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Spatio‐temporal analyses of marine predator diets from data‐rich and data‐limited systems
Fish and Fisheries ( IF 5.6 ) Pub Date : 2020-03-15 , DOI: 10.1111/faf.12457
Arnaud Grüss 1 , James T. Thorson 2 , Gemma Carroll 3, 4 , Elizabeth L. Ng 5 , Kirstin K. Holsman 6 , Kerim Aydin 6 , Stan Kotwicki 7 , Hem N. Morzaria‐Luna 8 , Cameron H. Ainsworth 9 , Kevin A. Thompson 10
Affiliation  

Accounting for variation in prey mortality and predator metabolic potential arising from spatial variation in consumption is an important task in ecology and resource management. However, there is no statistical method for processing stomach content data that accounts for fine‐scale spatio‐temporal structure while expanding individual stomach samples to population‐level estimates of predation. Therefore, we developed an approach that fits a spatio‐temporal model to both prey‐biomass‐per‐predator‐biomass data (i.e. the ratio of prey biomass in stomachs to predator weight) and predator biomass survey data, to predict “predator‐expanded‐stomach‐contents” (PESCs). PESC estimates can be used to visualize either the annual landscape of PESCs (spatio‐temporal variation), or can be aggregated across space to calculate annual variation in diet proportions (variation among prey items and among years). We demonstrated our approach in two contrasting scenarios: a data‐rich situation involving eastern Bering Sea (EBS) large‐size walleye pollock (Gadus chalcogrammus, Gadidae) for 1992–2015; and a data‐limited situation involving West Florida Shelf red grouper (Epinephelus morio, Epinephelidae) for 2011–2015. Large walleye pollock PESC was predicted to be higher in very warm years on the Middle Shelf of the EBS, where food is abundant. Red grouper PESC was variable in north‐western Florida waters, presumably due to spatio‐temporal variation in harmful algal bloom severity. Our approach can be employed to parameterize or validate diverse ecosystem models, and can serve to address many fundamental ecological questions, such as providing an improved understanding of how climate‐driven changes in spatial overlap between predator and prey distributions might influence predation pressure.

中文翻译:

来自数据丰富和数据受限的系统对海洋捕食者饮食的时空分析

解释由于消费空间变化而引起的猎物死亡率和捕食者新陈代谢潜力的变化,是生态和资源管理中的重要任务。但是,尚无用于处理胃内容数据的统计方法来解释精细规模的时空结构,同时又将单个胃样本扩展到人口级别的捕食估计。因此,我们开发了一种适合时空模型的方法,既适合于捕食生物量,每个捕食者生物量数据(即,胃中捕食生物量与捕食者体重的比率),也适合于捕食者生物量调查数据,以预测“捕食者扩展胃内容”(PESC)。PESC估算值可用于可视化PESC的年度景观(时空变化),或可以汇总整个空间以计算饮食比例的年度变化(猎物之间和年份之间的变化)。我们在两种截然不同的场景中展示了我们的方法:涉及白令海东部(EBS)大型角膜白斑鳕鱼(佳度chalcogrammus,鳕科)为1992至2015年; 以及涉及数据有限的情况,涉及2011-2015年的西佛罗里达州货架红石斑鱼(Epinephelus morio,Epinephelidae)。预计在非常温暖的年份中,EBS的中层架上有大量的角膜白斑PESC会很高,那里的食物丰富。在佛罗里达州西北海域,红色石斑鱼PESC是可变的,大概是由于有害藻华严重程度的时空变化。我们的方法可用于参数化或验证各种生态系统模型,并可用于解决许多基本的生态问题,例如提供对气候驱动的捕食者与猎物分布之间空间重叠的变化如何影响捕食压力的更好理解。
更新日期:2020-03-15
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