Legacy effects in radial tree growth are rarely significant after accounting for biological memory

auto-correlation; biological memory; lag effect; recovery; resilience; superposed epoch analysis; synthetic data; tree rings; Ecology, Evolution, Behavior and Systematics; Ecology; Plant Science

Abstract :

[en] Drought legacies in radial tree growth are an important feature of variability in biomass accumulation and are widely used to characterize forest resilience to climate change. Defined as a deviation from normal growth, the statistical significance of legacy effects depends on the definition of “normal”—expected growth under average conditions—which has not received sufficient scrutiny. We re-examined legacy effect analyses using the International Tree-Ring Data Bank (ITRDB) and then produced synthetic tree-ring data to disentangle four key variables influencing the magnitude of legacy effects. We hypothesized that legacy effects (i) are mainly influenced by the auto-correlation of the radial growth time series (phi), (ii) depend on climate-growth cross-correlation (rho), (iii) are directly proportional to the inherent variability of the growth time series (standard deviation, SD), and (iv) scale with the chosen extreme event threshold. Using a data simulation approach, we were able to reproduce observed lag patterns, demonstrating that legacy effects are a direct outcome of ubiquitous biological memory. We found that stronger legacy effects for conifers compared to angiosperms is a consequence of their higher auto-correlation, and that the detectability of legacy effects following rare drought events at individual sites is compromised by strong background stochasticity. Synthesis. We propose two pathways forward to improve the assessment and interpretation of legacy effects: First, we highlight the need to account for auto-correlated residuals of climate-growth regression models a posteriori, thereby retrospectively adjusting expectations for “normal” growth variability. Alternatively, we recommend including lagged climate variables in regression models a priori. By doing so, the magnitude of detected legacy effects is greatly reduced and biological memory is directly attributed to antecedent climatic drivers. We argue that future analyses should focus on understanding the functional reasons for how and why key statistical parameters describing this biological memory differ across species and sites. These two pathways should also stimulate improved process-based representation of vegetation carbon dynamics in mechanistic models.

Disciplines :

Environmental sciences & ecology

Author, co-author :

Klesse, Stefan ; Forest Dynamics, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmendorf, Switzerland

Babst, Flurin ; Laboratory of Tree Ring Research, University of Arizona, Tucson, United States ; School of Natural Resources and the Environment, University of Arizona, Tucson, United States

Evans, Margaret E. K. ; Laboratory of Tree Ring Research, University of Arizona, Tucson, United States

Hurley, Alexander ; Climate Dynamics and Landscape Evolution, GFZ German Research Centre for Geosciences, Potsdam, Germany

Pappas, Christoforos ; Department of Civil Engineering, University of Patras, Rio Patras, Greece

Peters, Richard ; Université de Liège - ULiège > TERRA Research Centre > Gestion durable des bio-agresseurs ; Forest Dynamics, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmendorf, Switzerland ; Department of Environmental Sciences, University of Basel, Basel, Switzerland

Language :

English

Title :

Legacy effects in radial tree growth are rarely significant after accounting for biological memory

Publication date :

2022

Journal title :

Journal of Ecology

ISSN :

0022-0477

eISSN :

1365-2745

Publisher :

John Wiley and Sons Inc

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2745.14045

Funders :

SNF - Schweizerische Nationalfonds zur Förderung der wissenschaftlichen Forschung [CH]
BAFU - Bundesamt für Umwelt [CH]

Funding text :

Stefan Klesse was supported by the SwissForestLab (Research Grants SFL‐17 P3 and SFL‐20 P5), and by the Federal Office for the Environment FOEN. Richard L. Peters acknowledges the support of the Swiss National Science Foundation (SNSF), Grant P2BSP3_184475.

Available on ORBi :

since 25 December 2022

Statistics

Number of views

25 (0 by ULiège)

Number of downloads

0 (0 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

Bibliography

Alfaro-Sánchez, R., Nguyen, H., Klesse, S., Hudson, A., Belmecheri, S., Köse, N., Diaz, H. F., Monson, R. K., Villalba, R., & Trouet, V. (2018). Climatic and volcanic forcing of tropical belt northern boundary over the past 800 years. Nature Geoscience, 11(12), 933–938. https://doi.org/10.1038/s41561-018-0242-1
Altman, J., Fibich, P., Dolezal, J., & Aakala, T. (2014). TRADER: A package for tree ring analysis of disturbance events in R. Dendrochronologia, 32(2), 107–112. https://doi.org/10.1016/j.dendro.2014.01.004
Anderegg, W. R. L., Schwalm, C., Biondi, F., Camarero, J. J., Koch, G., Litvak, M., Ogle, K., Shaw, J. D., Shevliakova, E., Williams, A. P., Wolf, A., Ziaco, E., & Pacala, S. (2015). Pervasive drought legacies in forest ecosystems and their implications for carbon cycle models. Science, 349(6247), 528–532. https://doi.org/10.1126/science.aab1833
Arend, M., Link, R. M., Zahnd, C., Hoch, G., Schuldt, B., & Kahmen, A. (2022). Lack of hydraulic recovery as a cause of post-drought foliage reduction and canopy decline in European beech. New Phytologist, 234(4), 1195–1205. https://doi.org/10.1111/nph.18065
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., … Ziehn, T. (2020). Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models. Biogeosciences, 17(16), 4173–4222. https://doi.org/10.5194/bg-17-4173-2020
Babst, F., Bouriaud, O., Poulter, B., Trouet, V., Girardin, M. P., & Frank, D. C. (2019). Twentieth century redistribution in climatic drivers of global tree growth. Science Advances, 5(1), eaat4313. https://doi.org/10.1126/sciadv.aat4313
Babst, F., Friend, A. D., Karamihalaki, M., Wei, J., von Arx, G., Papale, D., & Peters, R. L. (2021). Modeling ambitions outpace observations of forest carbon allocation. Trends in Plant Science, 26(3), 210–219. https://doi.org/10.1016/j.tplants.2020.10.002
Bachofen, C., Perret-Gentil, A., Wohlgemuth, T., Vollenweider, P., & Moser, B. (2021). Phenotypic plasticity versus ecotypic differentiation under recurrent summer drought in two drought-tolerant pine species. Journal of Ecology, 109(11), 3861–3876. https://doi.org/10.1111/1365-2745.13762
Baisan, C. H., & Swetnam, T. W. (1990). Fire history on a desert mountain range: Rincon Mountain Wilderness, Arizona, U.S.A. Canadian Journal of Forest Research, 20(10), 1559–1569. https://doi.org/10.1139/x90-208
Barichivich, J., Peylin, P., Launois, T., Daux, V., Risi, C., Jeong, J., & Luyssaert, S. (2021). A triple tree-ring constraint for tree growth and physiology in a global land surface model. Biogeosciences, 18(12), 3781–3803. https://doi.org/10.5194/bg-18-3781-2021
Bartoń, K. (2018). MuMIn: Multi-model inference. R package version 1.42.1. https://CRAN.R-project.org/package=MuMIn
Beguería, S., Vicente-Serrano, S. M., Reig, F., & Latorre, B. (2014). Standardized precipitation evapotranspiration index (SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. International Journal of Climatology, 34(10), 3001–3023. https://doi.org/10.1002/joc.3887
Beisner, B., Haydon, D., & Cuddington, K. (2003). Alternative stable states in ecology. Frontiers in Ecology and the Environment, 1(7), 376–382. https://doi.org/10.1890/1540-9295(2003)001[0376:ASSIE]2.0.CO;2
Brunner, I., Herzog, C., Dawes, M. A., Arend, M., & Sperisen, C. (2015). How tree roots respond to drought. Frontiers in Plant Science, 6, 547. https://doi.org/10.3389/fpls.2015.00547
Bunn, A., Korpela, M., Biondi, F., Campelo, F., Mérian, P., Qeadan, F., & Zang, C. (2019). DplR: Dendrochronology program library in R. R package version 1.7.0. https://CRAN.R-project.org/package=dplR
Cailleret, M., Dakos, V., Jansen, S., Robert, E. M. R., Aakala, T., Amoroso, M. M., Antos, J. A., Bigler, C., Bugmann, H., Caccianaga, M., Camarero, J.-J., Cherubini, P., Coyea, M. R., Čufar, K., Das, A. J., Davi, H., Gea-Izquierdo, G., Gillner, S., Haavik, L. J., … Martínez-Vilalta, J. (2019). Early-warning signals of individual tree mortality based on annual radial growth. Frontiers in Plant Science, 9, 1964. https://doi.org/10.3389/fpls.2018.01964
Castagneri, D., Vacchiano, G., Hacket-Pain, A., DeRose, R. J., Klein, T., & Bottero, A. (2022). Meta-analysis reveals different competition effects on tree growth resistance and resilience to drought. Ecosystems, 25(1), 30–43. https://doi.org/10.1007/s10021-021-00638-4
Cook, B. I., Smerdon, J. E., Seager, R., & Coats, S. (2014). Global warming and 21st century drying. Climate Dynamics, 43(9), 2607–2627. https://doi.org/10.1007/s00382-014-2075-y
Coussement, J. R., De Swaef, T., Lootens, P., Roldán-Ruiz, I., & Steppe, K. (2018). Introducing turgor-driven growth dynamics into functional–structural plant models. Annals of Botany, 121(5), 849–861. https://doi.org/10.1093/aob/mcx144
De Kauwe, M. G., Medlyn, B. E., Zaehle, S., Walker, A. P., Dietze, M. C., Wang, Y.-P., Luo, Y., Jain, A. K., El-Masri, B., Hickler, T., Wårlind, D., Weng, E., Parton, W. J., Thornton, P. E., Wang, S., Prentice, I. C., Asao, S., Smith, B., McCarthy, H. R., … Norby, R. J. (2014). Where does the carbon go? A model–data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free-air CO2 enrichment sites. The New Phytologist, 203(3), 883–899. https://doi.org/10.1111/nph.12847
Esper, J., Schneider, L., Krusic, P. J., Luterbacher, J., Büntgen, U., Timonen, M., Sirocko, F., & Zorita, E. (2013). European summer temperature response to annually dated volcanic eruptions over the past nine centuries. Bulletin of Volcanology, 75(7), 736. https://doi.org/10.1007/s00445-013-0736-z
Fatichi, S., Pappas, C., Zscheischler, J., & Leuzinger, S. (2019). Modelling carbon sources and sinks in terrestrial vegetation. New Phytologist, 221(2), 652–668. https://doi.org/10.1111/nph.15451
Flower, A., Gavin, D. G., Heyerdahl, E. K., Parsons, R. A., & Cohn, G. M. (2014). Drought-triggered western spruce budworm outbreaks in the interior Pacific Northwest: A multi-century dendrochronological record. Forest Ecology and Management, 324, 16–27. https://doi.org/10.1016/j.foreco.2014.03.042
Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Hauck, J., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Le Quéré, C., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S., Aragão, L. E. O. C., Arneth, A., Arora, V., Bates, N. R., … Zaehle, S. (2020). Global carbon budget 2020. Earth System Science Data, 12(4), 3269–3340. https://doi.org/10.5194/essd-12-3269-2020
Friend, A. D., Lucht, W., Rademacher, T. T., Keribin, R., Betts, R., Cadule, P., Ciais, P., Clark, D. B., Dankers, R., Falloon, P. D., Ito, A., Kahana, R., Kleidon, A., Lomas, M. R., Nishina, K., Ostberg, S., Pavlick, R., Peylin, P., Schaphoff, S., … Woodward, F. I. (2014). Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2. Proceedings of the National Academy of Sciences of the United States of America, 111(9), 3280–3285. https://doi.org/10.1073/pnas.1222477110
Fritts, H. C. (1976). Tree rings and climate. Academic Press.
Fritts, H. C., Smith, D. G., Cardis, J. W., & Budelsky, C. A. (1965). Tree-ring characteristics along a vegetation gradient in northern Arizona. Ecology, 46(4), 393–401. https://doi.org/10.2307/1934872
Gao, S., Liu, R., Zhou, T., Fang, W., Yi, C., Lu, R., Zhao, X., & Luo, H. (2018). Dynamic responses of tree-ring growth to multiple dimensions of drought. Global Change Biology, 24(11), 5380–5390. https://doi.org/10.1111/gcb.14367
Gazol, A., Camarero, J. J., Sánchez-Salguero, R., Vicente-Serrano, S. M., Serra-Maluquer, X., Gutiérrez, E., de Luis, M., Sangüesa-Barreda, G., Novak, K., Rozas, V., Tíscar, P. A., Linares, J. C., del Castillo, E. M., Ribas, M., García-González, I., Silla, F., Camisón, Á., Génova, M., Olano, J. M., … Galván, J. D. (2020). Drought legacies are short, prevail in dry conifer forests and depend on growth variability. Journal of Ecology, 108(6), 2473–2484. https://doi.org/10.1111/1365-2745.13435
Hacket-Pain, A. J., Ascoli, D., Vacchiano, G., Biondi, F., Cavin, L., Conedera, M., Drobyshev, I., Liñán, I. D., Friend, A. D., Grabner, M., Hartl, C., Kreyling, J., Lebourgeois, F., Levanič, T., Menzel, A., van der Maaten, E., van der Maaten-Theunissen, M., Muffler, L., Motta, R., … Zang, C. S. (2018). Climatically controlled reproduction drives interannual growth variability in a temperate tree species. Ecology Letters, 21(12), 1833–1844. https://doi.org/10.1111/ele.13158
Harr, L., Esper, J., Kirchhefer, J. A., Zhou, W., & Hartl, C. (2021). Growth response of Betula pubescens Ehrh. To varying disturbance factors in northern Norway. Trees, 35(2), 421–431. https://doi.org/10.1007/s00468-020-02043-1
Hartl, C., St. George, S., Konter, O., Harr, L., Scholz, D., Kirchhefer, A., & Esper, J. (2019). Warfare dendrochronology: Trees witness the deployment of the German battleship Tirpitz in Norway. Anthropocene, 27, 100212. https://doi.org/10.1016/j.ancene.2019.100212
Haurwitz, M. W., & Brier, G. W. (1981). A critique of the superposed epoch analysis method: Its application to solar–weather relations. Monthly Weather Review, 109(10), 2074–2079. https://doi.org/10.1175/1520-0493(1981)109<2074:ACOTSE>2.0.CO;2
Hoch, G., Richter, A., & Körner, C. (2003). Non-structural carbon compounds in temperate forest trees. Plant, Cell & Environment, 26(7), 1067–1081. https://doi.org/10.1046/j.0016-8025.2003.01032.x
Huang, J., Hammerbacher, A., Gershenzon, J., van Dam, N. M., Sala, A., McDowell, N. G., Chowdhury, S., Gleixner, G., Trumbore, S., & Hartmann, H. (2021). Storage of carbon reserves in spruce trees is prioritized over growth in the face of carbon limitation. Proceedings of the National Academy of Sciences of the United States of America, 118(33), e2023297118. https://doi.org/10.1073/pnas.2023297118
Huang, M., Wang, X., Keenan, T. F., & Piao, S. (2018). Drought timing influences the legacy of tree growth recovery. Global Change Biology, 24(8), 3546–3559. https://doi.org/10.1111/gcb.14294
Huntzinger, D. N., Michalak, A. M., Schwalm, C., Ciais, P., King, A. W., Fang, Y., Schaefer, K., Wei, Y., Cook, R. B., Fisher, J. B., Hayes, D., Huang, M., Ito, A., Jain, A. K., Lei, H., Lu, C., Maignan, F., Mao, J., Parazoo, N., … Zhao, F. (2017). Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-03818-2
IPCC (2021). In V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, & B. Zhou (Eds.), Climate change 2021: The physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.
Jiang, P., Liu, H., Piao, S., Ciais, P., Wu, X., Yin, Y., & Wang, H. (2019). Enhanced growth after extreme wetness compensates for post-drought carbon loss in dry forests. Nature Communications, 10(1), 195. https://doi.org/10.1038/s41467-018-08229-z
Kannenberg, S. A., Maxwell, J. T., Pederson, N., D'Orangeville, L., Ficklin, D. L., & Phillips, R. P. (2019). Drought legacies are dependent on water table depth, wood anatomy and drought timing across the eastern US. Ecology Letters, 22(1), 119–127. https://doi.org/10.1111/ele.13173
Kannenberg, S. A., Novick, K. A., Alexander, M. R., Maxwell, J. T., Moore, D. J. P., Phillips, R. P., & Anderegg, W. R. L. (2019). Linking drought legacy effects across scales: From leaves to tree rings to ecosystems. Global Change Biology, 25(9), 2978–2992. https://doi.org/10.1111/gcb.14710
Kannenberg, S. A., Schwalm, C. R., & Anderegg, W. R. L. (2020). Ghosts of the past: How drought legacy effects shape forest functioning and carbon cycling. Ecology Letters, 23(5), 891–901. https://doi.org/10.1111/ele.13485
Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., Zimmermann, N. E., Linder, H. P., & Kessler, M. (2017). Climatologies at high resolution for the earth's land surface areas. Scientific Data, 4(1), 170122. https://doi.org/10.1038/sdata.2017.122
Karger, D. N., & Zimmermann, N. E. (2018). CHELSAcruts—High resolution temperature and precipitation timeseries for the 20th century and beyond. EnviDat. https://doi.org/10.16904/envidat.159
Klesse, S., Babst, F., Lienert, S., Spahni, R., Joos, F., Bouriaud, O., Carrer, M., Filippo, A. D., Poulter, B., Trotsiuk, V., Wilson, R., & Frank, D. C. (2018). A combined tree ring and vegetation model assessment of European forest growth sensitivity to interannual climate variability. Global Biogeochemical Cycles, 32(8), 1226–1240. https://doi.org/10.1029/2017GB005856
Klesse, S., DeRose, R. J., Babst, F., Black, B. A., Anderegg, L. D. L., Axelson, J., Ettinger, A., Griesbauer, H., Guiterman, C. H., Harley, G., Harvey, J. E., Lo, Y.-H., Lynch, A. M., O'Connor, C., Restaino, C., Sauchyn, D., Shaw, J. D., Smith, D. J., Wood, L., … Evans, M. E. K. (2020). Continental-scale tree-ring-based projection of Douglas-fir growth: Testing the limits of space-for-time substitution. Global Change Biology, 26(9), 5146–5163. https://doi.org/10.1111/gcb.15170
Klesse, S., von Arx, G., Gossner, M. M., Hug, C., Rigling, A., & Queloz, V. (2021). Amplifying feedback loop between growth and wood anatomical characteristics of Fraxinus excelsior explains size-related susceptibility to ash dieback. Tree Physiology, 41(5), 683–696. https://doi.org/10.1093/treephys/tpaa091
Klesse, S., Babst, F., Evans, M. E. K., Hurley, A., Pappas, C., & Peters, R. L. (2022). Data from: Legacy effects in radial tree growth are rarely significant after accounting for biological memory. Figshare. https://doi.org/10.6084/m9.figshare.21493563.v1
Kolus, H. R., Huntzinger, D. N., Schwalm, C. R., Fisher, J. B., McKay, N., Fang, Y., Michalak, A. M., Schaefer, K., Wei, Y., Poulter, B., Mao, J., Parazoo, N. C., & Shi, X. (2019). Land carbon models underestimate the severity and duration of drought's impact on plant productivity. Scientific Reports, 9(1), 2758. https://doi.org/10.1038/s41598-019-39373-1
Körner, C. (2003). Limitation and stress – Always or never? Journal of Vegetation Science, 14(2), 141–143.
Lian, X., Piao, S., Chen, A., Wang, K., Li, X., Buermann, W., Huntingford, C., Peñuelas, J., Xu, H., & Myneni, R. B. (2021). Seasonal biological carryover dominates northern vegetation growth. Nature Communications, 12(1), 983. https://doi.org/10.1038/s41467-021-21223-2
Lloret, F., Keeling, E. G., & Sala, A. (2011). Components of tree resilience: Effects of successive low-growth episodes in old ponderosa pine forests. Oikos, 120(12), 1909–1920. https://doi.org/10.1111/j.1600-0706.2011.19372.x
Lough, J. M., & Fritts, H. C. (1987). An assessment of the possible effects of volcanic eruptions on north American climate using tree-ring data, 1602 to 1900 A.D. Climatic Change, 10(3), 219–239. https://doi.org/10.1007/BF00143903
Malevich, S. B., Guiterman, C. H., & Margolis, E. Q. (2018). Burnr: Fire history analysis and graphics in R. Dendrochronologia, 49, 9–15. https://doi.org/10.1016/j.dendro.2018.02.005
Marqués, L., Peltier, D. M. P., Camarero, J. J., Zavala, M. A., Madrigal-González, J., Sangüesa-Barreda, G., & Ogle, K. (2022). Disentangling the legacies of climate and management on tree growth. Ecosystems, 25(1), 215–235. https://doi.org/10.1007/s10021-021-00650-8
Martínez-Vilalta, J., Sala, A., Asensio, D., Galiano, L., Hoch, G., Palacio, S., Piper, F. I., & Lloret, F. (2016). Dynamics of non-structural carbohydrates in terrestrial plants: A global synthesis. Ecological Monographs, 86(4), 495–516. https://doi.org/10.1002/ecm.1231
Matalas, N. C. (1962). Statistical properties of tree ring data. International Association of Scientific Hydrology. Bulletin, 7(2), 39–47. https://doi.org/10.1080/02626666209493254
Meyer, K. (2016). A mathematical review of resilience in ecology. Natural Resource Modeling, 29(3), 339–352. https://doi.org/10.1111/nrm.12097
Nothdurft, A., & Engel, M. (2020). Climate sensitivity and resistance under pure- and mixed-stand scenarios in Lower Austria evaluated with distributed lag models and penalized regression splines for tree-ring time series. European Journal of Forest Research, 139(2), 189–211. https://doi.org/10.1007/s10342-019-01234-x
Ogle, K., Barber, J. J., Barron-Gafford, G. A., Bentley, L. P., Young, J. M., Huxman, T. E., Loik, M. E., & Tissue, D. T. (2015). Quantifying ecological memory in plant and ecosystem processes. Ecology Letters, 18(3), 221–235. https://doi.org/10.1111/ele.12399
Pappas, C., Fatichi, S., Leuzinger, S., Wolf, A., & Burlando, P. (2013). Sensitivity analysis of a process-based ecosystem model: Pinpointing parameterization and structural issues. Journal of Geophysical Research: Biogeosciences, 118(2), 505–528. Portico. https://doi.org/10.1002/jgrg.20035
Pappas, C., Frank, D. C., Koutsoyiannis, D., Babst, F., & Mahecha, M. D. (2017). Ecosystem functioning is enveloped by hydrometeorological variability. Nature Ecology & Evolution, 1(9), 1263–1270. https://doi.org/10.1038/s41559-017-0277-5
Pappas, C., Peters, R. L., & Fonti, P. (2020). Linking variability of tree water use and growth with species resilience to environmental changes. Ecography, 43(9), 1386–1399. https://doi.org/10.1111/ecog.04968
Pastore, M. (2018). Overlapping: A R package for estimating overlapping in empirical distributions. The Journal of Open Source Software, 3(32), 1023.
Peltier, D. M. P., Barber, J. J., & Ogle, K. (2018). Quantifying antecedent climatic drivers of tree growth in the Southwestern US. Journal of Ecology, 106(2), 613–624. https://doi.org/10.1111/1365-2745.12878
Peltier, D. M. P., & Ogle, K. (2019a). Legacies of La Niña: North American monsoon can rescue trees from winter drought. Global Change Biology, 25(1), 121–133. https://doi.org/10.1111/gcb.14487
Peltier, D. M. P., & Ogle, K. (2019b). Legacies of more frequent drought in ponderosa pine across the western United States. Global Change Biology, 25(11), 3803–3816. https://doi.org/10.1111/gcb.14720
Peltier, D. M. P., & Ogle, K. (2020). Tree growth sensitivity to climate is temporally variable. Ecology Letters, 23(11), 1561–1572. https://doi.org/10.1111/ele.13575
Peters, R. L., Groenendijk, P., Vlam, M., & Zuidema, P. A. (2015). Detecting long-term growth trends using tree rings: A critical evaluation of methods. Global Change Biology, 21(5), 2040–2054. https://doi.org/10.1111/gcb.12826
Peters, R. L., Klesse, S., Fonti, P., & Frank, D. C. (2017). Contribution of climate vs. larch budmoth outbreaks in regulating biomass accumulation in high-elevation forests. Forest Ecology and Management, 401, 147–158. https://doi.org/10.1016/j.foreco.2017.06.032
Peters, R. L., Miranda, J. C., Schönbeck, L., Nievergelt, D., Fonti, M. V., Saurer, M., Stritih, A., Fonti, P., Wermelinger, B., von Arx, G., & Lehmann, M. M. (2020). Tree physiological monitoring of the 2018 larch budmoth outbreak: Preference for leaf recovery and carbon storage over stem wood formation in Larix decidua. Tree Physiology, 40(12), 1697–1711. https://doi.org/10.1093/treephys/tpaa087
R Core Team. (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
Rao, M. P., Cook, E. R., Cook, B. I., Anchukaitis, K. J., D'Arrigo, R. D., Krusic, P. J., & LeGrande, A. N. (2019). A double bootstrap approach to superposed epoch analysis to evaluate response uncertainty. Dendrochronologia, 55, 119–124. https://doi.org/10.1016/j.dendro.2019.05.001
Reichstein, M., Bahn, M., Ciais, P., Frank, D., Mahecha, M. D., Seneviratne, S. I., Zscheischler, J., Beer, C., Buchmann, N., Frank, D. C., Papale, D., Rammig, A., Smith, P., Thonicke, K., van der Velde, M., Vicca, S., Walz, A., & Wattenbach, M. (2013). Climate extremes and the carbon cycle. Nature, 500(7462), 287–295. https://doi.org/10.1038/nature12350
Rollinson, C. R., Liu, Y., Raiho, A., Moore, D. J. P., McLachlan, J., Bishop, D. A., Dye, A., Matthes, J. H., Hessl, A., Hickler, T., Pederson, N., Poulter, B., Quaife, T., Schaefer, K., Steinkamp, J., & Dietze, M. C. (2017). Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America. Global Change Biology, 23(7), 2755–2767. https://doi.org/10.1111/gcb.13626
Schurgers, G., Ahlström, A., Arneth, A., Pugh, T. A. M., & Smith, B. (2018). Climate sensitivity controls uncertainty in future terrestrial carbon sink. Geophysical Research Letters, 45(9), 4329–4336. Portico. https://doi.org/10.1029/2018gl077528
Schwalm, C. R., Anderegg, W. R. L., Michalak, A. M., Fisher, J. B., Biondi, F., Koch, G., Litvak, M., Ogle, K., Shaw, J. D., Wolf, A., Huntzinger, D. N., Schaefer, K., Cook, R., Wei, Y., Fang, Y., Hayes, D., Huang, M., Jain, A., & Tian, H. (2017). Global patterns of drought recovery. Nature, 548(7666), Article 7666. https://doi.org/10.1038/nature23021
Schwarz, J., Skiadaresis, G., Kohler, M., Kunz, J., Schnabel, F., Vitali, V., & Bauhus, J. (2020). Quantifying growth responses of trees to drought—A critique of commonly used resilience indices and recommendations for future studies. Current Forestry Reports, 6(3), 185–200. https://doi.org/10.1007/s40725-020-00119-2
Song, Y., Sterck, F., Zhou, X., Liu, Q., Kruijt, B., & Poorter, L. (2022). Drought resilience of conifer species is driven by leaf lifespan but not by hydraulic traits. New Phytologist, 235(3), 978–992. https://doi.org/10.1111/nph.18177
Sullivan, G. M., & Feinn, R. (2012). Using effect size—Or why the P value is not enough. Journal of Graduate Medical Education, 4(3), 279–282. https://doi.org/10.4300/JGME-D-12-00156.1
Vavrek, M. J. (2011). Fossil: Palaeoecological and palaeogeographical analysis tools. Palaeontologia Electronica, 14(1), 1T.
Vicente-Serrano, S. M., Camarero, J. J., & Azorin-Molina, C. (2014). Diverse responses of forest growth to drought time-scales in the Northern Hemisphere. Global Ecology and Biogeography, 23(9), 1019–1030. https://doi.org/10.1111/geb.12183
von Arx, G., Arzac, A., Fonti, P., Frank, D., Zweifel, R., Rigling, A., Galiano, L., Gessler, A., & Olano, J. M. (2017). Responses of sapwood ray parenchyma and non-structural carbohydrates of Pinus sylvestris to drought and long-term irrigation. Functional Ecology, 31(7), 1371–1382. https://doi.org/10.1111/1365-2435.12860
Walthert, L., Ganthaler, A., Mayr, S., Saurer, M., Waldner, P., Walser, M., Zweifel, R., & von Arx, G. (2020). From the comfort zone to crown dieback: Sequence of physiological stress thresholds in mature European beech trees across progressive drought. Science of the Total Environment, 753, 141792. https://doi.org/10.1016/j.scitotenv.2020.141792
Wu, X., Liu, H., Li, X., Ciais, P., Babst, F., Guo, W., Zhang, C., Magliulo, V., Pavelka, M., Liu, S., Huang, Y., Wang, P., Shi, C., & Ma, Y. (2018). Differentiating drought legacy effects on vegetation growth over the temperate Northern Hemisphere. Global Change Biology, 24(1), 504–516. https://doi.org/10.1111/gcb.13920
Yang, Z., & Midmore, D. J. (2005). Modelling plant resource allocation and growth partitioning in response to environmental heterogeneity. Ecological Modelling, 181(1), 59–77. https://doi.org/10.1016/j.ecolmodel.2004.06.023
Zhang, X., Xing, Y., Yan, G., Han, S., & Wang, Q. (2019). Effects of precipitation change on fine root morphology and dynamics at a global scale: A meta-analysis. Canadian Journal of Soil Science, 99(1), 1–11. https://doi.org/10.1139/cjss-2018-0114
Zhang, Z., Babst, F., Bellassen, V., Frank, D., Launois, T., Tan, K., Ciais, P., & Poulter, B. (2018). Converging climate sensitivities of European forests between observed radial tree growth and vegetation models. Ecosystems, 21(3), 410–425. https://doi.org/10.1007/s10021-017-0157-5
Zhao, S., Pederson, N., D'Orangeville, L., HilleRisLambers, J., Boose, E., Penone, C., Bauer, B., Jiang, Y., & Manzanedo, R. D. (2019). The International Tree-Ring Data Bank (ITRDB) revisited: Data availability and global ecological representativity. Journal of Biogeography, 46(2), 355–368. https://doi.org/10.1111/jbi.13488
Zweifel, R., Etzold, S., Sterck, F., Gessler, A., Anfodillo, T., Mencuccini, M., von Arx, G., Lazzarin, M., Haeni, M., Feichtinger, L., Meusburger, K., Knuesel, S., Walthert, L., Salmon, Y., Bose, A. K., Schoenbeck, L., Hug, C., Girardi, N. D., Giuggiola, A., … Rigling, A. (2020). Determinants of legacy effects in pine trees – Implications from an irrigation-stop experiment. New Phytologist, 227(4), 1081–1096. https://doi.org/10.1111/nph.16582
Zweifel, R., & Sterck, F. (2018). A conceptual tree model explaining legacy effects on stem growth. Frontiers in Forests and Global Change, 1(9), 9. https://doi.org/10.3389/ffgc.2018.00009