Transcript The Impact of Climate Change on Maple Syrup Production in

Presented By Ashley Bell
Dr. Thomas Pfaff
Spring 2010 Whalen Symposium
Maple Syrup Overview
 Sugar maple
 Found throughout the local
region
 NY produces 362,000 gallons
per year
 40 liters of sap per 1 liter
syrup
 Sap flows when nights are
below 30˚F and days are
above 36˚F
Image Source: http://www.cnr.vt.edu/dendro/dendrology/fall/biglist_frame.cfm
Climate Change Scenarios
B1
A1
•Rapid economic
•Sustainable
development
growth
•Global population
•Emphasis
on globalincreases
equality
until midcentury
•Convergent
world
•New and more
•Population
peaks
efficient
midcentury
technology of clean energies
•Introduction
•Emissionsefficient
•Resource
increasetechnology
until 2080
B2
A2
•Heterogeneous
world
•Regional sustainability
•Continuously
increasing
•Emphasis on local
solutions to
population
economic, social and
•Self
reliance and
preservation
environmental
sustainability
of
local identities
•Continuously
increasing
•Economic
population development
(lower than A2)
regionally
•Diverse technology change
•Slow
technology
change
(less rapid
than B1)
•Highest emissions in 2100
Image source: http://sedac.ciesin.columbia.edu/ddc/sres/
Current vs. Simulation Emissions
 Current CO2 Levels (2010)
 Project CO2 Levels (2100)
826.6 GtC
1855.3 GtC
Question
 How will climate change effect the maple
syrup industry in Ithaca?
Methods
 Analyze observed temperature data from NCAR
 Check for optimal start date and sap flow days
 Optimal start date – The first day that yields the most sap
flow days for that season (Dec-May)
 Sap flow day – A day the falls below 30˚F at night and rises
above 36˚F during the day
 Repeat for simulated data – “current” and “future”
 Based on the A2 scenario (previous shown CO2 levels)
Extreme Value Distribution
 Maximum and minimum data – likely to be skewed
 Similar to normal – not everything is normal!
 Density equation – Normal
 Density equation – Extreme Value
 Three parameters
What is the probability of having a sap flow day?
0.5
0.45
0.4
Probability
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0
20
40
60
80
100
120
140
Day of the year
Preliminary data suggests highest probability throughout March
160
How will the start date change?
Probability
P robability
0.05
Current
Density
0.04
Projected
Density
0.03
Current Median:
85 ~ Feb 23
0.02
Future Median:
77 ~ Feb 15
0.01
Start Date
50
100
150
200
Start Date
In the future we expect to need to start 8 days earlier
What happens to the number of sap flow days?
Probability
Current
Density
Mean:
22.9 days
Standard
Deviation:
0.9 days
Number of Sap flow days
No change notably due to climate change (time?)
What if we start 10 days late?
Probability
Mean (ontime):
22.9 days
Mean (late):
20.1 days
Loss -12.2%
Number of Sap flow days
Loss in sap flow days expected to not change in the future!
…20 days late?
Probability
Current
Density
Projected
Density
Mean (ontime):
22.9 days
Mean (10 late):
20.1 days
Mean (20 late):
16.3 days
Loss- 28.8%
Mean future
(20 late):
16.1 days
Number of Sap flow days
Minimal change in sap flow days from current model
Loss – 29.7%
Conclusions
 In the future we expect,
 Earlier start date – 8 days earlier
 Maximum number of sap flow days for a season
(on time) not to change
 Loss of of sap flow days


10 late – remain the same as now in future
(Loss of 12.2%)
20 late – minimal differences between now and
future (Loss of 28.8%)
Questions?