کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1723343 1520501 2016 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Ecological rehabilitation prediction of enhanced key-food-web offshore restoration technique by wall roughening
ترجمه فارسی عنوان
پیش بینی توانبخشی زیست محیطی با استفاده از روش بهبود جایگزین کلیدواژگان غذایی وب توسط شستشوی دیوار
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات اقیانوس شناسی
چکیده انگلیسی


• Three techniques were proposed to enhance the key-food-web ecological restoration.
• The effect of present enhanced restoration was evaluated by Ecopath model and ocean health index.
• The maturity and health of the enhanced restoration ecosystems were improved comparing to the original ecosystem.
• The enhanced technique with the integration of artificial reefs and hard slope roughing is the best.

The enhanced key-food-web offshore restoration technique by wall roughening is proposed in this approach. Three kinds of wall roughening, i.e. artificial reefs, hard slope roughing and the integration of artificial reefs and hard slope roughing are applied to enhance the original key-food-web offshore restoration technique. The effects of ecological rehabilitation of the proposed enhanced key-food-web offshore restoration technique are predicted by the models of Ecopath model and ocean health index. The results indicate that the ecological rehabilitation of the enhanced key-food-web offshore restoration technique with different wall roughening is better than that of the original one. Among them, the enhanced key-food-web offshore restoration technique with the integration of artificial reefs and hard slope roughing is the best. After using it, the restored offshore ecosystem is the most mature, and the ocean health index is increased to 87.1 or 87.3 with respect to the case of 2% or 0.57% artificial reef for the conservative or optimistic analysis.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ocean & Coastal Management - Volume 128, August 2016, Pages 1–9
نویسندگان
, , ,