Bark temperature patterns in ponderosa pine stands and their possible effects on mountain pine beetle behavior

1991 ◽  
Vol 21 (10) ◽  
pp. 1439-1446 ◽  
Author(s):  
J. M. Schmid ◽  
S. A. Mata ◽  
R. A. Schmidt

Bark temperatures on the north and south sides of five ponderosa pines (Pinusponderosa Laws.) in each of four growing stock levels in two areas in the Black Hills of South Dakota were monitored periodically from May through August 1989. Temperatures were significantly different among growing stock levels and between sides of the tree. The magnitude of differences between the mean bark temperatures in partially cut stands and uncut controls was inversely related to stocking level. Maximum differences in mean bark temperatures among the growing stock levels occurred between 10:00 and 14:00, when differences between the lower growing stock levels and the controls reached 9 to 10°F (Fahrenheit temp. = 1.8(Celsius temp.) + 32). Diurnal differences were greatly influenced by the amount of cloud cover. Nocturnal temperatures generally differed by 1 to 2°F. North-side temperatures were cooler and less variable than south-side temperatures. Temperature relationships and mountain pine beetle (Dendroctonusponderosae Hopk.) behavior are discussed.

1991 ◽  
Vol 21 (6) ◽  
pp. 750-755 ◽  
Author(s):  
J. M. Schmid ◽  
S. A. Mata ◽  
R. K. Watkins ◽  
M. R. Kaufmann

Water potential was measured in five ponderosa pine (Pinusponderosa Laws.) in each of four stands of different growing-stock levels at two locations in the Black Hills of South Dakota. Mean water potentials at dawn and midday varied significantly among growing-stock levels at one location, but differences were not consistent. Mean dawn and midday water potentials within growing-stock levels significantly decreased during the summer but showed minor increases during the overall decline. Stress levels were considered high enough to influence physiological functioning and, therefore, influence susceptibility to mountain pine beetle (Dendroctonusponderosae Hopk.) attack. Mountain pine beetle infestations did not develop within the stressed stands, which suggests that resistance may be only one factor in the outbreak scenario.


1992 ◽  
Vol 22 (11) ◽  
pp. 1669-1675 ◽  
Author(s):  
J.M. Schmid ◽  
S.A. Mata ◽  
R.A. Schmidt

Bark temperatures were recorded on five lodgepole pine (Pinuscontorta Dougl. ex Loud.) in stands of different growing stock levels in Colorado and Wyoming. Mean bark temperatures were significantly different among growing stock levels. Temperatures in the partially cut growing stock levels were significantly warmer than in uncut controls during diurnal hours, but temperatures were cooler during nocturnal hours. Bark temperatures correlated with ambient air temperature. Equations were developed for predicting north- and south-side bark temperatures for partially cut stands of three growing stock levels and an uncut control from air temperatures. Bark temperature patterns in lodgepole and ponderosa pine (Pinusponderosa Laws.) stands are compared. The relationship between growing stock level and mountain pine beetle (Dendroctonusponderosae Hopk.) infestation is discussed from the standpoint of bark temperatures.


2018 ◽  
Vol 10 (1) ◽  
pp. 69 ◽  
Author(s):  
Kyle Mullen ◽  
Fei Yuan ◽  
Martin Mitchell

The recent and intense outbreak (first decade of 2000s) of the mountain pine beetle in the Black Hills of South Dakota and Wyoming, which impacted over 33% of the 1.2 million acre (486,000 ha) Black Hills National Forest, illustrates what can occur when forest management practices intersect with natural climatic oscillations and climate change to create the “perfect storm” in a region where the physical environment sets the stage for a plethora of economic activities ranging from extractive industries to tourism. This study evaluates the potential of WorldView-2 satellite imagery for green-attacked tree detection in the ponderosa pine forest of the Black Hills, USA. It also discusses the consequences of long term fire policy and climate change, and the use of remote sensing technology to enhance mitigation. It was found that the near-infrared one (band 7) of WorldView-2 imagery had the highest influence on the green-attack classification. The Random Forest classification produced the best results when transferred to the independent dataset, whereas the Logistic Regression models consistently yielded the highest accuracies when cross-validated with the training data. Lessons learned include: (1) utilizing recent advances in remote sensing technologies, most notably the use of WorldView-2 data, to assist in more effectively implementing mitigation measures during an epidemic, and (2) implementing pre-emptive thinning strategies; both of which can be applied elsewhere in the American West to more effectively blunt or preclude the consequences of a mountain pine beetle outbreak on an existing ponderosa pine forest. 


2017 ◽  
Vol 63 (5) ◽  
pp. 529-536 ◽  
Author(s):  
José F. Negrón ◽  
Kurt K. Allen ◽  
Angie Ambourn ◽  
Blaine Cook ◽  
Kenneth Marchand

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