Student Worksheet 2: Nutrient Cycling Model

Before you begin this activity, make sure you have read the Background Information of Unit 2, especially the Food Web section, and Supporting Material 2 provided by your instructor on nutrient flows in an ecosystem, the simplified ecosystem nutrient cycle model, and the three biomes we will use as examples in this simulation. Your instructor may have also assigned you additional readings on nutrient cycling. All these will deepen your understanding of this activity.

Purpose of the Activity
In this activity, we will test what happens to three different biomes when we interfere with nutrient cycling, the mass and energy flows in these systems. By "we" we mean us, running this computer simulation model, but if we take a step back from the modeling for a minute, "we" can also stand for humans more generally who interact with, and thereby affect, nutrient flows in ecosystems. It is even possible to think of the changes we evoke in this computer model as examples of what could happen through large environmental changes whether they are brought about by purely natural processes or through anthropogenic causes.

Download the file NUTCY4.WB1 to your own diskette or the hard drive of your computer by pressing the shift key and clicking the hotlinked file with your left mouse button.

Open the file in Quattro Pro for Windows 5.0® or import it into EXCEL®. The following descriptions are specific to handling a spreadsheet in Quattro Pro for Windows, but spreadsheet software is quite similar across many different brands, and even the differences between PCS and Macs are insubstantial. Your instructor will help you out if you are not using Quattro Pro for Windows.

Familiarize yourself first with this spreadsheet and the terminology that is commonly used to orient oneself in it: A spreadsheet is simply a computerized table made up of rows (going across) and columns (going down). Both columns (enumerated with the letters of the alphabet from left to right) and rows (enumerated with numbers from the top to the bottom) have headings, names, so one knows what the numbers in the cells mean. When a column and a row intersect, they form a cell. Each cell has a so-called cell address, for example "A3" which means that the cell is located at the intersection of column A and row 3. Most cells (or at least the ones of interest for any calculation) have cell entries, i.e., something written into them. Cell entries can be words, letters, or numbers. Let's relate all these terms to our example here: In the NUTCY4 spreadsheet (sample screen capture), columns represent nutrient storage volumes in each compartment (litter, soil, and biomass), followed by nutrient flow rates between compartments, respectively. The rows contain the numbers (one row for each year) that result from the simulation (see point below). Cell A3 in this case has the cell entry "Selva" -- the name of the first biome for which we run the simulation.

Before we "run a simulation," let's understand what that means. With your mouse cursor click on cell C4. This cell currently has the cell entry "6." If you paid close attention, you saw another part of the spreadsheet change just as you clicked on that cell: a grey-shaded area between the tool bar (the row of little icons) and the column letters. This grey-shaded area is very helpful because it gives you, on the left, the cell address (in this case, it says A:C4 because we are on page A of this spreadsheet in cell C4), and it gives you an in-depth look at the cell entry. You thought all that was in cell C4 was the entry "6" -- and now look at all that's in the cell: a whole string of cell addresses, mathematical symbols, and numbers! In short: a cell formula. The number 6 is simply the end result of the calculations prescribed by this cell formula.

The reason why we take the time to look at this cell formula is not that you should learn how to translate your ideas of what happens in an ecosystem into mathematical symbols and formulas -- that has already been done for you. Instead, the purpose is to understand that each number from row 4 onward is the result of such calculations and that the results from the calculations for any year enter in a more or less complicated fashion into the calculations for each following year. If you click on other cells in row 4 (which contain the results for year 1 of the simulation), you will find that some cell formulas are rather simple whereas others are more complicated. Some simply rely on the cell entry above (the beginning conditions of the nutrient cycle) and thus are readily calculated, while others rely on cell entries from the row above and from neighboring cells, i.e., other values for the first simulated year, which can thus only be calculated after the simple calculations have been completed. The degree of complication of these cell formulas simply reflects the fact that ecological relationships are more or less complex. Or in other words, it demonstrates that the simple measures you can take in the field are the result of many complex interactions among ecosystem compartments.

We can now see that all calculations ultimately go back to the entries in row 3. Therefore, we say that row 3 controls the rate of transfer between compartments at each annual step in the simulation. A "simulation," then, is just another word for computations of future states of something based on past and present data for that thing (e.g., storage and flows within an ecosystem). "Running a simulation" in a general sense means that you use a model to test what happens to it when you alter the inputs. A simulation allows you to understand the importance of such input change, and it allows you to see how whole systems change over time. In practice, running a simulation for a certain biome in a spreadsheet that comes with all the cell formulas, like NUTCY4, simply means changing the numbers in the row that controls all further calculations -- and that's it! You can page down to the last row and you will see that the simulation is set as a 270-year run (i.e., all calculations are repeated 270 times to get results of storage and flows for 270 years). The outcomes of all years are reported. The embedded graphs (a bar chart and a curve of cumulative changes) show how the nutrient storage changes in the litter, the biomass, and in the soil over the time for which we simulate nutrient flows.

5. So now, let's run a simulation for one of the other biomes. To the right of the simulation columns are examples of flow rates that model nutrient flows in three extreme environments, the selva, steppe, and tundra (followed by various alternative biome models, respectively). Copying these cells into the fields starting with column A, row 3 resets the starting storage for all compartments and the transfer rates between linked compartments.

Again, any change to the values in row 3 will automatically run the model for the newly inserted value(s).

To copy, click with your mouse cursor on one of the cells that contains the biome name of your choice and hold down the left mouse button as you move the cursor across the end of that row. This will block out this portion of the row. Now click on the copy button (or use the Edit menu or a key combination), click with your cursor on cell A3 and, finally, click on the Paste button (or use the Edit menu or a key combination). Within a few seconds, the computer will have recalculated the simulation for 270 years given these new entry values. You will also observe that the embedded graphs change, since the graphs automatically display whatever values have been calculated in the simulation.

Here are the steps involved in copying: block -- copy -- move to destination -- paste

In sequence, copy the fields for selva, steppe, and tundra into the cells starting in A3. You will perform a simulation experiment on each of these biomes in a "natural" state (e.g., selva) and for an alternate scenario of each of these entries (e.g., selva2) with the environmental change described below. As you go along, answer questions about the natural biome as well as the effects of changes on the system. Notice that only in one case will you be asked to actually alter cell entries (selva3). For all others, compartmental storage values and average flow rates for the altered biome are provided. To make better sense of the numbers, inputs of nutrients from rain, weathering rock, fertilizer, and removal of nutrients and biomass (through harvest) can be integers ranging from 0 to 9. The flows between compartments and losses from the system are decimal fractions ranging from 0.00 to 1.00.

Here are the descriptions and questions for each of the biomes and their altered states:


The selva, the common lowland tropical rainforest, is composed of a wide variety of broad leaf, evergreen trees. The standing biomass is huge, and fallout rates are low. Nutrient inputs from the atmosphere are high because of the very high rainfall. After you have run the selva model, record the storage values in each compartment and record losses to the system at year 270 (values from the last row) in the table below. When you look at the graph, you will find that the nutrient storage curves level off after some time, i.e., the amount of nutrients stored in each compartment doesn't change much after a certain time. The speed at which the system storage values stabilize depends on the slowest transfer rate. Examine the annual values to determine how quickly the relative storage among the compartments stabilized. Which compartment changes the slowest, which the fastest? Which compartment stores the most, the least, and the intermediate amount of nutrients? In a few sentences try to explain the storage amounts and the time it takes to reach that level. Given what you know about the storage amounts of nutrients in the three compartments we looked at in this run, what would you predict would happen to the fertility of this biome if you deforested it? Make a note of your observations on an extra sheet of paper.
Selva2 One of the forces that drives land cover change in this region is that the world market price for hamburger encourages ranchers in Brazil and in other tropical countries to convert rainforest into grazing land for cattle. Selva2 is a sensitivity experiment to see the effects of this land use change decision that involves cutting, burning, and sowing grasses. Copy the Selva2 values to A3. The starting conditions in the storage compartments are the same as those at the end of the Selva simulation; the flow rates are average rates for the kind of land use change that we try to simulate here. Describe on an extra sheet of paper how and why you think uptake and fallout change with a burning of the forest and planting of grass for cattle ranching. Think of what the changes would be in nutrient losses resulting from erosion and leaching. Record the storage values in each compartment and losses to the system at year 270 in the table below. If you're not sure about how flow rates would change, discuss this with a classmate.
Selva3 The starting conditions for the storage compartments are again as those at the end of the Selva simulation, and the flow rates are average rates for the land use described here. Under this sensitivity analysis, the land users are subsistence farmers practicing swidden or slash-and-burn agriculture: tropical forest is allowed to establish itself for a period and then small plots are cleared, burned, farmed, and abandoned when the soil fertility drops. In this farming practice, no materials are permanently removed from the site, and a wide range of crops are grown together (a practice called inter-cropping). This type of farming, though labor intensive, maximizes the use of soil and climate resources. In our example, the farmer uses the land for only two years and lets it be fallow for 38 years (it is allowed to grow back to forest, seeded by the trees that are close by). To mimic this 40-year rotation of swidden agriculture, selected cells in column K (fallout) must be modified. However, we will not mimic the cycle for the same plot over 270 years, but rather show only a few slash-and-burn periods. (Imagine you looked at one area in the biome, and every so often this area would happen to undergo the slash-and-burn disturbance.) To simulate this, insert the following formula into cell K84, i.e., add it on to the formula already in that cell by clicking with the cursor at the end of the existing formula: [+0.95*J83] (do not type in the brackets) and copy this new formula to the following cells: K85, K164, K165, K244, and K245. Record the storage values in each compartment and losses to the system at year 270 in the table below. How different are the outcomes of Selva3 and Selva2? What would happen if the rotation were shortened, say, to two years of farming, then only 15 years of fallow, and then cutting the forest again? (You may find it easier to answer this question by simulating such a rotation, using the same addition to the cell formula, and copying that extended cell formula to a greater number of cells.)
Steppe Steppe vegetation is dominated by grasses, which vary widely in their traits. Steppe grasses lose most of their annual production to grazers or fallout during the winter or the dry season. They are mostly perennial (except in California, where they have been largely replaced by annual grasses) and tolerant of defoliation by grazing animals, fire, and drought-induced leaf drop. Nutrient uptake is relatively slow because of the low demands of these much smaller plants. In semi-arid climates, the loss of nutrients in runoff water is slight and the leaching of nutrients from the soil is rare because the negative water balance keeps the soil water below field capacity (the amount of water soils can hold against the pull of gravity). For leaching of soluble minerals to occur, soil water must rise above field capacity. After you have run the steppe model, record the storage values in each compartment and losses to the system at year 270 in the table below. Compare, as you did for the selva biome, the storage amounts and stabilization times for soil, litter, and biomass. Now imagine cultivating a steppe for grain production. What changes in storage values and flow rates would you predict? How come?
Steppe2 Much of the world steppe biome has, in fact, been converted to fields for grain production. Grains are domesticated grasses whose seeds are used as food for livestock or humans. This biome has become the major grain region ("bread basket") of the world (including the corn and wheat belts of the U.S., Argentina, Australia, Russia, Ukraine, and China). In the case presented here, the values reflect the mechanized monoculture of the Midwest. It involves high inputs of chemical fertilizers to replace the nutrients removed in the grain. This simulation starts with the ending storage conditions of the Steppe simulation. The flow rates, again, are the average rates for the changed land use. Describe on an extra sheet of paper how uptake and fallout change to reflect a plowing of the grasslands and annual planting of corn. Suppose that fertilizers are applied at rates slightly larger than those supplied by rain. What changes in nutrient losses would result from erosion and leaching? Record the storage values in each compartment and losses to the system at year 270 in the table below.
Steppe3 The starting conditions are again the same as those at the end of the Steppe simulation, and the new flow rates typify the land use described here. The farming practice here uses a four-year crop rotation common in the Midwest up to 1950 (corn, corn, oats, hay/pasture). Chemical fertilizers were not used, and the only exports from the farm were meat and dairy products. Animal wastes (manure) were returned to the fields as fertilizer. Moreover, plant densities were much less than in Steppe2. A variety of institutional factors stimulated the abandonment of this type of farming in the heart of the corn belt. These included: (1) a rise in land costs and occasional high grain prices; (2) advice from universities, the U.S. Department of Agriculture, and lending institutions; (3) incentives to use land carelessly through the availability of profitable government farmland retirement programs; and (4) technological developments in equipment, plant genetics, and agricultural chemicals. Record the storage values in each compartment and losses to the system at year 270 in the table below. Describe the differences in the impact of this farming strategy with that used in the Steppe2 experiment.
Tundra Tundra is underlain by permanently frozen ground, permafrost, that prevents nutrient leaching. Plant growth is restricted by the short growing season (light and temperatures). After you have run the tundra model, record the storage values in each compartment and losses to the system at year 270 in the table below. Compare again, as you did for the selva and steppe models, how storage amounts and stabilization rates differ for soil, litter, and biomass. How do you explain what you see in the simulation? How would you expect the environmental conditions for plant growth (storage and flow rates in all three compartments) to change if you assumed that global climate change would significantly raise the average temperatures in the higher latitudes (say by 3 ºC)?
Tundra2 The loss of substantial carbon stores from the selva forests, the oxidation of soil carbon in cultivated steppes, and the release of carbon from burning fossil fuels are expected to double the carbon dioxide content of the atmosphere by about 2060. It is hypothesized that this doubling of CO2 will induce global climate change that will include substantial warming at high latitudes, particularly in winter. Many scientists expect that global warming will have a pronounced impact on the extent of permafrost and the abundance of plants adapted to a frozen substrate (soil and rock material plants grow on). A sustained increase in the depth of thawing would be seen as an indicator that global warming was occurring. Assume for this run that global warming has thawed the permafrost, allowing nutrients to be leached and lost from the system. On an extra sheet of paper, describe the changes in uptake and fallout that would result from a thawing of the tundra. Assume no significant change in vegetation (270 years is too short a time for a complete thaw of the permafrost and for significant in-migration of new plants to occur; thus there would be no radical increase in uptake in the short run). Record the storage values in each compartment and losses to the system at year 270 in the table below.

Table 1: Year 270 Summary















Write a 1-2 page critical summary of the impacts of the human-induced environmental changes you have modeled. Use your notes from the above 8 simulations to write this overall assessment of these impacts.

When you come back to class for the next session, be prepared to present to your class what you found in your simulations, how you would explain them, and what you concluded from these observations about the types of human-induced environmental changes you simulated in this model.