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User-Friendly Multivariate Analysis for Linking Predictive Water Quality Models to Biological Data

User-Friendly Multivariate Analysis for Linking Predictive Water Quality Models to Biological Data. Janna Owens. Water Quality Monitoring. Physical, chemical and biological assessments Calculate environmental impacts

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User-Friendly Multivariate Analysis for Linking Predictive Water Quality Models to Biological Data

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  1. User-Friendly Multivariate Analysis for Linking Predictive Water Quality Models to Biological Data Janna Owens

  2. Water Quality Monitoring • Physical, chemical and biological assessments • Calculate environmental impacts • Create models of water processes as predictive tools for physical/chemical data • Ideally, a compatible framework would integrate biological data

  3. PRIMER software • Plymouth Research Routines in Multivariate Ecological Research • Coherent strategy for interpretation of community structure • Wide range univariate/multivariate routines • Ease of use and comprehension

  4. Predictive Model

  5. Aquatic Biological Modeling • Deterministic models do not directly evaluate larger biological organisms • Won’t simulate many aspects of complex community • Statistical data modeling integrates biological and environmental variables • Basic methodologies: Cluster and Ordination

  6. techniques to classify objects Biological classification verified by environmental variables Difficult to use with environmental gradients Requires extensive database Mutivariate data presented in 2 dimensions Sample (dis)similarity represented by proximity in space Determines variables that affect biological data Spatial distortion possible without caution Cluster vs. Ordination

  7. Cluster Analysis ?

  8. Hierarchical Cluster Unstable Stable

  9. Ordination Analysis Multi-Variable

  10. PCA PC Eigenvalue %Variation Cum.%Variation 1 199 39.0 39.0 2 130 25.5 64.5 3 68.6 13.4 77.9 4 35.7 7.0 84.9 5 20.3 4.0 88.9

  11. PCA cont.

  12. MDS Stable sites: Less Urbanization Unstable sites: More Urbanization

  13. MDS Trajectory

  14. ANOSIM

  15. Dominance Curves Sites ~ 67% Cumulative Dominance (%) ~ 27% 3 Species rank by abundance

  16. Aggregation   ;-)   ;-)

  17. Phylogenetic Diversity

  18. TAXTEST 95%

  19. Sample Spreadsheet

  20. Applications • More productive data mining • Allow merging of historical and diverse sample efforts • Comparison to a variety of predictive models to assess trends • Universal comprehension

  21. Acknowledgments • US EPA Region IV • Dr. Andrew Simon, USDA, National Sedimentation Lab • Drs. Angus and Marion, UAB • Clarke, K.R. and Warwick, R.M. 1993. Change in Marine Communities: An approach to Statistical Analysis and Interpretation, Bourne Press Ltd., Bournemouth, U.K.

  22. Questions?

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