Climate Change Impacts on Maple Syrup Yield

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1 Climate Change Impacts on Maple Syrup Yield Rajasekaran R. Lada, Karen Nelson, Arumugam Thiagarajan Maple Research Programme, Dalhousie Agricultural Campus

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4 Canada is the largest maple producer in the world.

5 Quebec produces more than 90% of Canadian maple syrup.

6 Nova Scotia syrup yields are the lowest among major maple regions in north America

7 Number of taps in Nova Scotia has progressively increased from 75,000 to over 374,000 in 2012 Maple syrup yields (Liters of syrup/tap/year) followed a declining trend over the years from 0.44 to 0.33 L/tap

8 Differential diagnosis of the problem GENETICS TREE AGE TREE HEALTH SOIL (NUTRITION, DEPTH, MICROBIAL) LOW YIELD OF MAPLE TREE DENSITY CLIMATIC FACTORS TREE GROWTH COMPETITION SOIL WATER RELATIONS ROOT VOLUME

9 There is a link between certain climatic factors and low sap yield. If the specific climatic factor is identified, the sap yield response can be modeled to predict sap yield and sap flow start date.

10 Objectives To determine the extent of climate change that occurred within the maple production areas of Nova Scotia and its influence on Maple syrup production; investigate the linkages between weather parameters and syrup production yields and identify the nature of this relationship and to build a model to explain the relationship between key weather factors and predict the production and sap flow dates.

11 Methodology Weather data min, max temperature; precipitation, snow on the ground. Six Environment Canada weather stations. Halifax International Airport Weather Station Climate Change Analysis. Other station s data were used to analyze for a particular parameter that showed a significant link.

12 Table 1. Monthly climate parameters, times and their description investigated by preliminary regression analysis, for six weather stations (n=6) throughout the maple syrup regions in Nova Scotia Climate Parameters Time Periods Description Temperature Temperature Above 5 o C Temperature Below 5 o C Temperature Below 0 o C Freeze/Thaw Events Previous Years Effective Growing Degree Days Total Precipitation Snow on Ground Annually, Monthly, Dec Mar, Jan Feb, Jan Mar Annually, Monthly, Dec Mar, Jan Feb, Jan Mar Annually, Monthly, Dec Mar, Jan Feb, Jan Mar Annually, Monthly, Dec Mar, Jan Feb, Jan Mar Annually, Monthly, Dec Mar, Jan Feb, Jan Mar Annually Annually, Monthly, Dec Mar, Jan Feb, Jan Mar Annually, Monthly, Dec Mar, Jan Feb, Jan Mar Minimum, Maximum, Mean Temperature, and Temperature Differential Number of days with a minimum temperature above 5 o C Number of days with a minimum temperature below 5 o C Number of days with a minimum temperature below 0 o C Consecutive 3 days below 5 o C, followed by a day above 10 o C from December to March Number of degrees above >5 o C from April 1 st after budburst to October 31 st Amount of precipitation Amount of snow on ground from December to April, as well as the number of days from December to April with snow present on the ground.

13 Methods (contd). Trend Analysis Years blocked into to TWO ( ; ) Syrup data collected from TEN maple producers who kept records. Data included information on annual syrup production and sap yield (Liters), number of taps, sap brix content, timing of tapping, date of first boil, and date of last boil. Data was normalized as syrup yield L/tap/yr.

14 Methods (contd) The length of the maple season (last boil first boil) in days, and the number of days to the start and finish of the syrup season based on the Julian date were calculated from a January 1 start date for each year.

15 Model development In total 108 input variables chosen for establishing correlations with syrup yield. These parameters were chosen for two reasons: (i) based on the previous research reports and (ii) the physiological understanding of the sap flow suggest that critical weather factor(s) could reside in any month of the year.

16 Model development For reliability and completeness of data sites and 10 and 9 were chosen for model development. Used multiple correlations test using SAS 9.3 (SAS 2010) Regression coefficient, F value, P values used to identify the parameters that are highly linked to syrup yield.

17 Neural Network Analysis To identify the inter relationships among various parameters and to develop a model that is closely linked. (i) one dataset to train and build a model (ii) second set to internally verify, calibrate the model and (iii) a third dataset to validate the built model. Data from site 10 was split in to two data sets; one used to develop model and another set was used to calibrate. Data from sites 9 and 6 were used to test the model.

18 Results Is there an evidence for climate change?

19 Among 47 parameters regressed 12 parameters showed significant changes over 30 year time period Parameter F value P value R 2 value Mean Temperature Annual Mean Temperature Dec Feb Mean Temperature Jun Aug Mean Min Temp Annual Mean Min Temp Jun Aug Temp. differential Jun Aug Days above 5 deg. C Annual Days below 0 deg.c Annual EGDD Annual Total PPT Jan Feb Total PPT Jan March Total snow on ground Annual

20 Annual mean temperature increased by 1 degree C

21 Mean winter temperature increased by degree C and mean summer temperature increased by 0.69 degree C.

22 Number of days below zero declined by 15 since 1977.

23 Effective Growing Degree Days increased by 124 since 1977.

24 Mean total precipitation in Jan-March declined.

25 Mean snow cover on ground increased since 1977.

26 Previous years EGDDs negatively impacted syrup yield.

27 Start and End date has changed. In it was March to April In it was March 6 11 to April No change in number of days of sap flow. The average SL 34 d+/ 8.6d

28 Conclusions There is an increase of 1 o C in the mean annual temperature in Nova Scotia. The largest increase in temperature appears to occur during the winter months (Jan Mar), compared to the summer months (Jun Aug). The minimum temperature is increasing with declining number of days below freezing (0 o C) and the number of days above 5 o C increasing at our sites. The effective growing degree days has been increasing steadily in the last 15 years and Nova Scotia is experiencing more degree days than those typically recorded in 1980s. There has been a decrease in the amount of precipitation, particularly in the winter months. Interestingly, the amount of snow remaining on the ground appears to be increasing, this appears to have only occurred since the mid 1990.

29 Conclusions Weather factors in combination negatively affected the sap yield and shifted the sap flow season earlier. In general, the increase in EGDD paralleled the progressive decline in sap yield. Sap yield was reduced by 40% and the season has advanced by 5 days in the last years. Nevertheless, the season length remains largely unaffected.

30 Would the climate change parameters explain the decline in sap yield?

31 Input analysis Step wise regression analysis for 108 parameters showed the following parameters had significant relationship with syrup yield. Temperature difference in January ( o C) sap flow Freeze thaw events in April (# of events) sap flow Freeze thaw events in May (# of events) sap flow Freeze thaw events in October (# of events) root metabolism Total precipitation (mm) in January sap flow Total precipitation (mm) in July Tree growth More factors included in the model R 2 values increased.

32 Predicting sap flow start date The following parameters showed significant link with syrup yield. Maximum temperature in March. Mean temperature in February Snow on ground in November P value of <0.01 and an R 2 value of 0.85.

33 Neural Network Analysis Neural Network Analysis 6 chosen input parameters and one output parameter (syrup yield) Temperature difference in January ( o C) Freeze thaw events in April (# of events) Freeze thaw events in May (# of events) Freeze thaw events in October (# of events) Total precipitation (mm) in January Total precipitation (mm) in July 1000 training cycles were set Rest of the data was used to validate the model Start date prediction max temp in March, mean temp in Feb, snow on the ground in November were used 5000 cycles were run.

34 Figure 13. The fitness characteristics of the neural network based on the training set. The X axis indicates the sample #, y axis represents the syrup yield values (L/tap/yr). The violet line is built on predicted values and the black lines are original values. The red and blue lines represent the upper and lower 95% confidence interval values.

35 Syrup yield prediction Model moderately performed well. Under predicted by 23% Microclimate influenced the model for prediction as site 10 was used to establish the model and site 9 was used to validate the model.

36 Start date prediction Moderate predictability More sites needed and more microclimatic information needed for increasing accuracy.

37 Nova Scotia trees are growing slowly Stand Age (yr) Mean DBH (cm) Good site Medium site Poor site Table 6. Mean diameter breast height (DBH) of well stocked stands of northern hardwoods in the Lake States dominated by Sugar Maple. Source: Godman et al., (2009) Luzadis and Gossett (1996) New York state 30 year old tree averaging 76.2 to cm (5.24 cm, annually). Nova Scotia trees in the past 30 years added only 12.4 to 54.8 cm

38 Conclusions Temperature difference in January, number of freeze thaw events in the months of April, May and October, total precipitation received in January and July all showed a significant strong correlation with h syrup yields (P<0.001, R 2 =0.8) ). Neural network model that used these input parameters predicted the syrup yield of an independent site with a moderate accuracy (45%).

39 Differential diagnosis a key approach for successful research.

40 Thank you. Questions?

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