Like evolution, ecology is a central force within living and life-like systems. It stands to reason, then, that artificial ecologies come up in many different areas of ALife.
For a video version of this article, see Emily Dolson’s talk at the 2021 ISAL summer school below:
What is ecology?
Ecology is the study of interactions between organisms and other organisms and between organisms and their environment. In biology, there is a minor split between ecosystem ecologists (who focus on interactions between organisms and their abiotic environments) and community ecologists (which focuses on interactions between organisms and other organisms). Historically, artificial life has tended to involve more community ecology than ecosystem ecology, but in principle there is no reason that it can’t address both. For a cool example of studying ecosystem ecology with ALife, see .
We also use the word “ecology” to describe the property of a system having ecological interactions, which give rise to ecological dynamics. When we say that an ALife system “has ecology”, for instance, we generally mean that it allows for these interactions and dynamics to occur.
Ecosystem – An environment and all the organisms that live it (i.e. it contains both abiotic and biotic components)
Ecological community – A set of organisms that interact with each other. Usually these organisms are not all the same as each other. Biologists traditionally thought of a community as being composed of different species, but in artificial life we often think about them in terms of other “types” that an individual might belong to (genotypes, phenotypes, ecotypes, etc.).
Ecological interactions – Interactions between organisms/agents in a system. Generally, this term implies that these interactions depend on properties of the organisms interacting. To clarify this distinction, let’s imagine we have a physics-based ALife system with two types of agents. All the agents are floating around in the world and sometimes run into each other. If all agents bounce off each other when they collide (regardless of which agents are colliding), we usually wouldn’t call this an ecological interaction. However, if one type of agent eats the other type when they collide, we would call this an ecological interaction.
Some common types of ecological interactions include:
Competition: organisms harm each other by competing for resources
Predation: organisms eat each other
Facilitation: one organism helps another in some way and neither is harmed (both may be helped)
Symbiosis: describes a range of interactions that can occur between organisms living in close proximity to each other (often one lives on top of or inside the other). These interactions exist along a spectrum from mutualism (where two organisms help each other) to parasitism (where one organism benefits and the other is harmed).
Ecological dynamics – Patterns in system-level behavior resulting from ecological interactions. For instance, the way predator and prey population sizes can oscillate in response to each other is an ecological dynamic.
Ecologies – Systems that have ecological interactions/dynamics (can refer to ecological communities or whole ecosystems). In this sense of the word, “an ecology” generally refers to a unique set of ecological interactions that describe a given community/ecosystem.
Ecologies in “soft” ALife
Many artificial life software systems involve ecology. On the simple end, these can be models targeted at understanding/predicting a real-world ecosystem (this is the intersection between ALife and ecological modelling). On the more complex end, these systems may be complex worlds that instantiate ecological principles on a completely different ecological substrate than we see in nature. These complex systems are useful for asking questions about what we expect to see in the general case.
Thus far, most complex digital ALife systems in which people study ecological dynamics also involve a heavy evolution component (examples include Avida, Ecosim, and Symbulation). This is an interesting contrast to research in biology, in which eco-evolutionary dynamics research is largely a distinct subfield from ecological dynamics research.
Ecologies in “hard” ALife
As of yet, there are not very many artificial ecologies involving robotics. The most notable is the FloraRobotica project , which created an ecosystem of plants and robots in which the robots controlled plant growth by emitting light of different colors in different locations.
Ecologies in “wet” ALife
Much research has been done on constructing ecological communities out of organisms that wouldn’t normally coexist (or, in some cases, synthetic organisms that wouldn’t normally exist at all). This sub-field is known as synthetic ecology. Synthetic ecology is used both for the purposes of better understanding ecology and for the purposes of building ecological communities that carry out desirable tasks (e.g. breaking down waste, sequestering carbon, etc.).
There has also been some work on chemical ecologies as a possible precursor to the origin of life .
Ecology is frequently a tool and/or subject of ALife-related art. One particularly powerful type of ecological art are works depicting speculative ecologies that we might build in the future. The creative vision of such pieces can help inspire scientists to do the research necessary to make them a reality. An example of speculative artificial ecologies in art is Rachel Armstrong’s piece “Future Venice” , which imagines a possible future in which we build an ecosystem in Venice’s canals that can simultaneously remove pollutants and re-enforce eroding buildings.
Crombach, A., & Hogeweg, P. (2009). Evolution of resource cycling in ecosystems and individuals. BMC Evolutionary Biology, 9(1), 122. https://doi.org/10/bgqt4p
Hamann, H., Soorati, M. D., Heinrich, M. K., Hofstadler, D. N., Kuksin, I., Veenstra, F., Wahby, M., Nielsen, S. A., Risi, S., Skrzypczak, T., Zahadat, P., Wojtaszek, P., Støy, K., Schmickl, T., Kernbach, S., & Ayres, P. (2017). Flora robotica — An Architectural System Combining Living Natural Plants and Distributed Robots. ArXiv:1709.04291 [Cs]. http://arxiv.org/abs/1709.04291
Peng, Z., Plum, A. M., Gagrani, P., & Baum, D. A. (2020). An ecological framework for the analysis of prebiotic chemical reaction networks. Journal of Theoretical Biology, 507, 110451. https://doi.org/10/gk9mvr
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