A goal of the workshop was to define links between biological studies of insect nests and human architecture. However, it was difficult to draw any deep connection between them. Typical parallelisms between human and insect buildings include functional elements like thermoregulation. The bibliography cites termite mounds in the savannah as a classic example of biological thermoregulation. While it is clear that successful cultivation of fungi has specific thermal requirements (and thus imposes some structural constraints on the host termite nest), recent empirical evidence presented by Scott Turner at the workshop indicates that (at least in some cases) termite mounds do not always work as perfect thermoregulation devices. Instead, Turner discussed a very interesting hypothesis of the termite mounds as a humidity regulation device, bringing water from the soil to the mound during summer (and the other way around in winter) in order to keep the adequate level of humidity. Moreover, Turner proposed the idea the termite mount acts as a filtering device, where different parts of the mound filter different components out of environmental fluctuations. Then, we conclude there are different functional requirements between human and insect buildings.
As a complex network researcher, my own interest was to make connections between biological studies performed by field researchers (like John Menzel, Walter R. Tschinkel, Scott Turner and Flavio Roces, among others) and complex network theory. This was a natural way to proceed because I have already published some network studies on nests of Cubitermes Spp. termites (see Valverde et al, Physical Review E 79, 066106 (2009)) and we have some ongoing network works with nests coming from other species (including Trinervitermes and Procubitermes termites). Network theory enables us to look at insect nests from a fresh, new perspective. The network representation of a termite nest highlights the global pattern of interconnections instead of minute details regarding network elements, i.e., the node and the link. Indeed, we have proposed a classification method for networks based on counting how many different 4-node subgraphs occur in a network (i.e., network motifs).
In this context, network models can be quite useful to address the intrinsic limitations of empirical studies. For example, it may be quite costly to obtain enough experimental samples for a meaningful statistical study. A (valid) computer model has the potential to extend empirical studies with a few number of biological specimens to a large number of synthetic networks. This can be very valuable when testing a number of different hypothesis about the evolution and development of termite nests. Then, complex network theory has the potential to explore new biologically meaningful questions which will be difficult to answer with limited data. For example, are these networks optimal? and if affirmative, how we can measure the degree of optimality displayed by these insect nest networks? I think that we have started to answer the optimality question by comparing real insect nest networks with a simple network lattice model generated with a rule-based algorithm. In order to produce comparable structures, our algorithm is feed with the most appropriate parameters estimated directly from the real insect nest network.
On the other hand, computer renderings of networks have an aesthetic value. During my research I have produced many network visualizations of different natural and artificial systems. Many people found network renderings beautiful or even valuable from an artistic point of view. Recently, I have been asked for permission to republish a computer rendering of a large patent citation network in an incoming publication in the Art Journal (to be published, 2010). Human architecture is (and in particular, modern or contemporary architecture) related to aesthetics. Without doubt, we can find beauty in insect nests network. And it seems a perfectly valid goal to seek for inspiration in these biological structures for human architecture. Indeed, I have learned from the talk of Juhani Pallasmaa that there is a well-documented interest in biologically-inspired architecture.
However, aesthetics is a very difficult thing to measure. Still, the ancient greeks related beauty with some predefined ratios and geometric relationships. In a related research, evolutionary computation has been used to produce synthetic imagery. We can conceive a similar scheme to produce architectural designs resembling biological structures (i.e., insect nests). For example, we can create a software application that couples a human architect/designer with a genetic search algorithm that looks for the most beautiful or pleasant insect-like networks. We can conceive an hypothetical design session with this human-oriented genetic algorithm. At every step, the algorithm automatically will generate and show to the designer a small collection of random networks (e.g, and in order to produce more realistic results, we can use the computer model for insect nest networks discussed above). The designer evaluates and judges what the best design is, which in turn is used by the algorithm as a seed to create the next generation of designs. This process is repeated until the designer finds the ideal network shape, which can be used to create a physical or virtual art.
We can see that there is still a long way to go. However, we can readily appreciate the added value of using network theory when studying insect nest networks. And who knows if the same network formalism will be also useful for creative purposes, i.e., producing aesthetic, biologically-looking buildings and unique pieces of art.
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