temp_slr() will produce estimates of mean annual temperature and standard error
using leaf margin analysis. There are different ways to represent error. The most simple is using the standard error of the regression.
These are listed in the table below. However, this is not the only source of uncertainty and is too simplistic a measure of error.
This function instead uses the method outlined in Miller et al. 2006, and reported in Peppe et al 2018 (eq. 4), which also accounts
for binomial sampling error and overdispersion, offering what we consider a best practice approach. The standard error of the regression provides a minimum error value.
Note, Peppe et al. 2018 suggests that a conservative minimum uncertainty for all leaf margin analysis results is probably +/- 5 degrees Celsius.
Standard error of regression:
| Regression | SE |
| Peppe2018 | 4.5 |
| Peppe2011 | 4.8 |
| Peppe2011NH | 3.4 |
| Miller2006 | - |
| WingGreenwood | 0.8 |
| Wilf1997 | 2.0 |
| KowalskiDilcher | 3.6 |
Arguments
- data
A data frame that must include the columns "morphotype" and "margin". Can be leaf or species level data.
- regression
A string representing one of the following pre-loaded regressions:
"Peppe2018" - for global temperature estimates
"Peppe2011" - The Americas, Japan, and Oceania
"Peppe2011NH" - Peppe 2011 (Northern Hemisphere only)
"Miller2006" - North and Central America
"WingGreenwood" - East Asia - original leaf margin analysis regression
"Wilf1997" - The Americas
"KowalskiDilcher" - North America
- slope
Slope, if using a custom regression
- constant
Constant, if using a custom regression
- error
Standard error, if using a custom regression
References
Kowalski, E.A. & Dilcher, D.L. (2003). Warmer paleotemperatures for terrestrial ecosystems. Proceedings of the National Academy of Sciences, 100, 167–170.
Miller, I. M., Brandon, M. T., & Hickey, L. J. (2006). Using leaf margin analysis to estimate mid-Cretaceous (Albian) paleolatitude of the Baja BC block. Earth and Planetary Science Letters, 245, 95–114.
Peppe, D. J., Baumgartner, A., Flynn, A., & Blonder, B. (2018). Reconstructing paleoclimate and paleoecology using fossil leaves. Methods in paleoecology: Reconstructing Cenozoic terrestrial environments and ecological communities, 289-317.
Peppe, D.J., Royer, D.L., Cariglino, B., Oliver, S.Y., Newman, S., Leight, E., Enikolopov, G., Fernandez-Burgos, M., Herrera, F., Adams, J.M., Correa, E., Currano, E.D., Erickson, J.M., Hinojosa, L.F., Hoganson, J.W., Iglesias, A., Jaramillo, C.A., Johnson, K.R., Jordan, G.J., Kraft, N.J.B., Lovelock, E.C., Lusk, C.H., Niinemets, Ü., Peñuelas, J., Rapson, G., Wing, S.L. and Wright, I.J. (2011), Sensitivity of leaf size and shape to climate: global patterns and paleoclimatic applications. New Phytologist, 190: 724-739. https://doi.org/10.1111/j.1469-8137.2010.03615.x
Wing, S., & Greenwood, D. R. (1993). Fossils and fossil climate: the case for equable continental interiors in the Eocene. Philosophical Transactions of the Royal Society of London Series B, 341, 243–252.
Wilf, P. (1997). When are leaves good thermometers? A new case for leaf margin analysis. Paleobiology, 23, 373–390.