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Forest Age Rivals Climate to Explain Reproductive Allocation Patterns in Forest Ecosystems Globally

Research output: Contribution to Journal/MagazineReview articlepeer-review

E-pub ahead of print
  • Rachel E. Ward
  • Huanyuan Zhang‐Zheng
  • Kate Abernethy
  • Stephen Adu‐Bredu
  • Luzmilla Arroyo
  • Andrew Bailey
  • Liana Chesini‐Rossi
  • Percival Cho
  • Cecilia A. L. Dahlsjö
  • Eder Carvalho das Neves
  • Bianca de Oliveira Sales
  • William Farfan‐Rios
  • Joice Nunes Ferreira
  • Renata Freitag
  • Cécile Girardin
  • Walter Huaraca Huasco
  • Carlos A. Joly
  • Yadvinder Malhi
  • Beatriz Marimon
  • Ben Hur Marimon Junior
  • Alexandra C. Morel
  • Helene C. Muller‐Landau
  • Karine da Silva Peixoto
  • Simone Reis
  • Terhi Riutta
  • Norma Salinas
  • Marina Seixas
  • Miles R. Silman
  • Lara M. Kueppers
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Article numbere70191
<mark>Journal publication date</mark>31/08/2025
<mark>Journal</mark>Ecology Letters
Issue number8
Volume28
Publication StatusE-pub ahead of print
Early online date25/08/25
<mark>Original language</mark>English

Abstract

Forest allocation of net primary productivity (NPP) to reproduction (carbon required for flowers, fruits, and seeds) is poorly quantified globally, despite its critical role in forest regeneration and a well‐supported trade‐off with allocation to growth. Here, we present the first global synthesis of a biometric proxy for forest reproductive allocation (RA) across environmental and stand age gradients from a compiled dataset of 824 observations across 393 sites. We find that ecosystem‐scale RA increases ~60% from boreal to tropical forests. Climate shows important non‐linear relationships with RA, but is not the sole predictor. Forest age effects are comparable to climate in magnitude (MAT: ß = 0.24, p = 0.021; old growth forest: ß = 0.22, p < 0.001), while metrics of soil fertility show small but significant relationships with RA (soil pH: ß = 0.07, p = 0.001; soil N: ß = −0.07, p = 0.001). These results provide strong evidence that ecosystem‐scale RA is mediated by climate, forest age, and soil conditions, and is not a globally fixed fraction of positive NPP as assumed by most vegetation and ecosystem models. Our dataset and findings can be used by modellers to improve predictions of forest regeneration and carbon cycling.