RESISTANCE IN POPULATIONS
J. FRANTZEN
II. Populations of Host and Pathogen
Consider a group of spores, or seeds, placed regularly in a Petri dish to germinate.
We determine for each spore whether it germinates and the time at which it germinates.
If we plot the fraction of spores germinated against time we will see that not all spores germinate at the same time (Fig. 1). A few spores germinate rather quickly and a few spores rather slowly. For one spore we have only one germination time, for a group of spores we have a range of germination times. This range of germination times may be summarised as a mean and standard deviation, or any other relevant statistical parameter.
A population has one, or more, common attributes and has variation with respect to other attributes.
The population of spores was clearly defined in the above example: it consisted of all the spores inside the Petri dish.
Consider now another population that is limited in space: a wheat field surrounded by roads that separate it from fields with potatoes. Assuming that the farmer did his work well, the distribution of the wheat plants is regular with equal distances between plants within the rows, and between the rows: and the population of wheat plants has an uniform
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Figure 1. Fraction of spores germinated versus time after placing spores on water agar. The curve is sigmoidal and quite common for germination of spores. Fictional data are used.
distribution. A weed occurring in the field, e.g. Galium aparine (catchweed), will show a less regular distribution varying from random to clumped or aggregated.
The distribution of a pathogen, e.g. Puccinia recondita (brown leaf rust) may depend on time of observation. The rust fungus may infect a small group of plants at the start of an epidemic, i.e. a clumped pattern, but may infect nearly all plants at the end of an epidemic, achieving a nearly uniform pattern. Estimation of the distribution of the rust becomes more troublesome if we include also the spores. These are present on the soil surface, on the plants and in the air. We have therefore to include a third dimension to estimate adequately the distribution of the rust population. The question is then to which height should we trap spores?
Or, where is the border of this population. We will return to this question later.
A population has a certain distribution of the members belonging to it and this distribution is in the range of uniform to aggregated.
Consider again the wheat field. If we count the number of wheat plants and divide it by the area of the field we find the density of the wheat population. In fact, we don't have to count all plants because the distribution of the plants is uniform. Counting plants on a small sample area only can give an accurate measure of the density of the population. The story is different for a weed. The distribution of a weed may be patchy with a rather high density inside the patches and a low density outside the patches.
To estimate the population density of the weed we would have to count the number of weeds of a large sample area, or even of the whole field. Estimation of the density of the rust population is even more complicated and would require both counting diseased plants on a certain area and sampling a certain air volume to count spores.
164 J. Frantzen
The example of the rust points to another problem in the estimation of population density. The members of a population are never 100% similar. In the case of the rust we counted diseased plants, which reflect rust mycelium, and spores. Even if we translate diseased plants to a number of spores infecting each plant, the fact remains that the pathogen is present in two different forms and stating a density for the rust population does mask this difference. The differences between individuals are also present in the wheat population, but are more subtle. There will be small genetic differences between plants, and each plant has its own micro-environment shaping the phenotype. And so, we are back at the variation within a population mentioned above.
Density is a crude estimate masking the type of distribution of population members and masking differences between members of the population.
Estimation of the population density may sometimes be used for investigating processes in populations with a rather low amount of variation, like a crop variety, and an uniform spatial distribution. If the spatial distribution is heterogeneous, the density of a population should be indicated together with information about the spatial distribution. If the population is heterogeneous with respect to genotypes or phenotypes, the density of a population should be indicated together with information about the frequency distribution of genotypes or phenotypes.
Populations have their dynamics. The dynamics is predictable for the wheat population and depend completely on man. The dynamics of a weed is less predictable. Within the limits set by agriculture, density and distribution of the weed population change as a result of seed dispersal. Dispersal of spores changes the density and distribution of the rust population. Dispersal is referred to here as the movement of propagules within a population and as the movement causing extension of the population (Fig. 2).
The latter may result in the foundation of a new population if the dispersal distance is relatively large. In contrast, migration is the movement of propagules between existing populations.
Dispersal and migration do not only cause changes in density and distribution.
Independent of the type of propagule, be it spores, pollen, seeds or plant parts, genes are also transferred, resulting in changes in the genetic constitution of a population.
This gene flow may change both the frequencies of genes in a population and the spatial distribution of genes within a population.
Dispersal and migration cause changes in the density. the spatial distribution of the members. and the genetic constitution of a population.
Consider two adjacent wheat fields separated by a road and belonging to two different farmers. The direct influence of the wheat in one field on the wheat in the other field is negligible and it is useful to consider them as separate populations.
) Migration --+ Dispersal
o Dispersal unit
Figure 2. Dispersal and migration of dispersal units within and between populations. Dispersal is within and at the border of a population, migration is between populations.
The situation is less clear for a weed or rust occurring in the two fields. Most weed seeds may not be able to pass the road, but a few may do. Gene flow may occur at a relatively low rate. The rust, however, may easily pass the road and the rate of gene flow may be rather high. The distinction between the populations in the two fields then becomes vague. This again raises the question about the border of a population.
But we now have an additional tool to determine the border of a population, the rate of gene flow. Two populations of a species may be considered distinct if the gene flow between them is absent, low, or infrequent; although this leaves the terms "low" and
"infrequent" to be defined. We have, however, arrived at a measurable variable that can be used to define the border of a population. The availability of DNA markers facilitates the estimation of gene flow and may give research on gene flow a more pronounced place in studies on plant diseases (McDermott and McDonald, 1993).
We will now widen our view of populations. The example of brown rust has already suggested that the scale of a population may be larger than a field. For example, Wolfe et al. (1992) studied Erysiphe graminis f.sp. hordei (barley mildew) in Europe and considered it as one large population, made up of subpopulations. Subpopulations were not isolated and gene flow between them was possible. Despite this, subpopulations could be distinguished on the basis of differing virulence of isolates taken from the different subpopulations, and also by DNA markers and sensitivity to fungicides.
This suggested that local factors acting on the subpopulations were more important for the genetic constitution of a subpopulation than genes transferred between the subpopulations. In similar work the genetic variation of three Danish local populations
166 J Frantzen
of E. graminis f.sp. hordei was studied (Damgaard and Giese, 1996). There was no indication of genetic differentiation amongst the populations. In fact, the overall Danish population is likely to be part of the European population and may be considered as a subpopulation of it.
The example of E. graminis f.sp. hordei makes clear that (1) the border of a population is a priori determined more by the working range of the researcher than by biological criteria, (2) gene flow may occur over rather large distances increasing the population size to one covering a very large area, and (3) local factors may still influence parts of the population relatively strongly. There is consequently a tension between increasing the size of a population to take gene flow into account, and restricting size to account for local factors. Moreover, a researcher may prefer to study a smaller population for technical and indeed financial reasons.
Gene flow is not always as extensive as in E. graminis f.sp. hordei. Most plant species and pathogens such as soil-borne fungi have limited gene flow and it is easier to distinguish populations. But here another problem is encountered: small populations have a relatively high probability of extinction. This does not inevitably mean extinction of the species as new populations may be founded. One spore, or one seed, may be enough to found a new population at a suitable site. This single propagule will largely shape the genetic constitution of the population in later generations, if the population remains isolated. The strong dependency of the genetic constitution of a population on the original individual(s) is called founder-effect (Falconer, 1989).
If we look at the parent population from which the colonisers originate, many genotypes may be present and of these, many may disappear at the time of extinction of the population, others may found a new popUlation, or enter existing populations.
There is therefore a dynamic situation of extinction and appearance of populations with an infrequent gene flow. Against this pattern of instability at the population level, the species does persist at a higher level, the metapopulation (Olivieri et aI., 1990).
The concept of metapopulation takes into account local factors acting on individual populations and also gene flow between populations.
The concept of metapopulation was developed for endangered plant and animal species.
Plant pathologists do, however, recognise immediately the analogy with various pathogens.
A crop disease may be adequately controlled in a region by a resistant cultivar, leading to local extinction of the pathogen population. However, one virulent spore arriving from another region may build up a new population rendering the formerly resistant cultivar futile. The concept of metapopulation is a formalization of what had already been recognised for a long time by plant pathologists. Fry et al. (1992) successfully applied the concept of metapopulation to Phytophthora infestans causing potato late blight.
The rate of gene flow is a major criterion to distinguish populations.
The importance of gene flow is expressed in the concept of metapopulation.
Recent developments in modelling using the metapopulation concept (Han ski, 1994), and in analysis of genetic variation using DNA markers (McDermott and McDonald,
1993) offer new opportullitles to study populations and their interconnections on a large scale. The relative importance of studies at a smaller, local, scale may decrease, but understanding of processes at a small scale will still be required to underpin understanding of processes at a higher level.
The phenomenon of population will remain central in the following sections where host - pathogen interactions are considered at the population level, but there is an additional problem in considering host - pathogen interactions: the scale of the host population often does not fit the scale of the pathogen population. This drawback must be tackled in studies of host - pathogen interactions.