Evidence map›Paper›PMID 39655064›Full record

ArticleEvolutionary applications2024

Can Thinning Foster Forest Genetic Adaptation to Drought? A Demo-Genetic Modelling Approach With Disturbance Regimes.

Victor Fririon, Hendrik Davi, Sylvie Oddou-Muratorio, Gauthier Ligot, François Lefèvre

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Article in Evolutionary applications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Victor FririonINRAE, UR 629 Ecologie des Forêts Méditerranéennes (URFM), Domaine Saint Paul-Site Agroparc Avignon France.ORCID https://orcid.org/0000-0002-0945-7897
Hendrik DaviINRAE, UR 629 Ecologie des Forêts Méditerranéennes (URFM), Domaine Saint Paul-Site Agroparc Avignon France.
Sylvie Oddou-MuratorioINRAE, UR 629 Ecologie des Forêts Méditerranéennes (URFM), Domaine Saint Paul-Site Agroparc Avignon France.ORCID https://orcid.org/0000-0003-2374-8313
Gauthier LigotUniversity of Liège, Gembloux Agro-Bio Tech, TERRA, ForestIsLife Gembloux Belgium.
François LefèvreINRAE, UR 629 Ecologie des Forêts Méditerranéennes (URFM), Domaine Saint Paul-Site Agroparc Avignon France.ORCID https://orcid.org/0000-0003-2242-7251

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In managed populations-whether for production or conservation-management practices can interfere with natural eco-evolutionary processes, providing opportunities to mitigate immediate impacts of disturbances or enhance selection on tolerance traits. Here, we used a modelling approach to explore the interplay and feedback loops among drought regimes, natural selection and tree thinning in naturally regenerated monospecific forests. We conducted a simulation experiment spanning three nonoverlapping generations with the individual-based demo-genetic model Luberon2. Luberon2 integrates forest dynamics processes driving survival and mating success, including tree growth, competition, drought impacts and regeneration, with genetic variation in quantitative traits related to these processes. We focused on two variable traits: individual vigour, determining diameter growth potential without stress as the deviation from average stand growth, and individual sensitivity to drought stress as the slope of the relationship between diameter growth and drought stress level. We simulated simplified thinning scenarios, tailored to even-aged stands. Considering plausible genetic variation and contrasting drought regimes, the predicted evolutionary rates for both traits aligned with documented rates in wild plant and animal populations. Thinning considerably reduced natural selective pressures caused by competition and drought compared to unthinned stands. However, the conventional thinning practice of retaining the larger trees resulted in indirect anthropogenic selection that enhanced genetic gain in vigour and lowered sensitivity by up to 30%. More intensive thinning aimed at reducing drought stress by reducing stand density hampered the selection against sensitivity to drought, potentially hindering long-term adaptation. Conversely, avoiding the early, nonselective thinning step-thereby promoting both natural and anthropogenic selection-ultimately resulted in better stand performance while maintaining long-term evolvability. This study emphasises the potential of evolution-oriented forestry strategies to combine drought stress mitigation with genetic adaptation. It provides general insights into how population management, disturbance regimes and eco-evolutionary responses interfere, aiding sustainable decision-making amid environmental uncertainties.

Indexed as

demo‐genetic modellingdisturbance regimesdroughteco‐evolutionary dynamicsevolution‐oriented forestrygenetic adaptation

Identifiers

PMID39655064
PMCPMC11627118

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.