Millennial-scale tree-ring isotope chronologies from coast redwoods provide insights on controls over California hydroclimate variability
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To understand drivers of hydroclimate variability in north-coastal California, we obtained tree cross-sections from eleven coastal redwoods (mean age of 1232 years old) from the northern half of the species range. Tree rings from eight trees were cross-dated and sampled at sub-annual resolution for carbon isotope discrimination (Δ13C) and oxygen isotope composition (δ18O). Tree-ring Δ13C and δ18O, compared to modern climate data, demonstrate these signals primarily record summertime hydroclimate variability—primarily through variables associated with evaporative conditions and/or precipitation. Our 1100-year stable isotope chronologies showed that north-coastal California did not undergo the megadroughts observed elsewhere in California and the western United States. This result implicates extended periods of low winter precipitation, rather than growing season evaporation, as the primary driver of previous megadroughts across California and neighboring regions. Compared to cool conditions prevailing over the Northern Hemisphere during the Little Ice age (1301–1875 of the common era, CE), the frequency of isotopic events of a certain magnitude was greater during periods with warmer Northern Hemisphere temperatures such as the Medieval Climate Anomaly (900–1300 CE) and the modern period (1876 to present). This association between tree-ring isotopic variability and long-term shifts in temperatures is consistent with the expected patterns in mid-latitude hydroclimate variability expected from arctic amplification (i.e., shifts in equator-to-pole temperature differences that modify jet stream speed and amplitude) or amplified quasi-resonant wave activity (i.e., wave-patterns in high-altitude winds that become “trapped” within a certain pattern, thereby producing a longer-duration periods of drought or wetness) across mid-latitudes during the boreal summer.
KeywordsΔ13C δ18O Arctic amplification Megadrought Climate event frequency Medieval climate anomaly Little ice age
For processing many thousands of samples, we extend our gratitude to our tree-ring lab managers Ken Olejar and LeAnn Canady, our isotope lab managers Lin Roden, Stefania Mambelli and Wenbo Yang and the many undergraduate student workers at SOU and UCB. For providing access and support in collecting redwood slabs we thank the California Redwood State Parks, Jay Harris, and the trails crews at Humboldt Redwoods and Prairie Creek Redwoods State Parks. We thank Steve Sillett for providing Slab 1 and Allyson Carroll for all of her help in providing tree-ring chronologies that confirmed our cross-dating. This research was supported by the National Science Foundation Paleo Perspectives on Climate Change Grants AGS-1003050 and AGS-1003601. Finally, we thank two anonymous reviewers who provided comments that improved this manuscript greatly.
Author contribution statement
JSR and TED conceived of the research, oversaw and contributed to the research. SLV oversaw data collection, analyzed the data and wrote the manuscript. JSR and TED provided editorial advice.
- Bunn AG, Korpela M, Biondi F, Campelo F, Mérian P, Qeadan F, Zang C, Buras A, Cecile J, Mudelsee M, Schulz M, Pucha-Cofrep D, Wernicke J (2018) dplR: dendrochronology Program Library in R. R package version 1.6.7. http://R-Forge.R-project.org/projects/dplr/
- Cook ER, Krusic PJ (2014) ARSTAN version 44h3: A tree-ring standardization program based on detrending and autoregressive time series modeling, with interactive graphics. Tree-Ring Laboratory, Lamont-Doherty Earth Observatory of Columbia University, PalisadesGoogle Scholar
- Grissino-Mayer HD (2001) Evaluating crossdating accuracy: a manual and tutorial for the computer program COFECHA. Tree Ring Res 57:205–221Google Scholar
- Holmes R (1983) Computer assisted quality control in tree-ring dating and measurement. Tree Ring Bull 44:69–75Google Scholar
- Liu Y, Cobb KM, Song H, Li Q, Li C-Y, Nakatsuka T, An Z, Zhou W, Cai Q, Li J, Leavitt SW, Sun C, Mei R, Chuan-Chou S, Chan M-H, Sun J, Yan L, Lei Y, Ma Y, Li X, Chen D, Linderholm HW (2017) Recent enhancement of central Pacific El Niño variability relative to last eight centuries. Nat Commun 8:15386CrossRefPubMedPubMedCentralGoogle Scholar
- Mooney HA, Dawson TE (2015) Northern forest ecosystems (Chapter 26). In: Zavaleta E, Mooney H (eds) Ecosystems of California. University of California Press, CaliforniaGoogle Scholar
- R Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org/
- Sigl M, Winstrup M, McConnell JR, Welten KC, Plunkett G, Ludlow F, Büntgen U, Caffee M, Chellman N, Dahl-Jensen D, Fischer H, Kipfstuhl S, Kostick C, Maselli OJ, Mekhaldi F, Mulvaney R, Muscheler R, Pasteris DR, Pilcher JR, Salzer M, Schüpbach S, Steffensen JP, Vinther BM, Woodruff TE (2015) Timing and climate forcing of volcanic eruptions for the past 2,500 years. Nature 523:543–549CrossRefPubMedGoogle Scholar
- Sternberg LSL (1989) Oxygen and hydrogen isotope measurements in plant cellulose analysis. In: Linskens HF, Jackson JF (eds) Modern methods of plant analysis, vol 10. Plant fibers. Springer, Heidelberg, pp 89–99Google Scholar
- Kahmen A, Sachse D, Arndt SK, Tu KP Farrington H, Vitousek PM, Dawson TE (2011) Cellulose δ18O is an index of leaf-to-air vapor pressure difference (VPD) in tropical plants. Proc Natl Acad Sci 108:1981–1986Google Scholar