The effects of variability in catch effort on the precision of statistical population reconstruction

IF 1.7 3区 生物学 Q3 ECOLOGY Wildlife Biology Pub Date : 2024-07-22 DOI:10.1002/wlb3.01288
Sergey S. Berg, John D. Erb, Abby K. Westphal
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Abstract

Statistical population reconstruction (SPR) models have emerged as a robust and versatile framework for estimating the demographic dynamics of harvested wildlife populations using commonly collected age‐at‐harvest and catch‐effort data. Although numerous studies have suggested that higher interannual variability in catch effort may improve the accuracy and precision of reconstructed estimates, particularly in the absence of auxiliary data on annual abundance or survival, the extent and magnitude of these effects has not been explored. We examined the influence of catch‐effort variability, as measured by the ratio between years of highest and lowest effort, on the relative absolute deviation of reconstructed estimates of population abundance, as well as on the actual percent coverage and width of the corresponding confidence intervals. We used a Monte Carlo simulation to generate catch‐effort data with different levels of variability for populations experiencing a wide range of demographic and harvest conditions. For similar amounts of age‐at‐harvest data, using catch‐effort data with higher interannual variability resulted in reconstructed estimates of annual abundance that had significantly lower deviations from reality, better coverage, and narrower confidence intervals (as measured by the margin of error). These improvements were consistent and linear at low to medium levels of catch‐effort variability, but leveled off and became substantially less pronounced at higher levels. We found that the inclusion of auxiliary data largely mediated this relationship, although higher catch‐effort variability still resulted in more accurate and precise estimates of annual abundance even when these data were included. Our research highlights the need to include a thorough investigation of the available catch‐effort data alongside the established practices of assessing the number of years of available data, the average number of animals harvested each year, and the availability of auxiliary data from radio‐telemetry studies or other sources.
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渔获量变化对统计人口重建精度的影响
统计种群重建(SPR)模型已成为利用通常收集的捕获年龄和捕获努力量数据估算被捕获野生动物种群人口动态的一个稳健而通用的框架。尽管许多研究表明,较高的捕获量年际变异性可能会提高重建估算的准确性和精确度,尤其是在缺乏年度丰度或存活率辅助数据的情况下,但这些影响的程度和范围尚未得到探讨。我们研究了渔获量-努力量变异性(以最高和最低努力量年份之间的比率来衡量)对种群丰度重建估计值的相对绝对偏差以及实际覆盖百分比和相应置信区间宽度的影响。我们使用蒙特卡洛模拟法生成了具有不同变异水平的渔获量-努力量数据,这些数据适用于经历各种人口和捕捞条件的种群。在捕捞年龄数据量相近的情况下,使用年际变异性较高的渔获量数据重建的年丰度估计值与实际情况的偏差明显较小,覆盖范围更大,置信区间更窄(以误差率衡量)。在中低水平的渔获量变化时,这些改进是一致的、线性的,但在较高水平时,这些改进趋于平缓,且不那么明显。我们发现,纳入辅助数据在很大程度上调节了这种关系,尽管即使纳入了这些数据,较高的渔获量-努力量变异性仍能带来更准确、更精确的年丰度估计。我们的研究突出表明,在评估可用数据的年数、每年平均捕获的动物数量以及来自无线电遥测研究或其他来源的辅助数据的可用性等既定做法的同时,还需要对可用的渔获量-努力量数据进行彻底调查。
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来源期刊
Wildlife Biology
Wildlife Biology 生物-动物学
CiteScore
4.30
自引率
0.00%
发文量
33
审稿时长
>12 weeks
期刊介绍: WILDLIFE BIOLOGY is a high-quality scientific forum directing concise and up-to-date information to scientists, administrators, wildlife managers and conservationists. The journal encourages and welcomes original papers, short communications and reviews written in English from throughout the world. The journal accepts theoretical, empirical, and practical articles of high standard from all areas of wildlife science with the primary task of creating the scientific basis for the enhancement of wildlife management practices. Our concept of ''wildlife'' mainly includes mammal and bird species, but studies on other species or phenomena relevant to wildlife management are also of great interest. We adopt a broad concept of wildlife management, including all structures and actions with the purpose of conservation, sustainable use, and/or control of wildlife and its habitats, in order to safeguard sustainable relationships between wildlife and other human interests.
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