Technical Decisions:


1st Decision:

Deciding which areas to look at for the crops:

The Choice: The Kamloops Forest Region.

Why?  The Kamloops Forest Region has a handbook of the Ministry of Forest website which is broken down into subzones and zones and

the climatic information for this is extensive.  In addition, the Kamloops Forest Region contains the most relevant areas in British Columbia in terms

of wine-grape and apple growing.

2nd Decision:

Choosing the climatic variables.

The Choices: Average annual precipitation, frost-free period (ffp), growing degree days (GDD), january mean minimum temperature, and july mean maximum temperature.

Why?  These are climatic the factors of relevance most often mentioned in technical books and websites regarding the growing of wine grapes and apples.

3rd Decision:
 Choosing the future year in which to assess climate change.

The Choice: The year 2050.

Why?  The year 2050 is close enough in the future that the climatic implications of changes by that time seem relevant to today's agriculturalists, but it is

far enough in the future that there should be significant climatic changes by that time.


4th Decision:
How to put the climate data into the computer.

The choice: Add the climate data in fields to the biogeoclimatic zones in the Kamloops Forest District.

Why? Although there is some simplification of the climate data involved when a single value for a climatic variable is given across one whole biogeoclimatic zone subzone

polygon (e.g. BG xh1), this is still more accurate than point interpolation for British Columbia because of the constantly changing elevation in British Columbia.  For example,

Merritt and Kamloops are both very hot and dry cities in summer.  However, the area on the Coquihalla highway between them is slightly cooler and wetter. Yet, point

interpolation would also show this area as hot and dry --- which is inaccurate.  Biogeoclimatic zones and subzones are classified to a fairly specific levels which makes them

more accurate than point interpolation.  In addition, the nature of the Kamloops Forest Region shapefile that I have made it easier to enter the data using fields than by using

point interpolation..


5th Decision:
Which units to use for the climatic values?

The Choices:  - GDD uses units.      - FFP uses days.        
- Precipitation uses millimetres.         - July mean maximum temperature uses celsius.         - January mean minimum temperature uses kelvin.                                                                                                                                    

Why?   - GDD is given in units in the climatic data.      - FFP is given in days in the climatic data.
- Precipitation is given in millimetres in the climatic data.     -  July mean maximum temperature is given in celsius in the climatic data.


January is an interesting case.  Raster models are space-filling (every space on the screen must have a value).  Areas which have not been given a value are automatically

given a value near 0.  This presented a problem for January if celsius were to be used because the areas without a value (i.e. they have a null or zero value) would have greater

values than the other areas (which had negative values).  The only way to ensure that they were masked out of the analysis from what I ascertained was to put all temperatures

values in Kelvin.  This meant that there were no negative values for temperatures for areas where I had inputted values (because 0 degrees celsius = 273 degrees kelvin)

6th Decision:
How to calculate climatic values for 2050?

The Choice: Using the Climate Change brochure for British Columbia found on the BC Government website and information from the IPCC (Intergovernment Panel on Climate Change).

How?
GDD 2050 = GDD + 0.25*(GDD)
FFP 2050 = FFP + 30
Precip2050= Precip + (0.10*precip)
July2050= Julymax+1
Jan2050=Janminimum+3

Why?  - GDD values are expected to increase by 25% between 2000 (used for present climatic date) and 2050.
- There is expected to be an increase of 30 frost-free days per year between 2000 and 2050.
- There is expected to be an increase in precipitation by 10% between 2000 and 2050.
- July maximum temperatures are expected to increase by anywhere between 0.5 and 1 degrees celsius between 2000 and 2050.
- January minimum temperatures are expected to increase by anywhere between 2.5 and 3.5 degrees celsius between 2000 and 2050.


7th Decision:

How to decide suitability values.

The Choice: 0 =worst; 8=best (numbers entered for 0, 1,2,4,6, and 8 sometimes)

Why?  Using even numbers as the starting and ending points is more simple than using odd numbers.  Plus, the fact that 8 is a multiple of 1,2, and 4 makes it an

easier number to use than, say, 6 or 12, for the purposes of calculations.

8th Decision:
How to decide the suitability values for each climatic variable for each crop.

The Choices: Use data from websites and books to determine the optimal range of climatic conditions for each crop.

What are the values?

For Apples:

FFP: Value of 0 given for -999<x<1 (in order to mask out the areas with no data).
Value of 1 given for 1<x<110.             Value of 2 given for 110<x<130.
Value of 4 given for 130<x<150           Value of 8 given for 150<x<368

GDD: Value of 0 given for -999<x<1 (in order to mask out the areas with no data)
Value of 1 given for 1<x<1400.             Value of 2 given for 1400<x<1650.
Value of 6 given for 1650<x<1800         Value of  8 given for 1800<x<3000

Precip:  Value of 0 given for -999<x<1 ( in order to mask out the areas with no data)
Value of 1 given for 1<x<150 and 700<x<10000
Value of 2 given for  600<x<700 and 150<x<250       Value of 4 given for 250<x<300
Value of 8 given for 300<x<600.

July Temperature: Value of 0 given for -999<x<1 (in order to mask out the areas with no data)
Value of 1 given for 1<x<20.          Value of 2 given for 20<x<24.
Value of 4 given for 24<x<25 and 32<x<35           Value of 6 given for 25<x<27
Value of 8 given for 27<x<32.

January Temperature:  Value of  0 given for -999<x<1 (in order to mask out the areas with no data)
Value of 1 given for 1<x<263       Value of 2 given for 263<x<265.
Value of 4 given for 265<x<268       Value of 6 given for 268<x<271.
Value of 8 given for 271<x<300

For Grapes:

FFP: Value of 0 given for -999<x<1 (in order to mask out the areas with no data).
Value of 1 given for 1<x<120         Value of 2 given for 120<x<140
Value of 4 given for 140<x<160.       Value of 8 given for 160<x<368

GDD: Value of 0 given for -999<x<1 (in order to mask out the areas with no data).
Value of 1 given for 1<x<1500          Value of 2 given for 1500<x<1700
Value for 6 for 1700<x<1900            Value of 8 given for 1900<x<3000

Precip: Value of 0 given for -999<x<1 (in order to mask out the areas with no data).
Value of 1 given for 1<x<150 and 650<x<10000
Value of 2 given for 550<x<650       Value of 4 given for 150<x<250 and 400<x<550
Value of 8 given for 250<x<400

July Temperature:  Value of 0 given for -999<x<1 (in order to mask out the areas with no data).
Value of 1 given for 1<x<25  
Value of 2 given for 25<x<27       Value of 6 given for 27<x<30
Value of 8 given for 30<x<35        

January Temperature:  Value of 0 given for -999<x<1 (in order to mask out the areas with no data).
Value of 1 given for 1<x<265     
Value of 2 given for  265<x<267          Value of  4 given for 267<x<270
Value of  6 given for 270<x<273          Value of  8 given for 273<x<300

9th Decision:
Deciding on importance of various factors for MCE:

The Choice: Use the description of the importance of various factors in the books and websites to decide the relative importance of various factors.

How?
Grapes:  July Max - 8     FFP - 8      GDD - 4     Precip - 4  Jan Min -1

Apples: FFP - 4          GDD - 4 Precip - 4 July Max -2  Jan Min -1

Weights calculated for Grapes using MCE:
July Max - 0.3200   FFP - 0.3200  
GDD - 0.1600 Precip - 0.1600 
Jan Min - 0.0400

Weights Calculated for Apples using MCE:
FFP - 0.2667         GDD - 0.2667       Precip - 0.2667   July Max - 0.1333
Jan Min - 0.0667


10th Decision:
Constraints or no constraints.

The choice: No constraints.

Why? The areas in which one factor would be a serious constraint (namely, the alpine tundra), the other factors

tend to not be very favourable for grape and apple-growing (low GDD, short FFP, low winter temperatures, and low summer temperatures tend to go together in these climatic

models).  So, constraints are not needed.  Furthermore, with today's technological advances, if only one factor is a problem, there are ways of overcoming it (e.g. irrigation for

lack of precipitation, shielding and plastic to protect plants from cold).


11th Decision:
Deciding how high a suitability score was needed in order to give the area the 'suitable designation'.

The Choice: The scores ranged from 0 to 8 on the final suitability assessments and a score>6 warranted a 'suitable designation'.

Why?  A suitability of 6 or higher indicates that at the climatic conditions for growing the crop are at a level of at least 3/4 of the best possible climatic conditions.

There are many crops in the world that are grown in areas that aren't 100% suited for that crop, but they are still suitable enough that people grow that crop there.  If

the suitability is too low, though, too many additions have to be made to make the area good for growing that crop, and thus, profitable production of that crop in that area is

unlikely and that area is determined to have unsuitable climatic conditions for growing that crop.


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