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

Malve Heinz , Simone Prospero

Journal of Forestry Research ›› 2025, Vol. 36 ›› Issue (1) : 24

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Journal of Forestry Research ›› 2025, Vol. 36 ›› Issue (1) : 24 DOI: 10.1007/s11676-024-01805-8
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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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Abstract

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 potential 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 decision 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.

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Malve Heinz, Simone Prospero. A modeling approach to determine substitutive tree species for sweet chestnut in stands affected by ink disease. Journal of Forestry Research, 2025, 36(1): 24 DOI:10.1007/s11676-024-01805-8

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References

[1]

Aiello-Lammens ME, Boria RA, Radosavljevic A, Vilela B, Anderson RP. spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models Ecography, 2015, 38(5): 541-545.

[2]

Alcaide F, Solla A, Cuenca B, Martín . Molecular evidence of introgression of Asian germplasm into a natural Castanea sativa forest in Spain Forestry (Lond), 2022, 95(1): 95-104.

[3]

Amaral AG, Munhoz CBR, Walter BMT, Aguirre-Gutiérrez J, Raes N. Richness pattern and phytogeography of the Cerrado herb-shrub flora and implications for conservation J Veg Sci, 2017, 28(4): 848-858.

[4]

Anagnostakis SL. Chestnut blight: the classical problem of an introduced pathogen Mycologia, 1987, 79(1): 23.

[5]

Bauhus J, Forrester DI, Gardiner B, Jactel H, Vallejo R, Pretzsch H Pretzsch H, Forrester DI, Bauhus J. Ecological stability of mixed-species forests mixed-species forests, 2017 Berlin Heidelberg Springer 337-3824.

[6]

Booth TH. Species distribution modelling tools and databases to assist managing forests under climate change For Ecol Manag, 2018, 430: 196-203.

[7]

Bosso L, Di Febbraro M, Cristinzio G, Zoina A, Russo D. Shedding light on the effects of climate change on the potential distribution of Xylella fastidiosa in the Mediterranean basin Biol Invasions, 2016, 18(6): 1759-1768.

[8]

Böttinger M, Kasang D (2021) Die SSP-Szenarien—Deutsch. Deutsches Klimarechenzentrum. (In German) https://www.dkrz.de/de/kommunikation/klimasimulationen/cmip6-de/die-ssp-szenarien

[9]

Brun P, Thuiller W, Chauvier Y, Pellissier L, Wüest RO, Wang ZH, Zimmermann NE. Model complexity affects species distribution projections under climate change J Biogeogr, 2020, 47(1): 130-142.

[10]

Burke KL. Niche contraction of American chestnut in response to chestnut blight Can J for Res, 2012, 42(3): 614-620.

[11]

Byers AK, Condron L, Donavan T, O’Callaghan M, Patuawa T, Waipara N, Black A. Soil microbial diversity in adjacent forest systems—contrasting native, old growth kauri (Agathis australis) forest with exotic pine (Pinus radiata) plantation forest FEMS Microbiol Ecol, 2020, 96(5): fiaa047.

[12]

Chamberlain S, Barve V, Mcglinn D, Oldoni D, Desmet P, Geffert L, Ram K (2022) rgbif: Interface to the Global Biodiversity Information Facility API. R package version 3.7.9. Retrieved from https://github.com/ropensci/rgbif

[13]

Clark SL, Marcolin E, Patrício MS, Loewe-Muñoz V. A silvicultural synthesis of sweet (Castanea sativa) and American (C. Dentata) chestnuts For Ecol Manag, 2023, 539: 121041.

[14]

Conedera M, Krebs P, Tinner W, Pradella M, Torriani D. The cultivation of Castanea sativa (Mill.) in Europe, from its origin to its diffusion on a continental scale Veg Hist Archaeobot, 2004, 13(3): 161-179.

[15]

Conedera M, Colombaroli D, Tinner W, Krebs P, Whitlock C. Insights about past forest dynamics as a tool for present and future forest management in Switzerland For Ecol Manag, 2017, 388: 100-112.

[16]

Conedera M, Krebs P, Gehring E, Wunder J, Hülsmann L, Abegg M, Maringer J. How future-proof is Sweet chestnut (Castanea sativa) in a global change context? For Ecol Manag, 2021, 494. 119320

[17]

Crandall BS, Gravatt GF, Ryan M. Root disease of Castanea species and some coniferous and broadleaf nursery stocks, caused by Phytophthora cinnamomi Phytopathology, 1945, 35: 162-180

[18]

Desprez-Loustau ML, Robin C, Buée M, Courtecuisse R, Garbaye J, Suffert F, Sache I, Rizzo DM. The fungal dimension of biological invasions Trends Ecol Evol, 2007, 22(9): 472-480.

[19]

Dimitrakopoulos AP, Papaioannou KK. Flammability assessment of Mediterranean forest fuels Fire Technol, 2001, 37(2): 143-152.

[20]

Dyderski MK, Paź S, Frelich LE, Jagodziński AM. How much does climate change threaten European forest tree species distributions? Glob Chang Biol, 2018, 24(3): 1150-1163.

[21]

Ehrenfeld JG. Ecosystem consequences of biological invasions Annu Rev Ecol Evol Syst, 2010, 41: 59-80.

[22]

El-Gabbas A, Dormann CF. Improved species-occurrence predictions in data-poor regions: using large-scale data and bias correction with down-weighted Poisson regression and maxent Ecography, 2018, 41(7): 1161-1172.

[23]

Fantle-Lepczyk JE, Haubrock PJ, Kramer AM, Cuthbert RN, Turbelin AJ, Crystal-Ornelas R, Diagne C, Courchamp F. Economic costs of biological invasions in the United States Sci Total Environ, 2022, 806(Pt 3. 151318

[24]

Fois M, Cuena-Lombraña A, Fenu G, Bacchetta G. Using species distribution models at local scale to guide the search of poorly known species: review, methodological issues and future directions Ecol Model, 2018, 385: 124-132.

[25]

Franić I, Cleary M, Aday Kaya AG, Bragança H, Brodal G, Cech TL, Chandelier A, Doğmuş-Lehtijärvi T, Eschen R, Lehtijärvi A, Ormsby M, Prospero S, Schwanda K, Sikora K, Szmidla H, Talgø V, Tkaczyk M, Vettraino AM, Perez-Sierra A. The biosecurity risks of international forest tree seed movements Curr for Rep, 2024, 10 2): 89-102.

[26]

Gibbs JN. Intercontinental epidemiology of Dutch elm disease Annu Rev Phytopathol, 1978, 16: 287-307.

[27]

Gustafson EJ, Miranda BR, Dreaden TJ, Pinchot CC, Jacobs DF. Beyond blight: Phytophthora root rot under climate change limits populations of reintroduced American chestnut Ecosphere, 2022, 13(2. e3917

[28]

Heller G, Seshan VE, Moskowitz CS, Gönen M. Inference for the difference in the area under the ROC curve derived from nested binary regression models Biostatistics, 2017, 18 2): 260-274.

[29]

Hersbach H, Bell B, Berrisford P, Hirahara S, Horányi A, Muñoz-Sabater J, Nicolas J, Peubey C, Radu R, Schepers D, Simmons A, Soci C, Abdalla S, Abellan X, Balsamo G, Bechtold P, Biavati G, Bidlot J, Bonavita M, Chiara G, Dahlgren P, Dee D, Diamantakis M, Dragani R, Flemming J, Forbes R, Fuentes M, Geer A, Haimberger L, Healy S, Hogan R, Holm E, Janisková M, Keeley S, Laloyaux P, Lopez P, Lupu C, Radnoti G, Rosnay P, Rozum I, Vamborg F, Villaume S, Thepaut J. The ERA5 global reanalysis Q J R Meteor Soc, 2020, 146: 1999-2049.

[30]

Hijmans RJ, Phillips S, Leathwick J, Elith J (2015) Dismo: Species Distribution Modeling. R Package Version 1.0–12. http://CRAN.R-project.org/package=dismo

[31]

Hosni EM, Nasser MG, Al-Ashaal SA, Rady MH, Kenawy MA. Modeling current and future global distribution of Chrysomya bezziana under changing climate Sci Rep, 2020, 10(1): 4947.

[32]

Hulme PE, Pysek P, Nentwig W, Vilà M. Ecology. Will threat of biological invasions unite the European Union? Science, 2009, 324(5923): 40-41.

[33]

Karger DN, Conrad O, Böhner J, Kawohl T, Kreft H, Soria-Auza RW, Zimmermann NE, Linder HP, Kessler M. Climatologies at high resolution for the earth’s land surface areas Sci Data, 2017, 4. 170122

[34]

Kjær ED, Lobo A, Myking T. The role of exotic tree species in Nordic forestry Scand J for Res, 2014, 29(4): 323-332.

[35]

Li YC, Li MY, Li C, Liu ZZ. Optimized maxent model predictions of climate change impacts on the suitable distribution of Cunninghamia lanceolata in China Forests, 2020, 11(3): 302.

[36]

Liebhold AM, Brockerhoff EG, Garrett LJ, Parke JL, Britton KO. Live plant imports: the major pathway for forest insect and pathogen invasions of the US Frontiers Ecol Environ, 2012, 10(3): 135-143.

[37]

Liebhold AM, Brockerhoff EG, Nuñez MA. Biological invasions in forest ecosystems: a global problem requiring international and multidisciplinary integration Biol Invasions, 2017, 19(11): 3073-3077.

[38]

Liu CR, Berry PM, Dawson TP, Pearson RG. Selecting thresholds of occurrence in the prediction of species distributions Ecography, 2005, 28(3): 385-393.

[39]

Loo JA Langor DW, Sweeney J. Ecological impacts of non-indigenous invasive fungi as forest pathogens. Biol Invasions 11: 81–96 Ecological Impacts of Non-Native Invertebrates and Fungi on Terrestrial Ecosystems, 2009 Berlin Springer 157.

[40]

Low BW, Zeng YW, Tan HH, Yeo DCJ. Predictor complexity and feature selection affect maxent model transferability: evidence from global freshwater invasive species Divers Distrib, 2021, 27(3): 497-511.

[41]

Lyam PT, Duque-Lazo J, Durka W, Hauenschild F, Schnitzler J, Michalak I, Ogundipe OT, Muellner-Riehl AN. Genetic diversity and distribution of Senegalia senegal (L.) Britton under climate change scenarios in West Africa PLoS ONE, 2018, 13(4): e0194726.

[42]

Manzoor SA, Griffiths G, Lukac M. Species distribution model transferability and model grain size—finer may not always be better Sci Rep, 2018, 8(1): 7168.

[43]

Marzocchi G, Maresi G, Luchi N, Pecori F, Gionni A, Longa CMO, Pezzi G, Ferretti F. 85 years counteracting an invasion: chestnut ecosystems and landscapes survival against ink disease Biol Invasions, 2024, 26(7): 2049-2062.

[44]

MeteoSwiss (2019) Maps of extreme precipitation. https://www.meteoswiss.admin.ch/home/climate/swiss-climate-in-detail/extreme-value-analyses/maps-of-extreme-precipitation.html

[45]

Noce S, Cipriano C, Santini M. Altitudinal shifting of major forest tree species in Italian mountains under climate change Front for Glob Change, 2023, 6: 1250651.

[46]

O’Neill B, Tebaldi C, Vuuren D, Eyring V, Friedlingstein P, Hurtt G, Knutti R, Kriegler E, Lamarque J, Lowe J, Meehl G, Moss R, Riahi K, Sanderson B. The scenario model intercomparison project (ScenarioMIP) for CMIP6 Geosci Model Dev, 2016, 9: 3461-3482.

[47]

Paillet FL. Chestnut: history and ecology of a transformed species J Biogeogr, 2002, 29(10–11): 1517-1530.

[48]

Peterken GF. Ecological effects of introduced tree species in Britain For Ecol Manag, 2001, 141(1–2): 31-42.

[49]

Peters FS, Wunderlich L, Metzler B. First report of Phytophthora cinnamomi in forest stands in Germany For Pathol, 2019, 49(2. e12485

[50]

Phillips SJ, Anderson RP, Schapire RE. Maximum entropy modeling of species geographic distributions Ecol Model, 2006, 190 3–4): 231-259.

[51]

Poggio L, de Sousa LM, Batjes NH, Heuvelink GBM, Kempen B, Ribeiro E, Rossiter D. SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty Soil, 2021, 7(1): 217-240.

[52]

Prospero S, Heinz M, Augustiny E, Chen YY, Engelbrecht J, Fonti M, Hoste A, Ruffner B, Sigrist R, van den Berg N, Fonti P. Distribution, causal agents, and infection dynamic of emerging ink disease of sweet chestnut in Southern Switzerland Environ Microbiol, 2023, 25(11): 2250-2265.

[53]

R Core Team (2021) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Website https://www.r-project.org

[54]

Robin C, Marchand M Asiegbu FO, Kovalchuk A. Diseases of chestnut trees Forest Microbiology, Volume Two: Forest Tree Health, 2022 All Elsevier Inc. 311-323.

[55]

Simberloff D, Martin JL, Genovesi P, Maris V, Wardle DA, Aronson J, Courchamp F, Galil B, García-Berthou E, Pascal M, Pyšek P, Sousa R, Tabacchi E, Vilà M. Impacts of biological invasions: what’s what and the way forward Trends Ecol Evol, 2013, 28(1): 58-66.

[56]

Thurm EA, Hernandez L, Baltensweiler A, Ayan S, Rasztovits E, Bielak K, Zlatanov TM, Hladnik D, Balic B, Freudenschuss A, Büchsenmeister R, Falk W. Alternative tree species under climate warming in managed European forests For Ecol Manag, 2018, 430: 485-497.

[57]

Tinner W, Hubschmid P, Wehrli M, Ammann B, Conedera M. Long-term forest fire ecology and dynamics in southern Switzerland J Ecol, 1999, 87: 273-289.

[58]

Turchetti T, Maresi G. Management of diseases in chestnut orchards and stands: a significant prospect Adv Hortic Sci, 2006, 20: 33-39

[59]

Vacek Z, Vacek S, Cukor J. European forests under global climate change: review of tree growth processes, crises and management strategies J Environ Manage, 2023, 332. 117353

[60]

Vannini A, Vettraino A, Lellis SCD. Ink disease in chestnuts: impact on the European chestnut For Snow Landsc Res, 2001, 76(3): 345-350

[61]

Vettraino AM, Natili G, Anselmi N, Vannini A. Recovery and pathogenicity of Phytophthora species associated with a resurgence of ink disease in Castanea sativa in Italy Plant Pathol, 2001, 50(1): 90-96.

[62]

Vítková M, Müllerová J, Sádlo J, Pergl J, Pyšek P. Black locust (Robinia pseudoacacia) beloved and despised: a story of an invasive tree in central Europe For Ecol Manage, 2017, 384: 287-302.

[63]

Vitousek PM, D'Antonio CM, Loope LL, Westbrooks R. Biological invasions as global environmental change Am Sci, 1996, 84: 468-478

[64]

Wingfield MJ, Slippers B, Roux J, Wingfield BD. Worldwide movement of exotic forest fungi, especially in the tropics and the southern hemisphere Bioscience, 2001, 51(2): 134.

[65]

Wingfield MJ, Slippers B, Wingfield BD, Barnes I. The unified framework for biological invasions: a forest fungal pathogenperspective Biol Invasions, 2017, 19(11): 3201-3214.

[66]

Wüest RO, Bergamini A, Bollmann K, Brändli UB, Baltensweiler A. Modellierte Verbreitungskarten für die häufigsten Gehölzarten der Schweiz Schweiz Z fur Forstwesen, 2021, 172(4): 226-233. in German)

[67]

Yackulic CB, Chandler R, Zipkin EF, Royle JA, Nichols JD, Campbell Grant EH, Veran S. Presence-only modelling using MAXENT: When can we trust the inferences? Methods Ecol Evol, 2013, 4(3): 236-243.

[68]

Zentmyer GA. The effect of temperature on growth and pathogenesis of Phytophthora cinnamomiand on growth of its avocado host Phytopathology, 1981, 71(9): 925.

[69]

Zhang Y, Tang JS, Ren G, Zhao KX, Wang XF. Global potential distribution prediction of Xanthium italicum based on Maxent model Sci Rep, 2021, 11(1): 16545.

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WSL - Swiss Federal Institute for Forest, Snow and Landscape Research

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