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Pines grow faster and are more drought resilient in the Southern Hemisphere

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Acknowledgements

We thank H. Barrera, H. A. Beltrán, M. Karlsson, B. D. Martello, R. de la Mata, M. Morales, C. Morse, R. Páez, S. Paulgaard, M. Reto, A. I. Sánchez Villanueva, R. Sinamtwa, R. Sbrancia, N. Tabert, J. Vanden Berg and A. di Virgilio for assistance with field work, sampling processing or both; the Corporación Nacional Forestal, the Alabama Department of Conservation and Natural Resources, and the affiliated Weeks Bay Reserve for logistics, lodging, access to sites and permits for sampling sites in Chile and southwestern Alabama, respectively; W. Underwood, W. Barger and S. Phipps; the Mississippi Department of Marine Resources, Grand Bay National Estuarine Research Reserve; and J. Pitchford for lodging and permission to access and sample sites in southeastern Mississippi; the National Forests of Mississippi and the DeSoto Ranger District for site access and sampling permission at the long-term field sites in southeastern Mississippi; the Centre for Invasion Biology for logistics; and the land managers at MTO and Stellenbosch Municipality for access to plantations (South Africa).

Funding

This research was funded by ANID PIA/BASAL FB 210006 (Chile). Additional funding came from ANID/Fondecyt project grant 1231025 and Millenium Science Initiative Program NCN2024-040 (Chile). A.C.S.M. acknowledges the support of the Natural Sciences and Engineering Research Council of Canada. A.D. thanks the Universidad del Comahue, Research Project PI 04/S025 (Argentina). A.G. was supported by the ‘Ramón y Cajal’ Program of the Spanish MICINN (grant RyC2020-030647-I), CSIC (grant PIE-20223AT003) and the Spanish Science and Innovation Ministry (projects PID2021-123675OB-C43 and TED2021-129770B-C21; Spain). A.L. and M.P. thank the PREFER-Project (decision number 348103) funded by the Research Council of Finland (Finland). A.S. thanks McIntire-Stennis Cooperative Forestry Research Grant MONZ-1206 (College of Forestry and Conservation, University of Montana, USA). C.R.-B. thanks the ANID/Fondecyt post-doctoral project grant 3240649. D.P. and R.B. thank the project Winning Against Wildings from the Ministry of Business, Innovation and Employment Endeavour fund (New Zealand). E.C. thanks the Nelson-Marlborough Institute of Technology, PBRF funding (New Zealand). F.I.P. thanks ANID/Fondecyt project grant 1231026. M.J.G. thanks project VR #2016-03819 (Sweden). R.P.S. received financial support from the FLAIR Fellowship Programme (award number FLR\R1\191609) and the South African National Research Foundation (RA200103497833). S.K.-K. thanks The National Research Foundation (South Africa).

Author information

Authors and Affiliations

  1. Dirección de Investigación, Vicerrectoría Académica, Universidad de Talca, Talca, Chile

    Alex Fajardo & Claudia Reyes-Bahamonde

  2. Instituto de Ecología y Biodiversidad (IEB), Concepción, Chile

    Alex Fajardo & Frida I. Piper

  3. Instituto Milenio Limit of Life (LiLi), Valdivia, Chile

    Alex Fajardo, Frida I. Piper & Claudia Reyes-Bahamonde

  4. Instituto Pirenaico de Ecología (IPE-CSIC), Zaragoza, Spain

    Antonio Gazol, J. Julio Camarero, Ester González de Andrés & Cristina Valeriano

  5. Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, Sweden

    Michael J. Gundale

  6. Instituto de Ciencias Biológicas (ICB), Universidad de Talca, Talca, Chile

    Frida I. Piper

  7. Department of Biology, University of Mississippi, Oxford, MS, USA

    J. Stephen Brewer

  8. Manaaki Whenua (Landcare Research), Lincoln, New Zealand

    Rowan Buxton & Duane Peltzer

  9. Nelson-Marlborough Institute of Technology, Nelson, New Zealand

    Ellen Cieraad

  10. Grupo de Ecología y Manejo de Sistemas Forestales, Universidad Nacional del Comahue, San Martín de los Andes, Argentina

    Alejandro Dezzotti

  11. Departamento de Biología y Geología, Universidad de Almería, Almería, Spain

    Angel Fernández-Cortés

  12. Department of Conservation Biology, Georg-August-Universität Göttingen, Göttingen, Germany

    Florian Goedecke

  13. Department of Physical Geography and Geoecology, Faculty of Science, Charles University, Prague, Czech Republic

    Ester González de Andrés & Cristina Valeriano

  14. Centre for Invasion Biology, Stellenbosch University, Stellenbosch, South Africa

    Suzaan Kritzinger-Klopper

  15. Department of Forest Sciences, University of Helsinki, Helsinki, Finland

    Annamari Laurén & Marjo Palviainen

  16. Private Forestry Consulting, Coyhaique, Chile

    Juan C. Llancabure

  17. Science Department, Augustana Campus, University of Alberta, Camrose, Alberta, Canada

    Anne C. S. McIntosh

  18. IMASL, CONICET, Universidad de San Luis, San Luis, Argentina

    Tomás Milani

  19. Grupo de Ecología de Invasiones, INIBIOMA, CONICET, Universidad Nacional del Comahue, San Carlos de Bariloche, Argentina

    Jaime Moyano

  20. Department of Biology and Biogeochemistry, University of Houston, Houston, TX, USA

    Martín A. Núñez

  21. Albrecht-von-Haller Institute for Plant Science, Georg-August-Universität Göttingen, Göttingen, Germany

    Lina Rinne

  22. Division of Biological Sciences, University of Montana, Missoula, MT, USA

    Anna Sala & Ragan M. Callaway

  23. School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg, South Africa

    Robert P. Skelton

  24. South African Environmental Observation Network (SAEON), Cape Town, South Africa

    Robert P. Skelton

Authors

  1. Alex Fajardo
  2. Antonio Gazol
  3. J. Julio Camarero
  4. Michael J. Gundale
  5. Frida I. Piper
  6. J. Stephen Brewer
  7. Rowan Buxton
  8. Ellen Cieraad
  9. Alejandro Dezzotti
  10. Angel Fernández-Cortés
  11. Florian Goedecke
  12. Ester González de Andrés
  13. Suzaan Kritzinger-Klopper
  14. Annamari Laurén
  15. Juan C. Llancabure
  16. Anne C. S. McIntosh
  17. Tomás Milani
  18. Jaime Moyano
  19. Martín A. Núñez
  20. Marjo Palviainen
  21. Duane Peltzer
  22. Claudia Reyes-Bahamonde
  23. Lina Rinne
  24. Anna Sala
  25. Robert P. Skelton
  26. Cristina Valeriano
  27. Ragan M. Callaway

Contributions

A.F. and R.M.C. conceived and designed the study. A.F., R.M.C., A.G., E.G.d.A., M.J.G., J.S.B., R.B., E.C., A.D., F.G., S.K.-K., A.L., J.C.L., A.C.S.M., T.M., J.M., M.P., D.P., L.R. and R.P.S. conducted the fieldwork. J.J.C. and C.V. performed the dendrochronological analysis. F.I.P. and C.R.-B. oversaw the NSC analysis. A.F.-C. oversaw the isotopes analysis. A.F. performed the wood density analyses. M.A.N. and A.S. supplied data from plantations. A.G. carried out the statistical analyses. A.F. and R.M.C. wrote the manuscript with contributions from the rest of the co-authors. All authors read and edited the text.

Corresponding author

Correspondence to Alex Fajardo.

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Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks Sara Kuebbing, Drew Peltier, Justin Sheffield and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Whittaker biomass diagrams.

Study site distributions of conifer species across mean annual values of air temperature (MAT) and precipitation (MAP) (nCoN = 56, nCoN-N = 95, nAnN = 41). Dots depict the climatic location of sites with conifers in native ranges (CoN, green) and conifers in non-native ranges (CoN-N, yellow).

Extended Data Fig. 2 Tree age-growth relationships for conifers in native and non-native ranges and angiosperms growing adjacent to conifer plantations.

A, Southern Hemisphere. B, Europe. Each dot corresponds to one tree. The R2 is the coefficient of determination associated with a generalized additive mixed effect model (GAMM) fit using mean tree ring width for the period 2000-2020 as a response variable and tree age as an explanatory variable. We included an interaction between tree age and group in the models. The lines represent the non-linear relationship between mean tree growth and age in each group, with the solid line representing the fit and the dashed lines the lower and upper confidence bounds. Samples sizes (n) are included in the figure.

Extended Data Fig. 3 General growth trends for the 2000-2020 period.

A, General growth trends for conifers growing in native and non-native ranges and of angiosperms growing adjacent to conifer plantations. Upper panel: conifers in plantations in their North American native range (CoN, light green), conspecifics in plantations in non-native ranges in the Southern Hemisphere (CoN-N, brown), and angiosperm species growing adjacent to conifers plantations in the Southern Hemisphere (AnN, green). Lower panel: conifers in plantations in their North American native range, in plantations in their non-native ranges in Europe, and angiosperm species adjacent to the plantations. Shaded areas display gaussian kernel estimates of the mean growth (Basal Area Increment, BAI) for each individual within the first 20 years at DBH (a and c), or in the period 2000-2020 (b and d). Vertical lines indicate the mean BAIs for each group. Numbers indicate trees included in each group. B, Growth temporal trajectories (basal area increment, BAI), boxplots of diameter at breast height (DBH) and estimated age of conifers growing in their native range in the Northern Hemisphere (CoN, green) and of conifers growing in non-native ranges in the Southern Hemisphere (CoN-N, brown). Only trees with age ranging between 30 and 50 years were considered. Samples size (n rings; n trees) for species are: Larix decidua (nCoN = 887; 19, nCoN-N = 1,473; 39), Pinus contorta (nCoN = 1,193; 30, nCoN-N = 3,878; 106), P. elliottii (nCoN = 1,254; 32, nCoN-N = 930; 24), P. ponderosa (nCoN = 820; 20, nCoN-N = 2,834; 77), P. radiata (nCoN = 12, nCoN-N = 9), P. sylvestris (nCoN = 1,574; 39, nCoN-N = 1,551; 40), Pseudotsuga menziesii (nCoN = 310; 7, nCoN-N = 2,370; 61).

Extended Data Fig. 4 Growth metrics of conifers in native and non-native ranges.

A, General growth metrics in the first 25-year period for trees in plantations (yellow; nCoN-N = 6,886 tree rings) and invasions (red; nCoN-Ni = 3,404) in their non-native range in the Southern Hemisphere and conspecifics in their native ranges in the Northern Hemisphere and the native gymnosperm A. chilensis (light blue; nCoN = 5,239). Growth trends for the same two categories (invasions and plantations) during the 2010–2020 period in B, Argentina (Pinus contorta; nCoN-Ni = 874; nCoN-N = 849), C, Chile (Pinus contorta; nCoN-Ni = 462; nCoN-N = 648), and D, New Zealand (Pseudotsuga menziesii; nCoN-Ni = 272; nCoN-N = 394).

Extended Data Fig. 5 Growth metrics of conifers planted in native and in non-native ranges and angiosperms in the Southern Hemisphere.

A, General growth metrics and responses to drought for conifer plantations (CoN-N, brown; nCoN-N = 8,777) and natural angiosperm (AnN, green; nAnN = 4,067) forests in the Southern Hemisphere. B, General growth metrics and responses to drought for conifers planted in native ranges in North America (CoN, light green; nCoN = 924) and in non-native ranges in the Southern Hemisphere (CoN-N, brown; nCoN-N = 4,858). a Growth temporal trajectories (basal area index, BAI in mm2 per year), solid lines represent means, and dashed lines represent 95% confidence intervals of the mean; b Boxplots of diameter at breast height (DBH) and c estimated age; d Relationships between BAI and the Standardized Precipitation-Evapotranspiration Index (SPEI, drought index) from 2000 to 2020 (estimated marginal means and their confidence intervals) to all trees. The SPEI was calculated at 1-, 3-, 6-, 9-, and 12-month long scales for mid-summer in the Southern Hemispheres (January). Vertical dashed lines indicate zero SPEI-BAI relationship. When segments do not cross zero (upper and lower boundaries of the estimated marginal means), it indicates the relationship between SPEI and BAI is significant; e Tree-growth resistance to drought; f Recovery after drought (years); and g Tree-growth overall resilience to drought. Each dot represents the mean for each group, and the whiskers show the 95% confidence intervals of the mean. Different low-case letters indicate significant differences between groups at a P-value of 0.05.

Extended Data Fig. 6 Growth metrics of conifers planted in native and in non-native ranges and angiosperms in Europe.

A, General growth metrics and responses to drought for conifers in native ranges in North America (CoN, light green; nCoN = 2,296) and conifers in non-native ranges in Europe (CoN-N, brown; nCoN-N = 2,451). B, General growth metrics and responses to drought for angiosperms in native ranges (AnN, green; nAnN = 1,416) and conifers in non-native ranges in Europe (CoN-N, brown; nCoN-N = 2,451). a Growth temporal trajectories (basal area index, BAI in mm2 per year), solid lines represent means, and dashed lines represent 95% confidence intervals of the mean; b Boxplots of diameter at breast height (DBH) and c estimated age; d Relationships between BAI and the Standardized Precipitation-Evapotranspiration Index (SPEI, drought index) from 2000 to 2020 (estimated marginal means and their confidence intervals) to all trees. The SPEI was calculated at 1-, 3-, 6-, 9-, and 12-month long scales for mid-summer in the Northern Hemispheres (July). Vertical dashed lines indicate zero SPEI-BAI relationship. When segments do not cross zero (upper and lower boundaries of the estimated marginal means), it indicates the relationship between SPEI and BAI is significant; e Tree-growth resistance to drought; f Recovery after drought (years); and g Tree-growth overall resilience to drought. Each dot represents the mean for each group, and the whiskers show the 95% confidence intervals of the mean. Different low-case letters indicate significant differences between groups at a P-value of 0.05.

Extended Data Fig. 7 Wood density.

Boxplots showing sapwood density values for conifers planted in non-native ranges (CoN-N, brown; nCoN-N = 122) in the Southern Hemisphere and in Europe, conifers in native ranges (CoN, light green; nCoN = 105) in North America and Europe, and native angiosperms (AnN, green; nAnN = 158) in the Southern Hemisphere and Europe.

Extended Data Fig. 8 Physiological metrics of conifers and angiosperms related to drought.

A, Natural angiosperm (AnN, green; nAnN = 115) and conifers in plantations in the non-native ranges (CoN-N, brown; nCoN-N = 390) in stands in the Southern Hemisphere, and B, conifers in native ranges in North America (CoN, light green; nCoN = 217) and conifers in plantations in non-native ranges in Europe (CoN-N, brown; nCoN-N = 390). a wood δ13C; b non-structural carbohydrate (NSC); c starch; d and soluble sugar concentrations. Different letters indicate significant (p < 0.05) differences between the two compared groups.

Extended Data Fig. 9 Relationships between water balance and the SPEI.

A, Relationship between water balance and the 1-month SPEI (SPEI-01) for conifer species. The water balance (P-PET, precipitation – potential evapotranspiration) was calculated for each month in the period 1960–2020 for each site. The data are interpolated from TerraClimate (https://www.climatologylab.org/terraclimate-variables.html). Brown colours show planted or invaded stands in the Southern Hemisphere, while green colours show native or planted stands in the Northern Hemisphere. B, Comparison of the severity of drought events in conifer stands in native ranges in the Northern Hemisphere (green) and non-native ranges in the Southern Hemisphere (brown) based on the vapor pressure deficit (VPD), precipitation (P) and water balance (P-PET). Yearly values of VPD, P and P-PET were centred and standardized for the period 2000–2020. The standardized values in the five years before the selected drought year (negative values), the drought event (zero value) and the five years after the selected drought year (positive values) are shown. Samples size (n = gridded climatic records) for species are: Larix decidua (nCoN = 3,660, nCoN-N = 3,660), Pinus contorta (nCoN = 9,516, nCoN-N = 19,764), P. elliottii (nCoN = 7,320, nCoN-N = 5,856), P. ponderosa (nCoN = 8,052, nCoN-N = 7,320), P. radiata (nCoN = 3,660, nCoN-N = 9,516), P. sylvestris (nCoN = 6,588, nCoN-N = 3,660), Pseudotsuga menziesii (nCoN = 2,196; 7, nCoN-N = 59,292).

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Fajardo, A., Gazol, A., Camarero, J.J. et al. Pines grow faster and are more drought resilient in the Southern Hemisphere. Nature (2026). https://doi.org/10.1038/s41586-026-10969-8

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