See+feedback+for+all+reports+here

What follows is a list of points that apply to several writeups. Your hard copies will be returned via the supervisor of the first-listed person (the first sticker) You can see which number applies to your report from the note in the margin, but you should look at the points for all the reports.

1. Remember genetic drift can lead to the loss of a beneficial allele 2. Strong selection or strong drift can produce sudden changes in allele frequency, i.e. over short distances 3. The same selective regime could lead to different outcomes in different places, for example suppose there were selection for dark snails in wooded areas, that could be achieved by a dark background in one population, and by having five thick bands in another 4. Take care in excluding samples from an analysis, because they do not fit the general trend. This may be a legitimate exclusion of outliers. However, by doing this, you could also end up honing your data to have apparently significant patterns that fit your preconceptions. 5. If you find no significant differentiation between widely spaced locations in each habitat type, yet significant differentiation between two (or more) habitat types that does suggest drift is having a relatively small effect, and that the consistent difference between habitats is due to selection. However, you should ask yourself if the sites in the same habitat are closer together than sites in different habitats. If that is the case, then they might be more similar because of gene flow between them, rather than a consistent effect of selection. You should at least raise other possible explanations for any such consistent pattern, and evaluate them. 6. It is not the case that statistically significant results are more likely to be due to selection than to genetic drift. Both processes can lead to statistically significant differences. This point was made over and over again in the lectures! 7. Latin names are given in italics (or underlined) and the species name starts with a lower case letter: //Cepaea nemoralis.// 8. If you present other scientists’ results, it is best to give a) the evidence b) what the authors inferred c) the logical path that led to it. E.g. Jones found dark snails painted white behaved like light coloured snails (and //visa versa//) (evidence), hence the behaviour changed when the phenotype was changed although the alleles remained the same (logic), hence he concluded that alleles for dark shells do not directly affect behaviour but through their effect on the shell colour (what he inferred). 9. Remember the shells you collected were dead, so provide a summary of the genotypes that have lived and died over a period of several years (a decade?) in the locations where you collected 10.It’s means it is. Its means ‘belonging to it’ and has no apostrophe, just as his (belonging to him) has no apostrophe. 11.When you cite authors in the text, you do not put their initial in the text. Eg. you write something like ‘Nichols found a hybrid zone (Nichols 1984)’; not ‘Nichols, R found a hybrid zone(Nichols, R 1984)’. You only put the initial in references at the end. 12.Introductions should be written mostly in the present and past tense – not the future: It is thought that … our experimental design tests … we collected //etc.// 13.Do not round expected value to whole numbers 14.If you find significant differences within a particular habitat type (that could be due to drift, or undetected differences in micro-habitat), then it is hard to interpret any difference between major habitat types. 15.When a chi squared value is less than the critical value, it is best to say ‘we cannot reject the null hypothesis’, rather than ‘we accept the null hypothesis’. Similarly when it is greater than the 5% critical value say ‘we reject the null hypothesis at the 5% level’. 16.If your results are statistically significant, then it is rather weak to say that they could be due to sampling error – the whole point of the significant test is to show that is unlikely. 17.If you have a row or column with all zeros, you need to remove it from the contingency table (for calculating degrees of freedom). Similarly you should merge categories if expected values fall below 5-ish (certainly if they fall below 3). 18.If you find no significant differences, this can be due to chance (if stochastic forces are in operation), lack of statistical power (sample sizes need to be larger), or similar selection acting in both places, or gene flow between them, //etc.// 19.Remember before you combine samples, you should check that their phenotype frequencies are not significantly different from each other. 20.If you have two variables, say habitat (grass/bush) and altitude (high/low) then you can legitimately compare but it is problematic to compare high(both) with low(both) as, for example, you may have unequal numbers of each habitat category in each sample. 21.Be careful with the term ‘preference’. That implies a behavioural choice, e.g. for moving towards or staying in a particular habitat. That is different to selection acting to cull the unsuitable phenotypes from a habitat – which requires no preference on behalf of the snails. 22.Gene flow does not always create or sustain polymorphism; rather it moves alleles from one habitat to another. Hence gene flow might produce polymorphism on the boundary between two habitats under divergent selection. On the other hand reduced gene flow can prevent a whole area becoming fixed for one allele by drift (or selection), hence sustaining polymorphism. 23.You can test for significant differences among populations in a certain category (e.g. grassland ones) and, if you find none, you might decide to bulk them into a single large sample for other comparisons. However, there is no test that can tell you whether to combine, say pink and brown shells into one category. The test is for differences between populations, not categories. 24.You cannot use the test to tell if a particular colour is affected by random processes – you can only tell if differences between populations are so small they might be due to sampling error. If they are larger they might be due to drift or selection. 25.Bottlenecks do not only explain effects seen in small populations. Populations can go through bottlenecks then grow to become large. 26.The singular of species is species NOT specie. For goodness sake you are 2nd year Biologists! Ps the singular of sheep is sheep. 27.If there are subtle differences in allele frequency (small differences between one population and another) you will need larger sample sizes to detect a significant effect (usually).
 * grass/high with grass/low or
 * grass/high with bush/high