it explains why the flowers of some orchids have extraordinarily long spurs to store their nectar , and why the moths that pollinate them have extraordinarily long tongues to drink it . it explains why we do n't all succumb to diseases , and why diseases still exist . how coevolution actually works is far from clear , however , if one looks into it in any depth . how is the genetic variation that is the raw material of coevolution , or any other sort of evolution for that matter , maintained when faster or longer is always better ? how can genetically homogeneous populations attacked by pathogens survive long enough to mount a coevolutionary response ? the answers may lie in the fact that the world is not made up of single populations of organisms freely exchanging genes . instead , populations are not the same everywhere , and interactions between organisms are not the same everywhere . as is clear from our own species ' experience with its coevolving pathogens , things vary geographically . it was thinking about such questions over the past two decades that led john thompson to propose his geographic mosaic theory of coevolution . although this theory has been widely discussed and has become a unifying framework for many coevolutionary studies , it is still often misunderstood . that there are differences between how organisms interact at different spots on earth is , in itself , a fairly trivial observation , but thompson 's big idea is that without those differences , there would be no coevolution . the geographic mosaic drives coevolution , rather than being merely a consequence of the fragmentation of interacting populations . pattern and process it is significant that thompson 's book the coevolutionary process , which first brought his theory to most of the scientific community , emphasizes process rather than pattern . the processes underlying the geographic mosaic theory of coevolution are difficult to test experimentally , but a new study in bmc biology   of pines and their mycorrhizal fungi , provides the first experimental support for one of the key processes . the geographic mosaic theory of coevolution puts forward three distinct processes that are conjectured to be the basis of coevolutionary change ( figure 1 ) : coevolutionary hot and cold spots , selection mosaics and trait - mixing . a ) populations of interacting species are distributed in a spatial mosaic , with the strength of coevolutionary selection exerted by each partner on the other varying between populations . in cold spots ( here represented by light - colored tiles ) , the traits of each species evolve independently , whereas in hot spots ( dark tiles ) coevolutionary selection is intense . ( b ) as well as varying in strength , the direction of selection varies spatially ( there is a selection mosaic ; represented here as different colored tiles ) , depending on the interactions between the genotypes of both interacting species and the local environment . ( c ) there is some mixing of genes due to the dispersal of individuals between populations ( represented as the individual dots making up the shaded areas ) . the level of mixing must be sufficient to allow the occasional introduction of new genotypes into populations , but low enough that adaptations are not swamped by gene flow from populations experiencing different selection pressures or strengths . ( d ) the combination of all three elements leads to a system in which coevolution is a continuous dynamic process that , at the same time , retains ample genetic variation to allow long - term coevolution . termed hot spots , coevolutionary selection is intense , whereas in cold spots , the interacting species evolve independently of each other . this can be for the simple reason that one of the interacting partners is absent in a cold spot , as is often the case with parasitic interactions in which not every host population is parasitized . cold spots can also exist for other reasons , for example because alternative hosts are present that are preferred by a parasite . there is a continuum between cold and hot spots , with the strength of coevolutionary selection increasing as spots become progressively ' hotter ' . selection mosaics are also important for the theory , but these have often been misunderstood . it is not enough that the strength of coevolutionary selection varies between populations , it is also necessary that the direction of that selection varies , so that the outcomes of coevolution are different in different populations , depending on their environment . in other words , the costs and benefits to both partners of any particular adaptation are dependent not only on the adaptations of their partner , but also on the environment in which the interaction occurs . this is perhaps most easily seen in what have been termed ' conditional mutualisms ' , in which interactions can be mutualistic , commensal or parasitic depending on the ecological conditions in which the partners interact [ 15 - 17 ] . the variation does not , however , need to be so great as to lead to shifts between parasitism and mutualism , but outcomes are dependent on the interactions of the adaptations of both partners with the environment that they find themselves in . hence , the selection mosaic is a result of gene  gene  environment ( g  g  e ) interactions . the different outcomes in different environments can be due either to abiotic factors   or to biotic factors , such as the presence and density of a predator or competitor . finally , in order for the coevolutionary process to work , there must be a mechanism that allows traits that have evolved in one population to be transferred to and mixed with traits that have evolved in other areas . in other words , there must be gene flow between populations to enable genes that are favorable to track the conditions in which they are favorable , and to allow the maintenance of genetic variation that would otherwise disappear . gene flow must also be at the right level ; too much mixing , and there will never be a response to selection because the best adapted genes are always swamped by the inflow of non - adaptive genes ; too little mixing , however , will allow specific alleles to go to fixation so that , barring novel mutations , the coevolutionary process will grind to a halt . as well as the three processes involved in coevolutionary mosaics , there are several patterns that are expected to result from the process . for example , it is expected that there will be spatial variation in the traits that are involved with interspecific interactions ; that in some areas , traits will be mismatched ( local maladaptation ) ; and finally that there will be few species - level traits that have become fixed as a result of coevolution . these patterns are often used as evidence for the presence of a geographic mosaic of coevolution , but they can also result from other , non - coevolutionary processes . in a key paper last year , richard gomulkiewicz and co - workers   set out a rather daunting manifesto for how the geographic mosaic theory of coevolution should be tested and , specifically , how the presence of geographic mosaics of coevolution can be demonstrated . so far there are no studies that have fulfilled all the requirements that have been set forth for testing the theory . there have been several studies inferring hot and cold spots of coevolutionary selection , and others characterizing gene flow between populations involved in interspecific interactions , but most studies have been observational rather than experimental , so that process and pattern can not be disentangled . the area of the theory to which this limitation applies most is the demonstration of selection mosaics , and as a result these have received little rigorous attention . resolving this deficiency has been the focus of the paper in bmc biology , which is the first to examine explicitly the g  g  e interactions required for a selection mosaic to generate coevolutionary change . the study system chosen was the interaction between bishop pine ( pinus muricata ) and the ectomycorrhizal fungus rhizopogon occidentalis . interactions between plants and mycorrhizae are strong candidates for model systems to test the geographic mosaic theory of coevolution , because there are several clear cases of conditional mutualism in which not only the magnitude but also the nature of interaction ( mutualistic or antagonistic ) varies between different ecological situations [ 32 - 34 ] . in a simple but elegant factorial experimental design , piculell et al . tested the interaction between two different lineages of pine and two lineages of fungus in four environments , representing a factorial combination of two different abiotic environments ( two different sterile soil types ) and two different biotic environments ( the presence or absence of potentially competing soil microorganisms ) . measuring various fitness components of the pines and fungi showed that there were variable outcomes for the same combinations of pine and fungus lineages under different conditions ( figure 2 ) and that for one of the pine families , this could indeed result in a mutualistic or parasitic interaction depending on the environment . , showing the measured fitness components of two maternal half - sib families of bishop pine plants ( m18 and m19 , measured as relative growth rate and root length ) and two full - sib families of its mycorrhizal fungus ( 132 and 133 , measured as the number of roots of the host that are inoculated ) under four different environments . the performance of both partners in the interaction varies depending on both the lineage of partner they are interacting with and the environment . this is most clearly seen for fungal performance in field soil , where the number of host roots inoculated varies by an order of magnitude . one simple answer is that the need for such studies has only become apparent recently . piculell and co - workers   needed to successfully raise 128 combinations of pine and fungus , and this was still not quite sufficient to detect any statistically significant g  g  e effects ( although the g  g  biotic environment effects on relative growth rate and shoot : root ratio were close ; p = 0.066 and p = 0.059 respectively ; see additional file 2 in ) . in other systems , in which changes in interaction strength and direction are likely to be more subtle , the experimental replication required for tests powerful enough to demonstrate selection mosaics is intimidating . so , although theoretical studies of the geographic mosaic theory of coevolution are multiplying , it is almost inevitable that empirical studies are lagging behind and tend to be concerned with confirming the predicted patterns rather than experimentally testing the process . translating the outcomes of experimental studies such as that of piculell et al .   into real - world coevolutionary mosaics at the appropriate geographic scale remains a distant goal . in the meantime , large - scale studies of geographical patterns are still crucial for solidifying the foundations of the theory , and for parameterizing the next generation of theoretical models . i thank koos boomsma for valuable discussion and comments . funding for the centre for social evolution
the geographic mosaic theory is fast becoming a unifying framework for coevolutionary studies . a recent experimental study of interactions between pines and mycorrhizal fungi in bmc biology 
 is the first to rigorously test geographical selection mosaics , one of the cornerstones of the theory .