General Agricultural and Biological Sciences; Genetics; Ecology, Evolution, Behavior and Systematics
Abstract :
[en] AbstractBiological production systems and conservation programs benefit from and should care for evolutionary processes. Developing evolution‐oriented strategies requires knowledge of the evolutionary consequences of management across timescales. Here, we used an individual‐based demo‐genetic modelling approach to study the interactions and feedback between tree thinning, genetic evolution, and forest stand dynamics. The model combines processes that jointly drive survival and mating success—tree growth, competition and regeneration—with genetic variation of quantitative traits related to these processes. In various management and disturbance scenarios, the evolutionary rates predicted by the coupled demo‐genetic model for a growth‐related trait, vigor, fit within the range of empirical estimates found in the literature for wild plant and animal populations. We used this model to simulate non‐selective silviculture and disturbance scenarios over four generations of trees. We characterized and quantified the effect of thinning frequencies and intensities and length of the management cycle on viability selection driven by competition and fecundity selection. The thinning regimes had a drastic long‐term effect on the evolutionary rate of vigor over generations, potentially reaching 84% reduction, depending on management intensity, cycle length and disturbance regime. The reduction of genetic variance by viability selection within each generation was driven by changes in genotypic frequencies rather than by gene diversity, resulting in low‐long‐term erosion of the variance across generations, despite short‐term fluctuations within generations. The comparison among silviculture and disturbance scenarios was qualitatively robust to assumptions on the genetic architecture of the trait. Thus, the evolutionary consequences of management result from the interference between human interventions and natural evolutionary processes. Non‐selective thinning, as considered here, reduces the intensity of natural selection, while selective thinning (on tree size or other criteria) might reduce or reinforce it depending on the forester's tree choice and thinning intensity.
H2020 - 773383 - B4EST - Adaptive BREEDING for productive, sustainable and resilient FORESTs under climate change
Funders :
EU - European Union [BE]
Funding text :
This work was supported by the French Réseau Mixte et Technologique
AFORCE, the European Union's Horizon 2020 research and innovation
program as part of the B4EST project [grant number 773383], and
the French National Forests Office. We benefited from fruitful discussions
with colleagues from ONF, CNPF, PNR Luberon and SF–CDC to
frame the modeling project. We thank Rachel Spigler for helpful comments on a previous version of the manuscript.
Achim, A., Moreau, G., Coops, N. C., Axelson, J. N., Barrette, J., Bédard, S., Byrne, K. E., Caspersen, J., Dick, A. R., D'Orangeville, L., Drolet, G., Eskelson, B. N. I., Filipescu, C. N., Flamand-Hubert, M., Goodbody, T. R. H., Griess, V. C., Hagerman, S. M., Keys, K., Lafleur, B., … White, J. C. (2022). The changing culture of silviculture. Forestry, 95, 143–152. https://doi.org/10.1093/forestry/cpab047
Alberto, F., Aitken, S., Alia, R., González-Martínez, S., Hanninen, H., Kremer, A., Lefèvre, F., Lenormand, T., Yeaman, S., Whetten, R., & Savolainen, O. (2013). Potential for evolutionary responses to climate change – evidence from tree populations. Global Change Biology, 19, 1645–1661. https://doi.org/10.1111/gcb.12181
Allendorf, F. W., England, P. R., Luikart, G., Ritchie, P. A., & Ryman, N. (2008). Genetic effects of harvest on wild animal populations. Trends in Ecology & Evolution, 23, 327–337. https://doi.org/10.1016/j.tree.2008.02.008
Bell, D. A., Kovach, R. P., Robinson, Z. L., Whiteley, A. R., & Reed, T. E. (2021). The ecological causes and consequences of hard and soft selection. Ecology Letters, 24, 1505–1521. https://doi.org/10.1111/ele.13754
Bone, E., & Farres, A. (2001). Trends and rates of microevolution in plants. Genetica, 112–113, 165–182. https://doi.org/10.1023/A:1013378014069
Bonnet, T., Morrissey, M. B., de Villemereuil, P., Alberts, S. C., Arcese, P., Bailey, L. D., Boutin, S., Brekke, P., Brent, L. J. N., Camenisch, G., Charmantier, A., Clutton-Brock, T. H., Cockburn, A., Coltman, D. W., Courtiol, A., Davidian, E., Evans, S. R., Ewen, J. G., Festa-Bianchet, M., … Kruuk, L. E. B. (2022). Genetic variance in fitness indicates rapid contemporary adaptive evolution in wild animals. Science, 376(6596), 1012–1016. https://doi.org/10.1126/science.abk0853
Bouffet-Halle, A., Mériguet, J., Carmignac, D., Agostini, S., Millot, A., Perret, S., Motard, E., Decenciere, B., & Edeline, E. (2021). Density-dependent natural selection mediates harvest-induced trait changes. Ecology Letters, 24, 648–657. https://doi.org/10.1111/ele.13677
Bulmer, M. G. (1971). The effect of selection on genetic variability. The American Naturalist, 105, 201–211.
CNPF. (2020). Cèdre de l'Atlas en futaie régulière. in: Fiches itinéraires techniques par essence. Centre National de la Propriété Forestière, https://www.cnpf.fr/gestion-durable-des-forets/mise-en-oeuvre/fiches-itineraires-techniques-par-essence
Coltman, D. W., O'Donoghue, P., Jorgenson, J. T., Hogg, J. T., Strobeck, C., & Festa-Bianchet, M. (2003). Undesirable evolutionary consequences of trophy hunting. Nature, 426, 655–658. https://doi.org/10.1038/nature02177
Cornelius, J. (1994). Heritabilities and additive genetic coefficients of variation in forest trees. Canadian Journal of Forest Research, 24, 372–379. https://doi.org/10.1139/x94-050
Coulson, T., Benton, T. G., Lundberg, P., Dall, S. R. X., & Kendall, B. E. (2006). Putting evolutionary biology back in the ecological theatre: A demographic framework mapping genes to communities. Evolutionary Ecology Research, 8, 1155–1171.
Courbet, F. (2002). Modélisation de la croissance et de la qualité du Cèdre: intégration des modèles dans Capsis. In: Rapport Convention MAPA-DERF/INRA n° 61.45.47/01. https://hal.archives-ouvertes.fr/hal-03654591
Cubry, P., Oddou-Muratorio, S., Scotti, I., & Lefèvre, F. (2022). Interactions between micro-environment, selection and genetic architecture drive multiscale adaptation in a simulation experiment. Journal of Evolutionary Biology, 35, 451–466. https://doi.org/10.1111/jeb.13988
Curtis, R. O., & Marshall, D. D. (2000). Technical note: Why quadratic mean diameter? Western Journal of Applied Forestry, 15, 137–139. https://doi.org/10.1093/wjaf/15.3.137
Danjon, F. (1994). Heritabilities and genetic correlations for estimated growth curve parameters in maritime pine. Theoretical and Applied Genetics, 89, 911–921. https://doi.org/10.1007/BF00224517
Deleuze, C., Pain, O., Dhôte, J. F., & Hervé, J. C. (2004). A flexible radial increment model for individual trees in pure even-aged stands. Annals of Forest Science, 61, 327–335. https://doi.org/10.1051/forest:2004026
Dhôte, J.-F. (1991). Modélisation de la croissance des peuplements réguliers de hêtre: dynamique des hiérarchies sociales et facteurs de production. Annales Des Sciences Forestières, 48, 389–416. https://doi.org/10.1051/forest:19910404
Dreyfus, P., Pichot, C., De Coligny, F., Gourlet-Fleury, S., Cornu, G., Jésel, S., Dessard, H., Oddou-Muratorio, S., Gerber, S., Caron, H., Latouche-Hallé, C., Lefèvre, F., Courbet, F., & Seynave, I. (2005). Couplage de modèles de flux de gènes et de modèles de dynamique forestière. Les Actes du BRG, 5, 231–250. https://hal.science/hal-02761978v1
Dufour-Kowalski, S., Courbaud, B., Dreyfus, P., Meredieu, C., & de Coligny, F. (2012). Capsis: An open software framework and community for forest growth modelling. Annals of Forest Science, 69, 221–233. https://doi.org/10.1007/s13595-011-0140-9
Finkeldey, R., & Ziehe, M. (2004). Genetic implications of silvicultural regimes. Forest Ecology and Management, 197, 231–244. https://doi.org/10.1016/j.foreco.2004.05.036
Fririon, V., Davi, H., Oddou-Muratorio, S., Lebourgeois, F., & Lefèvre, F. (2023). Within and between population phenotypic variation in growth vigor and sensitivity to drought stress in five temperate tree species. Forest Ecology and Management, 531, 120754. https://doi.org/10.1016/j.foreco.2022.120754
Gingerich, P. D. (1993). Quantification and comparison of evolutionary rates. In P. Dodson & P. D. Gingerich (Eds.), Functional morphology and evolution (Vol. 293A, pp. 453–478). American Journal of Science.
Gingerich, P. D. (2009). Rates of evolution. Annual Review of Ecology, Evolution, and Systematics, 40, 657–675. https://doi.org/10.1146/annurev.ecolsys.39.110707.173457
Hansen, M. M., Olivieri, I., Waller, D. M., Nielsen, E. E., & the GeM Working Group. (2012). Monitoring adaptive genetic responses to environmental change. Molecular Ecology, 21, 1311–1329. https://doi.org/10.1111/j.1365-294X.2011.05463.x
Hendry, A. P. (2017). Eco-evolutionary dynamics. Princeton University Press.
Hendry, A. P., Farrugia, T., & Kinnison, M. T. (2008). Human influences on rates of phenotypic change in wild animal populations. Molecular Ecology, 17, 20–29. https://doi.org/10.1111/j.1365-294X.2007.03428.x
IPBES. (2016). In S. Ferrier, K. N. Ninan, P. Leadley, R. Alkemade, L. A. Acosta, H. R. Akçakaya, L. Brotons, W. W. L. Cheung, V. Christensen, K. A. Harhash, J. Kabubo-Mariara, C. Lundquist, M. Obersteiner, H. M. Pereira, G. Peterson, R. Pichs-Madruga, N. Ravindranath, C. Rondinini, & B. A. Wintle (Eds.), The methodological assessment report on scenarios and models of biodiversity and ecosystem services (p. 91). Secretariat of the intergovernmental science-policy platform on biodiversity and ecosystem services. 348 pages.
Jansson, G., Hansen, J. K., Haapanen, M., Kvaalen, H., & Steffenrem, A. (2017). The genetic and economic gains from forest tree breeding programmes in Scandinavia and Finland. Scandinavian Journal of Forest Research, 32, 273–286. https://doi.org/10.1080/02827581.2016.1242770
Ladier, J., Rey, F., & Dreyfus, P. (2012). Guide des sylvicultures de montagne – Alpes du Sud françaises. ONF Office National des Forêts, Département des Recherches Techniques.
Laikre, L., Schwartz, M. K., Waples, R. S., Ryman, N., & Ge, M. W. G. (2010). Compromising genetic diversity in the wild: Unmonitored large-scale release of plants and animals. Trends in Ecology & Evolution, 25, 520–529. https://doi.org/10.1016/j.tree.2010.06.013
Lamarins, A., Fririon, V., Folio, D., Vernier, C., Daupagne, L., Labonne, J., Buoro, M., Lefèvre, F., Piou, C., & Oddou-Muratorio, S. (2022). Importance of interindividual interactions in eco-evolutionary dynamics: The rise of demo-genetic agent-based models. Evolutionary Applications, 15, 1988–2001. https://doi.org/10.1111/eva.13508
Landguth, E. L., Holden, Z. A., Mahalovich, M. F., & Cushman, S. A. (2017). Using landscape genetics simulations for planting blister rust resistant whitebark pine in the US northern Rocky Mountains. Frontiers in Genetics, 8, 9. https://doi.org/10.3389/fgene.2017.00009
Le Corre, V., & Kremer, A. (2012). The genetic differentiation at quantitative trait loci under local adaptation. Molecular Ecology, 21, 1548–1566. https://doi.org/10.1111/j.1365-294X.2012.05479.x
Lefèvre, F., Boivin, T., Bontemps, A., Courbet, F., Davi, H., Durand-Gillmann, M., Fady, B., Gauzere, J., Gidoin, C., Karam, M. J., Lalagüe, H., Oddou-Muratorio, S., & Pichot, C. (2014). Considering evolutionary processes in adaptive forestry. Annals of Forest Science, 71, 723–739. https://doi.org/10.1007/s13595-013-0272-1
Mathevet, R., Bousquet, F., & Raymond, C. M. (2018). The concept of stewardship in sustainability science and conservation biology. Biological Conservation, 217, 363–370. https://doi.org/10.1016/j.biocon.2017.10.015
Mathieu-Bégné, E., Loot, G., Chevalier, M., Paz-Vinas, I., & Blanchet, S. (2019). Demographic and genetic collapses in spatially structured populations: Insights from a long-term survey in wild fish metapopulations. Oikos, 128, 196–207. https://doi.org/10.1111/oik.05511
Petit-Cailleux, C., Davi, H., Lefèvre, F., Garrigue, J., Magdalou, J. A., Hurson, C., Magnanou, E., & Oddou-Muratorio, S. (2021). Comparing statistical and mechanistic models to identify the drivers of mortality within a rear-edge beech population. Peer Community Journal, 1, e55. https://doi.org/10.24072/pcjournal.60
Pujol, B., Blanchet, S., Charmantier, A., Danchin, E., Facon, B., Marrot, P., Roux, F., Scotti, I., Teplitsky, C., Thomson, C. E., & Winney, I. (2018). The missing response to selection in the wild. Trends in Ecology & Evolution, 33, 337–346. https://doi.org/10.1016/j.tree.2018.02.007
Roskilly, B., Keeling, E., Hood, S., Giuggiola, A., & Sala, A. (2019). Conflicting functional effects of xylem pit structure relate to the growth-longevity trade-off in a conifer species. Proceedings of the National Academy of Sciences USA, 116, 15282–15287. https://doi.org/10.1073/pnas.1900734116
Schmid, M., Paniw, M., Postuma, M., Ozgul, A., & Guillaume, F. (2022). A trade-off between robustness to environmental fluctuations and speed of evolution. The American Naturalist, 200, E16–E35. https://doi.org/10.1086/719654
Seddon, P. J., Griffiths, C. J., Soorae, P. S., & Armstrong, D. P. (2014). Reversing defaunation: Restoring species in a changing world. Science, 345, 406–412. https://doi.org/10.1126/science.1251818
Seynave, I., & Pichot, C. (2004). Bibliothèque Genetics de Capsis, Documentation Internal report. https://capsis.cirad.fr/capsis/help_en/genetics#documentation
Skrøppa, T. (1994). Impacts of tree improvement on genetic structure and diversity of planted forests. Silva Fennica, 28, 5539. https://doi.org/10.14214/sf.a9179
Thomas, S., Vanlerberghe-Masutti, F., Mistral, P., Loiseau, A., & Boissot, N. (2016). Insight into the durability of plant resistance to aphids from a demo-genetic study of Aphis gossypii in melon crops. Evolutionary Applications, 9, 756–768. https://doi.org/10.1111/eva.12382
Wardlaw, I. F. (1990). The control of carbon partitioning in plants. New Phytologist, 116, 341–381. https://doi.org/10.1111/j.1469-8137.1990.tb00524.x
Whiteley, A. R., Fitzpatrick, S. W., Funk, W. C., & Tallmon, D. A. (2015). Genetic rescue to the rescue. Trends in Ecology & Evolution, 30, 42–49. https://doi.org/10.1016/j.tree.2014.10.009
