Using Generalized Additive Models to Assess, Explore and Unify Environmental Monitoring Datasets

File Size Format
64364_1.pdf 762Kb Adobe PDF View
Title Using Generalized Additive Models to Assess, Explore and Unify Environmental Monitoring Datasets
Author Richards, Russell; Tomlinson, Rodger Benson; Chaloupka, Milani
Publication Title Proceedings of the iEMSs Fifth Biennial Meeting: International Congress on Environmental Modelling and Software (iEMSs 2010)
Editor David A. Swayne, Wanhong Yang, A. A. Voinov, A. Rizzoli, T. Filatova
Year Published 2010
Place of publication Ottawa
Publisher iEMSs
Abstract An on-going challenge for decision makers is the interpretation of temporal trends from monitoring data given that environmental processes often generate complex data that are multivariate and potentially nonlinear. Generalized additive models (GAMs) is a well-suited modelling framework for uncovering such trends and unifying datasets. This approach allows flexible specification of regression splines to represent the functional relationships between a response variable (the parameter of interest) and a suite of temporal and spatial covariates that can be continuous or discrete using a link function and smooth functions of the covariates. We highlight the utility of using GAMs through three case studies. The first highlights the use of a GAM to unify the findings of an established longterm water quality-monitoring program with those of a focused short-term monitoring program. In the second, a GAM is used to evaluate the spatial patterns in a biomonitoring dataset whilst simultaneously accounting for variability in oyster size, which can have a confounding effect on such data. The final case study focuses on a 12 month continuous monitoring program of oceanographic data as part of an evaluation of the environmental conditions for a desalination plant intake pipe. The context for these studies is predominantly water quality in the coastal zone, however the benefits and widespread application to other research areas is clearly evident.
Peer Reviewed Yes
Published Yes
Publisher URI
Copyright Statement Copyright remains with the authors 2010. The attached file is reproduced here in accordance with the copyright policy of the publisher. For information about this conference please refer to the conference’s website or contact the authors.
Conference name International Environmental Modelling and Software Society (iEMSs) 2010 International Congress on En
Location Ottawa, Canada
Date From 2010-07-05
Date To 2010-07-08
Date Accessioned 2010-08-13
Language en_US
Research Centre Griffith Centre for Coastal Management
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Environmental Monitoring; Environmental Science and Management
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

Show simple item record

Griffith University copyright notice