Reproducing reproduction: How to simulate mast seeding in forest models

Giorgio Vacchiano, Davide Ascoli, Fabio Berzaghi, Manuel Esteban Lucas-Borja, Thomas Caignard, Alessio Collalti, Paola Mairota, Ciprian Palaghianu, Christopher P.O. Reyer, Tanja G.M. Sanders, Eliane Schermer, Thomas Wohlgemuth and Andrew Hacket-Pain

Ecological Modelling, 2018, vol. 376, issue C, 40-53

Abstract: Masting is the highly variable and synchronous production of seeds by plants. Masting can have cascading effects on plant population dynamics and forest properties such as tree growth, carbon stocks, regeneration, nutrient cycling, or future species composition. However, masting has often been missing from forest models. Those few that simulate masting have done so using relatively simple empirical rules, and lack an implementation of process-based mechanisms that control such events. Here we review more than 200 published papers on mechanistic formulations of masting, and summarize how the main processes involved in masting and their related patterns can be incorporated in forest models at different degrees of complexity.

Keywords: Masting; Seed production; Process-based models; Resource budget model; Resource allocation; Tree reproduction (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380018300887
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:376:y:2018:i:c:p:40-53

DOI: 10.1016/j.ecolmodel.2018.03.004

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().