Home Forest Ecosystems Article
PDF (4.4 MB)
Cite
EndNote(RIS) BibTeX
Collect
Research Article | Open Access

Assessing the effect of invasive organisms on forests under information uncertainty: The case of pine wood nematode in continental Europe

Nick Schafstalla, Laura Dobora, Marco Baldoa, Andrew M. Liebholda,b, Werner Rammerc, Juha Honkaniemid, Tomáš Hlásnya()
Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague, Czech Republic
US Forest Service Northern Forest Research Station, Morgantown, USA
Ecosystem Dynamics and Forest Management Group, Technical University of Munich, Germany
Natural Resources Institute Finland, Helsinki, Finland
Show Author Information

Abstract

Forests worldwide are experiencing increasingly intense biotic disturbances; however, assessing impacts of these disturbances is challenging due to the diverse range of organisms involved and the complex interactions among them. This particularly applies to invasive species, which can greatly alter ecological processes in their invaded territories. Here we focus on the pine wood nematode (PWN, Bursaphelenchus xylophilus), an invasive pathogen that has caused extensive mortality of pines in East Asia and more recently has invaded southern Europe. It is expected to expand its range into continental Europe with heavy impacts possible.

Given the unknown dynamics of PWN in continental Europe, we reviewed laboratory and field experiments conducted in Asia and southern Europe to parameterize the main components of PWN biology and host-pathogen interactions in the Biotic Disturbance Engine (BITE), a model designed to implement a variety of forest biotic agents, from fungi to large herbivores. To simulate dynamically changing host availability and conditions, BITE was coupled with the forest landscape model iLand. The potential impacts of introducing PWN were assessed in a Central European forest landscape (40,928 ​ha), likely within PWN’s reach in future decades.

A parameter sensitivity analysis indicated a substantial influence of factors related to dispersal, colonization, and vegetation impact, whereas parameters related to population growth manifested a minor effect. Selection of different assumptions about biological processes resulted in differential timing and size of the main mortality wave, eliminating 40%–95% of pine trees within 100 years post-introduction, with a maximum annual carbon loss between 1.3% and 4.2%. PWN-induced tree mortality reduced the Gross Primary Productivity, increased heterotrophic respiration, and generated a distinct legacy sink effect in the recovery period. This assessment has corroborated the ecological plausibility of the simulated dynamics and highlighted the need for new strategies to navigate the substantial uncertainty in the agent’s biology and population dynamics.

Keywords

Biological invasionsProcess-based modellingForest ecosystemsModel parameters

References

 

Akbulut, S., Stamps, W.T., 2011. Insect vectors of the pinewood nematode: a review of the biology and ecology of Monochamus species. For. Pathol. 42 (2), 89–99. https://doi.org/10.1111/j.1439-0329.2011.00733.x.

Crossref Google Scholar
 

Augustynczik, A.L.D., Dobor, L., Hlásny, T., 2021. Controlling landscape-scale bark beetle dynamics: can we hit the right spot? Landsc. Urban Plan. 209, 104035. https://doi.org/10.1016/j.landurbplan.2020.104035.

Crossref Google Scholar
 

Bebber, D.P., 2015. Range-expanding pests and pathogens in a warming world. Annu. Rev. Phytopathol. 53, 335–356. https://doi.org/10.1146/annurev-phyto-080614-120207.

Crossref Google Scholar
 

Blanco, J.A., Lo, Y.-H., 2023. Latest trends in modelling forest ecosystems: new approaches or just new methods? Curr. For. Rep. 9, 219–229. https://doi.org/10.1007/s40725-023-00189-y.

Crossref Google Scholar
 

Boyd, I.L., Freer-Smith, P.H., Gilligan, C.A., Godfray, H.C., 2013. The consequence of tree pests and diseases for ecosystem services. Science 342, 1235773. https://doi.org/10.1126/science.1235773.

Crossref Google Scholar
 

Calvão, T., Duarte, C.M., Pimentel, C.S., 2019. Climate and landscape patterns of pine forest decline after invasion by the pinewood nematode. For. Ecol. Manag. 433, 43–51. https://doi.org/10.1016/j.foreco.2018.10.039.

Crossref Google Scholar
 
Černý, M., Pařez, J., 1996. Růstové a Taxační Tabulky Hlavních Dřevin České Republiky: (Smrk, Borovice, Buk, Dub). IFER, Jílové U Prahy.
 

Chapin, F.S., Woodwell, G.M., Randerson, J.T., Rastetter, E.B., Lovett, G.M., Baldocchi, D.D., Clark, D.A., Harmon, M.E., Schimel, D.S., Valentini, R., Wirth, C., Aber, J.D., Cole, J.J., Goulden, M.L., Harden, J.W., Heimann, M., Howarth, R.W., Matson, P.A., McGuire, A.D., Melillo, J.M., Mooney, H.A., Neff, J.C., Houghton, R.A., Pace, M.L., Ryan, M.G., Running, S.W., Sala, O.E., Schlesinger, W.H., Schulze, E.-D., 2006. Reconciling carbon-cycle concepts, terminology, and methods. Ecosystems 9, 1041–1050. https://doi.org/10.1007/s10021-005-0105-7.

Crossref Google Scholar
 
Commission of the European Communities, 2009/420/EC (amending Decision 2006/133/EC).
 
Commission of the European Communities, 2015/226 (amending Implementing Decision 2012/535/EU).
 

Cuddington, K., Fortin, M.-J., Gerber, L.R., Hastings, A., Liebhold, A., O'Connor, M., Ray, C., 2013. Process-based models are required to manage ecological systems in a changing world. Ecosphere 4 (2), 1–12. https://doi.org/10.1890/ES12-00178.1.

Crossref Google Scholar
 

Cumming, G.S., Peterson, G.D., 2017. Unifying research on social–ecological resilience and collapse. Trends Ecol. Evol. 32 (9), 695–713. https://doi.org/10.1016/j.tree.2017.06.014.

Crossref Google Scholar
 

De la Fuente, B., Saura, S., Beck, P.S.A., 2018. Predicting the spread of an invasive tree pest: the pine wood nematode in Southern Europe. J. Appl. Ecol. 55 (5), 2374–2385. https://doi.org/10.1111/1365-2664.13177.

Crossref Google Scholar
 

Dobor, L., Hlásny, T., Rammer, W., Barka, I., Trombik, J., Pavlenda, P., Šebeň, V., Štěpánek, P., Seidl, R., 2018. Post-disturbance recovery of forest carbon in a temperate forest landscape under climate change. Agric. For. Meteorol. 263, 308–322. https://doi.org/10.1016/j.agrformet.2018.08.028.

Crossref Google Scholar
 

Dobor, L., Hlásny, T., Rammer, W., Zimová, S., Barka, I., Seidl, R., 2019. Is salvage logging effectively dampening bark beetle outbreaks and preserving forest carbon stocks? J. Appl. Ecol. 57 (1), 67–76. https://doi.org/10.1111/1365-2664.13518.

Crossref Google Scholar
 

Dobor, L., Hlásny, T., Rammer, W., Zimová, S., Barka, I., Seidl, R., 2020. Spatial configuration matters when removing windfelled trees to manage bark beetle disturbances in Central European forest landscapes. J. Environ. Manag. 254, 109792. https://doi.org/10.1016/j.jenvman.2019.109792.

Crossref Google Scholar
 

Dobor, L., Baldo, M., Bílek, L., Barka, I., Máliš, F., Štěpánek, P., Hlásny, T., 2024. The interacting effect of climate change and herbivory can trigger large-scale transformations of European temperate forests. Global Change Biol. 30 (2), e17194. https://doi.org/10.1111/gcb.17194.

Crossref Google Scholar
 

Evans, H.F., McNamara, D.G., Braasch, H., Chadoeuf, J., Magnusson, C., 1996. Pest risk analysis (PRA) for the territories of the European Union (as PRA area) on Bursaphelenchus xylophilus and its vectors in the genus Monochamus. Bull. OEPP 26, 199–249. https://doi.org/10.1111/j.1365-2338.1996.tb00594.x.

Crossref Google Scholar
 

Extebeste, I., Sanchez-Husillos, E., Álvarez, G., Mas i Gisbert, H., Pajares, J., 2015. Dispersal of Monochamus galloprovincialis (Col.: cerambycidae) as recorded by mark–release–recapture using pheromone traps. J. Appl. Entomol. 140, 485–499. https://doi.org/10.1111/jen.12278.

Crossref Google Scholar
 

Fei, S., Morin, R.S., Oswalt, C.M., Liebhold, A.M., 2019. Biomass losses resulting from insect and disease invasions in US forests. Proc. Natl. Acad. Sci. U.S.A. 116 (35), 17371–17376. https://doi.org/10.1073/pnas.1820601116.

Crossref Google Scholar
 

Fernández-Martínez, M., Vicca, S., Janssens, I.A., Sardans, J., Luyssaert, S., Campioli, M., Chapin III, F.S., Ciais, P., Malhi, Y., Obersteiner, M., Papale, D., Piao, S.L., Reichstein, M., Rodà, F., Peñuelas, J., 2014. Nutrient availability as the key regulator of global forest carbon balance. Nat. Clim. Change 4, 471–476. https://doi.org/10.1038/nclimate2177.

Crossref Google Scholar
 

Firminho, P.N., Calvão, T., Ayres, M.P., Pimentel, C.S., 2017. Monochamus galloprovincialis and Bursaphelenchus xylophilus life history in an area severely affected by pine wilt disease: implications for forest management. For. Ecol. Manag. 389, 105–115. https://doi.org/10.1016/j.foreco.2016.12.027.

Crossref Google Scholar
 

Forzieri, G., Girardello, M., Ceccherini, G., Spinoni, J., Feyen, L., Hartmann, H., Beck, P.S.A., Camps-Valls, G., Chirici, G., Mauri, A., Cescatti, A., 2021. Emergent vulnerability to climate-driven disturbances in European forests. Nat. Commun. 12, 1081. https://doi.org/10.1038/s41467-021-21399-7.

Crossref Google Scholar
 

Francardi, V., Pennacchio, F., 1996. Note sulla bioecologia di Monochamus galloprovincialis (Olivier) in Toscana e in Liguria (Coleoptera: Cerambycidae). Redia 79 (2), 153–169.

Google Scholar
 
Futai, K., 2008. In: Zhao, B.G., Futai, K., Sutherland, J.R., Takeuchi, Y. (Eds.), Pine Wilt in Japan: from First Incidence to the Present. Pine Wilt Disease, Springer, Tokyo. https://doi.org/10.1007/978-4-431-75655-2_2.
Crossref
 

Goulden, M.L., McMillan, A.M.S., Winston, G.C., Rocha, A.V., Manies, K.L., Harden, J.W., Bond-Lamberty, B.P., 2010. Patterns of NPP, GPP, respiration, and NEP during boreal forest succession. Global Change Biol. 17, 855–871. https://doi.org/10.1111/j.1365-2486.2010.02274.x.

Crossref Google Scholar
 

Gruffud, H.R., Schröder, T., Jenkins, T.A.R., Evans, H.F., 2018. Modelling pine wilt disease (PWD) for current and future climate scenarios as part of a pest risk analysis for pine wood nematode Bursaphelenchus xylophilus (Steiner and Buhrer) Nickle in Germany. J. Plant Dis. Prot. 126, 129–144. https://doi.org/10.1007/s41348-018-0197-x.

Crossref Google Scholar
 

Gustafson, E.J., 2013. When relationships estimated in the past cannot be used to predict the future: using mechanistic models to predict landscape ecological dynamics in a changing world. Landscape Ecol. 28 (8), 1429–1437. https://doi.org/10.1007/s10980-013-9927-4.

Crossref Google Scholar
 

Hirata, A., Nakamura, K., Nakao, K., Kominami, Y., Tanaka, N., Ohashi, H., Takano, K.T., Takeuchi, W., Matsui, T., 2017. Potential distribution of pine wilt disease under future climate change scenarios. PLoS One 12 (8), 0182837. https://doi.org/10.1371/journal.pone.0182837.

Crossref Google Scholar
 

Hlasný, T., König, L., Krokene, P., Lindner, M., Montagné-Huck, C., Müller, J., Qin, H., Raffa, K.F., Schelhaas, M.-J., Svoboda, M., Viiri, H., Seidl, R., 2021. Bark beetle outbreaks in Europe: state of knowledge and ways forward for management. Curr. For. Rep. 7, 138–165. https://doi.org/10.1007/s40725-021-00142-x.

Crossref Google Scholar
 

Honkaniemi, J., Rammer, W., Seidl, R., 2021. From mycelia to mastodons – a general approach for simulating biotic disturbances in forest ecosystems. Environ. Model. Softw. 138, 104977. https://doi.org/10.1016/j.envsoft.2021.104977.

Crossref Google Scholar
 
Houston Durrant, T., de Rigo, D., Caudullo, G., 2016. In: San-Miguel-Ayanz, J., de Rigo, D., Caudullo, G., Houston Durrant, T., Mauri, A. (Eds.), Pinus Sylvestris in Europe: Distribution, Habitat, Usage and Threats, European Atlas of Forest Tree Species. Publ. Off. EU, Luxembourg, p. e016b94.
 
Hungerford, R.D., Nemani, R.R., Running, S.W., Coughlan, J.C., 1989. MTCLIM: a mountain microclimate simulation model. Res. Pap. INT-RP-414. Ogden, UT, U.S. Department of Agriculture, Forest Service, Intermountain Research Station, p. 52 https://doi.org/10.2737/INT-RP-414.
Crossref
 
Keane, R.E., Loehman, R.A., Holsinger, L.M., 2011. The FireBGCv2 Landscape Fire and Succession Model: a Research Simulation Platform for Exploring Fire and Vegetation Dynamics. General Technical Report RMRS-GTR-255. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, p. 137.
Crossref
 

Kobayashi, F., Yamane, A., Ikeda, T., 1984. The Japanese pine sawyer beetle as the vector of pine wilt disease. Annu. Rev. Entomol. 29 (1), 115–135. https://doi.org/10.1146/annurev.en.29.010184.000555.

Crossref Google Scholar
 

Koch, D.C., Lewis, M.A., Lele, S.R., 2020. A unifying theory for two-dimensional spatial redistribution kernels with applications in population spread modelling. J. R. Soc. Interface 17 (170). https://doi.org/10.1098/rsif.2020.0434.

Crossref Google Scholar
 

Landsberg, J.J., Waring, R.H., 1997. A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. For. Ecol. Manag. 95 (3), 209–228. https://doi.org/10.1016/S0378-1127(97)00026-1.

Crossref Google Scholar
 

Lehmann, P., Ammunét, T., Barton, M., Battisti, A., Eigenbrode, S.D., Jepsen, J.U., Kalinkat, G., Neuvonen, S., Niemelä, P., Terblanche, J.S., Økland, B., 2020. Complex responses of global insect pests to climate warming. Front. Ecol. Environ. 18 (3), 141–150. https://doi.org/10.1002/fee.2160.

Crossref Google Scholar
 

Liebhold, A.M., Brockerhoff, E.G., Kalisz, S., Nuñez, M.A., Wardle, D.A., Wingfield, M.J., 2017. Biological invasions in forest ecosystems. Biol. Invasions 19, 3437–3458. https://doi.org/10.1007/s10530-017-1458-5.

Crossref Google Scholar
 

Lindroth, A., Lagergren, F., Grelle, A., Klemedtsson, L., Langvall, O., Weslien, P., Tuulik, J., 2009. Storms can cause Europe-wide reduction in forest carbon sink. Global Change Biol. 15, 346–355. https://doi.org/10.1111/j.1365-2486.2008.01719.x.

Crossref Google Scholar
 

Linit, M.J., 1990. Transmission of pinewood nematode through feeding wounds of Monochamus carolinensis (Coleoptera: cerambycidae). J. Nematol. 22 (2), 231–236. PMID: 19287715.

Google Scholar
 

Lovett, G.M., Canham, C.D., Arthur, M.A., Weathers, K.C., Fitzhugh, R.D., 2006. Forest ecosystem responses to exotic pests and pathogens in eastern North America. Bioscience 56 (5), 395–405. https://doi.org/10.1641/0006-3568(2006)056[0395:FERTEP]2.0.CO;2.

Crossref Google Scholar
 

Mamiya, Y., 1988. History of pine wilt disease in Japan. J. Nematol. 20 (2), 219–226.

Google Scholar
 

Mina, M., Messier, C., Duveneck, M.J., Fortin, M.-J., Aquilué, N., 2022. Managing for the unexpected: building resilient forest landscapes to cope with global change. Global Change Biol. 28 (14), 4323–4341. https://doi.org/10.1111/gcb.16197.

Crossref Google Scholar
 

Naves, P.M., Camacho, S., De Sousa, E.M., Quartau, J.A., 2007. Transmission of the pine wood nematode Bursaphelenchus xylophilus through feeding activity of Monochamus galloprovincialis (Col., Cerambycidae). J. Appl. Entomol. 131 (1), 21–25. https://doi.org/10.1111/j.1439-0418.2006.01111.x.

Crossref Google Scholar
 

Naves, P.M., De Sousa, E.M., Quartau, J.A., 2006a. Feeding and oviposition preferences of Monochamus galloprovincialis for certain conifers under laboratory conditions. Entomol. Exp. Appl. 120 (2), 99–104. https://doi.org/10.1111/j.1570-7458.2006.00430.x.

Crossref Google Scholar
 

Naves, P.M., De Sousa, E.M., Rodrigues, J.M., 2006b. Biology of Monochamus galloprovincialis (Coleoptera, Cerambycidae) in the pine wilt disease affected zone, southern Portugal. Silva Lusit. 16 (2), 133–148.

Google Scholar
 

Naves, P.M., Bonifacio, L., Inacio, M.L., De Sousa, E.M., 2018. Integrated management of pine wilt disease in Troia. Rev. Ciencias Agrar. 41, 11–20. https://doi.org/10.19084/RCA.17060.

Crossref Google Scholar
 

Patacca, M., Lindner, M., Lucas-Borja, M.E., Cordonnier, T., Fidej, G., Gardiner, B., Hauf, Y., Jasinevičius, G., Labonne, S., Linkevičius, E., Mahnken, M., Milanovic, S., Nabuurs, G.-J., Nagel, T.A., Nikinmaa, L., Panyatov, M., Bercak, R., Seidl, R., Sever, M.Z.O., Socha, J., Thom, D., Vuletic, D., Zudin, S., Schelhaas, M.-J., 2022. Significant increase in natural disturbance impacts on European forests since 1950. Global Change Biol. 29 (5), 1359–1376. https://doi.org/10.1111/gcb.16531.

Crossref Google Scholar
 

Peltzer, D.A., Allen, R.B., Lovett, G.M., Whitehead, D., Wardle, D.A., 2010. Effects of biological invasions on forest carbon sequestration. Global Change Biol. 16 (2), 732–746. https://doi.org/10.1111/j.1365-2486.2009.02038.x.

Crossref Google Scholar
 

Powell, A., Bentz, B.J., 2014. Phenology and density-dependent dispersal predict patterns of mountain pine beetle (Dendroctonus ponderosae) impact. Ecol. Model. 273, 73–185. https://doi.org/10.1016/j.ecolmodel.2013.10.034.

Crossref Google Scholar
 

Pukkala, T., Möykkynen, T., Robinet, C., 2014. Comparison of the potential spread of pinewood nematode (Bursaphelenchus xylophilus) in Finland and Iberia simulated with a cellular automaton model. For. Pathol. 44, 341–352. https://doi.org/10.1111/efp.12105.

Crossref Google Scholar
 

Rammer, W., Seidl, R., 2015. Coupling human and natural systems: simulating adaptive management agents in dynamically changing forest landscapes. Global Environ. Change 35, 475–485. https://doi.org/10.1016/j.gloenvcha.2015.10.003.

Crossref Google Scholar
 

Ramsfield, T.D., Bentz, B.J., Faccoli, M., Jactel, H., Brockerhoff, E.G., 2016. Forest health in a changing world: effects of globalization and climate change on forest insect and pathogen impacts. Forestry 89 (3), 245–252. https://doi.org/10.1093/forestry/cpw018.

Crossref Google Scholar
 

Robinet, C., van Opstal, N., Baker, R., Roques, A., 2011. Applying a spread model to identify the entry points from which the pine wood nematode, the vector of pine wilt disease, would spread most rapidly across Europe. Biol. Invasions 13, 2981–2995. https://doi:10.1007/s10530-011-9983-0.

Crossref Google Scholar
 

Robinet, C., David, G., Jactel, H., 2019. Modeling the distances traveled by flying insects based on the combination of flight mill and mark-release-recapture experiments. Ecol. Model. 402, 85–92. https://doi.org/10.1016/j.ecolmodel.2019.04.006.

Crossref Google Scholar
 
Rodrigues, J.M., 2008. National Eradication Programme for the Pinewood Nematode. In: Mota, M.M., Vieira, P. (Eds.), Pine Wilt Disease: A Worldwide Threat to Forest Ecosystems. Springer, Dordrecht, pp. 5–14.
Crossref
 

Rutherford, T.A., Webster, J.M., 1987. Distribution of pine wilt disease with respect to temperature in North America, Japan and Europe. Can. J. For. Res. 17, 1050–1059. https://doi.org/10.1139/x87-161.

Crossref Google Scholar
 

Schelhaas, M.J., Kramer, K., Peltola, H., van der Werf, D.C., Wijdeven, S.M.J., 2007. Introducing tree interactions in wind damage simulation. Ecol. Model. 207, 197–209. https://doi.org/10.1016/j.ecolmodel.2007.04.025.

Crossref Google Scholar
 

Schumacher, S., Bugmann, H., Mladenoff, D.J., 2004. Improving the formulation of tree growth and succession in a spatially explicit landscape model. Ecol. Model. 180 (1), 175–194. https://doi.org/10.1016/j.ecolmodel.2003.12.055.

Crossref Google Scholar
 

Seidl, R., Rammer, W., 2017. Climate change amplifies the interactions between wind and bark beetle disturbances in forest landscapes. Landscape Ecol. 32, 1485–1498. https://doi.org/10.1007/s10980-016-0396-4.

Crossref Google Scholar
 

Seidl, R., Fernandes, P.M., Fonseca, T.F., Gillet, F., Jönsson, A.M., Merganičová, K., Netherer, S., Arpaci, A., Bontemps, J.-D., Bugmann, H., González-Olabarria, J.R., Lasch, P., Meredieu, C., Moreira, F., Schelhaas, M.-J., Mohren, F., 2011. Modelling natural disturbances in forest ecosystems: a review. Ecol. Model. 222, 903–924. https://doi.org/10.1016/j.ecolmodel.2010.09.040.

Crossref Google Scholar
 

Seidl, R., Rammer, W., Scheller, R.M., Spies, T.A., 2012. An individual-based process model to simulate landscape-scale forest ecosystem dynamics. Ecol. Model. 231, 87–100. https://doi.org/10.1016/j.ecolmodel.2012.02.015.

Crossref Google Scholar
 

Seidl, R., Rammer, W., Blennow, K., 2014. Simulating wind disturbance impacts on forest landscapes: tree-level heterogeneity matters. Environ. Model. Softw. 51, 1–11. https://doi.org/10.1016/j.envsoft.2013.09.018.

Crossref Google Scholar
 

Seidl, R., Thom, D., Kautz, M., Martin-Benito, D., Peltoniemi, M., Vacchiano, G., Wild, J., Ascoli, D., Petr, M., Honkaniemi, J., Lexer, M.J., Trotsiuk, V., Mairota, P., Svoboda, M., Fabrika, M., Nagel, T.A., Reyer, C.P.O., 2017. Forest disturbances under climate change. Nat. Clim. Change 7, 395–402. https://doi.org/10.1038/nclimate3303.

Crossref Google Scholar
 

Seidl, R., Klonner, G., Rammer, W., Essl, F., Moreno, A., Neumann, M., Dullinger, S., 2018. Invasive alien pests threaten the carbon stored in Europe's forests. Nat. Commun. 9, 1626. https://doi.org/10.1038/s41467-018-04096-w.

Crossref Google Scholar
 
Sláma, M.E.F., 1998. Tesaříkovití – Cerambycidae České Republiky a Slovenské Republiky/Cerambycidae of the Czech Republic and Slovak Republic. Milan Sláma private printing, Krhanice, pp. 278–279.
 

Sturtevant, B.R., Gustafson, E.J., Li, W., He, H.S., 2004. Modeling biological disturbances in LANDIS: a module description and demonstration using spruce budworm. Ecol. Model. 180, 153–174. https://doi.org/10.1016/j.ecolmodel.2004.01.021.

Crossref Google Scholar
 

Takasu, F., 2009. Individual-based modeling of the spread of pine wilt disease: vector beetle dispersal and the Allee effect. Popul. Ecol. 51, 399–409. https://doi.org/10.1007/s10144-009-0145-5.

Crossref Google Scholar
 

Takasu, F., Yamamoto, N., Kawasaki, K., Togashi, K., Kishi, Y., Shigesada, N., 2000. Modeling the expansion of an introduced tree disease. Biol. Invasions 2, 141–150. https://doi.org/10.1023/A:1010048725497.

Crossref Google Scholar
 

Togashi, K., 1985. Transmission curves of Bursaphelenchus xylophilus from its vector, Monochamus alternatus, to pine trees with reference to population performance. Appl. Entomol. Zool. 20, 246–251. https://doi.org/10.1303/aez.20.246.

Crossref Google Scholar
 

Togashi, K., Shigesada, N., 2009. Spread of the pinewood nematode vectored by the Japanese pine sawyer: modeling and analytical approaches. Popul. Ecol. 48 (4), 271–283. https://doi.org/10.1007/s10144-006-0011-7.

Crossref Google Scholar
 

Tomminen, J., 1993. Development of Monochamus galloprovincialis Olivier (Coleoptera, Cerambycidae) in cut trees of young pines (Pinus sylvestris L.) and log bolts in southern Finland. Entomol. Fennica 4 (3), 137–142. https://doi.org/10.33338/ef.83759.

Crossref Google Scholar
 

Turner, M.G., Seidl, R., 2023. Novel disturbance regimes and ecological responses. Annu. Rev. Ecol. Evol. Syst. 54, 63–83. https://doi.org/10.1146/annurev-ecolsys-110421-101120.

Crossref Google Scholar
 

Yoshimura, A., Kawasaki, K., Takasu, F., Togashi, K., Futai, K., Shigesada, N., 1999. Modeling the spread of pine wilt disease caused by nematodes with pine sawyers as vector. Ecology 80, 1691–1702. https://doi.org/10.2307/176557.

Crossref Google Scholar
 

Yue, C., Ciais, P., Zhu, D., Wang, T., Peng, S.S., Piao, S.L., 2016. How have past fire disturbances contributed to the current carbon balance of boreal ecosystems? Biogeosciences 13, 675–690. https://doi.org/10.5194/bg-13-675-2016.

Crossref Google Scholar
 
Zhao, B., 2008. Pine Wilt Disease in China. In: Zhao, B.G., Futai, K., Sutherland, J.R., Takeuchi, Y. (Eds.), Pine Wilt Disease. Springer, Tokyo, pp. 18–25.
Crossref
Forest Ecosystems
Volume 11 Issue 5,
October 2024
Article number: 100226
DOI: 10.1016/j.fecs.2024.100226
Cite this article:
Schafstall N, Dobor L, Baldo M, et al. Assessing the effect of invasive organisms on forests under information uncertainty: The case of pine wood nematode in continental Europe. Forest Ecosystems, 2024, 11(5): 100226. https://doi.org/10.1016/j.fecs.2024.100226
Metrics & Citations  
Article History
Copyright
Rights and Permissions
Return