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In the funnel-web spider Coelotes terrestris (Agelenidae) the young are provided with prey by their mother for several weeks following emergence from the egg sac. Such a maternal activity has previously been shown to be influenced by stimuli emitted by the young (i.e. during mother-offspring interactions), which ensures the tuning of the prey supply to the offspring. The present paper aims to shed light on the conditions of onset and maintenance of prey-supply tendency. The experimental procedure consisted in confronting females, either sub-adult or at various stages of their reproductive life cycle, with a group of spiderlings constant in number and age, and in recording the behavioural interactions following the capture of a prey item. Females which did not yet have post-emergence offspring did not supply prey to the spiderlings and exhibited aggressive reactions towards them. In contrast, females which had had post-emergence offspring, even though their dispersal could have taken place many weeks before, provided prey to the experimental spiderlings, and behaved towards them as their real mothers would have done. When exposure to the experimental situation was prolonged for one week, the tendency to supply the young clearly appeared in previously unresponsive adult females (inseminated or incubating), but no change was observed in sub-adults. The results show that, in Coelotes terrestris, the maternal tendency to supply prey requires a particular internal state, which seems to develop at the time of the offspring's emergence but which does not become extinct after their dispersal. The results also suggest that the development of this internal state can somehow be influenced by stimuli from the young.

Coding Structure. The genetic representation of predators and scavengers is a tree-like coding structure. This genotype defines the phenotypic reaction to a prey, based on the (x, y)-value of this prey. That is, how does one process prey consisting of a certain amount of nutrients, x and y. The functional representation of this replicator would be (+ ($ x x) (* (+ y 3) y)).

Fitness Evaluation. Schematic representation of fitness evaluation of predators, scavengers and prey. Dashed lines denote on basis of which value a response is. That is, predators produce a value based on the (x, y)-values of a prey (colored red and green respectively). This value, relative to the value which the prey produces (based on the evolutionary target), defines the fraction of prey which is eaten by the predator. A scavenger feeds on the remains of prey, based on the same (x, y)-values of prey. Fitness is based on the fraction of prey which is eaten. In this particular example, the fitness of this prey would then be 0.2 (1. - 0.8) and the predator and scavenger would get respectively 0.82 (e-0.2) and 0.63 (e-0.47) added to their fitness.

The coding and the setup of our model-ecosystem enables the possibility to find two types of solutions: individual based solutions where all possible prey can be fully consumed by a single predator and an ecosystem based solution where a solution is formed by an ecosystem of multiple replicators, namely a predator and a scavenger. Simulations can be classified into three main classes: an individual based solution whereby the majority of prey are fully consumed by single predators coding for the full target function, an ecosystem based solution whereby the majority of prey are fully consumed by complementary predator-scavenger pairs which together code for exactly the target function, or no solution at all when none or only a small minority of prey is fully consumed (by predators or predator-scavenger pairs which do not code for the whole target function). Note that an individual based solution excludes an ecosystem based solution. However, it is possible that an individual based solution replaces an ecosystem based solution over evolutionary time.

Spatial Ecosystem Distribution. This figure shows the spatial structure of an ecosystem based solution under high mutation rates. The shade of green denotes the fitness of prey, or rather: how much of the prey is eaten. Prey depicted as yellow are fully eaten by an ecosystem based solution. Red denotes single prey which are fully eaten by a predator alone (not being an individual based solution). In this case the pattern is governed by the prey which are fully eaten by a predator-scavenger pair. Such a pattern, with comparable numbers of 'yellow' prey, can only be met when a correct ecosystem based solution is present in the population.

Example of evolved ecosystem based solution for the longest evolutionary target used: f(x, y) = y4 + x3 + y3 + y * x2 + y2. These predator-scavenger combinations can feed perfectly on all possible prey in the model universe.

Scavengers, feeding on the remains of prey, also speciate during evolution, trying to have a preference opposite to the dominant predator in their neighborhood. Under moderate mutation rates, predators keep evolving towards the full evolutionary target, possibly diminishing the remains of prey more and more. Scavengers can keep up in such a case only by feeding on smaller parts. Note that they can keep fitness, because fitness is assigned as a fraction of the remains. However, when an individual based solution evolves, scavengers loose all their functionality because there is nothing left to feed on.

Passing the Information threshold. When seeding a population under mutation rates above the information threshold (μ = 0.13), with correct individual based solutions, these solutions are quickly lost from the population. This is shown by the declining number of prey which are eaten by correct individual based solutions(black line). The loss of these individual based solutions creates a niche for ecosystem based solutions, which indeed arise as can be observed by the increase of prey consumed by a correct ecosystem based solution (red line).

Both predators and scavengers selected after evaluation are subject to point mutation, using a mutation rate μ per element and a gross chromosomal rearrangements(GCR) rate per genome. Due to the treelike representation of genomes, it is important to realize that mutating elements high in the hierarchy can possibly affect underlying elements. When a mutation leads to the change of an operator into a terminal (either a variable or constant), underlying elements are discarded. In the reversed case (terminal mutating into an operator) a random sub-tree of maximal 3 elements is added. In all other cases only the element itself mutates and the under-lying elements remainfluntouched. A gross chromosomal rearrangement-event (chance of μGCR) means that a randomly chosen part of a genome is overwritten with another randomly chosen (possibly overlap-ping) part of this genome. Where point mutations can only lead to a gradual increase or decrease in length, GCR can possibly lead to a sudden large increase in length. However, although GCR speeds up the process, even without GCR qualitatively similar results are obtained. Results are only shown for μGCR = 0.1 and μprey = 0.4, however test simulations have shown that qualitative results do not depend on these parameters. In most simulations we are interested in μ, which is varied between 0.02 and 0.15. Note that under neutral expectations there is a small bias for predators and scavengers to become smaller, due to the combination of mutational operators and treelike representation (it is easier to loose a large sub-tree, than to gain it). However, this bias is the same for all different μ and of no influence for the results shown.


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