Figure 2: Evaluation of seasonality of carbonate precipitation for biogenic, micrite, and biologically mediated lacustrine carbonates using the clumped isotope calibration of Anderson et al. (2021). White circles with black bars are Δ47-derived temperatures and with uncertainties, respectively. Results are compared to projected lake temperatures for different times of year, calculated using relationships from (Hren & Sheldon, 2012) and Mering (2015) in conjunction with MAAT for each location derived from the University of Delaware’s high-resolution gridded air temperature dataset (Willmott & Matsuura, 2001) provided by NOAA. Orange circles reflect early spring (Northern Hemisphere April-June (AMJ)) water temperatures, yellow circles indicate summer (Northern Hemisphere June-August (JJA)), blue circles indicate April-October water temperatures (A-O), and red circles indicate warmest month water temperatures (WMT). This comparison shows that for biologic carbonates, there is good agreement between Δ47-T and what is known about typical growth seasons in the Anderson et al. (2021) calibration in lower latitudes. However, the Anderson et al. (2021) calibration results in an overestimation of growth temperature at higher latitudes, with 37% of clumped isotope derived temperatures matching or exceeding estimated lake warmest month temperature, as indicated by the offset between the clumped isotope derived temperatures represented by a white circle with black error bands and the colored data points in panel A. For micrites, the Δ47 temperatures derived from the Anderson et al. (2021) calibration are likely underestimated in roughly half of the lakes examined here. Estimated temperatures from biologically mediated carbonates using the Anderson et al. (2021) calibration are reflecting warmest month temperatures in many cases, an overestimation from the projections derived from Hren and Sheldon (2012).
3.2 Δ47-Temperature Relationships
We utilize calibration data in Table 1 to derive regressions for our entire dataset (a composite freshwater calibration), and material-specific calibrations for biogenic carbonates (bivalves and gastropods), biologically mediated carbonates (microbialites and tufas), micrite, and travertines. Δ47 values for samples within this study range from 0.409 to 0.682‰ with independently measured water temperatures ranging from 5 to 95°C. Calibrations derived in this study are presented in Table 2.
Performing an ordinary least squares regression through all freshwater carbonate data in this study results in a steeper slope and shallower intercept than Anderson et al. (2021) calibration. Although the 95% confidence intervals on the estimated regression models overlap visually (Fig. 3), an analysis of covariance (ANCOVA) analysis shows that the slopes for the two calibrations are significantly different from each other (pslope = 0.0334; Table 3). The Anderson et al. (2021) calibration includes low temperature Antarctic microbialites that are offset from other data, with half of the samples from a high pH (10.3-10.7; Mackey et al., 2017) environment (Fig. 3 - dark red symbols). Low temperature and high pH are environmental factors that could give rise to potential kinetic isotope effects or DIC speciation effects (Tang et al., 2014; Tripati et al., 2015). In fact, all of the Antarctic samples are negatively offset from the rest of the data in this study, and thus, we exclude these data from both the composite and the biologically-mediated regressions we report in this study (Table 3). Additionally, we compare our results from the composite calibration to the synthesis of calibration data published in Petersen et al. (2019) that was projected into a 90°C reference frame. Similarly to Anderson et al. (2021), we find that the slope derived within this study yields a statistically significant difference in slope to that of Petersen et al. (2019) (pslope = 0.0036; Table 3). Despite improvements in data handling and standardization procedures that have been shown to resolve disparities in derived regression slopes in two large synthesis studies (Anderson et al., 2021; Petersen et al., 2019), we do not observe convergence between regression parameters derived from these syntheses and our composite freshwater regression (Fig. 3). However, our derived freshwater composite calibration parameters show agreement with two previous calibrations using authigenic lacustrine carbonates (H. Li et al., 2021) and travertines (Bernasconi et al., 2018) (Table 3).