Metadata
The general areas of investigation for the project were fruit rots, cankers and soil
pathogens within orchards and through the supply chain, including an assessment of some
of the physical characteristics that relate to the aggressiveness of disease potential. The
main objective of the project was to connect horticultural and pathological data to a
geographical mapping system via computer programming to determine the uniformity,
stability and potential shifts resulting from natural variability within pathogen populations
initiated by climate change. The elements of the project are outlined below in Figure 1.
Project Rationale: Understanding and predicting disease patterns
From the late 1970’s to the present, there have been significant changes in disease patterns
within local tree fruit populations. For example, in the late 1970’s there was great concern
about the market losses in stone fruits, particularly cherries, because of the fruit rot disease
Brown Rot. However, today Brown Rot is less common and only occurs as frequently as
Botrytis rot and Alternaria rot. Similarly, from the late 1980’s onward, Cytospora Canker
was rampant throughout cherry orchards in the Okanagan Valley, but was rarely seen on
apple. Today the disease is common on apple trees and appears to be much more
aggressive than it was in the 1980’s and 90’s. There also appears to be a shift in species
from mainly C. cincta to C. leucostoma.
These are two examples from many disease pattern-shifts that have occurred within the
industry. These shifts may, in some cases, be related to management and control strategies.
However, it is also plausible that changes in a climate pattern have had some influence on
these shifts and, if this is the case, it raises the question of how the potential for a shift to
occur can be monitored. The main purpose of this research is to develop and test a system
designed to help visualize changes that occur over time and correlate these to weather
patterns and weather pattern changes. When temperature patterns shift, degree-day
accumulation patterns also shift, which is more indicative of changes in climate patterns.
By coordinating climate changes with pathogen characteristics, it is possible to predict
pathogen aggression and adaptation capabilities.
The software ArcGIS is a geographic information system capable of layering data on a map
to show spatial relationships. As the database expands, and if the information in the
database reflect the characteristics of pathogens, then interpretation of the data and
elucidation of patterns can provide meaningful indications of pathogen shifts. For example,
4
there are obvious morphological variation among Botrytis colonies collected from the field,
variations in fungicide efficacy between field isolates, documented shifts in sporulation
patterns, and growth rate differences show a variation in optimal growth temperatures for
isolates. These and other pathogen characteristics are reported in more detail in the
Summary of Key Data section. If and how these characteristics are influenced by climate
change can be key to control strategies. Although dealing directly with pathogens and their
characteristics constitutes the basic emphasis of this project, these pathogens are so
intimately tied to general horticulture and to the structure of the industry that many
“spin-offs” have been included. The main pathogen growth rates, chemical control patterns,
sporulation, germination and visual morphology. These key issues will be discussed in
detail in the Summary of Key Data section. Spin-off effects that are important to
interpretations regarding climate change impact are also discussed
pathogens within orchards and through the supply chain, including an assessment of some
of the physical characteristics that relate to the aggressiveness of disease potential. The
main objective of the project was to connect horticultural and pathological data to a
geographical mapping system via computer programming to determine the uniformity,
stability and potential shifts resulting from natural variability within pathogen populations
initiated by climate change. The elements of the project are outlined below in Figure 1.
Project Rationale: Understanding and predicting disease patterns
From the late 1970’s to the present, there have been significant changes in disease patterns
within local tree fruit populations. For example, in the late 1970’s there was great concern
about the market losses in stone fruits, particularly cherries, because of the fruit rot disease
Brown Rot. However, today Brown Rot is less common and only occurs as frequently as
Botrytis rot and Alternaria rot. Similarly, from the late 1980’s onward, Cytospora Canker
was rampant throughout cherry orchards in the Okanagan Valley, but was rarely seen on
apple. Today the disease is common on apple trees and appears to be much more
aggressive than it was in the 1980’s and 90’s. There also appears to be a shift in species
from mainly C. cincta to C. leucostoma.
These are two examples from many disease pattern-shifts that have occurred within the
industry. These shifts may, in some cases, be related to management and control strategies.
However, it is also plausible that changes in a climate pattern have had some influence on
these shifts and, if this is the case, it raises the question of how the potential for a shift to
occur can be monitored. The main purpose of this research is to develop and test a system
designed to help visualize changes that occur over time and correlate these to weather
patterns and weather pattern changes. When temperature patterns shift, degree-day
accumulation patterns also shift, which is more indicative of changes in climate patterns.
By coordinating climate changes with pathogen characteristics, it is possible to predict
pathogen aggression and adaptation capabilities.
The software ArcGIS is a geographic information system capable of layering data on a map
to show spatial relationships. As the database expands, and if the information in the
database reflect the characteristics of pathogens, then interpretation of the data and
elucidation of patterns can provide meaningful indications of pathogen shifts. For example,
4
there are obvious morphological variation among Botrytis colonies collected from the field,
variations in fungicide efficacy between field isolates, documented shifts in sporulation
patterns, and growth rate differences show a variation in optimal growth temperatures for
isolates. These and other pathogen characteristics are reported in more detail in the
Summary of Key Data section. If and how these characteristics are influenced by climate
change can be key to control strategies. Although dealing directly with pathogens and their
characteristics constitutes the basic emphasis of this project, these pathogens are so
intimately tied to general horticulture and to the structure of the industry that many
“spin-offs” have been included. The main pathogen growth rates, chemical control patterns,
sporulation, germination and visual morphology. These key issues will be discussed in
detail in the Summary of Key Data section. Spin-off effects that are important to
interpretations regarding climate change impact are also discussed
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