Browsing by Autor "F. Schieving"

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Functional traits determine trade-offs and niches in a tropical forest community
(National Academy of Sciences, 2011) Frank J. Sterck; Lars Markesteijn; F. Schieving; Lourens Poorter
How numerous tree species can coexist in diverse forest communities is a key question in community ecology. Whereas neutral theory assumes that species are adapted to common field conditions and coexist by chance, niche theory predicts that species are functionally different and coexist because they are specialized for different niches. We integrated biophysical principles into a mathematical plant model to determine whether and how functional plant traits and trade-offs may cause functional divergence and niche separation of tree species. We used this model to compare the carbon budget of saplings across 13 co-occurring dry-forest tree species along gradients of light and water availability. We found that species ranged in strategy, from acquisitive species with high carbon budgets at highest resource levels to more conservative species with high tolerances for both shade and drought. The crown leaf area index and nitrogen mass per leaf area drove the functional divergence along the simulated light gradient, which was consistent with observed species distributions along light gradients in the forest. Stomatal coordination to avoid low water potentials or hydraulic failure caused functional divergence along the simulated water gradient, but was not correlated to observed species distributions along the water gradient in the forest. The trait-based biophysical model thus explains how functional traits cause functional divergence across species and whether such divergence contributes to niche separation along resource gradients.
Sapling performance along resource gradients drives tree species distributions within and across tropical forests
(Wiley, 2014) Frank J. Sterck; Lars Markesteijn; Marisol Toledo; F. Schieving; Lourens Poorter
Niche differentiation is a major hypothesized determinant of species distributions, but its practical importance is heavily debated and its underlying mechanisms are poorly understood. Trait‐based approaches have been used to infer niche differentiation and predict species distributions. For understanding underlying mechanisms, individual traits should be scaled up to whole‐plant performance, which has rarely been done. We measured seven key traits that are important for carbon and water balance for 37 tropical tree species. We used a process‐based plant physiological model to simulate the carbon budget of saplings along gradients of light and water availability, and quantified the performance of the species in terms of their light compensation points (a proxy for shade tolerance), water compensation points (proxy for drought tolerance), and maximum carbon gain rates (proxy for potential growth rate). We linked species performances to their observed distributions (the realized niches) at two spatial scales in Bolivian lowland forests: along a canopy openness gradient at local scale (∼1 km 2 ) and along a rainfall gradient (1100–2200 mm/yr) at regional (∼1000 km) scale. We show that the water compensation point was the best predictor of species distributions along water and light resource gradients within and across tropical forests. A sensitivity analysis suggests that the stomatal regulation of minimum leaf water potentials, rather than stem hydraulic traits (sapwood area and specific conductivity), contributed to the species differences in the water compensation point of saplings. The light compensation point and maximum carbon gain, both driven by leaf area index and leaf nitrogen concentration, also contributed to differential species distributions at the local scale, but not or only marginally at the regional scale. Trait‐and‐physiology‐based simulations of whole‐plant performance thus help to evaluate the possible roles of individual traits in physiological processes underlying species performance along environmental gradients. The development of such whole‐plant concepts will improve our ability to understand responses of plant communities to shifts in resource availability and stress under global change.