Insect Pests in Future Forests: More Severe Problems?

Björkman, Christer; Bylund, Helena; Klapwijk, Maartje J.; Kollberg, Ida; Schroeder, Martin

doi:10.3390/f2020474

Cited by 26 publications

(25 citation statements)

References 53 publications

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“…The original ALS data was thinned with simple random sampling procedure at 10% intervals and calculations of the ALS metrics and estimations of defoliation were made of the thinned data. Pulse densities of 20,18,16,14,12,10,8,6,4, and 2 pulses/m 2 were simulated and tested. The thinning, calculation of ALS metrics and classifications were repeated 10 times to provide more stability in the results.…”

Section: Simulation Of Pulse Densitiesmentioning

confidence: 99%

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Classification of Needle Loss of Individual Scots Pine Trees by Means of Airborne Laser Scanning

Kantola

Vastaranta

Lyytikäinen‐Saarenmaa

et al. 2013

Forests

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Forest disturbances caused by pest insects are threatening ecosystem stability, sustainable forest management and economic return in boreal forests. Climate change and increased extreme weather patterns can magnify the intensity of forest disturbances, particularly at higher latitudes. Due to rapid responses to elevating temperatures, forest insect pests can flexibly change their survival, dispersal and geographic distributions. The outbreak pattern of forest pests in Finland has evidently changed during the last decade. Projection of shifts in distributions of insect-caused forest damages has become a critical issue in the field of forest research. The Common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini has resulted in severe growth loss and mortality of Scots pine (Pinus sylvestris L.) (Pinaceae) in eastern Finland. In this study, tree-wise defoliation was estimated for five different needle loss category classification schemes and for 10 different simulated airborne laser scanning (ALS) pulse densities. The nearest neighbor (NN) approach, a nonparametric estimation method, was used for estimating needle loss of 701 Scots pines, using the means of individual tree features derived from ALS data. The Random Forest (RF) method was applied in NN-search. For the full dense data (~20 pulses/m 2 ), the overall estimation accuracies for tree-wise defoliation level varied

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Section: Simulation Of Pulse Densitiesmentioning

confidence: 99%

“…During global warming, increases in stress factors and patterns of insect outbreaks have been predicted [8][9][10][11][12]. Due to rapid responses to elevating temperatures, pest insects can flexibly change their survival, development, reproduction, dispersal and geographic distribution [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Classification of Needle Loss of Individual Scots Pine Trees by Means of Airborne Laser Scanning

Kantola

Vastaranta

Lyytikäinen‐Saarenmaa

et al. 2013

Forests

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“…According to the projections of climatic change impacts, distribution of forest pest insects, as well as insect-induced damage will gradually shift towards northern latitudes. This climate-driven phenomenon has already been evident with pine sawflies [2,3], moths [4,5] and bark beetles [6,7]. Rapidly increasing forest disturbances give rise to a threat for forest health and substantial economic losses [8].…”

Section: Introductionmentioning

confidence: 99%

Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level

Näsi

Honkavaara

Lyytikäinen‐Saarenmaa

et al. 2015

Remote Sensing

322

265

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Low-cost, miniaturized hyperspectral imaging technology is becoming available for small unmanned aerial vehicle (UAV) platforms. This technology can be efficient in carrying out small-area inspections of anomalous reflectance characteristics of trees at a very high level of detail. Increased frequency and intensity of insect induced forest disturbance has established a new demand for effective methods suitable in mapping and monitoring tasks. In this investigation, a novel miniaturized hyperspectral frame imaging sensor operating in the wavelength range of 500-900 nm was used to identify mature Norway spruce (Picea abies L. Karst.) trees suffering from infestation, representing a different outbreak phase, by the European spruce bark beetle (Ips typographus L.). We developed a new processing method for analyzing spectral characteristic for high spatial resolution photogrammetric and hyperspectral images in forested environments, as well as for identifying individual anomalous trees. The dense point clouds, measured using image matching, enabled detection of single trees with an accuracy of 74.7%. We classified the trees into classes of healthy, infested and dead, and the results were promising. The best OPEN ACCESSRemote Sens. 2015, 7 15468 results for the overall accuracy were 76% (Cohen's kappa 0.60), when using three color classes (healthy, infested, dead). For two color classes (healthy, dead), the best overall accuracy was 90% (kappa 0.80). The survey methodology based on high-resolution hyperspectral imaging will be of a high practical value for forest health management, indicating a status of bark beetle outbreak in time.

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“…(Hymenoptera: Diprionidae) can reach up to $40·ha -1 , and by the common pine sawfly (Diprion pini L.) (Hymenoptera: Diprionidae) up to $310·ha -1 (Lyytikäinen-Saarenmaa and Tomppo 2002). As a consequence of climate change, insect outbreaks are predicted to become more frequent (Björkman et al 2011;Netherer and Schopf 2012). Insect populations may experience increased survival, development, reproduction, and dispersal rates due to increasing temperatures (Logan et al 2003;Lindner et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Development of a method for monitoring of insect induced forest defoliation – limitation of MODIS data in Fennoscandian forest landscapes

Olsson¹,

Kantola²,

Lyytikäinen‐Saarenmaa³

et al. 2016

Silva Fenn.

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Highlights• We developed and tested a method to monitor insect induced defoliation in forests based on coarse-resolution satellite data (MODIS).• MODIS data may fail to detect defoliation in fragmented landscapes, especially if defoliation history is long. More homogenous forests results in higher detection accuracies.• The method may be applied to future coarse and medium-resolution satellite data with high temporal resolution. AbstractWe investigated if coarse-resolution satellite data from the MODIS sensor can be used for regional monitoring of insect disturbances in Fennoscandia. A damage detection method based on z-scores of seasonal maximums of the 2-band Enhanced Vegetation Index (EVI2) was developed. Time-series smoothing was applied and Receiver Operating Characteristics graphs were used for optimisation. The method was developed in fragmented and heavily managed forests in eastern Finland dominated by Scots pine (Pinus sylvestris L.) (pinaceae) and with defoliation of European pine sawfly (Neodiprion sertifer Geoffr.) (Hymenoptera: Diprionidae) and common pine sawfly (Diprion pini L.) (Hymenoptera: Diprionidae). The method was also applied to subalpine mountain birch (Betula pubescens ssp. Czerepanovii N.I. Orlova) forests in northern Sweden, infested by autumnal moth (Epirrita autumnata Borkhausen) and winter moth (Operophtera brumata L.). In Finland, detection accuracies were fairly low with 50% of the damaged stands detected, and a misclassification of healthy stands of 22%. In areas with long outbreak histories the method resulted in extensive misclassification. In northern Sweden accuracies were higher, with 75% of the damage detected and a misclassification of healthy samples of 19%. Our results indicate that MODIS data may fail to detect damage in fragmented forests, particularly when the damage history is long. Therefore, regional studies based on these data may underestimate defoliation. However, the method yielded accurate results in homogeneous forest ecosystems and when long-enough periods without damage could be identified. Furthermore, the method is likely to be useful for insect disturbance detection using future medium-resolution data, e.g. from Sentinel-2.

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Insect Pests in Future Forests: More Severe Problems?

Cited by 26 publications

References 53 publications

Classification of Needle Loss of Individual Scots Pine Trees by Means of Airborne Laser Scanning

Classification of Needle Loss of Individual Scots Pine Trees by Means of Airborne Laser Scanning

Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level

Development of a method for monitoring of insect induced forest defoliation – limitation of MODIS data in Fennoscandian forest landscapes

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