Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data

Key message The probability of pine sawfly damage was highest in drier sites, while Gremmeniella abietina damage showed an opposite pattern. ICP Forests and rolling National Forest Inventory (NFI) data have good potential for quantifying patterns in damage occurrence, but region-wise NFIs may produc...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Nevalainen, Seppo [verfasserIn] Sirkiä, Seija [verfasserIn] Peltoniemi, Mikko [verfasserIn] Neuvonen, Seppo [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	Forest damage Pine sawflies

Übergeordnetes Werk:	Enthalten in: Annals of forest science - Paris : Springer, 1999, 72(2015), 7 vom: 01. Okt., Seite 909-917
Übergeordnetes Werk:	volume:72 ; year:2015 ; number:7 ; day:01 ; month:10 ; pages:909-917

Links:	Volltext

DOI / URN:	10.1007/s13595-014-0435-8

Katalog-ID:	SPR031898246

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allfields	10.1007/s13595-014-0435-8 doi (DE-627)SPR031898246 (SPR)s13595-014-0435-8-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.00 bkl Nevalainen, Seppo verfasserin aut Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Key message The probability of pine sawfly damage was highest in drier sites, while Gremmeniella abietina damage showed an opposite pattern. ICP Forests and rolling National Forest Inventory (NFI) data have good potential for quantifying patterns in damage occurrence, but region-wise NFIs may produce biased results. Context Factors affecting the occurrence of important biotic damage on Pinus sylvestris were studied with data from large-scale forest monitoring networks. Aims We tested how much the probability of damage caused by pine sawflies (Neodiprion sertifer Geoffr. and Diprion pini L.) and G. abietina (Lagerb. (Morelet)) differed between different forest site types and the effects of relevant climatic factors on damage probabilities. Methods Long-term damage observations from ICP Forests Level 1 monitoring and National Forest Inventory (NFI) data were used. In addition to the traditional frequentist approach, we used a hierarchical Bayesian (HB) framework with the ICP Forests data to model the probabilities of pine sawfly outbreaks starting and continuing. Results The probability of pine sawfly damage was highest in drier sites while the probabilities for G. abietina damage showed an opposite pattern. The HB analysis revealed clear differences between forest site types in the probability of outbreak starting, but the differences in the probabilities of outbreaks continuing were not clear. Conclusion ICP Forests and rolling NFI data have good potential for quantifying patterns in damage occurrence, but annually region-wise NFIs may produce biased results. Forest damage (dpeaa)DE-He213 Pine sawflies (dpeaa)DE-He213 Sirkiä, Seija verfasserin aut Peltoniemi, Mikko verfasserin aut Neuvonen, Seppo verfasserin aut Enthalten in Annals of forest science Paris : Springer, 1999 72(2015), 7 vom: 01. Okt., Seite 909-917 (DE-627)312842457 (DE-600)2012340-1 1297-966X nnns volume:72 year:2015 number:7 day:01 month:10 pages:909-917 https://dx.doi.org/10.1007/s13595-014-0435-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-FOR SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 48.00 ASE AR 72 2015 7 01 10 909-917
spelling	10.1007/s13595-014-0435-8 doi (DE-627)SPR031898246 (SPR)s13595-014-0435-8-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.00 bkl Nevalainen, Seppo verfasserin aut Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Key message The probability of pine sawfly damage was highest in drier sites, while Gremmeniella abietina damage showed an opposite pattern. ICP Forests and rolling National Forest Inventory (NFI) data have good potential for quantifying patterns in damage occurrence, but region-wise NFIs may produce biased results. Context Factors affecting the occurrence of important biotic damage on Pinus sylvestris were studied with data from large-scale forest monitoring networks. Aims We tested how much the probability of damage caused by pine sawflies (Neodiprion sertifer Geoffr. and Diprion pini L.) and G. abietina (Lagerb. (Morelet)) differed between different forest site types and the effects of relevant climatic factors on damage probabilities. Methods Long-term damage observations from ICP Forests Level 1 monitoring and National Forest Inventory (NFI) data were used. In addition to the traditional frequentist approach, we used a hierarchical Bayesian (HB) framework with the ICP Forests data to model the probabilities of pine sawfly outbreaks starting and continuing. Results The probability of pine sawfly damage was highest in drier sites while the probabilities for G. abietina damage showed an opposite pattern. The HB analysis revealed clear differences between forest site types in the probability of outbreak starting, but the differences in the probabilities of outbreaks continuing were not clear. Conclusion ICP Forests and rolling NFI data have good potential for quantifying patterns in damage occurrence, but annually region-wise NFIs may produce biased results. Forest damage (dpeaa)DE-He213 Pine sawflies (dpeaa)DE-He213 Sirkiä, Seija verfasserin aut Peltoniemi, Mikko verfasserin aut Neuvonen, Seppo verfasserin aut Enthalten in Annals of forest science Paris : Springer, 1999 72(2015), 7 vom: 01. Okt., Seite 909-917 (DE-627)312842457 (DE-600)2012340-1 1297-966X nnns volume:72 year:2015 number:7 day:01 month:10 pages:909-917 https://dx.doi.org/10.1007/s13595-014-0435-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-FOR SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 48.00 ASE AR 72 2015 7 01 10 909-917
allfields_unstemmed	10.1007/s13595-014-0435-8 doi (DE-627)SPR031898246 (SPR)s13595-014-0435-8-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.00 bkl Nevalainen, Seppo verfasserin aut Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Key message The probability of pine sawfly damage was highest in drier sites, while Gremmeniella abietina damage showed an opposite pattern. ICP Forests and rolling National Forest Inventory (NFI) data have good potential for quantifying patterns in damage occurrence, but region-wise NFIs may produce biased results. Context Factors affecting the occurrence of important biotic damage on Pinus sylvestris were studied with data from large-scale forest monitoring networks. Aims We tested how much the probability of damage caused by pine sawflies (Neodiprion sertifer Geoffr. and Diprion pini L.) and G. abietina (Lagerb. (Morelet)) differed between different forest site types and the effects of relevant climatic factors on damage probabilities. Methods Long-term damage observations from ICP Forests Level 1 monitoring and National Forest Inventory (NFI) data were used. In addition to the traditional frequentist approach, we used a hierarchical Bayesian (HB) framework with the ICP Forests data to model the probabilities of pine sawfly outbreaks starting and continuing. Results The probability of pine sawfly damage was highest in drier sites while the probabilities for G. abietina damage showed an opposite pattern. The HB analysis revealed clear differences between forest site types in the probability of outbreak starting, but the differences in the probabilities of outbreaks continuing were not clear. Conclusion ICP Forests and rolling NFI data have good potential for quantifying patterns in damage occurrence, but annually region-wise NFIs may produce biased results. Forest damage (dpeaa)DE-He213 Pine sawflies (dpeaa)DE-He213 Sirkiä, Seija verfasserin aut Peltoniemi, Mikko verfasserin aut Neuvonen, Seppo verfasserin aut Enthalten in Annals of forest science Paris : Springer, 1999 72(2015), 7 vom: 01. Okt., Seite 909-917 (DE-627)312842457 (DE-600)2012340-1 1297-966X nnns volume:72 year:2015 number:7 day:01 month:10 pages:909-917 https://dx.doi.org/10.1007/s13595-014-0435-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-FOR SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 48.00 ASE AR 72 2015 7 01 10 909-917
allfieldsGer	10.1007/s13595-014-0435-8 doi (DE-627)SPR031898246 (SPR)s13595-014-0435-8-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.00 bkl Nevalainen, Seppo verfasserin aut Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Key message The probability of pine sawfly damage was highest in drier sites, while Gremmeniella abietina damage showed an opposite pattern. ICP Forests and rolling National Forest Inventory (NFI) data have good potential for quantifying patterns in damage occurrence, but region-wise NFIs may produce biased results. Context Factors affecting the occurrence of important biotic damage on Pinus sylvestris were studied with data from large-scale forest monitoring networks. Aims We tested how much the probability of damage caused by pine sawflies (Neodiprion sertifer Geoffr. and Diprion pini L.) and G. abietina (Lagerb. (Morelet)) differed between different forest site types and the effects of relevant climatic factors on damage probabilities. Methods Long-term damage observations from ICP Forests Level 1 monitoring and National Forest Inventory (NFI) data were used. In addition to the traditional frequentist approach, we used a hierarchical Bayesian (HB) framework with the ICP Forests data to model the probabilities of pine sawfly outbreaks starting and continuing. Results The probability of pine sawfly damage was highest in drier sites while the probabilities for G. abietina damage showed an opposite pattern. The HB analysis revealed clear differences between forest site types in the probability of outbreak starting, but the differences in the probabilities of outbreaks continuing were not clear. Conclusion ICP Forests and rolling NFI data have good potential for quantifying patterns in damage occurrence, but annually region-wise NFIs may produce biased results. Forest damage (dpeaa)DE-He213 Pine sawflies (dpeaa)DE-He213 Sirkiä, Seija verfasserin aut Peltoniemi, Mikko verfasserin aut Neuvonen, Seppo verfasserin aut Enthalten in Annals of forest science Paris : Springer, 1999 72(2015), 7 vom: 01. Okt., Seite 909-917 (DE-627)312842457 (DE-600)2012340-1 1297-966X nnns volume:72 year:2015 number:7 day:01 month:10 pages:909-917 https://dx.doi.org/10.1007/s13595-014-0435-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-FOR SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 48.00 ASE AR 72 2015 7 01 10 909-917
allfieldsSound	10.1007/s13595-014-0435-8 doi (DE-627)SPR031898246 (SPR)s13595-014-0435-8-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.00 bkl Nevalainen, Seppo verfasserin aut Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Key message The probability of pine sawfly damage was highest in drier sites, while Gremmeniella abietina damage showed an opposite pattern. ICP Forests and rolling National Forest Inventory (NFI) data have good potential for quantifying patterns in damage occurrence, but region-wise NFIs may produce biased results. Context Factors affecting the occurrence of important biotic damage on Pinus sylvestris were studied with data from large-scale forest monitoring networks. Aims We tested how much the probability of damage caused by pine sawflies (Neodiprion sertifer Geoffr. and Diprion pini L.) and G. abietina (Lagerb. (Morelet)) differed between different forest site types and the effects of relevant climatic factors on damage probabilities. Methods Long-term damage observations from ICP Forests Level 1 monitoring and National Forest Inventory (NFI) data were used. In addition to the traditional frequentist approach, we used a hierarchical Bayesian (HB) framework with the ICP Forests data to model the probabilities of pine sawfly outbreaks starting and continuing. Results The probability of pine sawfly damage was highest in drier sites while the probabilities for G. abietina damage showed an opposite pattern. The HB analysis revealed clear differences between forest site types in the probability of outbreak starting, but the differences in the probabilities of outbreaks continuing were not clear. Conclusion ICP Forests and rolling NFI data have good potential for quantifying patterns in damage occurrence, but annually region-wise NFIs may produce biased results. Forest damage (dpeaa)DE-He213 Pine sawflies (dpeaa)DE-He213 Sirkiä, Seija verfasserin aut Peltoniemi, Mikko verfasserin aut Neuvonen, Seppo verfasserin aut Enthalten in Annals of forest science Paris : Springer, 1999 72(2015), 7 vom: 01. Okt., Seite 909-917 (DE-627)312842457 (DE-600)2012340-1 1297-966X nnns volume:72 year:2015 number:7 day:01 month:10 pages:909-917 https://dx.doi.org/10.1007/s13595-014-0435-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-FOR SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 48.00 ASE AR 72 2015 7 01 10 909-917
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ICP Forests and rolling National Forest Inventory (NFI) data have good potential for quantifying patterns in damage occurrence, but region-wise NFIs may produce biased results. Context Factors affecting the occurrence of important biotic damage on Pinus sylvestris were studied with data from large-scale forest monitoring networks. Aims We tested how much the probability of damage caused by pine sawflies (Neodiprion sertifer Geoffr. and Diprion pini L.) and G. abietina (Lagerb. (Morelet)) differed between different forest site types and the effects of relevant climatic factors on damage probabilities. Methods Long-term damage observations from ICP Forests Level 1 monitoring and National Forest Inventory (NFI) data were used. In addition to the traditional frequentist approach, we used a hierarchical Bayesian (HB) framework with the ICP Forests data to model the probabilities of pine sawfly outbreaks starting and continuing. Results The probability of pine sawfly damage was highest in drier sites while the probabilities for G. abietina damage showed an opposite pattern. The HB analysis revealed clear differences between forest site types in the probability of outbreak starting, but the differences in the probabilities of outbreaks continuing were not clear. 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author	Nevalainen, Seppo
spellingShingle	Nevalainen, Seppo ddc 630 bkl 48.00 misc Forest damage misc Pine sawflies Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data
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topic_title	630 640 ASE 48.00 bkl Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data Forest damage (dpeaa)DE-He213 Pine sawflies (dpeaa)DE-He213
topic	ddc 630 bkl 48.00 misc Forest damage misc Pine sawflies
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title	Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data
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title_full	Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data
author_sort	Nevalainen, Seppo
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author_browse	Nevalainen, Seppo Sirkiä, Seija Peltoniemi, Mikko Neuvonen, Seppo
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title_sort	vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with scleroderris canker damage; results from finnish icp forests and nfi data
title_auth	Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data
abstract	Key message The probability of pine sawfly damage was highest in drier sites, while Gremmeniella abietina damage showed an opposite pattern. ICP Forests and rolling National Forest Inventory (NFI) data have good potential for quantifying patterns in damage occurrence, but region-wise NFIs may produce biased results. Context Factors affecting the occurrence of important biotic damage on Pinus sylvestris were studied with data from large-scale forest monitoring networks. Aims We tested how much the probability of damage caused by pine sawflies (Neodiprion sertifer Geoffr. and Diprion pini L.) and G. abietina (Lagerb. (Morelet)) differed between different forest site types and the effects of relevant climatic factors on damage probabilities. Methods Long-term damage observations from ICP Forests Level 1 monitoring and National Forest Inventory (NFI) data were used. In addition to the traditional frequentist approach, we used a hierarchical Bayesian (HB) framework with the ICP Forests data to model the probabilities of pine sawfly outbreaks starting and continuing. Results The probability of pine sawfly damage was highest in drier sites while the probabilities for G. abietina damage showed an opposite pattern. The HB analysis revealed clear differences between forest site types in the probability of outbreak starting, but the differences in the probabilities of outbreaks continuing were not clear. Conclusion ICP Forests and rolling NFI data have good potential for quantifying patterns in damage occurrence, but annually region-wise NFIs may produce biased results.
abstractGer	Key message The probability of pine sawfly damage was highest in drier sites, while Gremmeniella abietina damage showed an opposite pattern. ICP Forests and rolling National Forest Inventory (NFI) data have good potential for quantifying patterns in damage occurrence, but region-wise NFIs may produce biased results. Context Factors affecting the occurrence of important biotic damage on Pinus sylvestris were studied with data from large-scale forest monitoring networks. Aims We tested how much the probability of damage caused by pine sawflies (Neodiprion sertifer Geoffr. and Diprion pini L.) and G. abietina (Lagerb. (Morelet)) differed between different forest site types and the effects of relevant climatic factors on damage probabilities. Methods Long-term damage observations from ICP Forests Level 1 monitoring and National Forest Inventory (NFI) data were used. In addition to the traditional frequentist approach, we used a hierarchical Bayesian (HB) framework with the ICP Forests data to model the probabilities of pine sawfly outbreaks starting and continuing. Results The probability of pine sawfly damage was highest in drier sites while the probabilities for G. abietina damage showed an opposite pattern. The HB analysis revealed clear differences between forest site types in the probability of outbreak starting, but the differences in the probabilities of outbreaks continuing were not clear. Conclusion ICP Forests and rolling NFI data have good potential for quantifying patterns in damage occurrence, but annually region-wise NFIs may produce biased results.
abstract_unstemmed	Key message The probability of pine sawfly damage was highest in drier sites, while Gremmeniella abietina damage showed an opposite pattern. ICP Forests and rolling National Forest Inventory (NFI) data have good potential for quantifying patterns in damage occurrence, but region-wise NFIs may produce biased results. Context Factors affecting the occurrence of important biotic damage on Pinus sylvestris were studied with data from large-scale forest monitoring networks. Aims We tested how much the probability of damage caused by pine sawflies (Neodiprion sertifer Geoffr. and Diprion pini L.) and G. abietina (Lagerb. (Morelet)) differed between different forest site types and the effects of relevant climatic factors on damage probabilities. Methods Long-term damage observations from ICP Forests Level 1 monitoring and National Forest Inventory (NFI) data were used. In addition to the traditional frequentist approach, we used a hierarchical Bayesian (HB) framework with the ICP Forests data to model the probabilities of pine sawfly outbreaks starting and continuing. Results The probability of pine sawfly damage was highest in drier sites while the probabilities for G. abietina damage showed an opposite pattern. The HB analysis revealed clear differences between forest site types in the probability of outbreak starting, but the differences in the probabilities of outbreaks continuing were not clear. Conclusion ICP Forests and rolling NFI data have good potential for quantifying patterns in damage occurrence, but annually region-wise NFIs may produce biased results.
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title_short	Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data
url	https://dx.doi.org/10.1007/s13595-014-0435-8
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up_date	2024-07-04T01:44:18.355Z
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Results The probability of pine sawfly damage was highest in drier sites while the probabilities for G. abietina damage showed an opposite pattern. The HB analysis revealed clear differences between forest site types in the probability of outbreak starting, but the differences in the probabilities of outbreaks continuing were not clear. 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Vulnerability to pine sawfly damage decreases with site fertility but the opposite is true with Scleroderris canker damage; results from Finnish ICP Forests and NFI data

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