Journal article

Publication year: 2004

Pages: 189-194

Journal: Ecological Modelling

Volume number: 175

Issue number: 2

ISSN: 0304-3800

DOI Link: https://doi.org/10.1016/j.ecolmodel.2003.10.010

Publisher: Elsevier

Abstract: 
An artificial neural network (ANN) was used to simulate nitrous oxide (N2O) emissions from an intensive grassland ecosystem in New Zealand. Daily N2O emitted was simulated as a function of six input variables of daily rainfall, soil moisture content and temperature, soil nitrate (NO3-), ammonium (NH4+) and total inorganic nitrogen content. Results showed that the ANN was able to calibrate itself to within +/-0.77% of measured N2O values in the training data set, and within 2.0% of values used in the validation data set. This was well within the range of the calculated uncertainties (CV = 10-43%) of the measured N2O emissions in the field, and demonstrated that ANNs are a viable toot for simulating complex and highly variable biological systems. (C) 2003 Elsevier B.V. All rights reserved.

Harvard Citation style: Ryan, M., Müller, C., Di, H. and Cameron, K. (2004) The use of artificial neural networks (ANNs) to simulate N2O emissions from a temperate grassland ecosystem, Ecological Modelling, 175(2), pp. 189-194. https://doi.org/10.1016/j.ecolmodel.2003.10.010

APA Citation style: Ryan, M., Müller, C., Di, H., & Cameron, K. (2004). The use of artificial neural networks (ANNs) to simulate N2O emissions from a temperate grassland ecosystem. Ecological Modelling. 175(2), 189-194. https://doi.org/10.1016/j.ecolmodel.2003.10.010