The goal of the Ecology laboratory is to (1) allow students to explore various abiotic variables and how they define and affect different biomes and populations, and (2) allow students to place one or more species into a biome and observe how these species interact by monitoring the population of the species as a function of time. Defining biomes and modeling interacting species in a biome can be complicated, and in order to produce a simulation that is flexible, manageable, but qualitatively accurate forces several generalizations and assumptions. Given below is a list of generalizations and assumptions for the biomes as well as a description of how the population calculations are performed and the variables that are used.

Biome Assumptions. The abiotic variables that can be manipulated in the simulation include latitude, elevation, coastal region, yearly high (maximum) and yearly low (minimum) temperatures, rainy season start and length, average rainfall and interval, nutrient level, and toxicity level. One of the goals of the simulation is to explore how these variables affect the population growth of different species in different biomes. Given below is a list of generalizations and assumptions for these variables.

  1. Biomes. Naturally, there are many classifications and sub-classifications for biomes in the world. In the simulation, we have limited ourselves to nine general biomes because of restrictions due to art and space. These biomes include Chaparral, Coniferous Forest, Desert, Freshwater, Grassland, Marine, Tropical Forest, Temperate Deciduous Forest, and Tundra. These biomes have been defined by specifying a range of temperatures and an average yearly rainfall, except in the case of Freshwater and Marine, which are defined by being water environments and not subject changes in most of the abiotic variables. Selecting a biome in the simulation restricts the abiotic variables to a defined range of allowed values.
  2. Open Biome. In addition to the defined biomes, we have also defined an Open Biome where the different abiotic variables are not restricted. This will allow students to explore how different biomes are affected by changes in, for example, the latitude, elevation, or rainfall. In order for a biome to change from one into another, any changes in the maximum and minimum temperatures or the rainfall must move the original biome completely into the new one.
  3. Temperatures. Temperatures in the simulation are defined as the average daily temperature and not the daily high or low. As time advances through a year during the simulation, the average daily temperature will systematically change between the specified yearly high and yearly low temperatures, where the yearly low temperature occurs some time in January. Random daily variations in temperatures are also applied.
  4. Latitude and Temperature. By default, the simulation links the latitude to the biome temperatures or, in other words, changing the latitude specifies the yearly high and yearly low temperatures for the biome. Variations in average yearly temperatures as a function of latitude are remarkably systematic and have been fit to an appropriate function.
  5. Elevation and Temperature. Similar to the latitude, the biome elevation is also linked to the temperature in order to automatically specify the yearly high and yearly low temperatures for the biome. This data is also systematic and has been fit to an appropriate function.
  6. Temperature Swing. The latitude and elevation functions defined above only define the average yearly temperature and do not specify the yearly highs and yearly lows or the temperature swing from high to low throughout a year. No function could be found that described the temperature swing as a function of latitude or elevation. Instead we gathered hundreds of data points from http://www.weatherbase.com/ and found that the magnitude of the temperature swing (a) was clearly a linear function of latitude, (b) was not dependent on elevation, (c) had a different linear dependence for coastal and non-coastal regions, and (d) had a different linear dependence for the northern and southern hemispheres.

Population Model and Assumptions. The Ecology simulation uses a phenomenological approach to calculate the population of a set of interacting species as a function of time. That is, the model that has been developed for this simulation defines species in terms of a large set of variables such as average life span, birth rate, offspring per birth, consumption interval, and death rate, and the simulation essentially allows these species to live and interact as defined by these variables. The primary biotic interaction is by a species higher in the food chain consuming a species that is lower. Abiotic variables also affect population growth through seasonal temperature changes, rainfall, nutrient level, toxicity level, and cloud cover. Given below is a description of the variables that are used to define each of the species. Note that after adding a species to a biome, the default values for these variables can be edited to investigate the relative importance of these variables to cause changes in the population of the species.

  • Population: Specifies the initial population of the species at the beginning of the simulation. This can be changed in the Species Tracking section of the Setup menu.
  • Is Producer: Is this species a producer? Not selected means the species is a consumer.
  • Births Set By: Are births set by an interval or do they occur on a set day?
  • Birth Interval: The interval between births in days.
  • First Birth Day: The day of the first birth in the year.
  • Offspring per Birth: The number of offspring per birth.
  • Birthing Adults: The percent of total adults who give birth in a given year.
  • Age to Adult: The average number of days before adulthood. Adulthood is defined by being able to give birth.
  • Lifespan: The average lifespan of a healthy adult in days.
  • Death Rate: The number of deaths per 100 adults per year from natural causes.
  • Young Death Rate: The number of deaths per 100 young per year from natural causes.
  • Food Classification (Self): What kind of food is this species (e.g., large animal, small animal, etc.)?
  • Species is A: Species is an Herbivore or Carnivore?
  • Consumes: What food classification does it consume (e.g., grass, woody plants, etc.)?
  • Consumption Interval: How often does this species eat in days.
  • Consumption Qty: How much does this species consume. For herbivores, the quantity is in kg and for carnivores it is in numbers of species.
  • Consuming Young: Do the young consume? (Note that is for carnivores. Does a young carnivore have to kill its own food or does it share with an adult?)
  • Food Scarcity Death Inc: Multiplicative factor used to increase the death rate when food is scarce.
  • Food Scarcity Birth Dec: Multiplicative factor used to decrease the birth rate when food is scarce.
  • Food Scarcity Consumption Rate: The percent consumption is reduced when food is scarce.
  • Minimum Population: The minimum population below which this species is considered scarce.
  • Normal Population: After a species is labeled as scarce, the population before it is considered normal.
  • Pop. To Biomass (kg): The population to biomass conversion for adults.
  • Young Pop. To Biomass (kg): The population to biomass conversion for young.
  • Biomass to Energy: The conversion factor to convert biomass to energy content.
  • T Min (Birth/Grow/Live): The temperature below which this species will no longer give birth, grow, or die.
  • Days Below T Min: The number of days the species must be below T Min consecutively before something happens to the species.
  • T Min Result: The result (Death, Dormancy, None) when the Days Below T Min is met.
  • Missed Births to Kill: The number of missed births before the species goes to zero.
  • Water Required 1, Water Required 1 Temp, Water Required 2, and Water Required 2 Temp: These variables define a linear function that specifies the amount of rainfall required to stay out of a drought condition as a function of temperature. That is, the amount of rainfall required for a species is a function of temperature as defined by these four variables. As the days proceed in an experiment, the simulation counts the number of days where the precipitation is less than the amount specified by this linear function.
  • Days to Drought: This variable specifies the number of consecutive days without sufficient rainfall before a drought condition is established.
  • Drought Result: The results (Death, Dormancy, None) when a drought condition has been established.
  • Dormant Population Dec: If this species goes into dormancy for any reason, this specifies the percent of the population that does not survive dormancy.
  • Dormant Biomass Dec: If this species goes into dormancy for any reason, this specifies the percent biomass that is loss.
  • Max Dormant Days Drought: The maximum number of days a species can remain dormant because of drought before the entire population is killed off.
  • Max Dormant Days Temp: The maximum number of days a species can remain dormant because of temperature before the entire population is killed off.
  • Min Nutrients: For plants, marine, or freshwater species, the minimum nutrient level in the soil or water before the species is killed off.
  • Min Toxicity: For plants, marine, or freshwater species, the maximum toxicity level in the soil or water before the species is killed off.

And finally, here is a final note about complexity. The simulation engine for the Ecology laboratory is based on simply tracking the population of each species in a biome as births, deaths, predation, and variables are applied over time. While simple in concept, the simulation in practice provides an interplay between variables and species that leads to extremely complex outcomes. It is often interesting to explore the importance and effect of different variables on the populations of model systems and individual species.