Data and Management Strategies for Recreational Fisheries with Annual Catch Limits (2021) / Chapter Skim
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Appendix B: Leveraging Covariances and Conditionals
Appendix B: Leveraging Covariances and Conditionals
Pages 167-178
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From page 167... ...
As an example, consider MRIP catch estimates for two domains, where estimated catch in the first domain is C1, and estimated catch in the second domain is C2. For example, C1 might be the catch of a particular species in a particular location in a particular wave, and C2 might be the catch of a different species in that same location and wave.
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From page 168... ...
168 RECREATIONAL FISHERIES WITH ANNUAL CATCH LIMITS C1 = T1∙U1 C2 = T2∙U2 When the fish catch in one domain moves in the same direction as the fish catch in the other domain, the covariance between the two fish catches is positive. When the catches move in opposite directions, the covariance between the catches in the two domains is negative.
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From page 169... ...
(2000) investigated the effect of Red Snapper CPUE (from the Marine Recreational Fisheries Statistics Society on fishing effort (trips per angler)
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From page 170... ...
; or both. USING CONDITIONING TO REDUCE CATCH VARIANCE AND PSEs In some situations, the probability distribution of one variable, say, fish catch in a particular MRIP domain, C, may depend in part on the value of another variable, say, X
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From page 171... ...
12.66667 TABLE B.5 Negative cov(C1,C2) for a Single Species Across Location 1 and Location 2 Catch C1 Catch C2 Location 1 Location 2 Time 1 3 5 Time 2 5 3 Time 3 10 2 Time 4 2 10 cov(C1,C2)
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From page 172... ...
says that the probability of catching various numbers of Wahoo off the coast of North Carolina in June depends on the water temperature off the coast of North Carolina in May. The conditioning variable X could be anything that affects the probability distribution of C
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From page 173... ...
below the variance estimate provided by MRIP by taking the conditioning variable, such as water temperature, into account. If fishery managers could find a good conditioning variable X, they could use it to reduce the variance (and PSE)
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From page 174... ...
THE ROLE OF COVARIANCE WHEN FISHERY MANAGERS AGGREGATE OR DISAGGREGATE MRIP CATCH ESTIMATES The covariance between fish catch X in one MRIP domain and fish catch Y in a different MRIP domain can affect the variance (and PSE) of a catch forecast in situations in which fishery managers aggregate or disaggregate the domain-level fish catch estimates X and Y provided by MRIP.
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From page 175... ...
Disaggregating Fish Catches Across Domains Recognizing the importance of covariances is also important when one is disaggregating fish catches across domains (e.g., when disaggregating total regional fish catch into catches by subregion, when disaggregating total fish catch into catches by fishing mode, or when disaggregating total catch of a species group into catches by species [such as disaggregating total Grouper catch into catches by species of Grouper]
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From page 176... ...
* LIKELIHOOD LIKELIHOOD LIKELIHOODOF LIKELIHOOD OFOFOFNEGATIVE NEGATIVE NEGATIVE NEGATIVECOVARIANCES COVARIANCES COVARIANCES COVARIANCESAMONG AMONG AMONG AMONGSPECIES SPECIES SPECIES SPECIESIN INININAAAMULTISPECIES MULTISPECIES MULTISPECIES LIKELIHOOD LIKELIHOOD LIKELIHOOD OF OF NEGATIVE NEGATIVE OFFISHERYNEGATIVE FISHERY FISHERY COVARIANCES COVARIANCES COVARIANCES CONSTRAINED CONSTRAINED CONSTRAINED AMONG AMONG BY BYAMONG BY A SPECIES SPECIES A A BINDING BINDING BINDING SPECIES IN INACL A ACL ACL INAAMULTISPECIES A MULTISPECIES MULTISPECIES MULTISPECIES FISHERY FISHERY FISHERY CONSTRAINED FISHERYCONSTRAINED CONSTRAINED CONSTRAINED BY BY A ABY AABINDING BINDING BINDING BY BINDING ACL ACL ACL ACL In InIn a aamultispecies multispecies multispecies In a multispecies fishery fishery fishery fishery constrained constrained constrained constrained by byby a aa binding binding binding ACL, ACL, ACL, such such such as as asperhaps perhaps perhaps perhaps the the theSouth South South SouthAtlantic Atlantic Atlantic Atlanti In In aaa multispecies In multispecies multispecies snapper/grouper snapper/grouper snapper/grouper fishery fishery, fishery fishery,fishery fishery, one one constrained one constrained constrained might might might expect expect byby expect by aa by a binding covariances covariances covariances a ACL, binding binding binding ACL, across suchACL, ACL, across across as perhaps such such catches catches catches such as astotoperhaps to bebe as be the perhaps South negative negative negativethe the among the Atlantic South South among among Atlantic Atlantic species species species inin inthe the th snapper/grouper Snapper-Grouper snapper/grouper snapper/grouper fishery, fishery, fishery, fishery,one one one one might mightmight might expect expect expect expect covariances covariances covariances covariances across across across across catches catches catches catches to be be to totoexample.
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From page 177... ...
control of control variates. Forsuppose example, suppose that infish catch in i isdomain is Xi, and i fishery fishery managers in reducing the variance For (and PSE)
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From page 178... ...
For example, Xi and Xj could be the catches of two species in a multispecies fishery, or Xi and Xj could be the recreational and commercial catch of the same species, or Xi and Xj could be the catches of the same species in two different geographic regions, or Xi and Xj could be the catches of the same species at two different time periods. The control variate technique might be especially useful for the catch of a rare-event species Xi that is correlated with the total catch (Xi + Xj)
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