods
could be accomplished by an external, independent research group as
discussed in Chapter 6.
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Representative terms from entire chapter:
list frame
