Geographic variation in forest composition and precipitation predict the synchrony of forest insect outbreaks

Oikos ◽  
2017 ◽  
Vol 127 (4) ◽  
pp. 634-642 ◽  
Author(s):  
Kyle J. Haynes ◽  
Andrew M. Liebhold ◽  
Ottar N. Bjørnstad ◽  
Andrew J. Allstadt ◽  
Randall S. Morin
Keyword(s):  
Geographic Variation ◽  
Forest Composition ◽  
Insect Outbreaks ◽  
Forest Insect

Simulation of Forest Insect Outbreaks

1996 ◽  
pp. 414-430
Author(s):  
A. S. Isaev ◽  
V. V. Kiselev ◽  
T. M. Ovchinnikova
Keyword(s):  
Insect Outbreaks ◽  
Forest Insect

scholarly journals Impacts of insect outbreaks on tree mortality, productivity, and stand development

2015 ◽  
Vol 148 (S1) ◽  
pp. S138-S159 ◽  
Author(s):  
David A. MacLean
Keyword(s):  
Mountain Pine Beetle ◽  
Tree Mortality ◽  
Choristoneura Fumiferana ◽  
Population Level ◽  
Historical Record ◽  
Wildlife Habitat ◽  
Insect Population ◽  
Forest Composition ◽  
Stand Development ◽  
Insect Outbreaks

AbstractThe impacts of insect outbreaks on tree mortality, productivity, and stand development in Canada are reviewed, emphasising spruce budworm (Choristoneura fumiferana(Clemens), Lepidoptera: Tortricidae) and mountain pine beetle (Dendroctonus ponderosaeHopkins, Coleoptera: Curculionidae). Reduced growth and survival are a function of insect population and defoliation level. It is feasible to make short-term (annual) predictions of insect population and defoliation based upon sampling, but long-term, multi-year predictions are problematic. Given the historical record, it is expected that outbreaks will occur with relatively predictable frequency and basic host relationships and abiotic constraints will not change dramatically. However, the precision of predictions at fine scales is variable and reduced over time. Relationships between tree growth reduction, survival, and cumulative defoliation or beetle population level are available for major insect species. Understanding insect outbreak effects hinges on mortality, changes in interspecies competition, regeneration, and succession. Altered stand dynamics caused by insects can be interpreted for indicators such as wildlife habitat, old forest, riparian buffer cover, viewscapes, and connectivity. Anthropogenic changes are altering impacts via range expansions, northward shifts, and changes in forest composition. We can better understand effects of insect outbreaks and how best to ameliorate damage through a combination of empirical permanent plot studies, modelling, and manipulative experiments.

Spatial patterns of forest insect outbreaks: a review

2018 ◽  
Vol 38 (10) ◽  
Author(s):  
景天忠 JING Tianzhong ◽  
李田宇 LI Tianyu
Keyword(s):  
Spatial Patterns ◽  
Insect Outbreaks ◽  
Forest Insect

Tree mortality after synchronized forest insect outbreaks: Effects of tree species, bole diameter, and cutting history

2014 ◽  
Vol 319 ◽  
pp. 10-17 ◽  
Author(s):  
Tracey N. Johnson ◽  
Steven W. Buskirk ◽  
Gregory D. Hayward ◽  
Martin G. Raphael
Keyword(s):  
Tree Species ◽  
Tree Mortality ◽  
Insect Outbreaks ◽  
Forest Insect

scholarly journals Mapping Multiple Insect Outbreaks across Large Regions Annually Using Landsat Time Series Data

2020 ◽  
Vol 12 (10) ◽  
pp. 1655 ◽  
Author(s):  
Benjamin C. Bright ◽  
Andrew T. Hudak ◽  
Arjan J.H. Meddens ◽  
Joel M. Egan ◽  
Carl L. Jorgensen
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Tree Mortality ◽  
Landsat Imagery ◽  
Total Mortality ◽  
Google Earth ◽  
Series Data ◽  
Tree Level ◽  
Insect Outbreaks ◽  
Forest Insect

Forest insect outbreaks have caused and will continue to cause extensive tree mortality worldwide, affecting ecosystem services provided by forests. Remote sensing is an effective tool for detecting and mapping tree mortality caused by forest insect outbreaks. In this study, we map insect-caused tree mortality across three coniferous forests in the Western United States for the years 1984 to 2018. First, we mapped mortality at the tree level using field observations and high-resolution multispectral imagery collected in 2010, 2011, and 2018. Using these high-resolution maps of tree mortality as reference images, we then classified moderate-resolution Landsat imagery as disturbed or undisturbed and for disturbed pixels, predicted percent tree mortality with random forest (RF) models. The classification approach and RF models were then applied to time series of Landsat imagery generated with Google Earth Engine (GEE) to create annual maps of percent tree mortality. We separated disturbed from undisturbed forest with overall accuracies of 74% to 80%. Cross-validated RF models explained 61% to 68% of the variation in percent tree mortality within disturbed 30-m pixels. Landsat-derived maps of tree mortality were comparable to vector aerial survey data for a variety of insect agents, in terms of spatial patterns of mortality and annual estimates of total mortality area. However, low-level tree mortality was not always detected. We conclude that our methodology has the potential to generate reasonable estimates of annual tree mortality across large extents.

scholarly journals Coding and Non-coding RNAs: Molecular Basis of Forest-Insect Outbreaks

2020 ◽  
Vol 8 ◽  
Author(s):  
Sufang Zhang ◽  
Sifan Shen ◽  
Zhongwu Yang ◽  
Xiangbo Kong ◽  
Fu Liu ◽  
...  
Keyword(s):  
Molecular Basis ◽  
Insect Outbreaks ◽  
Forest Insect ◽  
Non Coding Rnas

TEMPERATE FOREST INSECT OUTBREAKS, TROPICAL DEFORESTATION AND MIGRATORY BIRDS

1988 ◽  
Vol 120 (S146) ◽  
pp. 21-32 ◽  
Author(s):  
C.S. Holling
Keyword(s):  
Renewable Resources ◽  
Temperate Forest ◽  
Migratory Birds ◽  
Contingency Planning ◽  
Eastern North America ◽  
Anthropogenic Influences ◽  
Insect Outbreaks ◽  
Forest Insect ◽  
Regional Patterns ◽  
Key Features

AbstractEcosystems that are managed for resource production are under continual structural change. Changes imposed by local management aggregate to produce regional patterns and new regionwide responses. Anthropogenic influences on hemispheric and global processes add another level of change. The result is a bewildering variety of real or anticipated changes unique to experience. For example, in the spruce/fir and budworm interaction of eastern North America, a syndrome of causes affects the vulnerability of renewable resources, and the triggers of change can never be predicted. Yet, it is possible to identify key features that affect resilience of ecosystems and robustness of regulation and to reject other possibilities. This approach provides a way to assign priorities for research and for contingency planning to adapt to change.

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