Multivariate Analysis of Trace Elements from Coral Cores

Slides:



Advertisements
Similar presentations
Chemical Reactions.
Advertisements

 Single Replacement Reactions + + . General Equation A + BX  AX + B.
Chapter 17 Overview of Multivariate Analysis Methods
1 Multivariate Statistics ESM 206, 5/17/05. 2 WHAT IS MULTIVARIATE STATISTICS? A collection of techniques to help us understand patterns in and make predictions.
Oxidation-Reduction (Redox) Reactions
Intro to Statistics for the Behavioral Sciences PSYC 1900 Lecture 17: Nonparametric Tests & Course Summary.
CHAPTER 30 Structural Equation Modeling From: McCune, B. & J. B. Grace Analysis of Ecological Communities. MjM Software Design, Gleneden Beach,
The Effect of Non-Composted and Composted Soil on Nutrient Concentrations in Green Beans By Nicol, Scott, and Jenn.
Ionisation Energy. Definition of the first ionisation energy The energy required to remove one mole of electrons from one mole of gaseous atoms to form.
Figure from Press and Seiver?. From Horowitz et al., 1990; Horowitz, 1991.
Census A survey to collect data on the entire population.   Data The facts and figures collected, analyzed, and summarized for presentation and.
Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey All rights reserved. Introductory Chemistry, Third Edition By Nivaldo J.
Analysis of Wear Metals in Lubricating Oil ICP-OES & ASTM Methodology Advanced Research Center 106 Access Rd, Suite 3 Norwood, MA Slide.
Principal Component Analysis Bamshad Mobasher DePaul University Bamshad Mobasher DePaul University.
Examining Relationships in Quantitative Research
Available at Chapter 13 Multivariate Analysis BCB 702: Biostatistics
Activity Series A method for predicting reactions.
Bill Ringer Balance the follwing equation and pridict the type of reaction a. Ca + N > Ca3N2 b. Cu2S > Cu +S c. NaBr.
Reactions Reference. Solubility Rules 1.All nitrates, acetates, and chlorates are soluble. 2.All chlorides, bromides, and iodides are soluble except for.
Project Presentation Template (May 6)  Make a 12 minute presentation of your results (14 students ~ 132 mins for the entire class) NOTE: send ppt by mid-night.
13.2a Developing a Redox table.  the relative reactivity of metals can be used to determine which redox reactions are spontaneous In all redox reactions,
Always Ox always change during redox reactions: Oxidation Increase Ox = Oxidation Reduction Decrease Ox = Reduction It’s a redox reaction if:element →
Multivariate Analysis and Data Reduction. Multivariate Analysis Multivariate analysis tries to find patterns and relationships among multiple dependent.
Reactions of Metals. Reactions of Metals with H 2 O The metal is the anode and will be oxidized. 2H 2 O + 2e-  2OH - + H 2 E° = V Mg  Mg 2+ +
Redox Reactions Oxidation - Reduction reactions Terms Oxidation loss of electrons electrons are a product Na --> Na + + e - Reduction gain of electrons.
Multivariate statistical methods. Multivariate methods multivariate dataset – group of n objects, m variables (as a rule n>m, if possible). confirmation.
Edinburgh Sept RIVER RHINE AS A SOURCE OF MICROPOLLUTANTS IN THE CANAL SEDIMENTS OF THE CITY OF DELFT (THE NETHERLANDS) Peter Kelderman *, Yang Xuedong.
Logistic Regression: Regression with a Binary Dependent Variable.
Chapter 12 Understanding Research Results: Description and Correlation
S2 SCIENCE CHEMICAL REACTIONS
Chemical Formula Stoichiometry Review
Bell Ringer Complete and balance each of the following synthesis reactions by writing chemical equations. a. Na + O2→ ______ b. Mg + F2 → ______ a. 4Na.
Fig. 2 Two-dimensional embedding result obtained using nMDS.
CONSTRUCTING RELATIVE REACTIVITY TABLES
Single Replacement, Double Replacement and Combustion Reactions
Kakhramon Yusupov June 15th, :30pm – 3:00pm Session 3
Correlation and Regression
Correlation – Regression
THE TRANSITION METALS.
3 Sets of Rules of Naming Rules
Single Replacement Reactions
Predicting Reactions.
Aim: How do we name binary ionic compounds given the chemical formula
KS4 Chemistry The Periodic Table.
THE TRANSITION METALS.
Reactions of Metals.
Multivarite Analysis Goals
Speed Dating Speed Dating H Na Speed Dating Speed Dating K Be.
Project Presentation Template
המרכז הפדגוגי לעובדי הוראה, ירושלים, אילנה זהר ©
Stranding Patterns in Stenella spp.
Coral Species distribution and Benthic Cover type He’eia HI
Multivariate Analysis on Stenella Longirostris Pathology Reports in the Main Hawaiian Islands Haley Boyd.
سامانه مدیریت آزمایشگاه‌های دانشگاه یزد
Drill: Ionic bonding Objective:
Edexcel Topic 1: Key concepts in chemistry
Multivariate Analysis of a Carbonate Chemistry Time-Series Study
Dariyus Z Kabraji MARS 6300 Project
Airborne Contaminants from Mining Operations In Arizona
PCA of Waimea Wave Climate
Ionic vs. Covalent Bonding
Dataset: Time-depth-recorder (TDR) raw data 1. Date 2
Naming Ionic Compounds
Multiple Regression – Split Sample Validation
Predicting the Product in Single Replacement Reactions
Chapter 6 Logistic Regression: Regression with a Binary Dependent Variable Copyright © 2010 Pearson Education, Inc., publishing as Prentice-Hall.
Group 1 Group 2 Group 3 Group 5 Group 4 Ag+, Pb2+, Hg22+
What should I know, Mrs. Cooke?
© The Author(s) Published by Science and Education Publishing.
Presentation transcript:

Multivariate Analysis of Trace Elements from Coral Cores Sheena Weller MARS6300 4/24/18

Dataset Timeseries of trace elements for three coral cores Samples Measured as depth downcore (cm) Different sample sizes Variables 21 trace elements Li/Ca, B/Ca, Mg/Ca, Al/Ca, Mn/Ca, Cu/Ca, Zn/Ca, Sr/Ca, Cd/Ca, Ba/Ca, Pb/Ca, U/Ca, Na/Ca, Fe/Ca, V/Ca, Co/Ca, Ni/Ca, Rb/Ca, Mo/Ca, Sn/Ca, Sb/Ca

What trace elements explain the most shared variability? 9 1 2 For all three cores combined For each core separately “The goal of this project was to …” determine the temporal and spatial patterns of shared variability in all trace elements measured, between cores and for each core separately Predictions: H0: H0 = There is no difference between trace elements HA = There is a difference between trace elements

Original Data Matrix - Combination of Three Cores 81 samples (depth downcore) 21 trace element to Ca ratios Quantitative data Core 1: 37 Samples 21 Elements Core 2: 18 Samples Core 9: 26 Samples

Summary Analysis Transformation: Relativization: log (x + 1) general No Outliers, no empty cells, no deleted cells General / sum I propose a log (x+1) transformation first since we have values ranging from 0 – 1500 (used log (x+1) so there are no negative data) Then a general relativization was preformed so that all variables have equal weight The three highest concentrations found across all three cores are U/Ca, B/Ca, and V/Ca Lowest concentrations found across all three cores Mn/Ca, Sn/Ca, and Co/Ca

New Matrix after Transformation and Relativization Ordination Method chosen NMDS Non parametric data

NMDS Analysis Autopilot / medium (50 runs) 2-D solution In order to determine the temporal and spatial patterns of shared variability in all trace elements measured, a non-metric multidimensional scaling (NMDS) analysis was run on elements of the three cores together. P- values Stress reduction rule Final stress 12.184 = according to clarks rule of thumb this data corresponds tp a usable picture Autopilot / medium (50 runs) 2-D solution Final stress: 12.184

NMS Ordination Plot Results Most Variance Explained (tau) Axis 1 Fe, Mn, Cu, Co, Al, Sn, Ba, Cd Axis 2 Cu, Co, Sn, Al Axis 1 explains 78% of the variance and is described by variability in Fe, Mn, Cu, Co, Al, Sn, Cd, Ba Axis 1 and axis 2 are completely independent from each other Second axis explains the difference, more so then the first one, changing more on the second 0-14

Inferences Axis 1 - Fe, Al, Mn, Ba, Cu, Co, Sn, Cd Indicators Al, Mn, Ba, Mg, and Fe: Reflect changes in Sedimentation that are directly related to development Ba, Mn: River discharge, precipitation Axis 2 - Cu, Co, Cd and Sn Indicators of heavy metal Directly related to increasing industrial activity, population, and tourism

Separate NMS Analysis of each Core

Correlations with Main Matrix Core 1 Core 2 Core 9 2-D Axis 1: Al, Mn, Zn, V, Fe, Ba, Pb, U, Mo Axis 2: Co, Cu, Sn, Na, Cd, Fe, Zn 3-D Axis 1: Al, Mn, Zn, Cd, Pb, Fe, V, Sb Axis 2: Cu, V, Co, Mo, Sn Axis 3: Pb, Fe, Mo 2-D Axis 1: Al, Mn, Zn, Fe, V, Co Axis 2: Zn, Fe, Sn, Sb 001 002 009 : all have Al, Mn, Fe (Ba, Cd, Co) 001 and 002 show more similarities – makes sense since there from the same location Have higher concentrations of heavy metals for the resuspended area 001/002 Combined Axis 1 : Fe, Mn, Cu, Co, Al, Sn, Ba, Cd Axis 2: Cu, Co, Sn, Al

Results Core 1 has the highest trace element concentrations, followed by core 2 and then core 9 More similarities between core 1 and core 2 Core 9 has fewer heavy trace elements incorporated Most variability for all three cores explained by Al, Mn, and then Fe Closest to urbanization makes sense since there from the same location, experience similar environmental conditions

Next Step - Reanalysis Follow up with ISA MRPP Non-parametric data H0: There is no difference between trace elements of the tree coral cores Grouping variable: cores Follow up with ISA MRPP is a non para testing the hypothesis of no differences between two or more groups Grouping variable will be the three cores Likely to see that there is a significant difference between the cores Could still do this: Do NMDS on important elements only (Al, Fe, Sn, Mn -> those with high loadings only (top 8-10 elements of axes) Do NMDS on temperature/salinity trace elements