دانلود مقاله ISI انگلیسی شماره 161856
ترجمه فارسی عنوان مقاله

تأثیر بارهای فسفر داخلی و ساختار غذای وب بر بهبود دریاچه ی عمیق از یوتروفیزاسیون

عنوان انگلیسی
Effects of internal phosphorus loadings and food-web structure on the recovery of a deep lake from eutrophication
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
161856 2017 10 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Great Lakes Research, Volume 43, Issue 2, April 2017, Pages 255-264

پیش نمایش مقاله
پیش نمایش مقاله  تأثیر بارهای فسفر داخلی و ساختار غذای وب بر بهبود دریاچه ی عمیق از یوتروفیزاسیون

چکیده انگلیسی

We used monitoring data from Lake Lugano (Switzerland and Italy) to assess key ecosystem responses to three decades of nutrient management (1983–2014). We investigated whether reductions in external phosphorus loadings (Lext) caused declines in lake phosphorus concentrations (P) and phytoplankton biomass (Chl a), as assumed by the predictive models that underpinned the management plan. Additionally, we examined the hypothesis that deep lakes respond quickly to Lext reductions. During the study period, nutrient management reduced Lext by approximately a half. However, the effects of such reduction on P and Chl a were complex. Far from the scenarios predicted by classic nutrient-management approaches, the responses of P and Chl a did not only reflect changes in Lext, but also variation in internal P loadings (Lint) and food-web structure. In turn, Lint varied depending on basin morphometry and climatic effects, whereas food-web structure varied due to apparently stochastic events of colonization and near-extinction of key species. Our results highlight the complexity of the trajectory of deep-lake ecosystems undergoing nutrient management. From an applied standpoint, they also suggest that [i] the recovery of warm monomictic lakes may be slower than expected due to the development of Lint, and that [ii] classic P and Chl a models based on Lext may be useful in nutrient management programs only if their predictions are used as starting points within adaptive frameworks.