There are 11 species of giant weta, most of which are significantly larger than other weta, despite already being large by insect standards. They are heavy insects with a body length of up to 10 cm (4 in) not inclusive of its lengthy legs and antennae (total length can be 20cm or 8″), and weigh more than 70 g (2.5 oz), making it one of the heaviest documented insects in the world  and heavier than a sparrow. The largest species of giant weta is the Little Barrier Island giant weta also known as the wetapunga. Giant weta tend to be less social and more passive than other weta. Their genus name, Deinacrida, is Greek for terrible grasshopper. They are found primarily on New Zealand offshore islands, having been almost exterminated on the mainland islands by introduced mammalian pests.
Two portions of two great articles I found on Wikipedia last night. I hope you enjoy them as much as I have.
Emergent properties and processes
An emergent behaviour or emergent property can appear when a number of simple entities (agents) operate in an environment, forming more complex behaviours as a collective. If emergence happens over disparate size scales, then the reason is usually a causal relation across different scales. In other words there is often a form of top-down feedback in systems with emergent properties. The processes from which emergent properties result may occur in either the observed or observing system, and can commonly be identified by their patterns of accumulating change, most generally called ‘growth’. Why emergent behaviours occur include: intricate causal relations across different scales and feedback, known as interconnectivity. The emergent property itself may be either very predictable or unpredictable and unprecedented, and represent a new level of the system’s evolution. The complex behaviour or properties are not a property of any single such entity, nor can they easily be predicted or deduced from behaviour in the lower-level entities: they are irreducible. No physical property of an individual molecule of air would lead one to think that a large collection of them will transmit sound. The shape and behaviour of a flock of birds or shoal of fish are also good examples.
One reason why emergent behaviour is hard to predict is that the number of interactions between components of a system increases combinatorially with the number of components, thus potentially allowing for many new and subtle types of behaviour to emerge. For example, the possible interactions between groups of molecules grows enormously with the number of molecules such that it is impossible for a computer to even count the number of arrangements for a system as small as 20 molecules.
On the other hand, merely having a large number of interactions is not enough by itself to guarantee emergent behaviour; many of the interactions may be negligible or irrelevant, or may cancel each other out. In some cases, a large number of interactions can in fact work against the emergence of interesting behaviour, by creating a lot of “noise” to drown out any emerging “signal”; the emergent behaviour may need to be temporarily isolated from other interactions before it reaches enough critical mass to be self-supporting. Thus it is not just the sheer number of connections between components which encourages emergence; it is also how these connections are organised. A hierarchical organisation is one example that can generate emergent behaviour (a bureaucracy may behave in a way quite different to that of the individual humans in that bureaucracy); but perhaps more interestingly, emergent behaviour can also arise from more decentralized organisational structures, such as a marketplace. In some cases, the system has to reach a combined threshold of diversity, organisation, and connectivity before emergent behaviour appears.
Unintended consequences and side effects are closely related to emergent properties. Luc Steels writes: “A component has a particular functionality but this is not recognizable as a subfunction of the global functionality. Instead a component implements a behaviour whose side effect contributes to the global functionality […] Each behaviour has a side effect and the sum of the side effects gives the desired functionality” (Steels 1990). In other words, the global or macroscopic functionality of a system with “emergent functionality” is the sum of all “side effects”, of all emergent properties and functionalities.
Systems with emergent properties or emergent structures may appear to defy entropic principles and the second law of thermodynamics, because they form and increase order despite the lack of command and central control. This is possible because open systems can extract information and order out of the environment.
Emergence helps to explain why the fallacy of division is a fallacy. According to an emergent perspective, intelligence emerges from the connections between neurons, and from this perspective it is not necessary to propose a “soul” to account for the fact that brains can be intelligent, even though the individual neurons of which they are made are not.
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