Relative influences of multiple sources of uncertainty on cumulative and incremental tree-ring-derived aboveground biomass estimates
How forest growth responds to climate change will impact the global carbon cycle. The sensitivity of tree growth and thus forest productivity to climate can be inferred from tree-ring increments, but individual tree responses may differ from the overall forest response. Tree-ring data have also been used to estimate interannual variability in aboveground biomass, but a shortage of robust uncertainty estimates often limits comparisons with other measurements of the carbon cycle across variable ecological settings. Here we identify and quantify four important sources of uncertainty that affect tree-ring-based aboveground biomass estimates: subsampling, allometry, forest density (sampling), and mortality. In addition, we investigate whether transforming rings widths into biomass affects the underlying growth-climate relationships at two coniferous forests located in the Valles Caldera in northern New Mexico. Allometric and mortality sources of uncertainty contributed most (34–57 and 24–42%, respectively) and subsampling uncertainty least (7–8%) to the total uncertainty for cumulative biomass estimates. Subsampling uncertainty, however, was the largest source of uncertainty for year-to-year variations in biomass estimates, and its large contribution indicates that between-tree growth variability remains influential to changes in year-to-year biomass estimates for a stand. The effect of the large contribution of the subsampling uncertainty is reflected by the different climate responses of large and small trees. Yet, the average influence of climate on tree growth persisted through the biomass transformation, and the biomass growth-climate relationship is comparable to that found in traditional climate reconstruction-oriented tree-ring chronologies. Including the uncertainties in estimates of aboveground biomass will aid comparisons of biomass increment across disparate forests, as well as further the use of these data in vegetation modeling frameworks.
KeywordsCarbon cycle Aboveground biomass estimates Uncertainty Tree rings Growth-climate relationships
This research was supported by the DOE Regional and Global Climate Modeling program DE-SC0016011 and by the University of Arizona Water, Environment, and Energy Solutions (WEES) and Sustainability of Semi-Arid Hydrology and Riparian Areas (SAHRA) programs. FB acknowledges funding from the Swiss National Science Foundation (Grant #P300P2_154543) and the EU H2020 Program (Grant 640176, “BACI”). The authors would like to thank Emily Dynes, Ian Schiach, and Bhaskar Mitra for help with sample collection, Amy Hudson for statistical input, and Marcy Litvak for her helpful comments and insights into the Valles Caldera.
MRA, VT, and DJPM conceived of main analyses and conducted field sampling. MRA performed tree ring analysis and data generation. MRA and CRR contributed to code generation and uncertainty analyses. All authors contributed to intellectual project development and to manuscript preparation and writing.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflicts of interest.
- Anschueta KF, Merlan T (2007) More than a scenic mountain landscape: Valles Caldera National Preserve land use history. Forest Service Rocky Mountain Research Station Gen. Tech. Rep. RMRSGTR-196. Fort Collins, COGoogle Scholar
- Babst F, Bouriaud O, Alexander R et al (2014b) Toward consistent measurements of carbon accumulation: a multi-site assessment of biomass and basal area increment across europe. 32:153–161Google Scholar
- Botkin DB, Simpson LG (1990) Biomass of the North American boreal forest: a step toward accurate global measures. Biogeochemistry 9:161–174Google Scholar
- Cole DM (1977) Protecting and storing increment cores in plastic straws. USDA Forest Service Intermountain Forest and Range Experiment Station Research Note INT-216. Ogden, UTGoogle Scholar
- Cook ER (1985) A time series analysis approach to tree ring standardization. PhD dissertation, University of Arizona, Tucson, p 175Google Scholar
- Douglass AE (1941) Crossdating in dendrochronology. J For 39:825–831Google Scholar
- Dye A, Barker Plotkin A, Bishop D et al (2016) Comparing tree-ring and permanent plot estimates of aboveground net primary production in three eastern U.S. forests. Ecosphere 7:1–13Google Scholar
- Foster JR, Finley AO, D’Amato AW et al (2016) Predicting tree biomass growth in the temperate–boreal ecotone: is tree size, age, competition, or climate response most important? Glob Change Biol 2138–2151Google Scholar
- Friedlingstein P, Cox P, Betts R et al (2006) Climate-carbon cycle feedback analysis: results from the C4MIP model intercomparison. J Geophys Res Biogeosci 19:3337–3353Google 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 RL (1983) Computer-assisted quality control in tree-ring dating and measurement. Tree Ring Bull 43:69–78Google Scholar
- Kaye JP, Hart SC, Fulé PZ et al (2005) Initial carbon, nitrogen, and phosphorus fluxes following ponderosa pine restoration treatments. Ecol Lett 15:1581–1593Google Scholar
- Lu M, Zhou X, Yang Q et al (2012) Responses of ecosystem carbon cycle to experimental warming: a meta-analysis. Ecology 94(3):726–738Google Scholar
- PRISM Climate Group (2004) Oregon State University. http://prism.oregonstate.edu
- Rollinson CR, Kaye MW, Canham CD (2016) Interspecific variation in growth responses to climate and competition of five eastern tree species. Ecology 97:1003–1011Google Scholar
- Speer JH (2010) Fundamentals of tree-ring research. U. of Arizona Press, Tucson.Google Scholar
- Stokes MA, Smiley TL (1968) An introduction to tree-ring dating. University of Chicago Press, ChicagoGoogle Scholar
- Swetnam TW, Lynch AM (1989) A tree-ring reconstruction of western spruce budworm history in the southern Rocky Mountains. Forest Sci 35:962–986Google Scholar
- Touchan R, Allen CD, Swetnam TW (1996) Fire history and climatic patterns in ponderosa pine and mixed-conifer forests of the Jemez Mountains, northern New Mexico. U.S. Forest Service General Technical Report RM-GTR-286, pp 33–46Google Scholar
- Williams AP, Allen CD, Macalady AK et al (2013) Temperature as a potent driver of regional forest drought stress and tree mortality. Nat Clim Change 3(3):292–297Google Scholar
- (2012) Temperature as a potent driver of regional forest drought stress and tree mortality. 2:1–6Google Scholar