کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5765400 1626774 2017 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Standardising fish stomach content analysis: The importance of prey condition
ترجمه فارسی عنوان
تجزیه و تحلیل محتوای معده ماهی استاندارد: اهمیت شرایط شکار
کلمات کلیدی
وب غذایی، محتویات معده، رژیم غذایی، شناسایی شکار، بوم شناسی جغرافیایی،
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم آبزیان
چکیده انگلیسی
Comparisons of fish trophic data are limited by the range of methods used to quantify dietary composition, with scientists yet to agree on a standard approach to stomach content analysis. This study examined how prey type and condition of stomach contents influenced identification of prey and the ability to estimate dietary importance by methodologies based on volume, weight, number and frequency of occurrence. A total of 154 stomachs were examined from six trophically diverse, temperate fish species. The condition of prey i.e. entirety, digestion state, and presence of mucus were recorded for each stomach, and the taxonomic level to which prey could be identified to assessed. The influence of prey condition on the application of each metric was then assessed. Descriptions based on prey volume or weight were significantly affected by differences in prey condition. In contrast, the simple presence/absence or frequency of occurrence approach (%F) provided a rapid, unambiguous and reliable account of diet composition and was not affected by the condition of prey. It was the only approach able to quantify the full spectrum of prey types in a consistent manner, making it the most practical metric. Variable prey condition also highlighted uncertainties in prey identification. We recommend routine reporting of how prey condition influences identification, the specific approaches used, and any assumptions made in identifying prey. In addition, %F data should be reported as a nested hierarchy of taxonomic levels which allows these data to be readily standardised across studies and used in meta-analyses.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fisheries Research - Volume 196, December 2017, Pages 126-140
نویسندگان
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