Quantitative Module I: Using Graphs to Make an Argument with Data. Winter Ecology Week 6 3 March 2011
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1 Quantitative Module I: Using Graphs to Make an Argument with Data Winter Ecology Week 6 3 March 2011
2 Quantitative Modules I: Using Graphs to Make an Argument with Data (this week) II: Hypothesis Testing Statistical Basis for Argument (April) Why are we doing this???
3 Informed citizens need to comprehend quantitative data
4 Your Microhabitat Study For each logger: 70 days x 48 readings/day 3360 readings
5 Different Types of Graphs for Different Jobs Know the Players X-Y Scatter Plot Line Graph Column Graph (Bar Graph) Pie Chart Useful summary of Excel chart types: balsam fir new growth (kg/ ha) the following summer mean daily snow depth (cm) for winter 8% 12% 20% compostion of mixed flocks 60% black-capped chickadee tufted titmouse white-breasted nuthatch golden-crowned kinglet
6 X-Y Scatter Plot Two value axes (two sets of continuous numerical data) new needle biomass (kg/ha) Balsam fir new needle biomass at the end of summer mean daily snow depth (cm) for previous winter
7 Line Plot categorical data (classes, dates etc.) on x-axis and numerical data on y-axis line effectively shows trends 10 significant snowstorms ( 4 inches) in New England # snowstorms state
8 Column Plot categorical data on x-axis and numerical data on y-axis effective for frequency data or summary data (means) significant snowstorms ( 4 inches) in New England 10 # snowstorms state
9 Pie Chart proportional data (add up to 100%, the whole pie) composition of mixed flock 12% 8% black-capped chickadee tufted titmouse 20% 60% white-breasted nuthatch golden-crowned kinglet
10 How to read a graph: A checklist Step One: Describe it. 1. What is represented on the axes? 2. What are the units on the axes? 3. What is the scale of the axes? 4. What do the symbols and legend represent? 5. Are there patterns in the data? Step Two: Interpret it. 1. What conclusions can you draw? Adapted from Picone et al. (2007) in the Ecological Society of America s Teaching Issues and Experiments in Ecology 5:1-54.
11 1. What is represented on the axes? a quasi-hypothetical case study new needle biomass (kg/ha) Balsam fir new needle biomass at the end of summer mean daily snow depth (cm) for previous winter x-axis = independent variable (manipulated or chosen to study its potential effect) y-axis = dependent variable ( depends upon/responds to the independent variable)
12 2. What are the units on the axes? new needle biomass (kg/ha) Balsam fir new needle biomass at the end of summer mean daily snow depth (cm) for previous winter
13 3. What is the scale of the axes? smaller scale: emphasizes trend new needle biomass (kg/ha) Balsam fir new needle biomass at the end of summer larger scale: deemphasizes trend new needle biomass (kg/ha) mean daily snow depth (cm) for previous winter
14 4. What do the symbols and legend represent? 450 Balsam fir new needle biomass at the end of summer balsam fir new growth (kg/ha) the following summer Michigan Maine mean daily snow depth (cm) for winter
15 5. Are there patterns in the data? For scatter plots does the dependent variable increase or decrease linearly with the independent variable? Or is it more complex? new needle biomass (kg/ha) Balsam fir new needle biomass at the end of summer mean daily snow depth (cm) for previous winter
16 5. Are there patterns in the data? For column plots, which categories are higher/lower than others? How much variation is there, relative to differences in column heights? balsam fir new growth (kg/ha) the following summer (mean ± S.D.) Balsam fir new needle biomass at the end of summer mean daily snow depth (cm) for winter
17 Interpretation What can you conclude from the data? new needle biomass (kg/ha) Understand how the data were collected Balsam fir new needle biomass at the end of summer Isle Royale, Michigan 15 years of data mean daily snow depth (cm) for previous winter
18 Observational studies (make use of natural variation in independent variable) can establish correlation (i.e., association). Experimental studies (manipulate independent variable to impose variation) can establish causation. Correlation does not necessarily imply causation!
19 D S C M C Enclosure with randomly assigned treatment locations M D S C D M S D C S D M C C M C S S M D Manipulated Snow Depth Treatments C = control (natural) S = shallow (25 cm) M = medium (50 cm) D = deep (75 cm)
20 Results of Experimental Study Balsam fir new needle biomass at the end of summer balsam fir new growth (kg/ha) the following summer (mean ± S.D.) S (25 cm) C (45 cm) M (50 cm) D (75 cm) mean daily snow depth (cm) for winter
21 What s going on? In years with deeper snow, greater wolf predation on moose. Fewer moose, more fir growth, due to decreased browsing. new needle biomass (kg/ha) mean daily snow depth (cm) for previous winter
22 In-class Exercise with Excel: Lake Mendota, Wisconsin years of ice records duration of winter ice coverage Lake Mendota The North Temperate Lakes LTER Program Open Excel spreadsheet in Moodle
23 Housatonic River Homework Assignment Shepaug Dam, Southbury, CT Eagle Counts: Last week in December mid March Wednesday Saturday Sunday therefore 34 potential observation days/winter Six winters: 2004/2005 = 2005 winter to 2009/2010 = 2010 winter Excel spreadsheet on Moodle: Shepaug Eagle Data homework.xls and handout with questions
24 How can this graph be improved?
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This is the drill hole location:
General Guidelines: All files should be built in 4-color (CMYK) mode only. If your job requires spot color inks or spot varnishes, please contact a GreenerPrinter Customer Service Representative at: csr@greenerprinter.com
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