Module 1B: Photosynthesis and Ecosystems

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Name ________________________
Module 1B: Photosynthesis and Ecosystems – ANSWER KEY
Part 1: Ecosystems and photosynthesis
There are three main types of photosynthesis found on this planet: CAM, C 4 and C3
. C3 photosynthesis is the dominant form and is found in plants ranging from algae to
Redwoods. Even though C4 plants comprise only 3% of living flowering plants most of
which reside in the grass family (or Poaceae), these plants still produce over 20% of
global primary productivity. They dominate tropical and warm-temperate grasslands,
and include vital food crops, invasive weeds, and even potential sources of biofuels
(i.e., corn). An even smaller percentage of plants use CAM but their numbers parallel
their distribution. Today they can only be found in extremely arid environments.
As hinted by the distribution of CAM plants, photosynthesis is strongly
constrained by water availability and temperature. These two environmental factors are
the primary controls on the distribution and abundance of photosynthesis types amongst
ecosystems. For example, C3 photosynthesis is much more efficient at lower
temperatures than C4 photosynthesis. These differences in photosynthetic and water
use efficient can affect nutrient and water cycling within ecosystems. Thus, the
dominant mode of photosynthesis has strong effects of ecosystem functioning (e.g.,
fire).
1a. Below is a map showing the simulated distribution of C4 grasses on the globe.
(Adapted from Woodward et al. 2004) Using the same cities as for Module 1A, fill in the
predicted amount of C4 grasses in these regions and explain briefly why C4 is found in
that abundance in the region.
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Name ________________________
City
Annual
Temp.
(°C)
Annual
Precip.
(cm)
Chicago, IL
9
89
Tuscon, AZ
21
22
Tabora,
Tanzania
23
87
Toolik Lake,
AK
-8
18
None: Too cold for C4.
12
63
Moderate to high: moderate temperatures
but low precipitation. Also high seasonality
which is something C4 plants “enjoy”
13
240
Low to none: It’s just too wet
2
101
None: Too cold for C4
27
282
Low to moderate: While very wet it still is
very hot.
30
29
High: Hot and dry
Beijing,
China
Valdivia,
Chile
Tromso,
Norway
Chanthaburi,
Thailand
Cairo, Egypt
Predicted C4 abundance
(high/moderate/low)
Briefly explain the abundance.
Moderate to high: Cool temperatures but
moderate/low precipitation;very high if you
include corn
Low to none: Why? Even though its hot
and dry, it is TOO dry. This is CAM
territory.
High: High temperatures coupled with high
seasonality and moderate to low
precipitation. Here we have savanna.
1b. What patterns do you see in the distribution of C4 grasses? Where are they mostly
found? (Northern/Southern Hemisphere; High/Low Latitudes etc.). How do these
patterns relate to the maps of precipitation and temperature in module 1A?
C4 grasses are preferentially found in tropical and sub-tropical regions with low
precipitation and high temperatures (in addition to high seasonality). They can also
often be found in the dryer central parts of continents like the great plains of North
America.
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Below is a flow diagram showing the dynamic relationship between C4 -grass cover, fire,
CO2 and the environment. (Blue: environment; Green: vegetation; Red: driver; Orange:
effect). Pluses correspond to a “positive effect” and minuses to a “negative effect”. For
example tree growth has a negative effect on tree mortality. (Modified from Beerling and
Osbourne 2006.)
1c. Locate a “positive feedback loop” in the above diagram (a loop with an even number
of positives and minuses). What do you think would happen to an ecosystem if this loop
continued unchecked?
Positive feedback loop: Forest cover->C4 grass cover->Fire->Tree death
If this loop is left unchecked, than we would have a wild grassland. Fire destroys trees
giving way to habat for fire resistant species to dominate. There are few better species
than grass when it comes to fire. (A savanna still has a few trees.)
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Name ________________________
1d. In your own words, explain how fire affects the amount of C4 grass cover.
Fire increases the abundance of C4 grass on the landscape. Even though fires rarely
kill adult canopy trees (other than in the most severe cases), they kill most saplings and
seedlings preventing recruitment of the next generation of trees into the canopy. Over
time as old trees senesce and die, grasses remain
1e. In your own words, explain how CO2 affects the amount of C4 grass cover. (Bonus:
How does CO2 affect the amount of fire?)
Increased CO2 in certain environments could lead to faster tree growth. As long as
other factors to do effect the envirnment (e.g., increased aridity) than it is possible that
trees (which are less flammable than grass) could increase in abundance and out
compete the grasses. Grass has a difficult time establishing itself in canopies.
1f. Below is a diagram showing the interactions between fire and herbivores (grazers
eat grass; browsers eat trees and shrubs). How does adding herbivory modify the effect
of fire on C4 grass cover?
There is no real “right” answer here. The point of the question is to be able to interprete
what happens when another factor is added to a system. For example, increasing
grazers could potentially increase tree death and decrease C4 grass but it could also in
turn decrease forest cover keeping grass cover relatively high. This maintains fire and
leads to more tree death. Etc etc.
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Part 2: The plant and photosynthesis
The type of photosynthesis a plant uses is often reflected in its physiognomy or
“characteristic physical structure.” Below are pictures of typical plants that use each of
the three types of photosynthesis. Brainstorm what characteristics that make them
different from each other and how these structures relate to water use efficiency (e.g.
size, leaf shape, overall structure etc.) in the space next to each picture.
2a. Saguarro cactus (CAM)
The saguaro, like most succulent
plants,(this is a “life strategy” rather than a
real monophyletic group (i.e., a group of
closely related species)) are stout leafless
plants. They want to reduce surface to
volume ratios to decrease water loss and
often possess surface deterrents (e.g.,
spines) to ward off thirty pests. While this
species is an exception, most other cacti
tend to me small and low to the ground.
2b. Red Maple (C3)
Red maple or Acer rubrum are large full
canopy trees with broad leaves that give
the plant a huge surface area to collect light
but also to lose water. Thus they are not
suited to environments where water is a
limiting resource.
2c. Switchgrass (C4)
Grasses are typical short small plants with
long blade-like leaves that help minimize
surface
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2d. Bonus: Can you think of any trees with C4 characteristics? The classic example here
would be the Euphorbia trees of the Hawaiian islands. These are very minor exceptions.
Most C4 plants rarely get larger than shrubs. C4 photosynthesis is not as efficient as C3
and thus not as adaptive in areas where trees would normally grow (i.e., wetter cooler
environments). The few C4 trees that exist tend to live in highly specialized
environments.
Part 3: Plant tissues and photosynthesis
On the scale of tissues and cells, plants show marked differences in their primary
structure. Each type of photosynthesis has its own modified physical architecture and
mode of exchanging gases and producing sugars from CO2. Below is a simplified
diagram showing these differences. Pay special attention to where and when
photosynthesis (Ps) is occurring and where and when a plant exchanges water and CO2
with the environment.
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3a. What are the major differences between how C3 , C4 and CAM plants acquire CO2
and convert then it to sugars?
Think in the terms of “space” and “time”. For C3, both CO2 acquisition and conversion
to sugars (i.e., photosynthesis) occurs during the day with only respiration occurring at
night. For C4 these two actions are separated in space. CO2 enters the mesophyll cell,
it is converted to a 4 carbon acid and transported to a sealed bundle sheath cell. Here
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CO2 is concentrated and then converted into sugars. Because of this method of CO2
concentration, RUBISCO (the enzyme that gets the photosynthesis rolling) is never
effect by the concentration of O2 in the cell. Oxygen competes with active sites on the
RUBISCO enzyme lowering its efficiency and thus forcing a plant to collect more CO2
than needed. Remember to collect CO2 a plant must leave its stomates open thus
promoting lose of H20 via transpiration. This is especially problematic in warmer
climates. For CAM plants, the separation is in time. CAM plants open their stomates at
night to collect CO2 when it is coolest thus reducing water loss. They convert the CO2
to a 4 carbon acid and store it until the day when photosynthesis can occur.
3b. What are the trade-offs for C4 plant that prevent them from being successful in
regions where C3 plants dominate? (Think in terms of trade-offs. Do C4 plants sacrifice
anything to be “well adapted” under certain climate conditions. No organism can be
good at everything. There are always trade-offs.)
C3 plants offer a much more simplified structure. They do not have the extra
architecture required to sequester and concentrate carbon. Because of this fact, C3 are
much more adaptive in cooler and wetter climates where the ability to concentrate CO2
and avoid water loss is superfluous. C3 plants will grow faster under these conditions
out competing their C4 brethren.
3c. What type of photosynthesis do you believe first appeared in the fossil record?
Justify your answer by referring to the above figures.
From simplicity comes complexity. C3 plants have the least complex photosynthetic
“architecture”. In fact, all plants perform “C3 photosynthesis” but CAM and C4 have a
little extra added twist before “C3 photosynthesis” occurs.
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Part 4: Photosynthesis and data visualization (Take home)
Ecologists and paleoecologists, like most scientists, need a way to convert all those
crazy numbers (Data) into a form that can be easily understood and shared. This can be
easily done by creating figures and diagrams much like the flow diagrams or map in
Part A. Below we’ve provided a table of simulated data derived from a grassland lake
record representing the past 10,000 years (also provided in a spreadsheet). Doesn’t
that look scary?! It needs to be repackaged if any sane scientist (or student) wants to
produce hypotheses.
time
Charcoal
pieces
0
250
500
750
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
3500
3750
4000
4250
4500
4750
5000
444
509
483
503
459
612
603
462
480
761
772
780
785
802
803
154
176
41
206
92
6
Percent
CO2
C4
(ppmv)
Pollen
63
310
55
300
59
295
66
283
73
279
67
278
71
278
64
277
74
290
96
265
90
274
84
272
87
280
90
269
83
267
22
265
3
263
10
261
10
259
6
290
24
257
time
Charcoal
pieces
5250
5500
5750
6000
6250
6500
6750
7000
7250
7500
7750
8000
8250
8500
8750
9000
9250
9500
9750
10000
218
955
816
921
930
860
966
279
304
369
297
413
440
405
330
336
631
312
674
302
Percent
CO2
C4
(ppmv)
Pollen
21
252
97
249
96
247
99
244
96
242
96
220
98
236
80
234
43
231
38
229
54
226
53
230
53
221
42
219
27
220
54
200
25
212
48
210
80
208
25
206
4a. How do you think you should graph the above data? (e.g., histogram, scatterplot,
pie chart etc.)
The best way to graph such data is through a scatterplot (i.e., a plot with an
independent variable (time – you KNOW this as fact) and a response variable (or
variables) These are variables that change in accordance with the independent variable
(here being time). Histograms are best for datasets where you have “categorical data”
(i.e., data in the form of names) or binned data (comparing the number of individuals in
a population that have a certain attribute.) Pie charts work best for proportional data
within one population.
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4b. Thanks to the advent of the Internet there are no limits to what you can find. This
includes a wonderful website (http://www.incompetech.com/graphpaper/) that allows
you to create your own graph paper! Using a graph paper of your own devising and
artistic talent, create a graph using the table above which you think would best
represent the data. Basic rules to follow: 1) the figure should be easy to understand at a
glace; 2) everything should be labeled; 3) it should be visually striking; 4) be creative!
(Do not worry about getting every data point. Be concerned only with the general
trends.) For inspiration check out Information is Beautiful
(www.informationisbeautiful.net): a blog devoted to visualizing data!
1000
120
900
Charcoal Pieces
700
80
600
500
60
400
40
300
200
Percent C4 pollen
100
800
20
100
0
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
0
10000
Age
Charcoal
CO2
C4 pollen
4c. Using your favorite spreadsheet program (or preferably Tableau), construct the
figure using the provided spreadsheet file. How does it compare to your own figure?
The main goal here is to see how students can take a bunch of numbers and convert it
into something they can understand and eventually interpret. How one graphs a dataset
can often affect how they interpret. Certain techniques can be used to guide a reader to
aspects of a figure that will lead them to the conclusion you want or something entirely
different. Oftentimes modifying scale etc. can accentuate or obscure parts of a dataset
that run counter to an established hypotheses.
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4d. Construct a hypotheses on what is “controlling” the amount of C4 grass on the
landscape. Is it CO2? Fire? Something else all together? What led to you concluding on
this particular hypothesis? Given what you know from Part A. Could other environmental
factors not shown here modify the patterns in C4 you see?
For example: There is no data here on precipitation. As you learned in the first section
of this worksheet, water balance has a strong effect on the dominance of C4 plants n a
region. It is possible that fire is not even a driver of C4 here but in fact aridity. Aridity
could potentially increase fire along with the abundance of C4 plants.
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