Results
The final dataset that we used to model carbon assimilation as a
function of temperature contained between 17 and 52 assimilation
measurements per each of 21 plant species. Changes in the sample chamber
concentrations from 400 to 405ppm caused no more than a 0.27 μ mol
m-2 s-1 increase in carbon
assimilation (Fig. S1 ). The fits of Eq. 1 and Eq. 2 to our
temperature-assimilation data are presented in Figure S2 , and
the carbon assimilation parameters (Tmax,
Popt, Topt, and Ω) estimated from these
models are provided in Table S1. The modeled changes in
Fv/Fm in response to heat treatments
used to calculate Tcrit, T50, and
T95 heat tolerances are presented in Figure S3and provided in Table S1. Below we present only values of
Topt and Popt estimated using Eq. 1
because they were highly correlated with their respective estimate from
Eq. 2. Results for hypotheses 3 and 4 using Popt and
Topt from Eq. 2 are provided in Figure S4 .
Figure 3 summarizes the mean Topt,
Tmax, Tcrit, T50, and
T95 relative to one another for each species and the
entire dataset. The mean trait values for the entire dataset show that
Tmax is encompassed within the range of temperatures
represented by the mean Tcrit and T50.
This was not the case for species-level data as Tcritexceeded Tmax for 7 species, but Tmaxnever exceeded T50. The only significant correlations we
observed among carbon assimilation parameters involved the Ω parameter,
which describes the breadth of the temperature-assimilation curves. We
observed that Ω was significantly correlated to Tmax (r
= 0.567, p = 0.007; Fig. 4A ), and negatively correlated to
Topt (r = 0.489, p = 0.024; Fig. 4B ). No
correlations were observed between Topt and
Popt estimated with either Eq. 1 or 2.
Figure 5 depicts the phylogenetically controlled correlations
between different metrics of heat tolerance for PSII photochemistry and
each parameter that describes carbon assimilation as a function of
temperature. Tcrit was negatively correlated to
T95 (r=-0.486, p= 0.025) and not correlated to
T50 (r=-0.089, p= 0.700). Our estimates of
T50 and T95 were highly correlated (r=
0.91, p<0.01) and exhibited similar relationships with the
carbon assimilation parameters.
We found that Tmax was not correlated with
Tcrit, T50, or T95(Fig. 5A-C; r=-0.334, p = 0.138; r=0.270, p = 0.237; r=0.372, p
= 0.256), which does not support our hypothesis H1.
Tcrit was not correlated with Ω (Fig. 5D;r=-0.190, p = 0.409), but in support of hypothesis H2 we found that
T50 and T95 were positively correlated
with Ω (Fig. 5E-F; r=0.581, p=0.006; r=0.590, p = 0.005). Our
hypothesis H3 was not supported since we found that
Tcrit was not correlated with Popt(Fig. 5G ; r = 0.211, p = 0.359), but T50 and
T95 were negatively correlated with Popt(Fig. 5H-I; r=-0.495, p=0.022; r =-0.521, p = 0.015). Similar
results were obtained using assimilation estimates from Eq. 2
(Fig. S4A-C ). Our hypothesis H4 was not supported as we
observed no correlation between Tcrit and
Topt from Eq.’s 1 or 2 (Fig. 5J; r = 0.193, p =
0.401; Fig S4D ). Furthermore, we observed that
T50 exhibited a marginally significant negative
correlation to Topt from Eq. 1 (Fig. 5K; r =
-0.432, p = 0.051), and a significant negative correlation to
Topt from Eq. 2 (Fig. S4E) . We found
T95 that was negatively correlated to
Topt from Eq. 1 (Fig. 5L, r = -0.452, p =
0.039) , but not from Eq. 2 (Fig. S4F). Two notable
patterns among these relationships are that 1) correlations between
Tcrit and each carbon assimilation parameter were in the
opposite direction as those observed for T50 and
T95, and 2) heat tolerances that signify greater PSII
impairment (T95>T50>Tcrit) tend to be more
strongly correlated with carbon assimilation parameters, with the
exception of Topt from Eq. 2 (Fig. S4D-F ).
When heat tolerances and carbon assimilation traits were not corrected
for phylogenetic non-independence, the only significant correlation that
persisted was between Ω and Topt. Figure S2suggests Eq. 2 provided a poor fit for our Hamelia patens data.
We excluded this species due to a potentially erroneous estimation of
Tmax, but exclusion of this species did not change our
results, so it remained in our final results. We also log- and square
root-transformed our estimates of Topt and
Tcrit, respectively to improve assumptions of normality
before our phylogenetic corrections, but this had no effect on our
results.
Given the poor coordination between Tmax and our
predefined estimates of PSII heat tolerance, we wanted to know if there
was a predictable level of damage in
FV/FM equal to Tmax. We
used Eq. 3 to predict the FV/FM at the
temperature equal to Tmax for each species. This
estimate of FV/FM was then divided by
the mean FV/FM values observed for our
control treatment temperatures. The mean
FV/FM damage represented by
Tmax was 0.07 with a range of <0.0 to 0.45. As
a point of comparison, our estimate of
FV/FM damage at Tcritwas 0.02 (0.00-0.08, 95% C.I.) damage. Based on this information, we
re-calculated a heat tolerance equivalent to the temperature that caused
FV/FM to decrease by 7%
(T07) for each species. After performing the
phylogenetic correction explained above, we found that
T07 was only correlated with Tcrit(r=0.70, p<0.01).