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Warm springs alter timing but not total growth of temperate deciduous trees

Abstract

As the climate changes, warmer spring temperatures are causing earlier leaf-out1,2,3 and commencement of CO2 uptake1,3 in temperate deciduous forests, resulting in a tendency towards increased growing season length3 and annual CO2 uptake1,3,4,5,6,7. However, less is known about how spring temperatures affect tree stem growth8,9, which sequesters carbon in wood that has a long residence time in the ecosystem10,11. Here we show that warmer spring temperatures shifted stem diameter growth of deciduous trees earlier but had no consistent effect on peak growing season length, maximum growth rates, or annual growth, using dendrometer band measurements from 440 trees across two forests. The latter finding was confirmed on the centennial scale by 207 tree-ring chronologies from 108 forests across eastern North America, where annual ring width was far more sensitive to temperatures during the peak growing season than in the spring. These findings imply that any extra CO2 uptake in years with warmer spring temperatures4,5 does not significantly contribute to increased sequestration in long-lived woody stem biomass. Rather, contradicting projections from global carbon cycle models1,12, our empirical results imply that warming spring temperatures are unlikely to increase woody productivity enough to strengthen the long-term CO2 sink of temperate deciduous forests.

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Fig. 1: Summary of temperate deciduous tree growth responses to warmer spring temperatures.
Fig. 2: Responses of foliage phenology and stem growth timing to spring temperatures at SCBI and Harvard Forest.
Fig. 3: Sensitivity of annual growth, as derived from tree rings, to monthly mean Tmax, for 207 chronologies from 108 sites across eastern North America.

Data availability

The datasets generated and analysed during the current study are available via GitHub in the growth_phenology repository of the ForestGEO Ecosystems & Climate Lab at SCBI (https://github.com/EcoClimLab/growth_phenology) and archived in Zenodo (https://doi.org/10.5281/zenodo.6632090). Master versions of the dendrometer band data are available for SCBI via GitHub in the Dendrobands repository of the SCBI ForestGEO plot (https://github.com/SCBI-ForestGEO/Dendrobands), which is archived in Zenodo (https://doi.org/10.5281/zenodo.5551143), and for Harvard Forest via the Harvard Forest Data Archive (https://harvardforest1.fas.harvard.edu/exist/apps/datasets/showData.html?id=HF149). Weather data for SCBI were obtained from the ForestGEO Climate Data Portal v1.0 (https://github.com/forestgeo/Climate/tree/master/Climate_Data/Met_Stations/SCBI), which is archived in Zenodo (https://doi.org/10.5281/zenodo.3958215), and the NCEI weather station located in Front Royal, VA, USA (https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:USC00443229/detail). Weather data for Harvard Forest are available through the Harvard Forest Data Archive (https://harvardforest1.fas.harvard.edu/exist/apps/datasets/showData.html?id=HF001 and https://harvardforest1.fas.harvard.edu/exist/apps/datasets/showData.html?id=HF000). Climate data were obtained from CRU v.4.04 via the ForestGEO Climate Data Portal v1.0 (https://github.com/forestgeo/Climate/tree/master/Climate_Data/CRU), which is archived in Zenodo (https://doi.org/10.5281/zenodo.3958215). The SPEI was obtained from the ForestGEO Climate Data Portal v1.0 (https://github.com/forestgeo/Climate/tree/master/Climate_Data/SPEI), which is archived in Zenodo (https://doi.org/10.5281/zenodo.3958215). Canopy foliage phenology data were extracted from the MCD12Q2 V6 Land Cover Dynamics product (that is, MODIS Global Vegetation Phenology product) via Google Earth Engine (https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MCD12Q2#description). In addition to being archived in the repository for this project, many tree-ring datasets are archived in the International Tree-Ring Data Bank (https://www.ncei.noaa.gov/products/paleoclimatology/tree-ring), the DendroEcological Network (https://www.uvm.edu/femc/dendro/) and/or the Harvard Forest Data Archive (https://harvardforest.fas.harvard.edu/harvard-forest-data-archive), as detailed in Supplementary Table 1. Original tree cores are archived at the institutions of various members of the author team (Harvard Forest, SCBI, Indiana University and University of Idaho) and will be made available on reasonable request.

Code availability

Data were analysed in the open source statistical software R (version 4.0). We used the packages climwin v.1.2.3 (https://cran.r-project.org/web/packages/climwin/index.html), dplR v.1.0.2, bootRes v1.2.4, rstanarm v.2.21.1 and functions from Rdendrom v.0.1.0 (https://github.com/seanmcm/RDendrom/). We used climpact software v.1.2.8 (see www.climpact-sci.org). Mixed-effect models were run within a hierarchical Bayesian framework and fit using the rstanarm version 2.21.3 R interface to the Stan programming language (source code available at https://github.com/EcoClimLab/growth_phenology#steps-to-replicate-the-analysis). Tree-ring chronologies were developed using the program ARSTAN V49_1b (https://www.geog.cam.ac.uk/research/projects/dendrosoftware/). All custom codes are available through the EcoClimlab GitHub repository (https://github.com/EcoClimLab/growth_phenology) and archived in Zenodo (https://doi.org/10.5281/zenodo.6632090).

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Acknowledgements

We acknowledge all researchers who assisted with data collection in the field and laboratory, particularly T. Fung Au, J. Bregy, J. Dickens, K. Heeter, A. Hennage, D. King, J. McGee, B. Lockwood, J. McGarvey, V. Meakem, J. Oliver, J. Shue, K. Schmidt-Simard, B. Strange, A. Terrell, B. Taylor, M. Thornton, S. Robeson, M. Wenzel and L. Wylie; and D. A. Orwig, R. Zweifel and members of the ForestGEO Ecosystems & Climate Lab at SCBI for helpful feedback. Analyses and SCBI data collection were funded by the Smithsonian Institution (ForestGEO—Smithsonian Tropical Research Institute, Smithsonian’s National Zoo & Conservation Biology Institute, and Scholarly Studies, Competitive Grants Program for Science and Grand Challenges Award Program grants to K.J.A.-T.). Collection of tree-ring samples was funded by the USDA Agriculture and Food Research Initiative grant 2017-67013-26191 (to J.T.M.), National Science Foundation grants nos. 1805276 (to G.L.H.) and 1805617 (to J.T.M.), and from the Indiana University Vice Provost for Research Faculty Research Program (to J.T.M.). L.D. received funding from the Natural Sciences and Engineering Research Council of Canada (DG RGPIN-2019-04353) and New Brunswick Innovation Foundation (RIF 2019-029). S.M.M. was partially funded by National Science Foundation RAPID-2030862.

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Contributions

C.D. and K.J.A.-T. conceived the ideas and designed the study. C.D., L.D., E.B.G.-A., R.H., G.L.H., J.T.M., I.R.M., W.J.M., N.P., A.J.T. and K.J.A.-T. collected or oversaw collection of data. C.D., A.Y.K., V.H., J.T.M., I.R.M. and S.M.M. analysed the data or provided analytical tools. C.D. and K.J.A.-T. led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication.

Corresponding author

Correspondence to Kristina J. Anderson-Teixeira.

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Nature thanks Cyrille Rathgeber, Roman Zweifel and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Seasonal patterns of forest canopy greenness (top row) and stem growth of ring- and diffuse-porous trees, represented as both relative and cumulative fractions of total annual growth (middle and bottom rows, respectively), at the Smithsonian Conservation Biology Institute (SCBI) and Harvard Forest.

In the top row, canopy greenness is characterized using the two band Enhanced Vegetation Index (EVI2), with each line representing a year between 2000 and 2018. For stem growth, each line represents the average growth over one year, as modeled based on a five-parameter logistic growth model to dendrometer band data. Dashed lines represent modeled DBH change which fell outside of the median DOY where predicted starting and ending DBHs were reached. Solid lines represent DBH change attributable to stem growth.

Extended Data Fig. 2 Landscapes of relationships between the day of year on which 25% of annual growth is achieved (DOY25) and temperature in prior weeks for ring- and diffuse-porous trees at the Smithsonian Conservation Biology Institute (SCBI) and Harvard Forest.

Shown are matrices of \(\beta \) coefficients from first-order linear regressions between mean maximum temperature (Tmax) and DOY25. Window Open and Window Close indicate number of weeks prior to DOY25 (listed in Extended Data Table 2). Yellow shading indicates neutral relationships, while orange or red shading indicates that DOY25 advances with increased Tmax over the given time window (negative \(\beta \)). Black circles indicate the critical temperature window selected based on minimization of ∆AICc, the difference in Akaike Information Criterion corrected for small sample size relative to a null model. Critical temperature windows are listed in Extended Data Table 2.

Extended Data Fig. 3 Response of stem growth timing and rates to mean maximum temperatures (Tmax) during the spring critial temperature window (CTW) for ring- and diffuse-porous species at the Smithsonian Conservation Biology Institute (SCBI) and Harvard Forest.

CTW was defined as the period over which Tmax was most strongly correlated with the day of year on which 25% of annual growth was achieved (DOY25; Extended Data Table 2, Extended Data Fig. 2). Shown are relationships between mean Tmax over the CTW and days of the year on which 25%, 50%, and 75% total stem growth were achieved (DOY25, DOY50, DOY75, respectively; first row); the length of the peak growing season (Lpgs; second row); maximum growth rate (gmax; third row); and total seasonal radial stem growth (∆DBH; fourth row). Posterior predictions of each variable that did not include zero are represented with solid lines, while those that do include zero use dotted lines. The 95% credible intervals are represented by bands centered on the posterior mean for each year. For both species groups at both sites, DOY25, DOY50, and DOY75 all declined significantly with mean Tmax during their respective CTW. Dots represent growth parameter values for individual tree-year combinations, which were derived by fitting a five-parameter logistic growth model to dendrometer band data.

Extended Data Fig. 4 Response of stem growth timing and rates to mean maximum temperatures (Tmax) for the month most closely corresponding to the spring critial temperature window (CTW) for ring- and diffuse-porous species at the Smithsonian Conservation Biology Institute (SCBI) and Harvard Forest.

CTW was defined as the period over which Tmax was most strongly correlated with the day of year on which 25% of annual growth was achieved (DOY25; Extended Data Table 2, Extended Data Fig. 2), and the most closely corresponding month was determined as that with the greatest number of days within the CTW. Shown are relationships between monthly Tmax and days of the year on which 25%, 50%, and 75% total stem growth were achieved (DOY25, DOY50, DOY75, respectively; first row); the length of the peak growing season (Lpgs; second row); maximum growth rate (gmax; third row); and total seasonal radial stem growth (∆DBH; fourth row). Posterior predictions of each variable that did not include zero are represented with solid lines, while those that do include zero use dotted lines. The 95% credible intervals are represented by bands centered on the posterior mean for each year. For both species groups at both sites, DOY25, DOY50, and DOY75 declined significantly with April Tmax, with the exception of DOY25 for ring-porous species at SCBI. Dots represent growth parameter values for individual tree-year combinations, which were derived by fitting a five-parameter logistic growth model to dendrometer band data.

Extended Data Fig. 5 Map of sampling locations of tree-ring chronologies analyzed in this study.

Sites are colored by the xylem porosity type of species sampled: ring poroous (RP), diffuse porous (DP), or both. Sampling details are provided in Supplementary Table 1. Base map source is ggplot2.

Extended Data Fig. 6 Sensitivity of annual growth, as derived from tree-rings, to monthly mean minimum temperatures (Tmin), for 207 chronologies from 108 sites across eastern North America (Extended Data Fig. 5).

Colors indicate the bootstrapped correlation between monthly Tmin and a dimensionless ring width index (RWI) derived from the multiple trees that form each chronology and emphasizing interannual variability associated with climate. Chronologies are grouped by xylem porosity and ordered by mean April Tmin. Plots are annotated to highlight records from our two focal sites, the Smithsonian Conservation Biology Institute (SCBI) and Harvard Forest (HF) (Extended Data Table 1). Species analyzed and numbers of significant correlations to Tmin are summarized in Extended Data Table 3, and chronology details are given in Supplementary Table 1.

Extended Data Fig. 7 Sensitivity of annual growth, as derived from tree-rings, to monthly mean maximum temperatures (Tmax) of the current and past year, for 207 chronologies from 108 sites across eastern North America (Extended Data Fig. 5).

Colors indicate the bootstrapped correlation between monthly Tmax and a dimensionless ring width index (RWI) derived from the multiple trees that form each chronology and emphasizing interannual variability associated with climate. Chronologies are grouped by xylem porosity and ordered by mean April Tmax. Plots are annotated to highlight records from our two focal sites, the Smithsonian Conservation Biology Institute (SCBI) and Harvard Forest (HF) (Extended Data Table 1). Figure presents the same results as Fig. 3 but extends back to include the previous year. Species analyzed and numbers of significant correlations to Tmax are summarized in Extended Data Table 3, and chronology details are given in Supplementary Table 1.

Extended Data Table 1 Dominant broadleaf deciduous species at the Smithsonian Conservation Biology Institute (SCBI) and Harvard Forest, along with sample sizes included in our final analysis
Extended Data Table 2 Summary of parameters describing the seasonality and temperature sensitivity of broadleaf deciduous tree woody growth and canopy phenology at the Smithsonian Conservation Biology Institute (SCBI) and Harvard Forest
Extended Data Table 3 Summary of tree-ring chronologies analyzed and number of significant (at significance level = 0.05) positive or negative correlations of ring width index to monthly Tmax in univariate and multivariate analyses

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Supplementary Table 1

Descriptions of the location, species, ring porosity, average minimum and maximum April temperatures, results from analyses, and details on where to find the tree core chronologies used in the analysis.

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Dow, C., Kim, A.Y., D’Orangeville, L. et al. Warm springs alter timing but not total growth of temperate deciduous trees. Nature 608, 552–557 (2022). https://doi.org/10.1038/s41586-022-05092-3

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