Genetic processes to increase genetic diversity of adaptive traits are immigration of genetic material by gene flow from other populations, and mutation. In case of perennial plants, gene flow means input of pollen and seeds, or planting of new genetic material. Considering mutation, the low natural rate of mutation makes that this is in a time frame of a few generations relevant only for very large randomly mating populations. An individual-plant model in which process-based modeling is connected to a quantitative genetic representation of eco-physiological parameters is the ForGEM model Forest Genetics, Ecophysiology, and Management Kramer et al.
In principle each of the model parameters can be characterized by the genetic model and evolve due to environmental change. The genetic system can be initialized, i. As the initial distribution of allele frequencies has a strong effect on the simulated rate of the adaptive response, we assume, based on theoretical considerations, that initially the allele frequency distribution follows a U-shaped beta distribution, phi.
Figure 1 Gillespie, That allele frequency distribution is a function of the heterozygosity of the traits H and the number of alleles k Nei, Multiplication of all combinations of initial allele frequencies leads to initial genotypic frequencies Figure 3 , for brevity in this example a 5-locus, 2 allele system is presented. Figure 1. Equilibrium allele frequency distribution, phi , for different values of heterozygosity H and number of alleles per locus k Nei, Most alleles have either a very low or a very high frequency, whereas few alleles have a frequency around 0.
Figure 2. Allele frequencies to initialize the ForGEM model for different values of heterozygosity H and number of alleles per locus k. The dots indicate the allelic effects for a locus trait evenly spaced over cumulative phi x.https://layfranunamam.ml/1904.php
Adaptation, migration or extirpation: climate change outcomes for tree populations
The same cumulative distribution of phi can be used if a trait is determined by another number of di-allelic loci. Figure 3. Example of initial genotype relative frequency distribution for a 5-locus, 2-allele genetic system see A1 of the Supplementary Material for the allele frequencies used. The allelic effect of a particular allele is the deviate from the population mean of the genotypes that possess that allele.
The deviate is expressed in units standard deviation of the genetic variance.
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Figure 4 shows the decline in allelic effect with increasing number of loci for a di-allelic genetic system with symmetric allelic effects. Genotypic values for a trait i. Phenotypic values are attained by enhancing the genotypic values with an environmental deviate based on the heritability of the trait. For example, the genotypic values of the trait range from 20 E to E in the population in case of a 10 locus, di-allele system, with E representing the allelic effect. Figure 5 presents an example of this approach for the outcome of the distribution of bud burst dates. See Appendix A in Supplementary Material for details on initial allele frequencies and attaining genotypic and phenotypic values, with a numerical example, and Kramer et al.
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Figure 4. Standardized additive allelic effects i. At higher values for the number of loci per trait, all alleles have virtually the same effect on the genotype right of the hashed line. Figure 5. Example of initial frequency distribution of a phenotypic trait: bud burst date based on the Dutch beech population.
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The ForGEM model is an individual-tree model. If no individual-tree measurements of a stand are available, observed stand information from National Forest Inventories NFI can be used to initialize the stand. Typical NFI information are mean height and diameter of the different tree species occurring on a plot, possible including a measure of variability. The statistics of the NFI plot are then used to generate a forest stand with statistically the same characteristics see Figure 6 for an example of a mixed species forest.
This approach can accommodate scenario assumptions on changes in forest management due to policy and market developments. Daily meteorological parameters are required.
Figure 6. Example of a mixed species forest stand to initialize the ForGEM model. Spatial distribution of trees and diameter distribution of a 2 ha observed plot from a national forest inventory with individually measured trees, and a representation of a 1 ha generated plot based on stand statistics of the observed plot density per species, mean and coefficient of variation of height and diameter at breast height.
A Visualization of the stand structure of the observed and generated plots, B distribution of DBH of observed and generated plot. Note that spatial structure is not accounted for in the generated plot. In the model analyses presented below, a pure beech forest was generated with this approach.
Table 1. As example we analyzed the adaptive response of phenological parameters for sites located in different environments. The source population was a Dutch beech population for which the values of a phenological model developed and tested for beech were available Kramer, a , b. All the other model parameters were kept constant. The gain of an earlier bud burst is an increase of productivity as described by the process-based model. Thus, there is a trade-off between: i a too-late bud burst, resulting in not capturing the available resources during the growing season and increased mortality relative to individual trees that do capture these resources; and ii a too early bud burst, resulting in a loss of offspring and increased cost for rebuilding the canopy.
See Appendix C in Supplementary Material for a description of how mortality is determined by the model. Pure beech stands at different locations in Europe Figure 7 , Table 2 were initialized with the same genetic composition distribution of allelic effects over 10 di-allelic loci as the Dutch population. To account for the stochasticity in the model, 5 replicates were simulated. New initial stands were generated for each replica based on the coefficient of variation for height and dbh.
An intensive even-aged forestry system was applied at all locations FMA 4 from Table 1. This system consists of a seed-tree cut at a stand age of 60, where the tree density is decreased to 50 trees per hectare. Trees lower than 5 m are retained. The seed trees are harvested at stand age Figure 7. Location of the sites for which the ForGEM model was run. Green indicates the distribution of beech in Europe Brus et al. This could indicate that the numerical method to estimate the model parameters can be improved by the genetic system applied in the ForGEM model.
It could also be due to the fact that the model parameters were estimated based on observed temperature series, whereas the simulations presented here are based on output of the Hadley Global Circulation Model without additional CO 2 forcing Pope et al. Figure 8.
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The results presented are the mean of 4 replicate runs to account for the genetic and environmental stochasticity one stand died. Figure 9. The results presented are the mean of 5 replicate runs to account for genetic and environmental stochasticity. The response of the bud burst day to average site temperature is a delay in bud burst day at the end of the simulation compared to the response at the start of the simulation Figure The penalty on a loss of foliage and flowers due to late night frost is probably too high. Thanks in advance for your time.
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Covers both responses and adaptation of plants to altered environmental states Illustrates the current impact of climate change on plant productivity, along with mitigation strategies Includes transcriptomic, proteomic, metabolomic and ionomic approaches. Powered by. You are connected as. Connect with:. Use your name:. Thank you for posting a review! We value your input. Concurrent consideration of air pollution effects O3, NOx, N deposition in addition to plant fertilization and greenhouse gas effects of elevated CO2 Authors carefully evaluate, challenge dogma, and propose and support new hypotheses on physiological functions Fills a gap in the field of tree ecophysiology State-of-the-art compendium of current knowledge in physiological ecology of trees see more benefits.
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