ecoevo

__**NOTE: THE INFORMATION ON THIS PAGE IS NO LONGER PART OF THE COURSE (removed from main wiki, 2014-2015)**__


 * TODO List**
 * REF Boerlijst Hogeweg ???? Which one?
 * REF Hogeweg 19994?: feedback accumulated information
 * Wolbachia: clarify alpha parameter

=[|Ecology] and [|evolution]: The [|fallacy] of separation of timescales=

The previous assessment of the value of group-level selection in solving the error threshold in individual sequences was not that successful. In this section we return to **ecology based solutions** of the error threshold (cf hypercycle). Eigen and Schuster's (1979) original approach to the hypercycle was in essence a purely ecological approach in the sense that **mutations** were **ignored**. Similarly, Boerlijst and Hogeweg (1991?) looked at the same system (based on similar assumptions), only in **space**, and results were that stability increased and spatial patterns led to new levels of selection. Paradoxically though, the whole point was to study the **information threshold**, i.e. what happens to information under high mutation rates. In sum we have therefore only approached this issue by studying [|invasion dynamics]. However, evolution is an interplay of **evolutionary //and// ecological dynamics**. Although mutations were added (Boerlijst and Hogeweg, 1991?), the structure of possible interaction networks was always kept constant. This more or less still restricts the system to the invasion regime. Moreover, in all these models that assess a possible increase in information, the information **is not used for anything.**

Feedback of accumulated information
In that sense a better model would be one that incorporates the evolved information into the behaviour of the system. A hypothetical model (Hogeweg 1994?) could be one where 2 RNAs form duplexes ([|ligation]) which then can catalyze the replication of (all) other RNAs (mutants and parasites alike). Such a system would form a [|star network]. Results (Hogeweg 1994?) show that such networks are very stable because the interface where duplexes form is very narrow and it is difficult for parasites to persist: In evolution the strength of ligation therefore declines, but levels off. This minimizes ligation so that duplexes just manage to maintain themselves and thus gives them an advantage over parasites which is always below its criticality. The system therefore allows a dominance of 2 RNAs due to their isolation at their interface. Moreover, if there is diversity of replicases parasites cannot optimize at all. If parasites do get ligated, then newly evolved parasites are killed because the ligation product is not active due to mutant.
 * parasites need to be where duplexes form
 * implicit trade-off between replication and being replicated, and a strong altruist loses the chance of being replicated

A crucial point here however is the **assumption** of a ligase product, i.e. extra information is assumed: an expandable matrix of who gives catalysis to who, and the mutant gets catalysis of the same things (but with (non-correlated) mutated parameters). It is however likely that there are implicit correlations which could have a profound impact on the system, but to obtain those requires a relationship between sequences based on their actual structure (see Takeuchi and Hogeweg [|2008]).


 * State of the art on information threshold**: We don't know how to solve it! There is no satisfactory answer at this moment, although it would appear that the parasite problem can be solved.

Eco-evolutionary timescales
At this stage we further investigate the consequences of using ecology-based models to study evolutionary implications. It is therefore important to be explicitly conscious about the assumptions and inclusions (omissions) in standard ecological and evolutionary models:
 * **ecological models**: study ecological stability and dynamics of //[|monomorphic] populations.//
 * **evolutionary models:** study invasion dynamics in populations with //constant population size// (e.g. quasi-species equation) or assumed //[|QSS]// (i.e. population dynamics in attractor, parameter dependence). Invasion dynamics assumes //low mutation rates// and //monomorphic populations//.

An important underlying assumption for all of these models is the assumption of **separation of timescales.** Ecological models assume that evolution is slow enough that it will not impact ecological processes, and evolutionary models assume that ecology is fast enough that populations will be at equilibrium or in a QSS. However, we have seen in the host-parasite system (?) that separation of time scales from dynamics and fate of parasites depends on which timescale is used and we have seen that similar time-scales can occur in multi-level evolution, i.e. replicator vesicle dynamics should be the same. In these models, where ecology and evolution are not separated we see a clear interlocking of both processes.



A striking example of the danger of the separation of timescales is demonstrated by a study on Male Killers ([|Groenenboom & Hogeweg 2002]). This study deals with [|Wolbachia] bacterial parasites that are maternally inherited and kill males to further bias populations to their hosts (females). In a spatial finite population model results show that there are qualitatively different results according to a parameter α (???): either no infection, coexistence, or dying out (no more males). However, if the model had considered //ratios// of infected and uninfected individuals one would have concluded that there was still infection and coexistence because the ratio remains constant despite (atto-)extinction! This is a common error in theoretical papers which tend to use ratios! They assume they can keep population size constant despite not having a viable population!