Two-Way Relationships in Ecosystems

There are many ways in which relationships in an ecosystem are two-way or mutual. This means that two organisms affect each other in some way. While domino models are helpful for conceptualizing the one-way process of energy flow, a different type of model is needed to address relationships where there are mutual effects.

In a two-way or mutual causal model, each organism acts as both a cause and an effect. For instance, when a bee pollinates a flower, the bee and the flower are affected. The bee gets the nectar it needs for food energy and the flower gets pollen that the bee picks up from other flowers. The pollen enables the flower to reproduce. Each organism has an effect on the other, so each acts as both a cause and an effect. There are a number of different types of mutually causal relationships in ecosystems. These are outlined below.

Mutualism

One of the easiest types of two-way relationships to understand is a symbiotic relationship that involves mutualism. These are instances where two organisms are interdependent in a way that benefits both organisms¹. For instance, ants known as Attini live in tropical regions in North, South and Central America (although some are found as far up the Atlantic coast as Long Island). These ants cultivate fungus gardens by chewing up leaf cuttings into a pulp and dropping bits of fungus onto this pulp, which is then deposited around the base of gardens. The ants eat the fungi and the fungi thrive in the garden that the ants create for it. The fungi that are cultivated by these ants are not found anywhere else and without the ants, would be overtaken by other types of fungi and bacteria.

Another example of mutualism is the relationship between the ox pecker bird and large animals, such as antelopes and zebras. The bird lands on the antelopes and zebras, where it feeds on the ticks and parasites that live on these animals. The antelopes and zebras benefit from the pest control that the ox pecker provides, while the ox pecker gets a meal. The ox pecker may also warn the antelope or zebra of an impending predator by flying upward and sounding a warning call.

Many Different Organisms Have Mutualistic Relationships

Mutual symbiotic relationships are found between plants and animals, animals and animals, and plants and plants. Lots of plants have symbiotic relationships with either bacteria or fungi that are found in soil. The bacteria and/or fungi incorporate themselves into the roots of the plants, helping the plants to thrive while the plants provide the bacteria/fungi with a food source. Lichen is actually made up of two different types of organisms, fungus and algae, and together these two organisms are able to thrive in conditions where neither could survive on its own.

As humans, we have symbiotic relationships with other organisms that are mutually beneficial. Bacteria live inside the intestines of humans and other animals such as cows. These bacteria help in the process of digestion as humans and other animals are not always capable of digesting all that they consume. The bacteria do this by digesting the food that is not broken down by the human's or other animal's digestive system. The animal's intestines provide food for the bacteria that in turn help the animal by finishing the job of digestion. (In humans, the bacteria "consume" the products of digestion and produce vitamins as a by-product. So they help more than by just digesting. Cows, on the other hand, are aided much more in digestion.)

Mutual Relationships can be Essential for Survival

Some mutual symbiotic relationships are so interdependent that one population cannot exist without the other. Not only is the two-way relationship beneficial, in these cases it is essential for the populations to survive. On the other hand, some mutually causal relationships happen infrequently, once a year or once every few years.

Parasitism

Another two-way symbiotic relationship is that of parasitism. In this case, one species benefits and the other is harmed in some way. For instance, fleas and ticks consume blood from their host animals and receive, in turn, matter and energy. They benefit, however, the host animal is typically weakened as an effect of the parasites.

Two-Way Causality in Food Web Relationships

One of the more difficult types of two-way relationships to understand involves food-web relationships where one type of organism (prey) provides food (or energy) for another (predator), and at the same time the predators help to keep the prey population in balance. For instance, rabbits provide energy for foxes and foxes cull the rabbit population of its weakest members so that the strongest rabbits reproduce, improving the population. This may not be best for the individual, but for the population of rabbits as a whole, it is beneficial.

What makes this so difficult to grasp? The two populations mutually affect each other; however, the effects are positive at the population level for the prey, but negative at the individual level. For the predator, the effects are positive at the individual and population level. This pattern is difficult to understand because:

• On the level of individual organisms, the effects are not parallel. As with parasitism, the effects are beneficial to one organism and detrimental to the other. So while there are two-way effects, the effects are not the same in substance or in quality of outcome.
• It juxtaposes reasoning about populations and reasoning about individuals. Many students have a hard time reasoning about populations at all², and here is an instance where what is good for the population is bad for the individual. This can be confusing to students.^*

Students typically miss the two-way connections in an ecosystem. It is a common tendency to reason in a unidirectional, linear way. Students need to see that the fates of populations as a whole are linked together in many different ways. This is why it is important to introduce two-way causality. Understanding it is a building block for other ecosystem concepts, such as the dynamics of balance and flux as explored in the next section.

Modeling Predator-Prey Relationships

This lesson uses a computer simulation called StarLogo.³ StarLogo is a program created by researchers at the MIT Media Lab to show what happens at a population level when individuals act according to a given set of rules. The resulting outcome is not usually one that can be predicted from the individual interactions, so it can be quite surprising.

StarLogo models the predator-prey relationships differently than what most teachers are familiar with. Models of predation are typically based on classical models, such as the Lotka-Volterra model (as is the case with the Lynx-Hare Cycles model in Section 6). It specifies interactions between predator and prey populations through differential equations that describe the rate of change of different variables over time. These classical models aim to predict at a different level than the modeling approach in the StarLogo program. StarLogo describes the behavior of individuals rather than populations. Therefore the outcomes with the StarLogo program often parallel, but sometimes diverge, from the classical models. Wilensky and Reisman⁴ have explored this issue in depth and give examples of explorations that students have engaged in when exploring the relationship between their StarLogo models (or embodied approaches as they call them) and classical models. They offer at least one instance where a student discovered that the Lotka-Volterra model gave a mistaken prediction and that Gause had previously discovered the discrepancy in 1934! As Wilensky and Reisman point out, classical tools allow one to make aggregate level assumptions; however, models focused on the individual level require assumptions to be coded at the individual level, and then one waits to see what the aggregate level consequences are.

Note to Teacher: You will notice that when there are no consumers for grass (in Simulation #1) and for rabbits (in Simulation #2), the population increases to a certain point and then the program stops running. Discuss with students what happens when a population reaches the limits of what the environment can support. Can it continue to grow beyond that point? What do they think?