کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6961982 | 1452244 | 2018 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Model-based analysis of the relationship between macroinvertebrate traits and environmental river conditions
ترجمه فارسی عنوان
تجزیه و تحلیل مدل مبتنی بر رابطه بین صفات ماکرومتری توبیت و شرایط محیطی رودخانه
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
رگرسیون دو جانبه منفی، استراتژی تغذیه، سرعت جریان جزیره ی استوایی، مدل های خطی کلی، فیلیپین،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزار
چکیده انگلیسی
Aquatic macroinvertebrates, 18 physical-chemical water characteristics and 30 hydromorphological variables were assessed at 85 locations on Leyte island, Philippines. Biological traits derived from literature were linked to the biological samples based on four different trait estimation methods. These data were used to determine the relation with river characteristics using negative binomial regression. At least five feeding habit modalities were associated with conductivity, velocity, pH, temperature, ammonium-N concentrations, and sediment. The various methods of estimating trait abundance differ in determined major patterns and ecological implications. Therefore, the estimation method used should be explicitly described in trait-related papers to avoid misinterpretation. Trait abundance-environment relationships can be linear or non-linear and therefore a careful selection of the functional relationship should be performed. The process of extracting knowledge from data is of paramount importance as relevant ecological insights were extracted providing insights on flow, wastewater and nutrient management in the rivers.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Environmental Modelling & Software - Volume 106, August 2018, Pages 57-67
Journal: Environmental Modelling & Software - Volume 106, August 2018, Pages 57-67
نویسندگان
Marie Anne Eurie Forio, Peter L.M. Goethals, Koen Lock, Victor Asio, Marlito Bande, Olivier Thas,