Squid resource estimation model based on environment factors

Abstract

A squid resource assessment model based on environmental factors. According to the remaining yield model, the remaining yield model based on the environmental factors of the spawning ground is constructed: log(B t )|K,σ 2 =log(K)+u t l o g ( B t ) | B t - 1 , K , r , σ 2 = log { B t - 1 + rB t - 1 ( 1 - B t - 1 S t - 1 K ) - C t - 1 } + u t Remaining yield model based on forage field environmental factors: log(B t )|K,σ 2 =log(K)+u t l o g ( B t ) | B t - 1 , K , r , σ 2 = log { B t - 1 + F t - 1 rB t - 1 ( 1 - B t - 1 K ) - C t - 1 } + u t Residual yield model based on comprehensive environmental factors: log(B t )|K,σ 2 =log(K)+u t l o g ( B t ) | B t - 1 , K , r , σ 2 = log { B t - 1 + F t - 1 rB t - 1 ( 1 - B t - 1 S t - 1 K ) - C t - 1 } + u t where B t is the biomass in year t, K is the environmental capacity, r is the natural intrinsic growth rate, q is the capture coefficient, I t is CPUE for year t, u t , v t are independent of each other and have the same distribution as IID N(0, σ 2 ), σ is the CPUE standard deviation.

Description

technical field [0001] The invention relates to a squid resource assessment model, in particular to a squid resource assessment model based on environmental factors. Background technique [0002] Marine fishery resources are important renewable resources. Scientifically assessing the amount of resources and proposing reasonable management measures are conducive to the development and utilization of fishery resources. Usually, people use the fishery population dynamics model to describe the dynamic changes of the fishery population, and use the model data for fitting under an assumed error structure, so as to realize the estimation of the relevant parameters of the model and the situation of fishery resources. Forecasts are made to evaluate the impact of different management measures on fishery resources. [0003] There are many types of fishery resources, and species with different life history characteristics have different changes in the quantity of fishery resources, so ...

AI Technical Summary

Problems solved by technology

However, the influence of environmental factors has not been taken into account in the previous evaluation models of soft fish resources. These models have produced large errors in application and actual data, and have provided many uncertain sources of error for resource evaluation.

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