一个演示遗传模型显示了造林如何减少树木种群中自然密度依赖的选择

IF 3.5 2区 生物学 Q1 EVOLUTIONARY BIOLOGY
Claire Godineau, Victor Fririon, Nicolas Beudez, François de Coligny, François Courbet, Gauthier Ligot, Sylvie Oddou-Muratorio, Leopoldo Sanchez, François Lefèvre
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引用次数: 0

摘要

生物生产系统和保护计划受益于并且应该关心进化过程。发展以进化为导向的战略需要跨时间尺度管理的进化后果的知识。在这里,我们使用基于个体的演示遗传建模方法来研究树木间伐、遗传进化和林分动态之间的相互作用和反馈。该模型结合了共同驱动生存和交配成功的过程——树的生长、竞争和再生——以及与这些过程相关的数量性状的遗传变异。在不同的管理和干扰情况下,通过耦合演示遗传模型预测的生长相关性状(活力)的进化速率符合文献中对野生动植物种群的经验估计范围。我们使用该模型模拟了4代树木的非选择性造林和干扰情景。我们描述并量化了间伐频率、间伐强度和间伐周期对竞争和繁殖力选择驱动的生存力选择的影响。间伐制度对世代间活力的进化率有显著的长期影响,根据管理强度、周期长度和干扰制度的不同,可能会降低84%。代内生存力选择导致的遗传变异的减少是由基因型频率的变化而不是由基因多样性驱动的,这导致了代间变异的长期侵蚀,尽管代内会有短期波动。造林和干扰情景的比较在质量上对性状遗传结构的假设是可靠的。因此,管理的进化后果源于人类干预与自然进化过程之间的干扰。如本文所述,非选择性间伐减少了自然选择的强度,而选择性间伐(根据树的大小或其他标准)可能会减少或加强自然选择的强度,这取决于林人的树木选择和间伐强度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A demo-genetic model shows how silviculture reduces natural density-dependent selection in tree populations

A demo-genetic model shows how silviculture reduces natural density-dependent selection in tree populations

Biological 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.

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来源期刊
Evolutionary Applications
Evolutionary Applications 生物-进化生物学
CiteScore
8.50
自引率
7.30%
发文量
175
审稿时长
6 months
期刊介绍: Evolutionary Applications is a fully peer reviewed open access journal. It publishes papers that utilize concepts from evolutionary biology to address biological questions of health, social and economic relevance. Papers are expected to employ evolutionary concepts or methods to make contributions to areas such as (but not limited to): medicine, agriculture, forestry, exploitation and management (fisheries and wildlife), aquaculture, conservation biology, environmental sciences (including climate change and invasion biology), microbiology, and toxicology. All taxonomic groups are covered from microbes, fungi, plants and animals. In order to better serve the community, we also now strongly encourage submissions of papers making use of modern molecular and genetic methods (population and functional genomics, transcriptomics, proteomics, epigenetics, quantitative genetics, association and linkage mapping) to address important questions in any of these disciplines and in an applied evolutionary framework. Theoretical, empirical, synthesis or perspective papers are welcome.
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