FLAG

Wednesday 28 November 2012

Full title and Summary

FOREST TREE ECOLOGICAL GENETICS: INTERPLAY OF GENE FLOW AND ENVIRONMENTAL VARIABILITY IN SHAPING LOCAL ADAPTATION AND GENETIC ADAPTIVE POTENTIAL

Environmental gradients and patchiness shape the level and the distribution of genetic diversity of adaptive significance. A rich literature describes how gene frequencies vary along gradients and deals with the interaction of local selection and global gene flow. The implicit assumption is that populations evolving according to divergent selective pressures have to be sufficiently isolated for long term selective divergence to take place. Genetic pools differentiating along gradients and between patches store large amounts of genetic variability and thus favour the maintenance of a species’ adaptive potential. Measuring and modelling the amount of divergence among populations under divergent ecological conditions is therefore central to the prediction of how populations may respond to future local and global environmental changes.

The turnover of genetic variants over gradients and habitat patches has traditionally been studied on geographical scales between regional and global. However, it can be argued that, for long-lived organisms, the large amounts of observed within-population genetic diversity may be maintained at least partly by local selection. In some instances, environmental conditions vary on a spatial scale that is comparable to, or even shorter than, average gene flow distances, thus setting the conditions for the interplay between selection and dispersal in the generation of observed patterns of diversity. Under these conditions, local differentiation among sub-populations for adaptive traits and genes may be maintained in spite of, and in some cases thanks to, ongoing gene flow. A combination of landscape and ecological genetic approaches makes it possible to investigate these phenomena, which have been shown to occur only for a limited set of plant species.

Strategies to infer and model the strength of selection at target genes require prior knowledge of the loci under selection; however, current sequencing technology, combined with intensive field sampling of natural populations, can lead to the identification of selectively significant loci by population genomic approaches, even for non-model species. Providing genotypes for thousands of Single Nucleotide Polymorphisms (SNP) for hundreds of individuals has currently become feasible and relatively cheap. Quantitative genetics tools can now be successfully used to validate the association between SNP frequencies, phenotypic values, and environmental gradients. The time is therefore ripe for starting to address these major ecological-genetic questions directly in ecologically relevant species.

The present project aims at investigating the complex genome-wide effects of local adaptation in nine keystone tree species from four major terrestrial ecosystems. Here we address the question of whether and how genetic diversity in forest tree stands, occurring across environmental gradients, is spatially structured by selective forces, and we propose to estimate the proportion of the genome undergoing such processes as well as to identify genes under selection. We propose an original use of classical quantitative genetic tools applied to in-situ progeny tests (reciprocal transplant experiment and replicated provenance tests) to validate SNP-trait-environment associations. The intensity of migratory and adaptive processes will be modelled thanks to advanced modelling strategies and will allow us to provide predictions of the response of forests to climate changes. We focus here on water availability gradients in particularly sensitive forest areas, such as the Guiana shield, the Mediterranean basin, Sub-Saharan Africa and the Brazilian Cerrado; all these regions suffer broad seasonal changes in soil water availability and are expected to undergo abrupt rainfall changes in the near future. Therefore, studying how forest tree populations cope with ecological gradients is at the fore among tools to predict the impact of expected future environmental changes.

Partnership

Seven laboratories are involved in the FLAG program: one in French Guiana, three in continental France, one in Brazil, one in Spain and One in Italy. All have a strong background in forest tree population genetics and genomics, in (wet and dry) tropical, Mediterranean or temperate species.

Partner 1, INRA-ECOFOG (Kourou)

INRA-ECOFOG (Kourou) is the coordinating partner. The Research Unit is devoted to the study of the ecology and genetics of tropical forest ecosystems, with focus on Amazonian forests. The team involved in the project is specialised in the identification of patterns of genetic diversity in tropical forest trees at scales varying from the stand to the continent. The processes studied by the team involve: adaptation to local and regional environmental gradients through the genotyping of SNPs in expressed sequences and the modelling of their diversity as a function of demographic and selective processes in contrasting environments at the local and regional scale; study of diversity in quantitative traits as a function of local and regional environmental variation through the use of reciprocal transplants; analysis of demographic patterns at the scale of the stand; phylogeography and historical biogeography; genomics of ecological speciation. The team’s background is in molecular biology and genetics, statistical genetics and evolutionary genetics. The team is and has been involved in several research partnerships, both at the national and international level, as coordinator or as participant.

Partner 2, INRA-URFM (Avignon)

INRA-URFM (Avignon) is a multi-disciplinary lab. The group of scientists involved in the project specializes in population genetics and ecology of Mediterranean trees. It has extensive knowledge in population and quantitative genetics, genotypic databases, spatial analyses, modelling and meta-analyses. It has produced genetic diversity estimates, modelling tools, reconstructed phylogeographic patterns and proposed conservation schemes for several Mediterranean trees. Partner 2 also has strong stakeholder engagements: it belongs to the Euforgen network as well as the French forest tree gene conservation network. INRA-URFM has also extensive expertise in functional ecology and community dynamics. It is currently involved in characterizing and modelling the main ecophysiological traits related to drought sensitivity and climate vulnerability in fir species. The group was part of the Network of Excellence Evoltree, it has coordinated the Integrated Project Fire-Paradix and has coordinated 8 WP in various EU-funded projects during the last 4 years. It develops intensive collaboration with the Mediterranean scientific community, noticeably through the European Forest Institute. Collectively, INRA-URFM has published over 67 papers on Mediterranean forest ecology, genetics and ecosystem functioning during the last 5 years.

International Partner 3: CIFOR-INIA (Madrid, Spain)

CIFOR-INIA: Centro de Investigación Forestal - Instituto Nacional de Investigación y Technología Agraria y Alimentaria, Madrid, Spain. CIFOR-INIA has expertise in population and quantitative genetics, evolutionary ecology and population dynamics. The team’s research focuses on the demographic, reproductive and genetic processes that influence adaptation to changing environments of forest species, including biogeography approaches and applications for management and conservation of forest genetic resources, and with particular interest in ecosystems of high biological diversity, such as the Mediterranean and tropical forests. The team develops studies on gene flow, local adaptation, plasticity and phenotypic integration and of the molecular basis of adaptation, as well as new statistical methods. The team is highly multidisciplinary with publications in the top part of SCI lists for Ecology, Forestry, Genetics & Heredity, Evolutionary Biology, Agronomy, Plant Sciences and Biodiversity & Conservation (over 120 SCI papers in the last 5 years; 32 papers in 2010).

International Partner 4: Universidade federal de Goiás (Goiânia, Brazil)

Universidade federal de Goiás – Goiânia, Brazil. Rosane G. Collevatti is an expert in tropical tree biodiversity and in the structure of genetic diversity within and between populations of tropical trees. She is involved in projects about the distribution of neutral and adaptive genetic variation within and among populations of several tree species from Amazonia and the cerrado. Her background is in the investigation of spatial genetic structure and phylogeography of tropical trees. Her expertise in the study of tropical ecosystems, and in particular about the genetics of adaptation to drought stress, is a major component of the project.

Partner 5: INRA-AGPF (Orléans)

INRA Orléans is developing a research line concerning the study of adaptation of forest trees. This research line is based on complementary phenotypic and genotypic approaches along an altitudinal gradient in the Alps. This research activity is conducted by a Functional Research Group called “Adaptation to Climate Variation”, part of the Research Unit “Amélioration, Génétique et Physiologie Forestières” (AGPF) of INRA Orléans. This functional group assembles scientists and technicians of the research unit AGPF and of the experimental unit GBFOR (also of INRA Orléans) that play a role in the research contracts contributing to the research line “adaptation to climate variation”. At the moment, three national (GRAAL, Xylome) and three international projects (ECOS-Sud, Baccara, NovelTree) are under way.

Partner 6: INRA-BIOGECO (Bordeaux)

The Research Unit UMR BIOGECO (https://www4.bordeaux-aquitaine.inra.fr/biogeco/) is a joint Research group of INRA and University of Bordeaux 1. The unit comprises population, quantitative and evolutionary geneticists, plant pathologists, entomologists and ecologists (25 scientists). The main research activities address the analysis and evolution of biological diversity in terrestrial ecosystems, with particular emphasis on temperate forest ecosystems. The core of our research is to develop methods for assessing, monitoring, predicting and using diversity and its components in the perspective of the sustainable management of terrestrial ecosystems. More specifically, the activities of BIOGECO related to this project are oriented in four different fields: 1) Population and evolutionary genetics of Fagaceae species (mainly Quercus (oaks) and Fagus (beech)), tropical trees of the French Guyana rain forest and Maritime pine (Pinus pinaster), 2) Genetic mapping, QTL analysis in Maritime pine, Oaks and Eucalyptus; 3) Proteome and transcriptome analysis in Maritime pine, Eucalyptus, Oak and Poplar; 4) Tree improvement and selection methods in Maritime pine. Concerning excellence, UMR BIOGECO coordinated within FP4 and FP5 different research projects supported by the EU (FAIROAK, OAKFLOW, FORADAPT, CYTOFOR, GEMINI) related to population and molecular genetics of forest trees. It has excellent publication records in top ranking international journals (Science,Current Opinion, PNAS, Genetics Evolution, Molecular Biology and Evolution, Proteomics, Plant Physiol, New Phytol…). By its expertise and experience, UMR BIOGECO has significantly contributed to the recent developments of population genetics and genomics in forest trees in Europe. This research unit coordinated the network of excellence EVOLTREE (http://www.evoltree.org/). Two teams of BIOGECO will be involved (“population genetics” team focusing on Larix decidua, “functional genomics and ecophysiology” team on Pinus pinaster).

International Partner 7: CNR-IGV (Florence, Italy)

The Research Group of the CNR-Firenze is experienced in developing and using molecular markers in forest species. Investigations have been carried out on relevant aspects of population and conservation genetics of forest species. Analyses have been conducted on genetic variability using DNA markers for the description of reproductive processes, geographic variation, spatial genetic structure, for understanding migration history in the post-glacial period and the molecular basis of adaptation. The group has developed and optimised different methods of molecular analysis. In the lab all the techniques for the analysis of DNA markers have been automated and optimised in fully equipped labs. Expertise is also available on genetic data analysis and statistics, including approaches for spatial interpolation to produce maps of the distribution of diversity. The group maintains contacts and has been engaged in collaborative works with many international research units, within EU funded projects (more than 20 EU sponsored projects). The group published several scientific papers in the most relevant journals on population and conservation genetics of forest tree species. The CNR Firenze takes advantage by the cooperation with the Biotechnological Platform on Genomic and Proteomics (Genexpress laboratory) of the University of Florence. Genexpress lab is equipped with a MegaBace 96 capillary automatic sequencer, an ABI Biosystem 16 capillary automatic sequencer, 2 robotic workstations, a colony picker, 15 PCR thermal cyclers.

Background

Environmental gradients and contrasts and the interplay between adaptation and gene flow

The idea that environmental variation causes differential selection is intrinsic to the Theory of evolution and is the base for the mechanism of population divergence by natural selection (Darwin 1859) and of speciation (Coyne& Orr 2004; Schluter 2001). If single traits or groups of traits are involved in local adaptation, if those fitness-related traits are heritable and if fitness of a given phenotype is a function of environmental conditions, then different genotypes or alleles will be favoured in different environmental conditions; thus ecological filtering provides the basis for natural selection. In the classical view, populations subject to different environments diverge towards different phenotypic and genetic optima under the action of natural selection and tend eventually to diverge until fixation of different alleles. Migration and drift mitigate this trend; they retard fixation and lead to a dynamic evolutionary equilibrium at some intermediate level of divergence.

This general frame of reference acquires further complexity when considerations about the spatial distribution of environmental conditions are added to the picture. The scale at which the relevant ecological parameters change can vary from very local and chaotic, with a patchy spatial distribution of fitness optima, to intermediate, with ecological turnover at the landscape scale, to regional and continental, with very gradual and often smooth changes occurring at the scale of a species’ distribution range. If the environmental change is roughly monotonic, then it is called a gradient. The study of the way genetic diversity is coupled with environmental gradients rests on solid theory, and starts from the rather intuitive idea that genetic turnover can be quantified through changes in allele frequencies, and that if a gradient influences allele frequencies, then the latter must be correlated to the former (Epperson 2003). Although with considerable refinement, this is the base of all studies of ecological-genetic gradients (Bergmann 1978; Coop et al. 2010; Eckert et al. 2010a; Eckert et al. 2009; Ingvarsson et al. 2005; Joost et al. 2007; Montesinos-Navarro et al. 2011). This treatment can be extended to contrasts between environments that are arranged in more complex geographic patterns, for example in the case of mosaic habitat heterogeneity; the underlying assumption can be generalized as a detectable difference in gene frequencies between populations inhabiting contrasting habitats.

It can of course be argued that ecological conditions can exert their effect on gradients of allele frequencies only insofar as (a) all genotypes are exposed to all environments, so that ecological filtering adjusts genetic composition to maximised population fitness in each environment and (b) genetic drift and migration do not erase the effects of ecological filtering. Therefore, the possibility of local adaptation depends not only on variation in ecological conditions, but also on dispersal rates and gene flow (Lenormand 2002, Kawecki and Ebert 2004).

In the last decades, population geneticists have devoted much ingenuity to the estimation of gene flow from in situ biological data. Traditional approaches rely on patterns of genetic structure among populations or individuals to derive indirect estimate of the historical rate of gene flow assuming a model of population structure (e.g. isolation by distance). More recently, highly variable molecular markers such as microsatellite combined with parentage analyses have been increasingly used to estimate real-time patterns of seed and pollen flow from parental to offspring generation. These approaches have been applied to many different forest trees in the last decade (see review by Ashley et al. 2010): they show that long-distance dispersal of pollen is common in both wind and animal dispersed systems, with average pollination distances commonly being hundreds of meters. Seed dispersal appears more restricted, though it may be erroneous to assume that seeds growing under the crown of a conspecific adult are growing beneath their mother, or that seed dispersal distances are more limited than pollen dispersal distances. Overall, both pollen and seed dispersal are typically leptokurtic in trees, with most of the dispersal event occurring in close neighbourhood, and few, often non-negligible long-distance dispersal event (Austerlitz et al 2004, Oddou-Muratorio & Klein 2008).

Local adaptation can occur at short geographical scales

In general, the effect of environmental gradients is sought at scales that go from regional to continental, because it is implicitly assumed that at shorter scales migration will systematically overwhelm selection, especially for highly mobile organisms (at least at some stage of their biological cycle), such as vascular plants. According to a generally accepted point of view, the scale of population-divergence processes is roughly proportional to the size of the organisms (Holderegger et al. 2010). However, the interaction of selection and gene flow has been the focus of population genetics for decades, and Antonovics (1968) has modelled it more than forty years ago. There are reasons to think that the action of selection should be visible even at very local scales. One reason is that gene flow tends to homogenise sub-populations at each generation, but selection can accumulate its effects over several generations, thus gradually shifting sub-populations towards differentiation. The second is that even in the absence of selection gradients, genetic relatedness tends to be spatially structured in plant populations (and particularly in trees) because of preferential dispersal in the close neighbourhood, and this should reinforce differential, spatially structured selection. Finally, most plant populations produce a large excess of seeds and seedlings each season, which should set the stage for very strong selection, even if it is partially confounded by random processes. Tree populations can display adaptive divergence within a range of less than 3 km (Jump et al. 2006) and parapatric speciation for palms has likely occurred on a single 12-km² island, sometimes even interpreted as sympatric speciation (Babik et al. 2009; Savolainen et al. 2006), a kind of event among the most elusive to detect. Thus, even for long-lived organisms such as trees and palms it is possible to observe genetic divergence at a very local scale, in spite of the (real or expected) presence of recurrent gene flow among environmental patches or portions of the gradient. It is therefore entirely legitimate to ask the question as to whether local interplay of selection and gene flow contributes to the diversification of subpopulations and to the build-up and maintenance of genetic diversity and adaptive potential in tree species.

Jump and Peñuelas (2005) have reviewed proofs that intra-population genetic variation for traits and genes related to response to climate change exists in plant species. They came to the conclusion that, depending on the species and on the amount of standing heritable variation, populations may or may not be able to adapt to rapidly changing environmental conditions. Their analysis rests on a long tradition of studies on local adaptation to patchy or continuously varying environments, of which clear examples are found in annual plants for the landscape level (Angert& Schemske 2005; Manel et al. 2010; Poncet et al. 2010) but also for the within-population scale (Schmitt& Gamble 1990), both for quantitative traits and for molecular variation. In some instances, local adaptation has been identified at the molecular level for tree species (Jump et al. 2006) while adaptation at the regional scale is a well known phenomenon for all plants and for trees in particular (Eckert et al. 2010a; Eckert et al. 2010b; Eckert et al. 2009; Savolainen et al. 2007). Environmental gradients influence fitness, which tends to be optimized in locally adapted populations (Angert& Schemske 2005). Even though this is not always the case, this is a direct indication of the way natural selection shapes the distribution of genetic diversity.

Environmental gradients and the distribution of genotypes

Indications in favour of local adaptation in spite of gene flow have been reported at the very short spatial scale in artificial plots for outcrossing, wind-pollinated annual plants (Freeland et al. 2010) but also on larger scales for wind-pollinated trees (Eckert et al. 2010a; Eckert et al. 2010b; Eckert et al. 2009; Eveno et al. 2008; Savolainen et al. 2007). Recent unpublished results, obtained in the coordinator’s laboratory show that it is possible to single out SNP loci showing strong divergence between sub-populations of the tropical tree Eperua falcata being separated by no more than 100 m along a soil water content gradient, whereas overall divergence is effectively zero (Audigeos, PhD thesis and Audigeos et al. in press). The same pattern is observed for AFLP markers in another tropical tree, Symphonia globulifera (Casalis unpublished) and for quantitative traits in E. falcata (Brousseau et al. submitted), as well as for AFLP markers in Virola michelii (Montaigne et al. in prep.). Interestingly, these patterns are not restricted to tropical species, as association between SNPs with environmental traits varying at a scale of hundred of meters have also been found in sympatric Mediterranean pine (Pinus pinaster and P. halepensis) populations in eastern Spain (Budde, PhD thesis and Budde et al. in prep.). In general, the possibility of strong divergence in spite of gene flow can be explained because realised gene flow is constrained by habitat selection (Kawecki& Ebert 2004), with selection operating on each cohort by selecting genotypes adapted to each habitat. On the other hand, gene flow may actually enhance the capacity of populations to adapt to their environment thanks to the introgression of beneficial alleles (Kane et al. 2009) and quantitative-trait population divergence by local adaptation may be enhanced by moderate levels of gene flow (Goudet et al. 2009).

Linking environment, adaptation, traits and genomic loci

An essential element of the description of the way genetic processes lead to local adaptation is the link between genotypes, phenotypes and response to the environment (or fitness). In particular a strong hypothesis underlying the existence of gradients of allele frequencies driven by ecological conditions is that adaptive response to ecological filtering is somehow gradual, without major threshold effects corresponding for instance to trade-off in strategies involved in local adaptation. Whereas genome scan approaches to link genetic variation to gradients has rapidly advanced, our capacity to perform extensive phenotypic measurement in situ and to map relationships between genotypes and phenotypes and phenotype and fitness in natural populations is lagging behind.

The relation between environment (e.g. climate) and the traits involved in local adaptation can be addressed through the concept of functional traits. Different functional traits (leaf, physiological, phenological, reproductive and allometric traits) are likely to affect plant fitness, i. e. to favour survival or reproduction of individual showing phenotypic values close to the optimum value for one or several traits. Comparative studies have shown the existence of clines of phenotypic variation along environmental gradients (Geber, Griffen, 2003; Wright et al., 2004). Ex-situ experimental plantations were also used to quantify the genetic determinism of functional traits within species (Arntz, Delph, 2001; Geber, Griffen, 2003, Scotti et al 2010). However, we still have limited knowledge in tree populations of the respective importance of environmental (phenotypic plasticity) versus genetic (adaptation) determinism of the variability in functional traits observed within species, and on the strength of selection on functional traits. Yet, investigating this issue is crucial to predict the adaptive response of tree population in response to ongoing and predicted climate change. As described below, we propose here to merge approaches to detect loci correlated to environmental gradients and loci underlying functional traits. We will focus on vigour / survival traits, because they are likely to be among the most relevant traits for seedling establishment and initial growth (which in its turn increases the chances of survival) and simple measures of photosynthetic capacity. These traits are easy to measure in seedlings and reciprocal transplants (as well as common garden / provenance tests, replicated across environmental conditions) will permit to obtain large amounts of trait data; these will be matched to SNP genotype data, in an approach inspired by association mapping strategies (Price et al. 2010; Neale and Savolainen 2004), to confirm the biological role of SNPs that will have been found to be associated with environmental gradients. Although the approach we will use is not typical association mapping, the population stratification used to produce reciprocal transplants and replicated common gardens will provide enough statistical power to verify the association between loci and traits.

Indeed, studying local adaptation requires high statistical power, and this means large samples and a population genomic approach (Luikart et al. 2003; Santiago C. González-Martínez et al. 2006) to identify loci under selection. Recent technological and methodological advances permit to apply high-throughput sequencing methods to non-model species (Eckert et al. 2010a; Eckert et al. 2010b), to contrast the genomic composition of populations (Turner et al. 2010) and to apply tests to detect selection to genome-wide SNP data (Nielsen et al. 2009; Nielsen et al. 2005; Siol et al. 2010). Given that obtaining genomic data has been made cost- and time-effective by the very same techniques, the current rapidity and ease of obtaining genome sequences, polymorphism information and SNP data provides the opportunity to quickly obtain powerful information even in poorly characterised species. The focus can now shift from easy-to-characterise, but often ecologically unimportant, model species, to ecologically important species. Important evolutionary-ecological questions, such as those described above on local adaptation, can now be answered directly in the relevant populations.

The state of the art in FLAG target species

To address the question of the amount of local adaptation in these ecosystems, we will concentrate on common tree species that (a) have been shown to occur over relatively large spans of environmental conditions (b) display trait and/or allele frequency distributions that correlate with the gradients; and for which (c) genomic and/or population-genetic data are already available. Moreover, the species chosen are social (i.e. they grow in relatively dense stands) and share reproductive and dispersal properties (i.e. they are outcrossing and have long-distance pollen dispersal and limited seed dispersal). These shared properties will allow us to extrapolate ecological-genetic trends with a common demographic background, and to take full advantage of the diversity of ecosystems the species belong to. The combination of dense stands, limited seed dispersal and intense mixing through pollen is ideal to pinpoint the interplay between local selection and gene flow.

The partners involved in this project have already proceeded to establish experimental setups aiming to answer questions on the interplay of selection and gene flow in local gradients and contrasts by combining genome scans and quantitative genetics and developed mathematical models to describe these processes. In tropical trees, low-throughput sequencing and genotyping techniques have been used to detect loci under selection in natural stands (Audigeos et al. 2010; Chevolot et al. 2011), and reciprocal transplants have been set up to study genotype  environment interactions and to validate the SNPs under selection by correlating them with survival and fitness traits. The existence of heritable diversity in growth and survival traits in tropical forest tree populations has been proven (Coutand et al. 2010; Scotti et al. 2010), and genomic data are available or are due shortly for all the target tropical species. In Fagus sylvatica, three populations of minimum 110 individuals each distributed along a 600 m-elevation gradient in Mont Ventoux, South-Eastern France, have been phenotyped for fitness-related tree-ring characteristics and budburst phenology. Around 20 variable microsatellites loci are available, 485 SNP were identified in 57 gene fragments.

In Abies alba, three altitudinal gradients in South-Eastern France of adults are intensively monitored since 2005, and reciprocal transplant experiments involving 70 half-sib families from 3 sites and 3 altitudinal levels each were installed in 2009.

Cedrus atlantica was introduced in France 150 years ago and it provides a unique opportunity to follow genetic changes during a naturalisation process in a new environment since we have access to the consecutive generations of trees (Lefèvre et al, 2004). In situ, 200 adult trees from three generations that experienced different environments during the stand development were characterised for their response to water stress (Fallour-Rubio et al, 2009). A progeny test comparing 74 of these seed-trees was installed in controlled stress condition. SNP from drought related candidate genes are available, transcriptome-wide SNP discovery is currently in progress.

In Larix decidua, four populations of 200 individuals each, distributed along a 1000 m-elevation gradient in the Alps, have been phenotyped for fitness-related tree-ring characteristics. Each population is currently being genotyped using a set of microsatellite markers. Reciprocal transplant experiments involving 30 randomly-selected individuals from each altitudinal plot are under preparation.

Linking genetics and environment through modelling: the predictive power of ecological genetics

The future response of tree populations to changing climatic conditions depends on the response to climate-induced selection, pollen and seed migration abilities and phenotypic plasticity (Aitken et al. 2008) The adaptive potential of tree populations in general and the role of pollen flow in introducing new favourable alleles along spatio-temporal environmental gradient remain largely unresolved (Kremer et al. in press). Theoretical models dealing with local adaptation have provided valuable predictions for the respective effect of gene flow, environmental gradient and genetic architecture of selected traits on evolutionary trajectories of populations (e.g. Slatkin 1978; Kirkpatrick & Barton 1997, Garcia-Ramos & Kirkpatrick 1997). However, these models show several limitations when addressing the adaptive response of natural populations to climate change. First, there is a need for short-time scale predictions (few generations), and for populations out of equilibrium, particularly for long-lived organism such as trees. Theoretical model usually consider equilibrium situation as can be reached after several thousands of generations and typically assume a fixed relationship between phenotype at a given trait and fitness, with optimum value varying through space (and rarely through time, but see Pease et al 1989). Yet, we can expect the relation between life history trait and fitness to change when environment changes both in space and time (both optimum values and type/intensity of selection vary). Finally the effect of climate change as a selective pressure is non linear and complex.
More recently, process –based model coupling ecophysiological and/or demographic model in a quantitative genetics context have been proposed to study the rates of multi-traits evolution by including genetic details and demographic/ecological feedback at short time and spatial scale (the so-called eco-genetic, or demo-genetic models, Dunlop et al., 2009). For example, Kramer et al. (2008) studied the potential of adaptive response of a beech stand for different traits (budburst phenology, spiral grain, height growth) explicitly connected to climatic input variables through an ecophysiological model. Kuparinen et al (2010) fitted a mechanistic model of pollen and seed dispersal into a quantitative genetic individual-based simulations model to disentangle the relative roles of mortality, dispersal ability and maturation age for the speed of adaptation in Scots pine (Pinus sylvestris) and Silver birch (Betula pendula). Eco-genetic models are thus interesting tool to model the adaptive dynamics of individuals as a function of their genotype, and of environmental conditions.

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Nielsen R, Williamson S, Kim Y, et al. (2005) Genomic scans for selective sweeps using SNP data. Genome research 15, 1566-1575.

Poncet BN, Herrmann D, Gugerli F, et al. (2010) Tracking genes of ecological relevance using a genome scan in two independent regional population samples of Arabis alpina. Molecular Ecology 19, 2896-2907.

Santiago C. González-Martínez, Konstantin V. Krutovsky, David B. Neale (2006) Forest-tree population genomics and adaptive evolution. New Phytologist 170, 227-238.

Savolainen O, Pyhäjärvi T, Knürr T (2007) Gene Flow and Local Adaptation in Trees. Annual Review of Ecology, Evolution, and Systematics 38, 595-619.

Savolainen V, Anstett M-C, Lexer C, et al. (2006) Sympatric speciation in palms on an oceanic island. Nature 441, 210-213.

Schluter D (2001) Ecology and the origin of species. Trends in ecology & evolution (Personal edition) 16, 372-380.

Schmitt J, Gamble S (1990) The effect of distance from the parental site on offspring performance and inbreeding depression in Impatiens capensis: a test of the local adaptation hypothesis Evolution 44, 2022-2030.

Scotti I, Calvo-Vialettes L, Scotti-Saintagne C, et al. (2010) Genetic variation for growth, morphological, and physiological traits in a wild population of the Neotropical shadetolerant rainforest tree Sextonia rubra (Mez) van der Werff (Lauraceae). Tree Genetics & Genomes 6, 319-329.

Siol M, Wright SI, Barrett SCH (2010) The population genomics of plant adaptation. New Phytologist 188, 313-332.

Turner TL, Bourne EC, Von Wettberg EJ, Hu TT, Nuzhdin SV (2010) Population resequencing reveals local adaptation of Arabidopsis lyrata to serpentine soils. Nat Genet 42, 260-263.

Project description

We propose here to address the genetic response of forest tree populations to gradients and habitat contrasts related to soil water content (SWC) and temperature. These gradients are major determinants of tree growth and survival, and the physiological and molecular properties of plant responses to heat, cold, drought and flooding stress are among the most finely characterised processes in plant biology (e.g. see Jung et al. 2009; Parelle et al. 2007; Tournaire-Roux et al. 2003 for recent examples). Therefore, studying evolutionary-genetic patterns related to these stresses in natural populations of non-model organisms will take advantage of the field’s large body of knowledge. The fact that such environmental gradients are relevant in tree populations is proven by several case studies reporting survival and growth response to changes in temperature and SWC (Baraloto et al. 2006; Baraloto et al. 2005; Baraloto et al. 2007; Cohen et al. 2007; Mayle& Power 2008; Meir& Woodward 2010; Phillips et al. 2009).

Our strategy is three-pronged, and is based on two experimental phases, addressing questions in population genomics and quantitative genetics, and a modelling phase, building on the data gathered in the experimental phases to model the processes underlying the maintenance of genetic diversity and to predict future changes.

SNP and indel markers will be identified from ongoing or new high-throughput genome sequence activities, and used to genotype natural populations of each species, growing in sites displaying a gradient or contrast of environmental (drought / flooding / temperature) conditions, for which relevant environmental information is available or will be obtained during the project. Each adult tree will be genotyped and the frequency of alleles at each locus will be tested for correlation with the gradients (or association with the contrasts).

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Between1000 and 2000 loci per species will be screened by next-generation sequencing of short DNA fragments containing the loci, based on the Restriction Associated DNA (RAD) technique (Miller et al. 2007), a novel method to genotype whole genomes directly without the need for prior sequence information, that has recently been applied to the study of population divergence by genome scan (Hohenlohe et al. 2010). FLAG will be one of the earliest applications of RAD to population genetics and will provide an unprecedented wealth of data. This activity will lead to the estimate of the amount of loci under selection along the gradient as well as to the identification of loci and polymorphisms related to stress response / adaptation to the environment. Moreover, cross-species, cross-biome comparisons will allow us to look for conserved patterns of response to stresses in multiple environments. SNP markers found to be correlated to environmental gradients will be used to genotype seedling being grown in reciprocal transplant experiments and replicated common gardens involving the same populations and sites as the adult stands screened as described above. As the reciprocal transplant and common garden populations are recurrently measured for growth, physiological and survival traits, SNP markers\\A?Z E@C@~s83vkk(PwSs4π+ Ģ;novel, and wT8

Relationships among FLAG workpackages

Workpackage 1 (Coordination)

will have the goal of supervising the coherence of the project (harmonisation of data collection and treatment among species), insuring that tasks are completed on time, and organising meetings among partners. It will involve continuous checking of financial and administrative coherence of the project, streamlining regular publication of technical reports and scientific publications, and the organisation of a workshop within an international conference (e.g. IUFRO, ESEB, Plant and Animal Genomnovel, and will possibly lead to the direct identification of characters that contribute to adaptation. This strategy rests on the fact that potentially adaptive traits (“functional” traits sensu Violle et al. (2007)) can be identified based on knowledge gathered on model species. In particular, characters involved in the response to particular environmental stresses (temperature, drought) can be singled out and measured precisely to test the adaptation of populations to these constraints. Therefore, it makes sense to first identify loci under divergent selection in natural populations, and then test whether they contribute to the genetic control of traits putatively involved, or proven to be involved, in the response to environmental divergence. The simultaneous detection of selection at a locus and of its involvement in the control of an adaptive trait, if found, is compelling evidence that the locus acts on adaptive processes through the expression of the trait (but absence of detection of selected loci linked to a given trait cannot be taken as evidence of non adaptive value of the trait; such a test is beyond the scope of this program). This project will contribute novel and original data to the study of the ecological genetics of forests worldwide and to the knowledge of their standing capacity to adapt to environmental variation and to respond to future changes. It specifically includes tropical forests, which have much higher biodiversity than the mostly temperate models in which molecular genetic studies of adaptation to gradients have so far been carried out, and Mediterranean forests, also genetically diverse, which will suffer increased drought stress due to climate change. The newly developed markers and genotyping strategies will be available for the screening of other forests in the context of conservation strategies and assessment of biological diversity. The high dimensionality of the data collected here (several hundreds of individuals x several hundreds of markers per species) will provide a very powerful basis for modelling evolutionary forces , the interactions between selection and gene flow and correlation between loci in their response to environmental pressure. (3) modelling non-equilibrium population-genetic processes and predicting the impact of global change. The data gathered within the FLAG project will be used to calibrate eco-genetic models currently in use or under development by the partnership. Partner 2 in particular is currently developing physio-demo-genetic models that couple (1) a physical and physiological module simulating the tree response to environmental variations, (2) a demographic module converting tree reserves into seed productions and tree mortality and modelling migration and (3) a quantitative genetics model allowing to account for genetic variation among individuals for various functional traits (Davi & Oddou-Muratorio 2010). FLAG will explicitly model the processes leading to the observed patterns of genetic divergence, then use this model to predict the effect of changes in selective regimes. This will allow us to simulate adaptive dynamic trajectories of trees populations in response to realistic climatic scenarios. The results obtained with this activity will make it possible to better understand the building of local adaptation in tree population along climatic gradient, and to gauge the quantitative impact of selection, plasticity, migration and species life history traits on the evolutionary dynamics of tree populations under environmental change.

References

Baraloto C, Bonal D, Goldberg D (2006) Differential seedling growth response to soil resource availability among nine neotropical tree species. Journal of tropical ecology 22, 487-497.

Baraloto C, Goldberg D, Bonal D (2005) Performance trade-offs among tropical tree seedlings in contrasting microhabitats. Ecology 86, 2461-2472.

Baraloto C, Morneau F, Bonal D, Blanc L, Ferry B (2007) Seasonal water stress tolerance and habitat associations within four neotropical tree genera. Ecology 88, 478-489.

Cohen AS, Stone JR, Beuning KRM, et al. (2007) Ecological consequences of early Late Pleistocene megadroughts in tropical Africa. Proceedings of the National Academy of Sciences 104, 16422-16427.

Jung V, Hoffmann L, Muller S (2009) Ecophysiological responses of nine floodplain meadow species to changing hydrological conditions. Plant Ecology 201, 589-598.

Mayle FE, Power MJ (2008) Impact of a drier Early-Mid-Holocene climate upon Amazonian forests. Philosophical Transactions of the Royal Society B: Biological Sciences 363, 1829-1838.

Meir P, Woodward IF (2010) Amazonian rain forests and drought: response and vulnerability. New Phytologist 187, 553-557.

Parelle J, Zapater M, Scotti-Saintagne C, et al. (2007) Quantitative trait loci of tolerance to waterlogging in a European oak (Quercus robur L.): physiological relevance and temporal effect patterns. Plant, Cell and Environment 30, 422-434.

Phillips OL, Aragao LEOC, Lewis SL, et al. (2009) Drought Sensitivity of the Amazon Rainforest. Science 323, 1344-1347.

Tournaire-Roux C, Sutka M, Javot H, et al. (2003) Cytosolic pH regulates root water transport during anoxic stress through gating of aquaporins. Nature 425, 393-396.

Workpackages

The project is composed of six workpackages.

Relationships among FLAG workpackages

Workpackage 1 (Coordination)

will have the goal of supervising the coherence of the project (harmonisation of data collection and treatment among species), insuring that tasks are completed on time, and organising meetings among partners. It will involve continuous checking of financial and administrative coherence of the project, streamlining regular publication of technical reports and scientific publications, and the organisation of a workshop within an international conference (e.g. IUFRO, ESEB, Plant and Animal Genome) on the genomics of adaptation to local gradients. It will as well organise technology transfer to stakeholder and communication of results to the general public.

Workpackage 2 (Genome scan)

will provide the population genomic data on which rests the analysis of levels of selection at the molecular level. Data will be acquired by RAD on replicated cases of populations distributed across environmental gradients and contrasts. Allele frequencies will be characterised for 1000-2000 polymorphisms per species.

Workpackage 3 (seedling trait measurement)

will rest on reciprocal transplants and replicated common gardens to obtain quantitative trait data from seedlings belonging to the same populations as the adult stand, and planted in plots close to, or within the perimeter of, the adults stands. The seedling will be measured repeatedly for the duration of the project.

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Workpackage 4 (Genomics of adaptation)

is the first data analysis step. It will lead to the identification of SNP/indel markers that are statistically associated to environments and are submitted to divergent selection. This will be achieved by applying an array of statistical techniques based on correlation, on population divergence and on estimation of genetic diversity. The loci under selection identified in Task 4 will be used in Task 5.

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Workpackage 5 (Association genetics)

will test the association of loci under selection with characters putatively under selection in contrasting environments and gradients, building on results from Task 3 and from Task 4. The association between traits and SNPs will be investigated by standard association genetics approaches, by taking into account population structure both within and between sites.

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Workpackage 6 (modelling and simulation)

will allow us to estimate selection coefficients at molecular loci and on quantitative characters and to model the interplay between gene flow and selection in shaping patterns of genetic diversity at adaptive and neutral genes. For this task, we will use models or modelling platform already developed in the frame of the EU Evoltree NoE (http://www.evoltree.eu/index.php/modelling-platform) and/or under development in the frame of the EU Biodiversa Linktree project (http://www.igv.fi.cnr.it/linktree/?project/8). Finally, adaptive potential of populations to future environmental changes will be modelled.

Relationships among scientific activities. Numbers indicate the Task in which they will be executed.

Project updates

11 December 2013 Alternative GBS method proposed to the consortium: exome capture. We plan to obtain 10k SNPs per species, 100 individually tagged trees per species.

15 November 2013 Isabelle Lesur hired as bioinformatics specialist for one year to deal with NGS and GBS data.

October 2013. Data collection of full genome sequencing in Eperua falcata.

September 2013 Larch reciprocal transplant established; first trait measurement campaign on Eperua reciprocal transplant.

15 July 2013 Decision of the performance of in-house RADseq protocol. RADseq are deemed unsatisfactory and other options for GBS are considered. See the paper by Arnold et al. for methodological considerations.

July 2013. Data analysis of RADseq data in Eperua falcata from outsourced genotyping.

30 June 2013 (scheduled) Delivery of 6-month project report to the funding agency

3 June 2013: all samples received and accepted by Partner 6 for RADseq tests.

20 May 2013: RADseq tests started on a limited set of samples by Partner 6.

25-26 March 2013: meeting between the Coordinator and Partner 6 to discuss technical details of RADseq genotyping.

20 March 2013 Postdoc at EcoFoG recruited, scheduled start of the contract: 1st July 2013.

5 March 2013 Draft of the Kick-off meeting minutes sent to the partners.

4 March 2013 Shortlist of candidates for the FLAG postdoc at EcoFoG (see “Open Positions” folder.

End of February 2013 - Christophe BOURY joins the project (RADseq for all species, Partner 6).

End of January 2013 (scheduled) delivery of DNA samples to Partner 6 for the preparation of RADseq libraries

15-18 January 2013 Kick-off meeting In Avignon (France), joint with the ERANET-TIPTREE Kick-off meeting.

10 January 2013 Project presentation at the Kick-off meeting of the ANR-BIOADAPT funding program (ANR, Paris)

30 December 2012 : Post-doc position in population genomics open (see “Open positions” folder)

1st November 2012: Project started

Results

Reciprocal transplants in Larix decidua (September 2013)

The larch reciprocal transplants have been set up in the Alps near Briançon. The establishment of the trials has involved the whole AGPF team and was carried out with heavy equipment!

(photo credits: Natacha CLAIRET)

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Reciprocal transplants in Eperua falcata(September 2013)

The reciprocal transplants were established in April-May 2011 with 800 seedlings grown from seeds collected at the sites of Laussat and Régina, French Guiana, in seasonally flooded and dry (hilltop) habitats in both sites. Seeds were collected at equally spaced positions on grids covering the adult stands used to detect selection. The seedlings were distributed to three fenced “gardens” for each site x habitat in a fully balanced experimental plan. In addition to having a mosaic of dry and wet habitats, the sites also have a mosaic of white sand and brown soils.

(photo credits: Bruno FERRY)

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The seedlings have been measured for growth, survival, herbivory, general plant health in September 2013. Site-of-origin, Habitat-of-origin, Site-of-plantation, and Habitat-of-plantation effects were detected, but no interactions. So far there is no evidence of local adaptation. Generally speaking, all seedlings fare better on hilltops than in flood-prone bottomlands, which goes counter the general description of the species as preferring seasonally flooded soils.

Transcriptomics in Larix decidua

Larch cDNA, obtained from cambium and leaves of pools of individuals from different positions in the ecological (elevation) gradient, and from the species range, is now ready for NGS. The data will be used to define the unigenes and to identify polymorphisms to screen in the adult populations.

Population sampling in pines and in Eperua falcata

Sampling and genomic DNA extraction from two ecological transects has been completed for Pinus pinaster (two sites in Spain), Pinus halepensis (two sites in Italy, Mount Gargano, and one site in Spain, Valencia) and Eperua falcata (two sites in French Guiana).

The Eslida (Spain) maritime pine stand

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Images from the Aleppo pine sampling sites

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The Marzini pine stand

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Open positions

Post-doc position open in modelling of intra-populational evolutionary processes (URFM, Avignon)

What are the processes that maintain adaptive genetic diversity within populations in forest tree species?

(Sub-title): Estimating selection processes in situ in small spatial and temporal ecological gradients

See the call for applications below:

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FLAG PostDoc at INRA URFM, Avignon

Post-doc position in population genomics and ecological genetics of tropical forest trees (call now closed)

A post-doc position for 12 months, renewable for 18 further months, is open to work on tropical tree population genomics at Kourou, French Guiana, at the EcoFoG joint research unit.

The hired post-doc will work on a project (FLAG, http://www.ecofog.gf/spip.php?article635) revolving around the detection of disruptive selection across ecological gradients and contrasts in tropical tree populations, in the context of evolutionary/ecological genomics and of the modelling of the response of tree stands to expected global change. He/she will prepare DNA samples for NGS genotyping and analyse the data derived from such genotyping activities (which will be outsourced), mostly focussing on modelling of population genetic processes with a minor involvement in bioinformatic data treatment. He/she will also be involved in the setup of reciprocal transplants and in the measurement of quantitative traits in the field. The hired post-doc will closely interact with a resident team (http://www.ecofog.gf/spip.php?rubrique91) of three scientists, two Ph. D. students and two technicians, plus he/she will work with another post-doc, hired in the same partnership to work on the same kind of data on temperate trees, and with the rest of the partnership (see FLAG website) for the modelling activities. The EcoFoG Ecological Genetics team is a leader in the population and ecological genetics and in the genomics of tropical tree species and offers wide opportunities for networking with other laboratories around the world.

The grant will start on April 1st, 2013. Propensity for team work, data analysis, statistics and modelling, programming skills (particularly with R), as well as the capacity to live in a remote (hot, humid) place and work in a ‘real natural’ forest, are prerequisites for the job. Speaking at least rudimentary French and a will to improve it are a good thing for everyday survival and for interaction with team members. Net salary will be around 1700 € / month plus the benefits of the French welfare system. for further questions please contact Ivan Scotti (FLAG project coordinator and Team leader) at ivan.scotti@ecofog.gf.

Useful References

In this section you will find a mixed bag of references on “local adaptation” (whatever it may mean for you, the reader). The list of references will be recurrently updated with the contribution of project partners.

V. L. Sork, S. N. Aitken, R. J. Dyer, A. J. Eckert, P. Legendre and D. B. Neale (2013) Putting the landscape into the genomics of trees: approaches for understanding local adaptation and population responses to changing climate. Tree Genetics & Genomes 9: 901-911. http://dx.doi.org/10.1007/s11295-013-0596-x

A. Shafer and J. Wolf (2013) Widespread evidence for incipient ecological speciation: a meta-analysis of isolation-by-ecology. Ecology letters

H. Lalagüe (2013) Genetic response of tree population to spatial climatic variation : an experimental genomic and simulation approach in Fagus sylvatica populations along altitudinal gradients. PhD:

T. Günther and G. Coop (2013) Robust identification of local adaptation from allele frequencies. Genetics 195: 205-220.

S. De Mita, A.-C. Thuillet, L. Gay, N. Ahmadi, S. Manel, J. Ronfort and Y. Vigouroux (2013) Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations. Molecular Ecology 22: 1383-1399. http://dx.doi.org/10.1111/mec.12182

D. Audigeos, L. Brousseau, S. Traissac, C. Scotti-Saintagne and I. Scotti (2013) Molecular divergence in tropical tree populations occupying environmental mosaics. Journal of Evolutionary biology 26: 529-544.

F. J. Alberto, S. N. Aitken, R. Alía, S. C. González-Martínez, H. Hänninen, A. Kremer, F. Lefèvre, T. Lenormand, S. Yeaman, R. Whetten and O. Savolainen (2013) Potential for evolutionary responses to climate change – evidence from tree populations. Global Change Biology 19: 1645-1661. http://dx.doi.org/10.1111/gcb.12181

J.-P. Soularue and A. Kremer (2012) Assortative mating and gene flow generate clinal phenological variation in trees. BMC Evolutionary Biology 12: 79. http://www.biomedcentral.com/1471-2148/12/79

S. D. Schoville, A. l. Bonin, O. François, S. p. Lobreaux, C. Melodelima and S. p. Manel (2012) Adaptive genetic variation on the landscape: methods and cases. Annual Review of Ecology, Evolution, and Systematics 43: 23-43. http://www.annualreviews.org/doi/abs/10.1146/annurev-ecolsys-110411-160248

A. Duputié, F. Massol, I. Chuine, M. Kirkpatrick and O. Ronce (2012) How do genetic correlations affect species range shifts in a changing environment? Ecology letters 15: 251-259. http://dx.doi.org/10.1111/j.1461-0248.2011.01734.x

F. Blanquart, S. Gandon and S. L. Nuismer (2012) The effects of migration and drift on local adaptation to a heterogeneous environment. Journal of Evolutionary biology 25: 1351-1363. http://dx.doi.org/10.1111/j.1420-9101.2012.02524.x

B. Rhoné, R. Vitalis, I. Goldringer and I. Bonnin (2010) Evolution of flowering time in experimental wheat populations: a comprehensive approach to detect genetic signatures of natural selection. Evolution 64: 2110-2125. http://dx.doi.org/10.1111/j.1558-5646.2010.00970.x

B. Pujol, A. J. Wilson, R. I. C. Ross and J. R. Pannell (2008) Are QSTFST comparisons for natural populations meaningful? Molecular Ecology 17: 4782-4785. http://dx.doi.org/10.1111/j.1365-294X.2008.03958.x

P. Nosil, S. P. Egan and D. J. Funk (2008) Heterogeneous genomic differentiation between walking-stick ecotypes: “isolation by adaptation” and multiple roles for divergent selection

Evolution 62: 316-336. http://dx.doi.org/10.1111/j.1558-5646.2007.00299.x

D. Garant, S. E. Forde and A. P. Hendry (2007) The multifarious effects of dispersal and gene flow on contemporary adaptation. Functional ecology 21: 434-443.

A. Bonin, P. Taberlet, C. Miaud and F. Pompanon (2006) Explorative genome scan to detect candidate loci for adaptation along a gradient of altitude in the common frog (Rana temporaria). Molecular Biology and Evolution 23: 773-783. http://mbe.oxfordjournals.org/content/23/4/773.abstract

M. Alleaume-Benharira, I. R. Pen and O. Ronce (2006) Geographical patterns of adaptation within a species’ range: interactions between drift and gene flow. Journal of Evolutionary biology 19: 203-215. http://dx.doi.org/10.1111/j.1420-9101.2005.00976.x

E. Porcher, T. Giraud, I. Goldringer and C. Lavigne (2004) Experimental demonstration of a causal relationship between heterogeneity of selection and genetic differentiation in quantitative traits. Evolution 58: 1434-1445. http://dx.doi.org/10.1111/j.0014-3820.2004.tb01725.x

M. J. Hovenden and J. K. Vander Schoor (2004) Nature vs nurture in the leaf morphology of Southern beech, Nothofagus cunninghamii (Nothofagaceae). New Phytologist 161: 585-594. http://dx.doi.org/10.1046/j.1469-8137.2003.00931.x

C. Schlötterer (2002) Towards a molecular characterization of adaptation in local populations. Current Opinion in Genetics & Development 12: 683-687. http://www.sciencedirect.com/science/article/pii/S0959437X02003490

T. Lenormand (2002) Gene flow and the limits to natural selection. Trends in Ecology & Evolution 17: 183-189. http://www.sciencedirect.com/science/article/pii/S0169534702024977

O. Ronce and M. Kirkpatrick (2001) When sources become sinks: migrational meltdown in heterogeneous habitats. Evolution 55: 1520-1531.

F. W. Allendorf and R. F. Leary (1986) Heterozygosity and fitness in natural populations of animals. Conservation Biology: the science of scarcity and diversity.

T. Nagylaki (1978) Clines with asymmetric migration. Genetics 88: 813-827. http://www.genetics.org/content/88/4/813.abstract

M. Caisse and J. Antonovics (1978) Evolution in closely adjacent plant populations. Heredity 40: 371-384. http://dx.doi.org/10.1038/hdy.1978.44

J. Antonovics (1971) The effect of a heterogeneous environment on the genetics of natural populations. The American scientist 59: 593-599.

S. K. Jain and A. D. Bradshaw (1966) Evolutionary divergence among adjacent plant populations I. The evidence and its theoretical analysis. Heredity 21: 407-441. http://dx.doi.org/10.1038/hdy.1966.42

Authorship

The FLAG webpages are maintained by Ivan Scotti (ivan.scotti[at]ecofog.gf)


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