Comparison of Constant Effort Harvest Policies for Fish Stocks with Variable Recruitment

Abstract

. 1985. Comparison of constant effort harvest policies for fish stocks Environmental variability may have a substantial influence on marine fish stocks, primarily by affecting survival to the time of recruitment. Simulation studies at low, intermediate, and high levels of variability in recruitment were used to compare alternative constant effort policies for anchovy (Engraulis capensis), Atlantic menhaden (Brevoortia tyrannus), and Pacific ocean perch (Sebastes alutus) fisheries. These policies were either to maintain effort at the level producing maximum sustainable yield (fMSY), or to permit levels of effort 25-100% greater than fMsY. An increase in effort of 25% above fMsY typically did not reduce annual yield significantly; however, a significant reduction in yield was apparent in all cases when effort increased by 75-100%. When recruitment is highly variable, comparable yields may be obtained at several levels of fishing effort. In such cases, environmental variability provides the fishery manager with considerable flexibility to enhance social or economic benefits without decreasing yields significantly.La variabilite environnementale peut avoir u n e influence importante sur les stocks de poissons marins, surtout pour la survie jusqu'h I'epoque du recrutement. On a utilis6 des etudes de simulation A des niveaux de variabilite du recrutement faible, intermediaire et eleve pour comparer divers regimes d'effortconstant pour la p&che de I'anchois (€ngraulis capensis), de I'alose tyran (Brevoortia tyrannus) et du sebaste A longue machoire (Sebastes alutus). Ces regimes visaient soit le maintien de I'effort au niveau produisant un rendement maximal soutenu (fRMS) ou u n accroissement des niveaux d'effort le rendant de 25 A 100 % plus eleve que le fRMS. Un effort superieur de 25% au fRMS n'a pas abaisse le rendement annuel de facon significative ; toutefois, une baisse importante du rendement etait Cvidente dans tous les cas quand I'effort etait superieur de 75 A 100 %. Quand le recrutement est tres variable, on peut obtenir des rendements comparables A plusieurs niveaux d'effort de peche. Dans de tels cas, la variabilite environnementale procure u n e Rrande latitude au gestionnaire des pCches pour accroitre les avantages sociaux ou econowith variable recruitment. Can. J. Fish. Aquat. Sci. 42: 982-988. miques sans ibaisser nettement'ies rendements.

Effects of delay, truncations and density dependence in reproduction schedules on stability of nonlinear Leslie matrix models

“…In our terminology this means w(t) = E(t), that is, ~i =f-, i = 1, 2,..., n. This assumption was made in the models proposed in Reed (1980), Levin and Goodyear (1980), Levin (1981), Horwood and Shepherd (1982), Hightower and Grossman (1985) and Bergh and Getz (1988). In our terminology this means w(t) = E(t), that is, ~i =f-, i = 1, 2,..., n. This assumption was made in the models proposed in Reed (1980), Levin and Goodyear (1980), Levin (1981), Horwood and Shepherd (1982), Hightower and Grossman (1985) and Bergh and Getz (1988).…”

On Managing Variable Marine Fisheries

“…Also, in marine fisheries of the type considered here, GV' s in the region of $8 -128% have been observed (Hightower and Grossman 1985). The problem of harvesting stocks that exhibit considerable recruitment variability has been investigated in the case of Atlantic menhaden (Brevoortiia tyrwnnus) by Rupgert et al (1985) and in the cases sf South African anchovy, Atlantic menhaden, and Pacific ocean perch by Hightower and Grossman (1985).…”

Dynamics and biological reference points in a stochastic age-structured fish population model with an illustration of the Patagonian toothfish population

“…where Y (F ) is given in (9). We denote F MSY as the fishing mortality that produces the maximum sustainable yield, that is,…”

“…For biological realism, two modifications are useful: (1) nonlinear dynamics during the early life history stage to obtain equilibrium or sustainability, and (2) stochastic variation in early life survival to account for the large amount of uncertainty due to environmental conditions. Stochastic variability in fish population models due to recruitment has already been studied in [1,5,7,9,10,19]. [10] study the sensitivity of a age-structured model with respect to noise in general form, by means of Fourier analysis.…”