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UA ATMO 529 - Lecture Notes

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Investigation of Spatial Mosquito Population Trends Using EOF Analysis: Model Vs Count Data in Pasco County FloridaPresentation OutlineObjectivesMosquitoes: Aedes AegyptiMosquitoes: Culex QuinquefasciatusModeling MosquitoesConceptual Model (DyMSiM) Dynamic Mosquito Simulation ModelDataSample of Model RunRegression + Correlation CoefficientsCorrelation/Pearson CoefficientsEOF AnalysisSpring North TestEOF 1 for SpringEOF 2 for SpringSummer North TestEOF 1 for SummerFall North TestEOF 1 for FallEOF 2 for FallConclusionsModel LimitationsSlide 23Investigation of Spatial Investigation of Spatial Mosquito Population Trends Mosquito Population Trends UsingUsingEOF Analysis: Model Vs EOF Analysis: Model Vs Count Data in Pasco Count Data in Pasco County FloridaCounty Florida Cory MorinCory MorinPresentation OutlinePresentation OutlineOutline of Objectives of StudyOutline of Objectives of StudyBackground of Research – Why Study Background of Research – Why Study Mosquitoes?Mosquitoes?Introduction to DyMSiMIntroduction to DyMSiMModel Runs + Correlation and Model Runs + Correlation and Regression CoefficientsRegression CoefficientsEOF AnalysisEOF AnalysisConclusions and DiscussionConclusions and DiscussionObjectivesObjectivesValidate Model (DyMSiM) with Validate Model (DyMSiM) with Mosquito Count DataMosquito Count Data–Using 25 Locations within Pasco County Using 25 Locations within Pasco County Florida (1995-1997,2002-2004)Florida (1995-1997,2002-2004)–Correlation Coefficients (Daily)Correlation Coefficients (Daily)–Regression Coefficients (Daily, Weekly, Regression Coefficients (Daily, Weekly, and Monthly)and Monthly)–EOF Analysis of Model and Trap DataEOF Analysis of Model and Trap DataSpring, Summer, and Fall (weekly)Spring, Summer, and Fall (weekly)Mosquitoes: Mosquitoes: Aedes AegyptiAedes AegyptiCharacteristicsCharacteristics–Urban, Container Urban, Container Breeding MosquitoBreeding Mosquito–Tropical HabitatTropical Habitat–Dengue Fever VectorDengue Fever VectorDengue FeverDengue Fever–100 Million Cases a Year 100 Million Cases a Year WorldwideWorldwide–4 Serotypes without 4 Serotypes without Cross Immunity Cross Immunity –Dengue Hemorrhagic Dengue Hemorrhagic Fever from Multiple Fever from Multiple InfectionsInfectionsPicture taken from http://www.interet-general.info/IMG/Aedes-Aegypti-2.jpgPicture from http://www.cdc.gov/ncidod/dvbid/dengue/map-distribution-2005.htmMosquitoes: Mosquitoes: Culex QuinquefasciatusCulex QuinquefasciatusImage taken from http://www.lahey.org/Medical/InfectiousDiseases/WestNileVirus.aspCharacteristicsCharacteristics–Urban MosquitoUrban Mosquito–Feeds on Humans Feeds on Humans and Animalsand Animals–West Nile Virus West Nile Virus VectorVectorWest Nile VirusWest Nile Virus–Arrived in New York Arrived in New York 19991999–Symptoms: Mild Symptoms: Mild Fever-EncephalitisFever-EncephalitisData from CDC.govModeling MosquitoesModeling MosquitoesInputsInputs–Temperature, Precipitation, LatitudeTemperature, Precipitation, Latitude–Evaporation Derived (Hamon’s Equation) Evaporation Derived (Hamon’s Equation) –Irrigation/Land Cover Irrigation/Land Cover Governing RulesGoverning Rules–Development Rates Development Rates –Death Rates Death Rates –Reproductive RatesReproductive Rates–Larval/Pupa CapacityLarval/Pupa Capacity–Water Flux (sources and sinks)Water Flux (sources and sinks)Conceptual Model (DyMSiM) Dynamic Conceptual Model (DyMSiM) Dynamic Mosquito Simulation ModelMosquito Simulation ModelDataDataTemperature Data was Temperature Data was Obtained from the Obtained from the National Climate Data National Climate Data Center Center Precipitation Data was Precipitation Data was Obtained from the Obtained from the National Climate Data National Climate Data Center and The Pasco Center and The Pasco County Vector and County Vector and Mosquito Control DistrictMosquito Control DistrictMosquito Data was Mosquito Data was Obtained from the Pasco Obtained from the Pasco County Vector and County Vector and Mosquito Control DistrictMosquito Control DistrictImage from http://pix.epodunk.com/locatorMaps/fl/FL_8834.gifSample of Model RunSample of Model RunRegression + Correlation Regression + Correlation CoefficientsCoefficientsRegression CoefficientRegression Coefficient–Best fit line in the data that minimizes Best fit line in the data that minimizes the sum of the square of the errorthe sum of the square of the error–Shows how the magnitude of one Shows how the magnitude of one variable changes with anothervariable changes with anotherCorrelation CoefficientCorrelation Coefficient–Calculated from the square root of the Calculated from the square root of the variance explainedvariance explained–Describes the relationship between two Describes the relationship between two variables (Range from -1 to 1)variables (Range from -1 to 1)Correlation/Pearson CoefficientsCorrelation/Pearson CoefficientsTime Span D-ValueAverage CorrelationSignificant (0.95)1995-1997 0.4111 0.1343 Yes2002-2004 0.3821 0.1190 YesTime SpanDaily RegressionWeekly RegressionMonthly Regression1995-1997 0.0910 0.7337 0.93542002-2004 0.0695 0.7068 1.0270EOF AnalysisEOF AnalysisUsed to Analyze Spatial Patterns in a Used to Analyze Spatial Patterns in a DatasetDatasetThe 1st EOF Shows the Largest The 1st EOF Shows the Largest Fraction of Variance Explained in a Fraction of Variance Explained in a DatasetDataset–Found from Eigenvalues and Found from Eigenvalues and EigenvectorsEigenvectors–Only a limited number of EOFs are Only a limited number of EOFs are Significant (North Test)Significant (North Test)Spring North TestSpring North TestNorth Test: Spring Trap Data00.10.20.30.40.50.60.70.80.910 1 2 3 4 5 6 7 8 9 10EigenvalueVariance ExplainedVariance Explainedupper confidence 0.95lower confidence -0.95North Test: Spring Model Data00.10.20.30.40.50.60.70.80.910 1 2 3 4 5 6 7 8 9 10EigenvalueVariance ExplainedVariance Explainedupper confidence 0.95lower confidence -0.95- The first two EOFs in both Whisker Plots are SignificantEOF 1 for SpringEOF 1 for Spring1st EOF for Trap Data1st EOF for Model DataEOF 2 for SpringEOF 2 for Spring2nd EOF Trap Data2nd EOF Model DataSummer North TestSummer North TestNorth Test: Summer Model Data00.20.40.60.811.20 1 2 3 4 5 6 7 8 9 10EigenvalueVariance ExplainedVariance Explainedupper confidence 0.95lower confidence -0.95North Test: Summer Trap


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