2018
DOI: 10.1016/j.foreco.2018.08.020
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Accuracy of aerial detection surveys for mapping insect and disease disturbances in the United States

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Cited by 77 publications
(46 citation statements)
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“…Sites were chosen to represent either (1) forest stands that had experienced significant mortality of mature Engelmann spruce from spruce beetle (proportion of overstory basal area mortality ranged from 43 to 89%; n = 13) or (2) forest stands that had little or no evidence of contemporary overstory tree mortality (proportion of overstory basal area mortality ranged from 0 to 28%; n = 15). Initial site selection of spruce beetle-affected locations was achieved using data from federal aerial detection surveys 13 and was standardized to reflect spruce stands with mapped spruce beetle-driven tree mortality 5–10 years prior to the time of the study (i.e., overstory mortality was recorded by surveyors between 2009 and 2013).
Figure 2 Map of the study landscape across six mountain pass regions within Colorado.
…”
Section: Methodsmentioning
confidence: 99%
“…Sites were chosen to represent either (1) forest stands that had experienced significant mortality of mature Engelmann spruce from spruce beetle (proportion of overstory basal area mortality ranged from 43 to 89%; n = 13) or (2) forest stands that had little or no evidence of contemporary overstory tree mortality (proportion of overstory basal area mortality ranged from 0 to 28%; n = 15). Initial site selection of spruce beetle-affected locations was achieved using data from federal aerial detection surveys 13 and was standardized to reflect spruce stands with mapped spruce beetle-driven tree mortality 5–10 years prior to the time of the study (i.e., overstory mortality was recorded by surveyors between 2009 and 2013).
Figure 2 Map of the study landscape across six mountain pass regions within Colorado.
…”
Section: Methodsmentioning
confidence: 99%
“…; and dwarf mistletoe (Arceuthobium campylopodum Engelmann (DMR, Hawksworth, 1977;Furniss and Carolyn, 1992). Except for DMR, the insects and diseases were collated into functional guilds (approach influenced by FIA [1] , Bezemer and Jones, 1998;Coleman et al, 2018). Foliar insects included weevils, phloem feeders, and scales (LF BI); leaf biotic fungi included needle blight and dead needles (LF BF); bole insects included all bark beetles and wood borers (B I).…”
Section: Metrics For Crown and Whole Tree Vigormentioning
confidence: 99%
“…Also, for ease of interpretation, the signs of the parameter estimates reflect that the highest life satisfaction levels were coded as 4 and lowest life satisfaction levels were coded as 1. Drawing upon forest resource data for counties in Colorado [30], Table 3 shows that Grand County suffered a dramatic decrease in the net growth of pine (−75.7 mm ft 3 ) during the study period, followed by net growth losses in Routt County (−21.8 mm ft 3 ) and Summit County (−7.4 mm ft 3 ). The housing stocks in these rural counties are also notably smaller than housing stocks in the more urbanized counties of Boulder and Larimer (Although Larimer County registered a high degree of forest mortality, especially between the years 2009-2011, much of the housing stock in this county is located in areas with no host trees [20].…”
Section: Resultsmentioning
confidence: 99%
“…In most cases, these surveys (commonly referred to as insect and disease surveys or aerial detection surveys) are conducted annually by forest health personnel from fixed-wing aircraft using digital aerial sketch-mapping tools [29]. Although there are known data quality and accuracy limitations for these surveys, they represent the only national-scale geospatial data that associates documented forest health impacts with specific disturbance agents [29,30]. Insect and disease detection survey ("IDS" hereafter) data are compiled on a yearly basis.…”
Section: Methodsmentioning
confidence: 99%