Abstract

Subalpine fir (Abies lasiocarpa var. lasiocarpa) is commonly used for nursery stock and Christmas tree applications. Spring frost damage to new buds, however, can jeopardize the longterm investment of growers and reduce the quality of the resulting fir trees. Hence, it is important to evaluate the risk of frost damage when considering prospective growing sites. A prediction model for bud development based on heat units can be used in conjunction with historical climate data to assess the likelihood of frost damage. That is, given the probability of a frost event at a given location and time, and the corresponding probability of bud break at that time, the probability of frost damage can be estimated. Factors affecting estimation, such as multiple environments inherent in the data, as well as temporal variation, must also be considered. These issues will be explored using parametric, non-parametric, and computer intensive estimation techniques. Examples will be demonstrated using data collected from replicated bud break experiments conducted in northern Idaho.

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Apr 27th, 8:30 AM

ALTERNATIVE ESTIMATION TECHNIQUES FOR ASSESSING PROBABILITY OF FROST DAMAGE IN SUBALPINE FIR TREES

Subalpine fir (Abies lasiocarpa var. lasiocarpa) is commonly used for nursery stock and Christmas tree applications. Spring frost damage to new buds, however, can jeopardize the longterm investment of growers and reduce the quality of the resulting fir trees. Hence, it is important to evaluate the risk of frost damage when considering prospective growing sites. A prediction model for bud development based on heat units can be used in conjunction with historical climate data to assess the likelihood of frost damage. That is, given the probability of a frost event at a given location and time, and the corresponding probability of bud break at that time, the probability of frost damage can be estimated. Factors affecting estimation, such as multiple environments inherent in the data, as well as temporal variation, must also be considered. These issues will be explored using parametric, non-parametric, and computer intensive estimation techniques. Examples will be demonstrated using data collected from replicated bud break experiments conducted in northern Idaho.