Jeremy J. Burdon

The conservation of plant biodiversity

Preface Part I. Introduction: 1. The biological system of conservation Part II. Diversity and Conservation of Plant Genes: 2. The genetic diversity of wild plants 3. The genetic diversity of cultivated plants 4. The conservation of cultivated plants Part III. Conservation of Plant Species: 5. Plant species conservation and population biology 6. The conservation in situ of useful or endangered wild species 7. Ex situ conservation of threatened and endangered plants Part IV. Conservation of Plant Communities: 8. Community structure and species interactions 9. Choosing plant community reserves 10. Managing plant community reserves 11. Conclusions References Index.

Life history determines genetic structure and evolutionary potential of host–parasite interactions

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns.

LOCAL ADAPTATION IN THE LINUM MARGINALE–MELAMPSORA LINI HOST-PATHOGEN INTERACTION

Abstract The potential for local adaptation between pathogens and their hosts has generated strong theoretical and empirical interest with evidence both for and against local adaptation reported for a range of systems. We use the Linum marginale—Melampsora lini plant‐pathogen system and a hierarchical spatial structure to investigate patterns of local adaptation within a metapopulation characterised by epidemic dynamics and frequent extinction of pathogen populations. Based on large sample sizes and comprehensive cross‐inoculation trials, our analyses demonstrate strong local adaptation by Melampsora to its host populations, with this effect being greatest at regional scales, as predicted from the broader spatial scales at which M. lini disperses relative to L. marginale. However, there was no consistent trend for more distant pathogen populations to perform more poorly. Our results further show how the coevolutionary interaction between hosts and pathogens can be influenced by local structure such that resistant hosts select for generally virulent pathogens, while susceptible hosts select for more avirulent pathogens. Empirically, local adaptation has generally been tested in two contrasting ways: (1) pathogen performance on sympatric versus allopatric hosts; and (2) sympatric versus allopatric pathogens on a given host population. In situations where no host population is more resistant or susceptible than others when averaged across pathogen populations (and likewise, no pathogen population is more virulent or avirulent than others), results from these tests should generally be congruent. We argue that this is unlikely to be the case in the metapopulation situations that predominate in natural host‐pathogen interactions, thus requiring tests that control simultaneously for variation in plant and pathogen populations.

Host-pathogen dynamics in a metapopulation context:the ecological and evolutionary consequences of being spatial

1 The metapopulation concept is useful when considering ecological and evolutionary dynamics of spatially structured populations. However, debate has focused on genetic variation that is neutral rather than under selection. This distinction is particularly important in antagonistic or co-evolutionary interactions such as host-pathogen or predator-prey systems. Plant host-pathogen systems provide some of the best examples of studies in which numerical and genetic dynamics have been investigated in a spatially explicit context, and where genes under selection can be unambiguously identified. 2 Empirical studies of natural host-pathogen interactions have shown that, while in some cases pathogens appear to be locally adapted to their hosts, in others there is no local correspondence between resistance and virulence genes. Recent theory suggests that the dynamics (epidemic vs. endemic) and migration rates of host and pathogen will be important factors in the maintenance of genetic polymorphisms in resistance and virulence. 3 We argue that the relative spatial scales at which hosts and pathogens interact are crucial to understanding the evolution of resistance/virulence structure. Pathogens that disperse further than their hosts will be more likely to show gene-for-gene interactions than pathogens dispersing over spatial scales similar to or smaller than their hosts. 4 We predict that life-history features that influence encounter rates between specific host and pathogen genotypes will be important factors in determining the evolution of resistance-virulence structures. In particular, we would expect correlative and/or causal relationships between pathogen life-history features [e.g. local vs. systemic infection, type (fecundity vs. mortality) and severity of effects], and whether dynamics are endemic or epidemic. 5 Plant host-pathogen systems provide ideal models for investigating the evolution of non-neutral genetic variation in spatial systems. Understanding the co-evolution of such systems will require research programmes that integrate long-term descriptive and experimental studies of multiple populations, with analytical and computer simulation modelling and comparative/phylogenetic studies.

Host-pathogen interactions in natural populations of Linum marginale and Melampsora lini. I, Patterns of resistance and racial variation in a large host population

Populations of wild flax, Linum marginale and its associated rust fungus Melampsora lini growing at Kiandra, New South Wales, Australia, were sampled during the 1986–1987 growing season. Thirteen different races of M. lini were detected in a sample of 96 isolates. The distribution of isolates was uneven: race A comprised 73% of the samples; race N, 8%; and race H, 5%; while the remaining races were represented by only one or two samples. The dominance of race A increased over the course of the growing season, comprising 67% of the early season samples and increasing to 78% for those collected late in the season. The overall diversity of the pathogen population decreased late in the growing season, but this trend was not statistically significant. The average virulence of individual isolates of the pathogen population increased during the growing season. This trend was most pronounced among the minor races, where the mean number of differential hosts infected increased from 4.58 for early season samples to 5.12 and 5.08 for mid and late season samples, respectively. In contrast to the virulence pattern in the pathogen, the L. marginale population displayed a more even distribution of resistance. In a sample of 67 plants 10 resistance phenotypes were detected from their pattern of resistance/susceptibility to seven pathogen isolates. No phenotype had a frequency that exceeded 30%. Resistance phenotypes were randomly distributed on both a population level and on a fine scale.

Rapid genetic change underpins antagonistic coevolution in a natural host‐pathogen metapopulation

Antagonistic coevolution is a critical force driving the evolution of diversity, yet the selective processes underpinning reciprocal adaptive changes in nature are not well understood. Local adaptation studies demonstrate partner impacts on fitness and adaptive change, but do not directly expose genetic processes predicted by theory. Specifically, we have little knowledge of the relative importance of fluctuating selection vs. arms-race dynamics in maintaining polymorphism in natural systems where metapopulation processes predominate. We conducted cross-year epidemiological, infection and genetic studies of multiple wild host and pathogen populations in the Linum-Melampsora association. We observed asynchronous phenotypic fluctuations in resistance and infectivity among demes. Importantly, changes in allelic frequencies at pathogen infectivity loci, and in host recognition of these genetic variants, correlated with disease prevalence during natural epidemics. These data strongly support reciprocal coevolution maintaining balanced resistance and infectivity polymorphisms, and highlight the importance of characterising spatial and temporal dynamics in antagonistic interactions.

Host-pathogen interactions in natural populations of Linum marginale and Melampsora lini. III. Influence of pathogen epidemics on host survivorship and flower production.

SummaryThe epidemiology of rust caused by the fungus Melampsora lini and the effects of infection by this pathogen on its host, the herbaceous perennial Linum marginale, were determined in the field and in garden experiments. There was considerable natural variability in disease levels over the four years (1986–1989) of the study. In two years (1986, 1989) major rust epidemics occurred. In the field, the main effect of disease was to reduce survivorship during the winter following infection. Plants which were heavily infected during the 1986 or 1989 growing seasons had reduced survivorship relative to more lightly infected plants. Melampsora lini infections did not appear to affect survivorship in either 1987 or 1988. Flowering was correlated with environmental factors and the number of stems a plant possessed. A severe drought in 1987 completely inhibited flowering. In the other three years the number of flowers produced by a plant was strongly positively correlated with the number of stems it possessed. Disease levels had no consistent effect on flowering. Controlled garden experiments were also used to examine the response of seedlings and adult plants to infection. These showed that both the timing and severity of disease appears to determine the effect of M. lini infections on L. marginale. Early, severe infection reduced growing season and overwintering survivorship as well as capsule production. However, plants in the field were most often infected only after flowering had begun, and the predominant effect of infection was a reduction in overwintering survivorship. The high variability in disease levels from year to year and the deferred nature of the effect of the rust on its host have significant implications for the design of experiments aimed at assessing the role of diseases in plant communities.

Evolution in agriculture: the application of evolutionary approaches to the management of biotic interactions in agro-ecosystems

Anthropogenic impacts increasingly drive ecological and evolutionary processes at many spatio‐temporal scales, demanding greater capacity to predict and manage their consequences. This is particularly true for agro‐ecosystems, which not only comprise a significant proportion of land use, but which also involve conflicting imperatives to expand or intensify production while simultaneously reducing environmental impacts. These imperatives reinforce the likelihood of further major changes in agriculture over the next 30–40 years. Key transformations include genetic technologies as well as changes in land use. The use of evolutionary principles is not new in agriculture (e.g. crop breeding, domestication of animals, management of selection for pest resistance), but given land‐use trends and other transformative processes in production landscapes, ecological and evolutionary research in agro‐ecosystems must consider such issues in a broader systems context. Here, we focus on biotic interactions involving pests and pathogens as exemplars of situations where integration of agronomic, ecological and evolutionary perspectives has practical value. Although their presence in agro‐ecosystems may be new, many traits involved in these associations evolved in natural settings. We advocate the use of predictive frameworks based on evolutionary models as pre‐emptive management tools and identify some specific research opportunities to facilitate this. We conclude with a brief discussion of multidisciplinary approaches in applied evolutionary problems.

Coevolution of plants and their pathogens in natural habitats.

Understanding of plant-pathogen coevolution in natural systems continues to develop as new theories at the population and species level are increasingly informed by studies unraveling the molecular basis of interactions between individual plants and their pathogens. The next challenge lies in further integration of these approaches to develop a comprehensive picture of how life history traits of both players interact with the environment to shape evolutionary trajectories.

Pathogen evolution across the agro-ecological interface: implications for disease management.

Infectious disease is a major causal factor in the demography of human, plant and animal populations. While it is generally accepted in medical, veterinary and agricultural contexts that variation in host resistance and pathogen virulence and aggressiveness is of central importance to understanding patterns of infection, there has been remarkably little effort to directly investigate causal links between population genetic structure and disease dynamics, and even less work on factors influencing host–pathogen coevolution. The lack of empirical evidence is particularly surprising, given the potential for such variation to not only affect disease dynamics and prevalence, but also when or where new diseases or pathotypes emerge. Increasingly, this lack of knowledge has led to calls for an integrated approach to disease management, incorporating both ecological and evolutionary processes. Here, we argue that plant pathogens occurring in agro‐ecosystems represent one clear example where the application of evolutionary principles to disease management would be of great benefit, as well as providing model systems for advancing our ability to generalize about the long‐term coevolutionary dynamics of host–pathogen systems. We suggest that this is particularly the case given that agro‐ecological host–pathogen interactions represent a diversity of situations ranging from those that only involve agricultural crops through to those that also include weedy crop relatives or even unrelated native plant communities. We begin by examining some of the criteria that are important in determining involvement in agricultural pathogen evolution by noncrop plants. Throughout we use empirical examples to illustrate the fact that different processes may dominate in different systems, and suggest that consideration of life history and spatial structure are central to understanding dynamics and direction of the interaction. We then discuss the implications that such interactions have for disease management in agro‐ecosystems and how we can influence those outcomes. Finally, we identify several major gaps where future research could increase our ability to utilize evolutionary principles in managing disease in agro‐ecosystems.