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The Benthic Exchange of O2, N2 and Dissolved Nutrients Using Small Core Incubations
10:11

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Published on: August 3, 2016

Nutrient cycling in a simulated pond ecosystem.

B Mukherjee1, D Mukherjee, M Nivedita

  • 1Section of Environmental Biology, P.G. Department of Zoology, Ranchi College, Ranchi, India. bm_ebag@rediffmail.com

Journal of Environmental Biology
|February 4, 2010
PubMed
Summary
This summary is machine-generated.

This study models inorganic carbon and nutrient cycling in a simulated pond, revealing balanced ecosystem processes. Computational modeling aids in understanding and managing aquatic systems, crucial for assessing eutrophication impacts.

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Last Updated: Jun 16, 2026

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09:38

Understanding Dissolved Organic Matter Biogeochemistry Through In Situ Nutrient Manipulations in Stream Ecosystems

Published on: October 29, 2016

Area of Science:

  • Ecosystem dynamics
  • Biogeochemical cycling
  • Aquatic ecosystem modeling

Background:

  • Mathematical ecosystem modeling requires detailed knowledge of subsystems and rate processes.
  • Cultural eutrophication complicates assessment of aquatic bodies due to varied inputs.
  • Understanding background conditions and water quality is vital for aquatic system management.

Purpose of the Study:

  • To analyze inorganic carbon and nutrient transfer rates and budgets in a simulated pond.
  • To compare simulated pond dynamics with aquatic bodies affected by cultural eutrophication.
  • To demonstrate the utility of computational modeling for ecosystem analysis and management.

Main Methods:

  • Utilized a compartmental model of biogeochemical cycling.
  • Incorporated external variables: light and temperature.
  • Included state variables: biotic and abiotic compartments.
  • Studied key processes: photosynthesis, respiration, and decomposition.

Main Results:

  • The simulated pond exhibited perfect carbon cycling, with withdrawal rates equaling return rates.
  • Approximately 0.284 millimoles/liter of carbon was withdrawn daily for primary production and returned via respiration and decomposition.
  • Nitrate and phosphate concentrations correlated with carbon utilization and system productivity.

Conclusions:

  • Computational modeling is valuable for analyzing and managing ecosystems, aiding in process control and optimization.
  • The simulated system maintained dynamic equilibrium through balanced nutrient cycling.
  • Findings provide insights into aquatic ecosystem functioning and the impacts of eutrophication.