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A modeling approach to determine substitutive tree species for sweet chestnut in stands affected by ink disease

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A modeling approach to determine substitutive tree species for sweet chestnut in stands affected by ink disease
Biological invasions,driven mainly by human activities,pose significant threats to global ecosystems and economies,with fungi and fungal-like oomycetes playing a pivotal role.Ink disease,caused by Phytophthora cinnamomi and P.× cambivora,is a growing concern for sweet chestnut stands(Castanea sativa)in Europe.Since both pathogens are thermophilic organisms,ongoing climate change will likely exacerbate their impact.In this study,we applied species distribution modeling techniques to identify poten-tial substitutive species for sweet chestnut in the light of future climate scenarios SSP126 and SSP370 in southern Switzerland.Using the presence-only machine learning algorithm MaxEnt and leveraging occurrence data from the global dataset GBIF,we delineated the current and projected(2070-2100)distribution of 28 tree species.Several exotic species emerged as valuable alternatives to sweet chestnut,although careful consideration of all potential ecological consequences is required.We also identified several native tree species as promising substitutes,offering ecological benefits and potential adaptability to climatic conditions.Since species diversification fosters forest resilience,we also determined communities of alternative species that can be grown together.Our findings represent a valuable deci-sion tool for forest managers confronted with the challenges posed by ink disease and climate change.Given that,even in absence of disease,sweet chestnut is not a future-proof tree species in the study region,the identified species could offer a pathway toward resilient and sustainable forests within the entire chestnut belt.

Invasive pathogensTree distribution modelingClimate changeForest area

Malve Heinz、Simone Prospero

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Swiss Federal Institute for Forest,Snow and Landscape Research WSL,CH-8903 Birmensdorf,Switzerland

Agroseope,Reckenholastrasse 191,CH-8903 Zurich,Switzerland

Invasive pathogens Tree distribution modeling Climate change Forest area

2025

林业研究(英文版)
东北林业大学,中国生态学学会

林业研究(英文版)

影响因子:0.365
ISSN:1007-662X
年,卷(期):2025.36(3)