Fast-slow continuum and reproductive strategies structure plant life-history variation worldwide
de Kroon, H
Proceedings of the National Academy of Sciences
National Academy of Sciences
The identification of patterns in life-history strategies across the tree of life is essential to our prediction of population persistence, extinction, and diversification. Plants exhibit a wide range of patterns of longevity, growth, and reproduction, but the general determinants of this enormous variation in life history are poorly understood. We use demographic data from 418 plant species in the wild, from annual herbs to supercentennial trees, to examine how growth form, habitat, and phylogenetic relationships structure plant life histories and to develop a framework to predict population performance. We show that 55% of the variation in plant life-history strategies is adequately characterized using two independent axes: the fast-slow continuum, including fast-growing, short-lived plant species at one end and slow-growing, long-lived species at the other, and a reproductive strategy axis, with highly reproductive, iteroparous species at one extreme and poorly reproductive, semelparous plants with frequent shrinkage at the other. Our findings remain consistent across major habitats and are minimally affected by plant growth form and phylogenetic ancestry, suggesting that the relative independence of the fast-slow and reproduction strategy axes is general in the plant kingdom. Our findings have similarities with how life-history strategies are structured in mammals, birds, and reptiles. The position of plant species populations in the 2D space produced by both axes predicts their rate of recovery from disturbances and population growth rate. This life-history framework may complement trait-based frameworks on leaf and wood economics; together these frameworks may allow prediction of responses of plants to anthropogenic disturbances and changing environments.
M. Franco provided the phylogenetic tree. We thank H. Possingham, D. Koons, and F. Colchero for feedback and the COMPADRE Plant Matrix Database team for data digitalization and error-checking. This work was supported by the Max Planck Institute for Demographic Research, Australian Research Council Grant DE140100505 (to R.S.-G.), and a Marie-Curie Career Integration Grant (to Y.M.B.).
This is the author accepted manuscript. The final version is available from National Academy of Sciences via the DOI in this record.
Vol. 113 (1), pp. 230 - 235
Place of publication