Use of the Daily Egg Production Method for Stock Assessment of Sardine, Sardinops sagax; Lessons Learned over a Decade of Application off Southern Australia

T. Ward, P. Burch, L. McLeay, Alex R. Ivey
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引用次数: 24

Abstract

Analyses of data collected over a decade off southern Australia confirm that estimates of spawning biomass of Sardinops sagax obtained using the daily egg production method are imprecise and suggest that if inappropriate analytical methods are used, estimates may also be biased. Spawning biomass estimates are most affected by variation in mean daily egg production (P0), spawning area, and spawning fraction. The log-linear mortality model (with one egg added to each day class of eggs at each positive site) should be used to estimate P0 because it fits strongly over-dispersed sardine egg density data better and provides more logically consistent and precautionary estimates of P0 than the exponential mortality model or generalized linear models. Most generalized linear models produced inflated estimates of P0 when egg data were strongly over-dispersed. The area surveyed should be sub-divided into a large number (e.g., 300) of similar sized grids. The Voronoi natural neighbor method should be used to calculate grid size for estimation of the spawning area because it reduces subjectivity in sub-division of the sampling area. Potential biases in spawning fraction can be minimized by calculating this parameter using data from all three stages of post-ovulatory follicles (combined). Priorities for future research are identified.
沙丁鱼日产蛋法在种群数量评估中的应用十多年来在南澳大利亚应用的经验教训
对南澳大利亚十多年来收集的数据的分析证实,使用每日产蛋法获得的萨丁鱼产卵生物量估计是不精确的,并且表明如果使用不适当的分析方法,估计也可能有偏差。产卵生物量估计受平均日产蛋量(P0)、产卵面积和产卵比例变化的影响最大。对数线性死亡率模型(在每个阳性位点每天增加一个卵)应该用于估计P0,因为它更适合过度分散的沙丁鱼卵密度数据,并且比指数死亡率模型或广义线性模型提供更逻辑一致和预防性的P0估计。当卵子数据过度分散时,大多数广义线性模型会产生虚高的P0估计。被测量的区域应被细分为大量(例如,300个)类似大小的网格。由于Voronoi自然邻域法减少了采样区域细分的主观性,因此在估计产卵区域时应采用Voronoi自然邻域法计算网格大小。通过使用排卵后所有三个阶段的卵泡(合并)的数据计算该参数,可以最大限度地减少产卵分数的潜在偏差。确定了未来研究的重点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Reviews in Fisheries Science
Reviews in Fisheries Science 农林科学-渔业
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