Draft Basic Lesson 4

Studying Topography, Orographic Rainfall, and Ecosystems (STORE)

Basic Lesson 4: Vegetation and Climate

Introduction

Two main factors determine local climate: long-term average precipitation and temperature. As we learned in Basic Lessons 1 through 3, precipitation and temperature are influenced by topography (i.e., elevation). Building on Basic Lessons 1 through 3, this lesson explores how local climate affects vegetation. Figure 1, below, shows a generalized view of how temperature and precipitation are dominant influences controlling the location of ecosystems. Differences in average annual precipitation and temperature (together with soil type) determine the locations of biomes (e.g., tropical, temperate, and cold deserts, grasslands, and forests). Students will use the GIS software to analyze ecosystem data (i.e., predominating vegetation types) obtained from U.S. Geological Survey (USGS) Land Cover Institute’s National Land Cover Dataset (NLCD). The USGS is the world leader in acquiring, processing and distributing remotely sensed data to scientists, policy makers, and educators. Distribution and identification of vegetation communities in this dataset were determined using Landsat Thematic Mapper Imagery. Students look at overlaying vegetation zones (grouped by vegetation communities) on maps of precipitation and temperature, and analyze this data.

Figure 1(Source: Living in the Environment by G. Tyler Miller)

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Objective

To challenge students to explore biomes ranges as they relate to precipitation and temperature.

Requirements

Google Earth software Download “STORE CA Data.kmz” or “STORE Data.kmz”.

Lesson Duration

1/2 class period, 20 to 30 minutes

Part 1: Set-up (ignore if you have already done these steps for a prior STORE lesson)

1. Open Google Earth from your computer. Once Google Earth (GE) is open, click “File” at the top right corner of the Google Earth window, and click on “Open” from the drop down menu. In this window, navigate to the “STORE CA Data.kmz” or “STORE Data.kmz” file downloaded on your computer. Once you have selected the kmz file, click “Open”. (Note: the file names may also include a date, because revisions have been made from time to time).

2. Save “STORE Data” file in GE to “My Places” by dragging and dropping the folder into “My Places” under the “Places” Panel on the right of the screen.

3. Tip before you start: It can get confusing when you have multiple layers selected at once and multiple folders and subfolders open. To avoid confusion, close layers, folders and subfolders you are finished with before opening new ones. To start this lesson, if any layers are open on the map, turn off all of them at once by un-checking the box that is to the left of the "California Study Area Data" folder in Places Panel.

Part 2: Vegetation and Topography

1. Table 1 shows the elevation ranges in meters and feet for the different predominating land cover types in the California study area. The table below lists their elevation ranges in meters and feet.

Table 1:

Land cover Elevation ranges (meters)

Elevation ranges (feet)

Deciduous forest 100-2800 328-9186Shrub scrub 100-3300 328-10827Mixed forest 100-1700 328-5577Grassland-Herbaceous

100-3300 328-10827

Evergreen Forest 100-3200 328-10499Cultivated crops 0-1500 0-4921

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Emergent herbaceous wetlands

0-2700 0-8858

Woody wetlands 0-1900 0-6234

The elevation ranges in meters are also listed in the layer “Elevation Ranges for Land Cover Types within the California Study Area.”

To see the contents of Table 1 on your screen, click the name of the “Elevation Ranges for Land Cover Types within the California Study Area” layer.

Question 1: Based on what you now know about the elevation ranges, identify a type that is likely to have a shrinking habitat in the California Study Area if global warming predictions come true. Then, explain why, using evidence from the map. Hint: Think about what elevation ranges support the different vegetation types and about the topography of the Study Area.

Figure 2. USGS NLCD vegetation overlain on a topographic relief map.

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Part 3: Vegetation and Precipitation

The students will examine the deciduous and evergreen forests in relation to precipitation. For further investigation, they can also examine other types of predominating land cover in the STORE California data set. The students will click on and off each of the vegetation types displaying these feature classes one at a time and compare the vegetation to the underlying “Precipitation Data Recent Ranges of Values” layer to determine the range of precipitation associated with that community.

1. Click the box next to the “Recent Average Annual Precipitation Totals” layer to display it on the map. (Later, as with any layer, you can remove it from your map by clicking the box again). This layer represents the precipitation per year averaged over a 30 year period (1961-1990).

2. Then go to the “Recent Predominating Types of Land Cover” folder (and expand “The Actual Data Showing Recent Predominating Land Cover” and “Broad Predominating Land Cover Ranges” subfolders. To expand the folder, click the box to the far left of the label. Depending on what version of Google Earth you have, the box will have either a “+” sign in it or a carrot ( ) facing right. Checking the “+” sign turns it into a “-“ sign and checking the carrot makes it appear face down ( ).

3. Also, expand the subfolder “Broad Predominating Land Cover Ranges” in the same way. Names of layers for all the different type of land cover such as Deciduous Forest will now be displayed on the Places panel.

4. Turn ‘on’ the “Deciduous Forest” layers in both folders. On the map, the “actual” Deciduous Forest data will appear as dark blue dots. The broad range of deciduous forest appears in a polygon surrounded by black lines.

5. If you make the precipitation data layer more transparent, you can see the deciduous Forest data more clearly. Do this by first clicking the name of the “Recent Average Annual Precipitation Totals” folder.

Then, select the partially shaded rectangular icon at the bottom of the Places panel, which opens the “transparency bar.” Google Earth will now know that you want to use the bar to change the transparency of the layers in that precipitation folder.

The transparency bar has a gauge. Notice how the gauge is set all the way to the right when you open the precipitation layer. Google Earth does this by default because it presumes that you want the layer to appear on the map in its most opaque (i.e., thickly colored) state.

You can make the layer less opaque (i.e. more transparent) by holding down on the gauge with your mouse, then dragging it to the left as far as you want it to go. Dragging it all the way to the far left will make it completely transparent (i.e. invisible).

6. Study the relationship between where deciduous trees predominate in relation to the average annual precipitation levels. Determine the underlying average annual precipitation ranges for the areas in which the deciduous vegetation type predominate by examining the legend for the precipitation layer.

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If the legend colors are is not clear enough to help you decipher what the colors represent, click one of the precipitation ranges on the map. A pop-up table will appear indicating the precipitation totals for that area. (NOTE: If you do this, make sure that the map area you click only has one layer on it and that this layer is the one you want to bring up a popup window about. Otherwise the popup window that appears might be for that other layer.)

7. Repeat Steps 4-8 for evergreen trees to examine where they predominate in relation to average annual precipitation levels.

Question 2: What range of precipitation totals is associated with high concentration of deciduous forests and how does this compare to the range of precipitation totals associated with high concentrations of evergreen forests?

Part 3: Vegetation and Temperature

Use what you learned in Part 2 of this lesson to explore where deciduous and evergreen trees predominate in relation to July and January temperatures. But first, here is some background information about the STORE temperature data that will help you.

BACKGROUND: The STORE data sets for July temperatures include (a) the average highest July temperature, (b) the average daily highest July temperature, and (c) the average daily July temperature. This background section of the lesson contains some made-up data that you can study to understand what these three statistics mean.

Table 2: Highest July temperatures:

Each of the yearly cells in this table shows the highest temperature reached in a particular location each July over a five-year period from 2005 to 2009. The five-year average is calculated by adding up each of the individual highest temperatures and dividing them by five (i.e., 99 + 101 + 95 + 91 + 96 = 482. 482/5= 96.40°)

In contrast, Table 3 shows the average daily highest temperatures across all the months of July during the same five-year period (2005-2009).

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Table 3: Average daily highest July temperatures:

To calculate the average daily highest July temperature, let us presume that the data collectors use a thermometer to take a temperature reading each hour, yielding 24 readings (from midnight to midnight), and that they then identify the highest temperature. Then, to calculate the average of these highest daily temperatures, they sum them for all 31 days of July, then divide by 31. Lastly, to determine the “average of the averages” over the five-year span, they sum each July’s average highest value, then divide by five.

To calculate the daily averages, let us presume that the data collectors do exactly what was described above for the average daily highest temperatures, except this time the data collectors’ start with the daily average temperature rather than the daily highest temperature. In other words, they start by adding up each of the hourly readings then divide by 24. Then, they do the same averaging over the monthly and yearly spans.

Of course, if you compared the average daily highest July temperature to the average daily July temperature, you would find that the average daily highest temperature would be higher than the

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average daily temperature, unless each hour’s temperature was exactly the same (which would be highly unlikely). It would also be the case that the average daily highest temperature would always be lower than the average monthly highest temperature, unless each daily high was exactly the same. For example, in Table 3, notice that the highest temperature in July 2009 was 96°, but average daily highest was only 87.90°.

The January data for the California Study Area were calculated in a very similar way as the July data; the difference being that the January data include the lowest temperatures rather than the highest temperatures. This is because in California, the highest July temperatures and lowest January temperatures are good approximations of annual temperature extremes, since January is often the coldest month and July is often the warmest.

Question 3. Which do you think would be worse for most plants, an intolerably high monthly peak temperature or a sustained yet slightly lower high temperature? Why? (NOTE: there is not a simple correct answer for this question.) For more on this topic, read Wahid, A. Gelani, S., Ashraf, M, Foolad. M.R. (2007). Heat tolerance in plants: An overview. Environmental and Experimental Botany 61. 199–223. The article can be read or downloaded at http://startinternational.org/library/archive/files/heat-tolerance=eeb-2007_fc9bd2df67.pdf.

Question 4. Think of a place in the world where the extremes in July and January would be the opposite. Why?

Question 5. Now that you understand more about the STORE temperature data, study the relationship between that data and the ranges of evergreen and deciduous forests. Which of the two types of trees seem to be more tolerant of temperature extremes, evergreens or deciduous? Justify your answer with evidence from the data.

Field Demonstration

1. Plan a field trip to a local natural area. 2. What vegetation community do you anticipate to see based on the elevation and average

annual precipitation of this area? Check your map in GE. 3. Test your hypothesis by traveling to this area and conducting a vegetation survey along a

10-meter transect line. Identify and record the types of trees and vegetation present of this area. Were you right?

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