This document describes three case studies that demonstrate the use of generalized additive models (GAMs) to analyze environmental monitoring data. In the first case study, a GAM is used to unify data from a short-term water quality monitoring program with data from an established long-term program in an Australian estuary. The second case study uses a GAMM to evaluate spatial patterns in biomonitoring data while accounting for variability in animal size. The third case study uses a GAMM to explore trends in continuous oceanographic monitoring data while accounting for temporal autocorrelation. Overall, the case studies highlight how GAMs provide a flexible framework for uncovering nonlinear trends in complex, multivariate environmental monitoring datasets.

Richards Et Al (2010) - Using Generalized Additive Models To Assess, Explore and Unify Environmental Monitoring Datasets PDF

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