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Minding the Data-Gap Trap: Exploring Dynamics of Abundant Dolphin Populations Under Uncertainty
Frontiers in Marine Science ( IF 3.7 ) Pub Date : 2021-01-27 , DOI: 10.3389/fmars.2021.606932
Erin Ashe , Rob Williams , Christopher Clark , Christine Erbe , Leah R. Gerber , Ailsa J. Hall , Philip S. Hammond , Robert C. Lacy , Randall Reeves , Nicole L. Vollmer

Preventing declines in common species is key to sustaining the structure and function of marine ecosystems. Yet for many common marine mammals, including oceanic dolphins, statistical power to detect declines remains low due to patchy distribution and large variability in group sizes. In this study, population viability analyses (PVA) were used to model the dynamics of four oceanic dolphin populations off the United States West Coast: eastern North Pacific long-beaked common dolphins (Delphinus delphis capensis), short-beaked common dolphins (D. delphis delphis), Pacific white-sided dolphins (Lagenorhynchus obliquidens), and “offshore” common bottlenose dolphins (Tursiops truncatus). We calibrated the PVA with life-history tables, studies on proxy species, and stock assessment reports. We explored the sensitivity of populations to demographic variation and projected how they may respond to changes in three sublethal threats (prey limitation, ocean noise, and chemical pollution) and one lethal threat (fisheries bycatch). We found the most serious projected declines in long-beaked common dolphins, which showed the lowest birth rate. Most threat scenarios resulted in declines that would not be detected by existing monitoring programs in the United States, which are among the most data-rich surveys of their kind. The cumulative effects of the three sublethal stressors exceeded the effect of the one lethal stressor (fisheries bycatch). To implement pro-active management and monitoring programs, anticipating which cetaceans are more at risk and which anthropogenic threats could cause declines is paramount. Our study highlights the value of model testing with PVA when monitoring data are poor, thereby identifying priorities for future research, monitoring, and management.



中文翻译:

注意数据鸿沟:不确定性下的大量海豚种群动态

防止常见物种的减少是维持海洋生态系统的结构和功能的关键。然而,对于许多常见的海洋哺乳动物,包括海洋海豚,由于斑块状分布和群体规模的巨大差异,发现下降的统计能力仍然很低。在这项研究中,种群生存力分析(PVA)用于模拟美国西海岸外的四个海洋海豚种群的动态:北太平洋东部长喙普通海豚(德尔菲海豚),短嘴普通海豚(D. delphis德尔菲斯),太平洋白海豚(闭生紫草)和“离岸”常见的宽吻海豚(s藜)。我们使用生命历史表,代用物种研究和种群评估报告对PVA进行了校准。我们探讨了人口对人口变化的敏感性,并预测了他们如何应对三种亚致死性威胁(猎物限制,海洋噪声和化学污染)和一种致死性威胁(渔业兼捕)的变化。我们发现,长喙普通海豚的预计下降最为严重,这表明其出生率最低。大多数威胁情景导致的下降量是美国现有的监控程序无法检测到的,而美国现有的监控程序是同类数据中最丰富的调查之一。三个亚致死应激源的累积效应超过了一个致死应激源(渔业兼捕)的效应。为了实施积极的管理和监督计划,预测哪些鲸类动物面临更大的风险以及哪些人为威胁可能导致其下降至关重要。我们的研究强调了在监视数据不佳时使用PVA进行模型测试的价值,从而确定了未来研究,监视和管理的重点。

更新日期:2021-02-18
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