Evolutionary potential of a widespread clonal grass under changing climate

. 2019 Oct ; 32 (10) : 1057-1068. [epub] 20190903

Jazyk angličtina Země Velká Británie, Anglie Médium print-electronic

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid31287927

Adaptive responses are probably the most effective long-term responses of populations to climate change, but they require sufficient evolutionary potential upon which selection can act. This requires high genetic variance for the traits under selection and low antagonizing genetic covariances between the different traits. Evolutionary potential estimates are still scarce for long-lived, clonal plants, although these species are predicted to dominate the landscape with climate change. We studied the evolutionary potential of a perennial grass, Festuca rubra, in western Norway, in two controlled environments corresponding to extreme environments in natural populations: cold-dry and warm-wet, the latter being consistent with the climatic predictions for the country. We estimated genetic variances, covariances, selection gradients and response to selection for a wide range of growth, resource acquisition and physiological traits, and compared their estimates between the environments. We showed that the evolutionary potential of F. rubra is high in both environments, and genetic covariances define one main direction along which selection can act with relatively few constraints to selection. The observed response to selection at present is not sufficient to produce genotypes adapted to the predicted climate change under a simple, space for time substitution model. However, the current populations contain genotypes which are pre-adapted to the new climate, especially for growth and resource acquisition traits. Overall, these results suggest that the present populations of the long-lived clonal plant may have sufficient evolutionary potential to withstand long-term climate changes through adaptive responses.

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Ackerly, D. D., Dudley, S. A., Sultan, S. E., Schmitt, J., Coleman, J. S., Linder, C. R., … Lechowicz, M. J. (2000). The evolution of plant ecophysiological traits: Recent advances and future directions: New research addresses natural selection, genetic constraints, and the adaptive evolution of plant ecophysiological traits. BioScience, 50, 979-995.

Arntz, M. A., & Delph, L. F. (2001). Pattern and process: Evidence for the evolution of photosynthetic traits in natural populations. Oecologia, 127, 455-467. https://doi.org/10.1007/s004420100650

Baumann, U., Juttner, J., Bian, X., & Langridge, P. (2000). Self-incompatibility in the grasses. Annals of Botany, 85, 203-209. https://doi.org/10.1006/anbo.1999.1056

Becklin, K. M., Anderson, J. T., Gerhart, L. M., Wadgymar, S. M., Wessinger, C. A., & Ward, J. K. (2016). Examining plant physiological responses to climate change through an evolutionary lens. Plant Physiology, 172, 635-649.

Blows, M. W., & Hoffmann, A. A. (2005). A reassessment of genetic limits to evolutionary change. Ecology, 86, 1371-1384. https://doi.org/10.1890/04-1209

Butler, D. G., Cullis, B. R., Gilmour, A. R., & Gogel, B. J. (2009). ASReml-R reference manual. Brisbane, QLD: The State of Queensland, Department of Primary Industries and Fisheries.

Castro, S., Münzbergová, Z., Raabová, J., & Loureiro, J. (2010). Breeding barriers at a diploid-hexaploid contact zone in Aster amellus. Evolutionary Ecology, 25, 795-814.

Chambers, J. C. (1991). Patterns of growth and reproduction in a perennial tundra forb (Geum rossii): Effects of clone area and neighborhood. Canadian Journal of Botany, 69, 1977-1983. https://doi.org/10.1139/b91-248

Cheverud, J. M., & Marroig, G. (2007). Comparing covariance matrices: Random skewers method compared to the common principal components model. Genetics and Molecular Biology, 30, 461-469. https://doi.org/10.1590/S1415-47572007000300027

Chirgwin, E., Monro, K., Sgro, C. M., & Marshall, D. J. (2015). Revealing hidden evolutionary capacity to cope with global change. Global Change Biology, 21, 3356-3366. https://doi.org/10.1111/gcb.12929

Cotto, O., Wessely, J., Georges, D., Klonner, G., Schmid, M., Dullinger, S., … Guillaume, F. (2017). A dynamic eco-evolutionary model predicts slow response of alpine plants to climate warming. Nature Communications, 8, 15399. https://doi.org/10.1038/ncomms15399

Cox, P. M. (2001). Description of the TRIFFID dynamic global vegetation model. Hadley Centre Technical Note, 24, 1-16.

de Villemereuil, P. (2012). Estimation of a biological trait heritability using the animal model. How to use the MCMCglmm R package.

Dufresne, F., Stift, M., Vergilino, R., & Mable, B. K. (2014). Recent progress and challenges in population genetics of polyploid organisms: An overview of current state-of-the-art molecular and statistical tools. Molecular Ecology, 23, 40-69. https://doi.org/10.1111/mec.12581

El-Kassaby, Y. A., Cappa, E. P., Liewlaksaneeyanawin, C., Klápště, J., & Lstibŭrek, M. (2011). Breeding without breeding: Is a complete pedigree necessary for efficient breeding? PLoS ONE, 6, e25737. https://doi.org/10.1371/journal.pone.0025737

Ellstrand, N. C., & Roose, M. L. (1987). Patterns of genotypic diversity in clonal plant species. American Journal of Botany, 74, 123-131. https://doi.org/10.1002/j.1537-2197.1987.tb08586.x

Etterson, J. R., & Shaw, R. G. (2001). Constraint to adaptive evolution in response to global warming. Science, 294, 151-154. https://doi.org/10.1126/science.1063656

Fahad, S., Bajwa, A. A., Nazir, U., Anjum, S. A., Farooq, A., Zohaib, A., … Huang, J. (2017). Crop production under drought and heat stress: Plant responses and management options. Frontiers in Plant Science, 8, 1147. https://doi.org/10.3389/fpls.2017.01147

Falconer, D. S., & Mackay, T. F. C. (1996). Introduction to quantitative genetics. London, UK: Longman.

Franco, M., & Silvertown, J. (2004). A comparative demography of plants based upon elasticities of vital rates. Ecology, 85, 531-538. https://doi.org/10.1890/02-0651

Gauzere, J., Klein, E. K., Brendel, O., Davi, H., & Oddou-Muratorio, S. (2016). Using partial genotyping to estimate the genetic and maternal determinants of adaptive traits in a progeny trial of Fagus sylvatica. Tree Genetics & Genomes, 12, 115. https://doi.org/10.1007/s11295-016-1062-3

Gauzere, J., Oddou-Muratorio, S., Pichot, C., Lefèvre, F., & Klein, E. (2013). Biases in quantitative genetic analyses using open-pollinated progeny tests from natural tree populations. Acta Botanica Gallica, 160, 227-238. https://doi.org/10.1080/12538078.2013.822827

Geber, M. A., & Griffen, L. R. (2003). Inheritance and natural selection on functional traits. International Journal of Plant Sciences, 164, S21-S42. https://doi.org/10.1086/368233

Gienapp, P., Teplitsky, C., Alho, J. S., Mills, J. A., & Merilä, J. (2008). Climate change and evolution: Disentangling environmental and genetic responses. Molecular Ecology, 17, 167-178. https://doi.org/10.1111/j.1365-294X.2007.03413.x

Gray, S. B., & Brady, S. M. (2016). Plant developmental responses to climate change. Developmental Biology, 419, 64-77. https://doi.org/10.1016/j.ydbio.2016.07.023

Hadfield, J. D. (2010). MCMC methods for multi-response generalized linear mixed models: The MCMCglmm R package. Journal of Statistical Software, 33, 1-22.

Hadfield, J. D., Wilson, A. J., Garant, D., Sheldon, B. C., & Kruuk, L. E. B. (2010). The misuse of BLUP in ecology and evolution. The American Naturalist, 175, 116-125. https://doi.org/10.1086/648604

Hansen, T. F., Pélabon, C., & Houle, D. (2011). Heritability is not evolvability. Evolutionary Biology, 38, 258. https://doi.org/10.1007/s11692-011-9127-6

Hanssen-Bauer, I., Achberger, C., Benestad, R. E., Chen, D., & Førland, E. J. (2005). Statistical downscaling of climate scenarios over Scandinavia. Climate Research, 29, 255-268. https://doi.org/10.3354/cr029255

Herben, T., Krahulec, F., Hadincová, V., Kovářová, M., & Skálová, H. (1993). Tiller demography of Festuca rubra in a mountain grassland: Seasonal development, life span, and flowering. Preslia, 65, 341-353.

Herben, T., Krahulec, F., Hadincová, V., & Pecháčková, S. (2001). Clone-specific response of Festuca rubra to natural variation in biomass and species composition of neighbours. Oikos, 95, 43-52. https://doi.org/10.1034/j.1600-0706.2001.950105.x

Hoffmann, A. A., & Merilä, J. (1999). Heritable variation and evolution under favourable and unfavourable conditions. Trends in Ecology & Evolution, 14, 96-101. https://doi.org/10.1016/S0169-5347(99)01595-5

Hoffmann, A. A., & Sgrò, C. M. (2011). Climate change and evolutionary adaptation. Nature, 470, 479-485. https://doi.org/10.1038/nature09670

IPCC. (2014). Climate change 2014 - impacts, adaptation and vulnerability: Regional aspects. Cambridge, UK: Cambridge University Press.

Jones, M. B., Finnan, J., & Hodkinson, T. R. (2015). Morphological and physiological traits for higher biomass production in perennial rhizomatous grasses grown on marginal land. GCB Bioenergy, 7, 375-385. https://doi.org/10.1111/gcbb.12203

Kirkpatrick, M. (2009). Patterns of quantitative genetic variation in multiple dimensions. Genetica, 136, 271-284. https://doi.org/10.1007/s10709-008-9302-6

Klápště, J., Suontama, M., Telfer, E., Graham, N., Low, C., Stovold, T., … Dungey, H. (2017). Exploration of genetic architecture through sib-ship reconstruction in advanced breeding population of Eucalyptus nitens. PLoS ONE, 12, e0185137.

Lande, R., & Arnold, S. J. (1983). The measurement of selection on correlated characters. Evolution, 37, 1210-1226. https://doi.org/10.1111/j.1558-5646.1983.tb00236.x

Loiselle, B. A., Sork, V. L., Nason, J., & Graham, C. (1995). Spatial genetic structure of a tropical understory shrub, Psychotria officinalis (Rubiaceae). American Journal of Botany, 82, 1420-1425. https://doi.org/10.1002/j.1537-2197.1995.tb12679.x

Meineri, E., Skarpaas, O., Spindelböck, J., Bargmann, T., & Vandvik, V. (2014). Direct and size-dependent effects of climate on flowering performance in alpine and lowland herbaceous species. Journal of Vegetation Science, 25, 275-286. https://doi.org/10.1111/jvs.12062

Merilä, J., & Hendry, A. P. (2014). Climate change, adaptation, and phenotypic plasticity: The problem and the evidence. Evolutionary Applications, 7, 1-14. https://doi.org/10.1111/eva.12137

Münzbergová, Z., Hadincová, V., Skálová, H., & Vandvik, V. (2017). Genetic differentiation and plasticity interact along temperature and precipitation gradients to determine plant performance under climate change. Journal of Ecology, 1358-1373. https://doi.org/10.1111/1365-2745.12762

Peng, S., Krieg, D. R., & Girma, F. S. (1991). Leaf photosynthetic rate is correlated with biomass and grain production in grain sorghum lines. Photosynthesis Research, 28, 1-7. https://doi.org/10.1007/BF00027171

Price, G. R. (1970). Selection and covariance. Nature, 227, 520-521. https://doi.org/10.1038/227520a0

R Core Team. (2014). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.

Revell, L. J. (2012). phytools: An R package for phylogenetic comparative biology (and other things). Methods in Ecology and Evolution, 3, 217-223. https://doi.org/10.1111/j.2041-210X.2011.00169.x

Robertson, A. (1966). A mathematical model of the culling process in dairy cattle. Animal Science, 8, 95-108. https://doi.org/10.1017/S0003356100037752

Roff, D. A., Prokkola, J. M., Krams, I., & Rantala, M. J. (2012). There is more than one way to skin a G matrix. Journal of Evolutionary Biology, 25, 1113-1126. https://doi.org/10.1111/j.1420-9101.2012.02500.x

Simeão, R., Silva, A., Valle, C., Resende, M. D., & Medeiros, S. (2016). Genetic evaluation and selection index in tetraploid Brachiaria ruziziensis. Plant Breeding, 135, 246-253. https://doi.org/10.1111/pbr.12353

Skálová, H., Pecháčková, S., Suzuki, J., Herben, T., Hara, T., Hadincová, V., & Krahulec, F. (1997). Within population genetic differentiation in traits affecting clonal growth: Festuca rubra in a mountain grassland. Journal of Evolutionary Biology, 10, 383-406.

Sternberg, M., Brown, V. K., Masters, G. J., & Clarke, I. P. (1999). Plant community dynamics in a calcareous grassland under climate change manipulations. Plant Ecology, 143, 29-37. https://doi.org/10.1023/A:1009812024996

Stojanova, B., Šurinová, M., Klápště, J., Koláříková, V., Hadincová, V., & Münzbergová, Z. (2018). Adaptive differentiation of Festuca rubra along a climate gradient revealed by molecular markers and quantitative traits. PLoS ONE, 13, e0194670. https://doi.org/10.1371/journal.pone.0194670

Stuefer, J. F., Van Hulzen, J. B., & During, H. J. (2002). A genotypic trade-off between the number and size of clonal offspring in the stoloniferous herb Potentilla reptans. Journal of Evolutionary Biology, 15, 880-884. https://doi.org/10.1046/j.1420-9101.2002.00435.x

Šurinová, M., Hadincová, V., Vandvik, V., & Münzbergová, Z. (2019). Temperature and precipitation, but not geographic distance, explain genetic relatedness among populations in the perennial grass Festuca rubra. Journal of Plant Ecology, 12, 730-741.

Suzuki, J.-I., Herben, T., & Maki, M. (2005). An under-appreciated difficulty: Sampling of plant populations for analysis using molecular markers. Evolutionary Ecology, 18, 625-646.

Villegas, A. C. (2001). Spatial and temporal variability in clonal reproduction of Aechmea magdalenae, a tropical understory herb. Biotropica, 33, 48-59. https://doi.org/10.1111/j.1744-7429.2001.tb00156.x

Weimarck, A. (1968). Self-incompatibility in the Gramineae. Hereditas, 60, 157-166.

Wilson, A. J., Réale, D., Clements, M. N., Morrissey, M. M., Postma, E., Walling, C. A., … Nussey, D. H. (2010). An ecologist's guide to the animal model. Journal of Animal Ecology, 79, 13-26. https://doi.org/10.1111/j.1365-2656.2009.01639.x

Wood, C. W., & Brodie, E. D. (2015). Environmental effects on the structure of the G-matrix. Evolution, 69, 2927-2940. https://doi.org/10.1111/evo.12795

Xie, X.-F., Song, Y.-B., Zhang, Y.-L., Pan, X., & Dong, M. (2014). Phylogenetic meta-analysis of the functional traits of clonal plants foraging in changing environments. PLoS ONE, 9, e107114. https://doi.org/10.1371/journal.pone.0107114

Zar, J. H. (2013). Biostatistical analysis: Pearson new international edition. New York, NY: Pearson Higher Education.

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