The Dynamics of Non-Masting Red Maples and Masting Sugar Maples

A data package titled, Maple Reproduction and Sap Flow at Harvard Forest since 2011, closely studied the properties of maple trees. The aim of this report is to answer the question: Do non-masting maple trees have muted dynamics compared to the masting sugar maple? There are 14 different data sets within this package, however, there are 2 data sets that contain data relevent to the leading question. These datasets are the ones related to sap collection and tree tapping. Within these data sets, we will be looking at the variables species, dbh, tap.bearing, and sap.wt. Under the species column, there are two possible options, ACSA, representing the sugar maples, and ACRU, representing Red Maples. DBH represents the diameter of a tree at 1.4m above ground. Tap.Bearing represents how much was collected from the tap. Finally Sap.wt represents the amount of sap collected from a tree.

Do Sugar Maples produce more sap than Red Maples?

Since there is so much information within this data package, it has to broken up into different sections as to not look at too much information at one time. First, we are going to look at the amount of sap produced by the trees in the data set titled Maple-Sap. We will primarily be focusing on the variables tree and sap.wt

These two variables will allow us to see how much each tree produced, also showing us which type of tree it came from.

Maple_sap2
## # A tibble: 8,391 × 8
##    date       tree  tap   time   datetime            sugar species sap.wt
##    <date>     <chr> <chr> <time> <dttm>              <dbl> <chr>    <dbl>
##  1 2012-02-16 HF1   A     12:41  2012-02-16 12:41:00   2.7 ACSA      4.24
##  2 2012-02-16 HF1   B     12:41  2012-02-16 12:41:00   2.4 ACSA      1.08
##  3 2012-02-16 HF4   A     12:26  2012-02-16 12:26:00   2.1 ACSA      2.32
##  4 2012-02-16 HF4   B     12:26  2012-02-16 12:26:00   2.4 ACSA      1.48
##  5 2012-02-16 HF6   A     12:31  2012-02-16 12:31:00   2.6 ACSA      1.84
##  6 2012-02-16 HF6   B     12:31  2012-02-16 12:31:00   2.6 ACSA      0.88
##  7 2012-02-16 HF7   A     12:27  2012-02-16 12:27:00   2.1 ACSA      1.66
##  8 2012-02-16 HF7   B     12:27  2012-02-16 12:27:00   3   ACSA      1.2 
##  9 2012-02-16 HF18  A     12:24  2012-02-16 12:24:00   2.6 ACSA      3.99
## 10 2012-02-16 HF21  A     12:18  2012-02-16 12:18:00   2   ACSA      2.4 
## # ℹ 8,381 more rows
ggplot(data = Maple_sap2, mapping = aes(x = tree, y = sap.wt)) +
  geom_boxplot() +
  labs(x = "Species of Tree",
       title = "Correlation of Species and Sap Weight",
       y = "Sap Weight")

Looking at box plot comparing the type of tree and the sap weight, we can see a general trend that Sugar Maple trees, represented by HF, are much higher overall than Red Maples, represented by AR. The biggest outlier value for Sugar Maples is just under 25, and the biggest outlier for Sugar Maples is around 13 or 14. Comparitively, they’re averages are very different, the smallest for Sugar Maples being around 3, and the smallest for Red Maples being around 1.

While the box plots could help us come to the conclusion that Red maples do have muted dynamics, we still need more evidence. Next, we can look at the overall averages for both types of trees.

Maple_sap2 %>%
  group_by(species)%>%
  summarize(mean(sap.wt))
## # A tibble: 2 × 2
##   species `mean(sap.wt)`
##   <chr>            <dbl>
## 1 ACRU              1.90
## 2 ACSA              4.16

From these two averages, it is clear that, ACSA, representing Sugar Maples produce substantially more Sap than ACRU, representing Red Maples. There is a difference of 2.26 units between the two species of trees.

Is the Difference in Sap Weight Statistically Significant?

Taking it one step further in order to be certain of our claim that Red Maples produce significantly less sap than Sugar maples, we can create a model and look at the statistical significance that the species of tree has a direct effect on sap weight.

Maple_sap2_model <- lm(sap.wt ~ species, data = Maple_sap2)
summary(Maple_sap2_model)
## 
## Call:
## lm(formula = sap.wt ~ species, data = Maple_sap2)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.1475 -2.2575 -0.5975  1.6225 19.8825 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  1.89603    0.09755   19.44   <2e-16 ***
## speciesACSA  2.26149    0.10379   21.79   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.054 on 8389 degrees of freedom
## Multiple R-squared:  0.05356,    Adjusted R-squared:  0.05345 
## F-statistic: 474.7 on 1 and 8389 DF,  p-value: < 2.2e-16

Looking at the three statistical measurements such as RSE, R^2, and the p-value will help us create a claim. The RSE of this model is 3.054 which is an okay value, but isn’t horrible, but it is not great. The R^2 value is 0.054 which is a little small, which is just like the RSE not horrible but not great. The P-value is the only of the statistical tests that can allow us to say that there is significant evidence that the regression model outperforms the mean model.

There is evidence to conclude that there is a significant impact on Sap Weight depending on the species, however this claim is not very strong yet.

The Significance of Species on Tap Bearing

Although the amount of sap collected from a tree could indicate whether a species is healthier than another, there is still a lot more evidence that could strengthen the claim.

Looking at the data set, Maple_tap, we can look at the tap bearingof a tree to see the overall difference in Sugar and Maple trees.

Maple_tap2
## # A tibble: 375 × 7
##    date       tree  tap   species   dbh tap.bearing tap.height
##    <date>     <chr> <chr> <chr>   <dbl>       <dbl>      <dbl>
##  1 2012-02-14 HF1   A     ACSA     85.5         142         95
##  2 2012-02-14 HF1   B     ACSA     85.5         322         95
##  3 2012-02-14 HF18  A     ACSA     75.1         188        105
##  4 2012-02-14 HF21  A     ACSA     64.1         215        119
##  5 2012-02-14 HF21  B     ACSA     64.1          35        119
##  6 2012-02-14 HF22  A     ACSA     80.7         116        159
##  7 2012-02-14 HF22  B     ACSA     80.7         296        159
##  8 2012-02-14 HF35  A     ACSA     37.3         125        154
##  9 2012-02-14 HF38  A     ACSA     61.4         189        148
## 10 2012-02-14 HF38  B     ACSA     61.4           9        148
## # ℹ 365 more rows
ggplot(data = Maple_tap2, mapping = aes(x = tree, y = tap.bearing)) +
  geom_boxplot() +
  labs(x = "Species of Tree",
       title = "Correlation of Species and Tap Bearing",
       y = "Tap Bearing")

The box plots of the tap bearing column, is not as conclusive as the sap weight column because the values are so close. However, there are a few very high values for the Red Maples, potentially skewing the results. The Red Maples have a little higher of an average than the Sugar Maple, contradicting our previous claim. In order to gain more insight, we can look at the overall averages of each type of tree, HF representing Sugar Maple trees, and HFR representing Red Maples.

Maple_tap2 %>%
  group_by(species)%>%
  summarize(mean(tap.bearing))
## # A tibble: 2 × 2
##   species `mean(tap.bearing)`
##   <chr>                 <dbl>
## 1 ACRU                   180.
## 2 ACSA                   173.

Alike the box plots, Sugar maples have a little bit smaller average than the Red Maples, contradicting our previous claim.

Is Tap Bearing Statistically Significant?

In order to come to a claim regarding the significance of species on tap bearing, we can create a mode to measure statistical signficance.

Maple_tap2_model <- lm(tap.bearing ~ species, data = Maple_tap2)
summary(Maple_tap2_model)
## 
## Call:
## lm(formula = tap.bearing ~ species, data = Maple_tap2)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -173.215  -97.215    6.444   87.785  184.785 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   179.56      17.64  10.177   <2e-16 ***
## speciesACSA    -6.34      18.56  -0.342    0.733    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 105.9 on 373 degrees of freedom
## Multiple R-squared:  0.0003128,  Adjusted R-squared:  -0.002367 
## F-statistic: 0.1167 on 1 and 373 DF,  p-value: 0.7328

Looking at the values the RSE being 105.9 which is extremely high, R^2 value being 0.0003128 which is very low and far from 1, and the p-value of 0.7327, which is too large to be statistically significant.

All of these values are statistically insignificant meaning this does not provide evidence for our claim that Red Maples have muted dynamics compared to Sugar Maples.

Conclusion

From all the data collected, we can conclude that our claim that Non-Masting Red Maples have muted dynamics compared to Masting Sugar maples is inconclusive. Based on the findings from sap weight, we have significant evidence to prove that Red Maples do posses muted dynamics compared to Sugar maples, however, tap bearing did not provide any evidence for the claim.

Citation

Rapp, J., E. Crone, and K. Stinson. 2023. Maple Reproduction and Sap Flow at Harvard Forest since 2011 ver 6. Environmental Data Initiative. https://doi.org/10.6073/pasta/7c2ddd7b75680980d84478011c5fbba9 (Accessed 2024-12-11).