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This model is described in detail here.
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view/download model file: PALM.nlogo
The Prehistoric Agricultural Landuse Model (PALM) presented here is an effort to create a simple, expandable, and configurable agent based model of agricultural landuse in the Pueblo region of the prehistoric American Southwest. This model was developed using the NetLogo platform and is based on the Sugarscape model presented by Epstein and Axtell in their influential book Growing Artificial Societies (1996). PALM is also similar, in many respects, to the Artificial Anasazi (Dean et al. 1999; Axtell et al. 2002; Gumerman et al. 2003) and Village Project (Van West 1994; Kohler and Carr 1997; Kohler et al. 1999; Reynolds et al. 2004; Kohler et al. 2005) models which have been developed to examine specific locations of the prehistoric Plateau Southwest.
We have developed a small number of simple variables through which various assumptions regarding decision making and environmental variability can be explored in different environments. The objective of this model is to understand and analyze migration patterns between various settlements over time.
Assumptions:
1) Timestep = 1 year
2) Agent = 1 household (with varying household size)
3) Patches = Agricultural Land (different levels represented by the colors)
4) Non spatial arrangement, i.e. physical distance is NOT considered.
5) In case agents migrate, they appear in a random patch at the destination.
6) Number of agents stay constant. We don't consider possibilities of dying/new households.
7) One the resources on a patch are depleted to 0, it becomes barren (gray).
8) Two kinds of information available to agents for migration - Resources and Social Capital.
9) Agents decide probabilistically which information to base their decisions on.
Parameters:
1) numTurtles - Number of Agents to be present on the map.
2) max-harvest - Maximum harvest value for each agent.
3) time-to-regrow - Maximum time interval for regrowth countdown for land.
4) max-intensity - Maximum value for land-destruction intensity for each agent.
5) storage-decay-rate - Rate at which storage decays for each agent.
6) wait-to-migrate - Maximum wait time that an agent waits to consider migrating.
7) landscape - Select one of 4 predefined maps available.
8) social-capital? - Turn social capital on/off.
9) think-sc-prob - Probability that a certain agent would follow social capital.
10) imperfect-info? - Toggle for imperfect information (NOT INCLUDED IN RESULTS)
11) uncertainity - Measure of imperfection in the information. (NOT INCLUDED IN RESULTS)
Set the parameters according to requirements.
Click "setup" button.
Then either hit "go" or "step" to start the simulation.
"Disaster" button is there to simulate a disaster scenario where resources are reduced throughout the landscape. Can be compared to a natural disaster.
NOTE: The first timestep takes a bit longer than usual. This is due to overhead involved in setup.
Let's delve into the results with respect to variable changes -
1) Number of Agents -
As would be expected, the resource degradation of the environment is relative to the number of houselhold. Therefore, increasing the households would result in an increase in resource degradation.
2) Maximum Intensity -
Resource degradation increases quite a bit with increase in this variable.
3) Maximum Harvest -
This is where things start getting interesting. Increasing the maximum possible harvest of the model environment does not drastically effect the degradation of the resources of either landscape. On the other hand, the maximum harvest is strongly related to the average number of migrations per year. It is seen that as the maximum harvest increases, the number of migrations per year declines rapidly.
There is a major threshold point in the maximum productive potential values, past which the number of migrations per year decline rapidly. Interestingly, this threshold is approximately 3.0. This value is twice the mean resource requirement for each household.
NOTE: When all agents choose their location based purely on resource level per household and the total population is set at the default level (200 households), no scenario was produced where the resource base of any settlement was completely degraded. When agents are allowed to choose their location based on the social capital of each settlement, however, the behavior of the model changes significantly.
4) Social Capital -
As the probability of choosing a location based on its social capital increases, the level of resource degradation increases in both landscapes. In landscape 2, where all settlements are close in total resource level, each settlement appears to be affected about equally. In landscape 1, however, where settlement 3 is much larger than all others, settlement 3 becomes severely degraded more frequently at lower values for the social capital decision parameter.
Furthermore, when the probability of choosing a location based on social capital increases, the average number of migrations per year increases rapidly. In addition to this, the number of migrations increases rapidly as resources are depleted.
Possible improvements that we thought would make the model better:
1) Consider social investments on labor in a settlement.
2) Providing agents with a memory of their previous locations.
3) Including spatial consideration in the model.
4) In-depth analysis of external disturbances.
5) Effects of improper information by delaying information.
This model was implemented using NetLogo version 3.0.1 on PC based Windows XP professionial computers. The test runs were done using 5 seperate computers, each with the following specifications.