کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
8846137 1617379 2018 11 صفحه PDF سفارش دهید دانلود رایگان
عنوان انگلیسی مقاله ISI
Causal networks reveal the dominance of bottom-up interactions in large, deep lakes
ترجمه فارسی عنوان
شبکه های علمی حاکی از تسلط بر تعاملات پایین به بالا در دریاچه های بزرگ و عمیق است
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کلمات کلیدی
دینامیک غیر خطی، نقشه برداری متقابل، علیت، تعامل محیطی، شبکه، کنترل پایین،
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک بوم شناسی، تکامل، رفتار و سامانه شناسی
چکیده انگلیسی
Ecological dynamics often exhibit significant temporal variability and sudden shifts that characterize their non-equilibrium and nonlinear nature, challenging our ability to understand and predict their trajectories. Among a set of ecological time series originating from the long-term monitoring of three large and deep lakes, nonlinear forecasting methods (Simplex projection and S-map) indicated that most of the time series exhibited hallmarks of complex dynamics in the form of nonlinear behaviors. Convergent Cross Mapping (CCM) was used to estimate the causal relationships among these time series by considering different time lags. The significant causal relationships were then used to construct causal networks from which nodes were characterized using PageRank and CheiRank. For the three lakes, the dominance of bottom-up control was revealed and was mostly indirect (i.e., nutrient-forcing zooplankton). This result likely evidences the transitivity of the causal relationships obtained by CCM as well as the mixed phytoplankton diet of zooplankton species limiting the identification of causal relationships among these two ecological components. Complementarily, the consistence of causal relationships for the different time lags may highlight a temporal transitivity by which the instantaneous causal signal was transmitted over time. The dual representation of both PageRank and CheiRank provided a straightforward classification of each node and enabled their thorough implications in the information flow within the causal networks. The complementary use of CCM and network metrics constituted an efficient way to delineate ecological causation using a high-resolution time series, for which linear methods performed poorly, and provided insights into the dynamic hierarchy of the different ecological variables in aquatic ecosystems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ecological Modelling - Volume 368, 24 January 2018, Pages 136-146
نویسندگان
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