Seed mass predicts migration lag of European trees
We reanalysed a dataset of tree distribution ranges in Europe to identify which plant traits best explain migration potential in woody species. Contrary to our intuition that tree longevity would best explain the ability of trees to migrate, we found that seed biomass was the only good descriptor of migration potential: trees with heavier seeds lag more.
Context To cope with global warming, the majority of plants have either to migrate polewards or risk extinction. This is why conservationists value predictive models that can flag plant species that may not keep pace with global warming.
Aims To identify which plant traits best explain migration potential in woody species by reanalysing a dataset of tree distribution ranges in Europe.
Methods We used two statistical approaches to quantify migration lag. A direct approach compared frequency of large trees in the two latitudinal extremes and a modelling approach in which we first corrected data for the influence of temperature and then assessed the influence of latitude over the entire distribution of the tree species.
Results Contrary to our intuition that tree longevity would best explain the ability of trees to migrate, we found that seed mass was the only good descriptor of migration potential: trees with heavier seeds lag more.
Conclusion We interpret our results in terms of the well-established trade-off between seed mass and seed production in spermatophytes and discuss the possible functional implications that will result from selectively losing large-seeded trees. In summary, we provide an empirical study on how woody communities will respond to global warming over the next years.
Keywords
Climate change, Seed dispersal, Extinction debt, Forest ecology, Global warming, Plant migration
Publication
Veresoglou, S.D. & Halley, J.M. Annals of Forest Science (2018) 75: 86.
https://doi.org/10.1007/s13595-018-0766-y
For the read-only version of the full text: https://rdcu.be/5QOe
Data availability
The data used are public data. The authors cite the sources and present some of the intermediate data in the form of Table 1 and Table S4.
