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Inferring forest fate from demographic data: from vital rates to population dynamic models.
Needham, Jessica; Merow, Cory; Chang-Yang, Chia-Hao; Caswell, Hal; McMahon, Sean M.
Afiliação
  • Needham J; Smithsonian Institution Forest Global Earth Observatory, Smithsonian Environmental Research Center, 647 Contees Wharf Road, Edgewater, MD 21307-0028, USA needhamj@si.edu.
  • Merow C; Ecology and Evolutionary Biology, Yale University, 165 Prospect Street, New Haven, CT 06511-8934, USA.
  • Chang-Yang CH; Smithsonian Institution Forest Global Earth Observatory, Smithsonian Environmental Research Center, 647 Contees Wharf Road, Edgewater, MD 21307-0028, USA.
  • Caswell H; Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands.
  • McMahon SM; Smithsonian Institution Forest Global Earth Observatory, Smithsonian Environmental Research Center, 647 Contees Wharf Road, Edgewater, MD 21307-0028, USA.
Proc Biol Sci ; 285(1874)2018 03 14.
Article em En | MEDLINE | ID: mdl-29514966
As population-level patterns of interest in forests emerge from individual vital rates, modelling forest dynamics requires making the link between the scales at which data are collected (individual stems) and the scales at which questions are asked (e.g. populations and communities). Structured population models (e.g. integral projection models (IPMs)) are useful tools for linking vital rates to population dynamics. However, the application of such models to forest trees remains challenging owing to features of tree life cycles, such as slow growth, long lifespan and lack of data on crucial ontogenic stages. We developed a survival model that accounts for size-dependent mortality and a growth model that characterizes individual heterogeneity. We integrated vital rate models into two types of population model; an analytically tractable form of IPM and an individual-based model (IBM) that is applied with stochastic simulations. We calculated longevities, passage times to, and occupancy time in, different life cycle stages, important metrics for understanding how demographic rates translate into patterns of forest turnover and carbon residence times. Here, we illustrate the methods for three tropical forest species with varying life-forms. Population dynamics from IPMs and IBMs matched a 34 year time series of data (albeit a snapshot of the life cycle for canopy trees) and highlight differences in life-history strategies between species. Specifically, the greater variation in growth rates within the two canopy species suggests an ability to respond to available resources, which in turn manifests as faster passage times and greater occupancy times in larger size classes. The framework presented here offers a novel and accessible approach to modelling the population dynamics of forest trees.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Árvores / Clima Tropical / Florestas Tipo de estudo: Prognostic_studies País/Região como assunto: America central / Panama Idioma: En Revista: Proc Biol Sci Assunto da revista: BIOLOGIA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Reino Unido
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Árvores / Clima Tropical / Florestas Tipo de estudo: Prognostic_studies País/Região como assunto: America central / Panama Idioma: En Revista: Proc Biol Sci Assunto da revista: BIOLOGIA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Reino Unido