Digital Analysis of Quadrats to Determine Percent Cover of Metaphyton in Conesus Lake, NY Alternate method for accurate determination of percent cover.

Slides:



Advertisements
Similar presentations
Sediment Phosphorus and Release Rates Daniel White Department of Environmental Science and Biology SUNY Brockport.
Advertisements

Review Feb Adapted from: Taylor, S. (2009). Statistical Analysis. Taken from:
ANOVA and Linear Models. Data Data is from the University of York project on variation in British liquids. Data is from the University of York project.
Determining the Impact of Stream Nutrient Loading on Metaphyton in Littoral Areas of Conesus Lake Peter D’Aiuto Department of Biological Sciences S.U.N.Y.
CALCULATING DAILY PARTICULATE PHOSPHORUS LOADS FROM DISCRETE SAMPLES AND DAILY FLOW DATA METHODS RESULTS * y= (flow) – 2.247; * 1 Y= 0.052(flow)^0.1947;
Identification of E. coli Sources in the Conesus Lake Watershed Using PCR Jason Somarelli Advisor: Dr. Joseph Makarewicz SUNY Brockport Department of Environmental.
Identification of E. coli Sources in the Conesus Lake Watershed Using PCR Jason Somarelli Advisor: Dr. Joseph Makarewicz SUNY Brockport Department of Environmental.
Research Methods for Counselors COUN 597 University of Saint Joseph Class # 8 Copyright © 2015 by R. Halstead. All rights reserved.
Distribution and Biomass of Macrophytes and Metaphyton Associated with Streams Project Goals: Characterize changes in macrophyte biomass and bed standing.
Intermediate methods in observational epidemiology 2008 Quality Assurance and Quality Control.
Ranked Set Sampling: Improving Estimates from a Stratified Simple Random Sample Christopher Sroka, Elizabeth Stasny, and Douglas Wolfe Department of Statistics.
Statistical Concepts (continued) Concepts to cover or review today: –Population parameter –Sample statistics –Mean –Standard deviation –Coefficient of.
B a c kn e x t h o m e Classification of Variables Discrete Numerical Variable A variable that produces a response that comes from a counting process.
Timed. Transects Statistics indicate that overall species Richness varies only as a function of method and that there is no difference between sites.
2.3. Measures of Dispersion (Variation):
AP Biology Intro to Statistic
Distribution and Biomass of Macrophytes Growing Near Streams.
The sampling and preparation of algae Maria Kahlert.
Measuring Stream Microbiology:
6 - 1 Basic Univariate Statistics Chapter Basic Statistics A statistic is a number, computed from sample data, such as a mean or variance. The.
Data Collection & Processing Hand Grip Strength P textbook.
Topic 6.1 Statistical Analysis. Lesson 1: Mean and Range.
Welcome to SUNY FLORIDA. *The CSREES National Water Quality Program enabled the formation and linkage of 10 Regional Water Quality Coordination projects.
Why Is It There? Getting Started with Geographic Information Systems Chapter 6.
Sec 3 SMTP Research Module ADVANCED STATISTICS Mrs Goh Cheng Wai.
Sensing for Robotics & Control – Remote Sensors R. R. Lindeke, Ph.D.
Automated CBC Parameters
Chapter 2 Describing Data.
MATH IN THE FORM OF STATISTICS IS VERY COMMON IN AP BIOLOGY YOU WILL NEED TO BE ABLE TO CALCULATE USING THE FORMULA OR INTERPRET THE MEANING OF THE RESULTS.
Ch4 Describing Relationships Between Variables. Section 4.1: Fitting a Line by Least Squares Often we want to fit a straight line to data. For example.
Stream Monitoring of Selected Sub-watersheds of Conesus Lake.
A Survey of Diel-Vertical Migration of Freshwater Zooplankton at Pinchot Lake Eric Holtzapple Department of Biological Sciences, York College of Pennsylvania.
STA 286 week 131 Inference for the Regression Coefficient Recall, b 0 and b 1 are the estimates of the slope β 1 and intercept β 0 of population regression.
ICCS 2009 IDB Workshop, 18 th February 2010, Madrid 1 Training Workshop on the ICCS 2009 database Weighting and Variance Estimation picture.
The Single-Sample t Test Chapter 9. t distributions >Sometimes, we do not have the population standard deviation. (that’s actually really common). >So.
CPE 619 One Factor Experiments Aleksandar Milenković The LaCASA Laboratory Electrical and Computer Engineering Department The University of Alabama in.
Education 793 Class Notes Inference and Hypothesis Testing Using the Normal Distribution 8 October 2003.
Supplementary data 2: Reproducibility of metabolite MSI Reproducibility of MSI data was evaluated by mean ± standard deviation (5 biological replications).
Introductory Statistics for Laboratorians dealing with High Throughput Data sets Centers for Disease Control.
1 Probability and Statistics Confidence Intervals.
Above and Below ground decomposition of leaf litter Sukhpreet Sandhu.
Light Microscopy. The light microscope is a common and widely used tool that has been used to look at biological samples for many years and is still very.
Point Count System for Measuring Ground Cover from Digital Photos. Edward B. Rayburn West Virginia University 1078 Ag. Science Morgantown, WV
Class Seven Turn In: Chapter 18: 32, 34, 36 Chapter 19: 26, 34, 44 Quiz 3 For Class Eight: Chapter 20: 18, 20, 24 Chapter 22: 34, 36 Read Chapters 23 &
Chapter 11 Summarizing & Reporting Descriptive Data.
Estimating standard error using bootstrap
(Category, Teacher, Period) Student Name Banneker AHS 2017
Control Charts Definition:
Organizing Data.
Statistical Process Control (SPC)
Attribute Control Charts
Experimental Power Graphing Program
Inverse Transformation Scale Experimental Power Graphing
AP Biology Intro to Statistics
Research Statistics Objective: Students will acquire knowledge related to research Statistics in order to identify how they are used to develop research.
CHAPTER 1: Picturing Distributions with Graphs
Regression Computer Print Out
Effect of Measurement Error on SPC
Sampling Distribution
Sampling Distribution
Basic Training for Statistical Process Control
Basic Training for Statistical Process Control
AP Biology Intro to Statistic
AP Biology Intro to Statistic
AP Biology Intro to Statistic
Chapter 11: Measuring Research Variables
Intermediate methods in observational epidemiology 2008
2.3. Measures of Dispersion (Variation):
Data Literacy Graphing and Statisitics
Measurement System Analysis
Presentation transcript:

Digital Analysis of Quadrats to Determine Percent Cover of Metaphyton in Conesus Lake, NY Alternate method for accurate determination of percent cover Michael Pagano Dr. Sid Bosch State University of New York at Geneseo Summer 2003

Problem at Conesus Lake- Metaphyton Correlation between growth of metaphyton with nutrient loading from streams

Problem with determination of percent cover Metaphyton biomass hard to estimate Entangled in Milfoil, can’t separate Percent Cover best estimation

Traditional Method Visual determination of cover Stationed off side of boat Dependant on researcher Lack of precision

Alternate Method Construction of new quadrat (.5x.5m) to enable use of digital camera to capture image of algae Camera mounted Tri-pod Polarized lens used to reduce glare

Alternate Method Digital Pictures (3.2mp) uploaded onto computer Images enhanced using Kodak Photo Enhancer

Alternate Method Images then analyzed using Image J to determine percent cover Percent Cover= Total Cover Total Area

Results Error bars indicate one standard deviation above and below mean Bars above represent results of Tukey’s Statistical Analysis ANOVA p<0.05

Results Graywood 2003, Cottonwood 2002, Sandpoint 2002, & Sutton 2002 not used due to sampling error which included date and condition of weed beds. Numbers above bars represent one standard deviation

Results No loading data for McPherson, Graywood Gully not used for statistical purposes because unrepresentative sampling period; Error Bars (+/- 1 S.D.) to small to see P=0.06

Metaphyton Cover Determination Is Digital Analysis more accurate than traditional visual estimation?

Results Coefficient of Variation –CV= S.D./Mean –Measure of Relative Variability OrganismCoefficient of Variation Plankton0.70 Benthic Organisms (grab sample)0.40 Benthic Organisms (Surber sampler, counts) 0.60 Benthic Organisms (Surber sampler, biomass) 0.80 Terrestrial Organisms (Roadside Counts) 0.80 Shellfish0.40

Alternate Method Mean C.V. 2001= = =

Conclusions No consistent trends seen between weed beds Correlation seen between metaphyton percent cover and summer SRP loading, 2003 Alternate method more accurate for determination of percent cover, but more replicates needed

Special Thanks Dr. Sid Bosch, Mentor and Project Advisor Megan Mongiovi, Jamie Romieser, Evan Zynda, Student Researchers SUNY Geneseo Biology