Using dynamic vegetation models to simulate plant range shifts

By R. Snell, Andreas Huth, J. Nabel, Greta Bocedi, Justin M. J. Travis, Dominique Gravel, Harald Bugmann, Á. Gutiérrez, Thomas Hickler, Steven Higgins and 4 more. 2014

127 citations recorded by the source corpus.

Dynamic vegetation models (DVMs) follow a process-based approach to simulate plant population demography, and have been used to address questions about disturbances, plant succession, community composition, and provisioning of ecosystem services under climate change scenarios. Despite their potential, they have seldom been used for studying species range dynamics explicitly. In this perspective paper, we make the case that DVMs should be used to this end and can improve our understanding of the factors that influence species range expansions and contractions. We review the benefits of using process-based, dynamic models, emphasizing how DVMs can be applied specifically to questions about species range dynamics. Subsequently, we provide a critical evaluation of some of the limitations and trade-offs associated with DVMs, and we use those to guide our discussions about future model development. This includes a discussion on which processes are lacking, specifically a mechanistic representation of dispersal, inclusion of the seedling stage, trait variability, and a dynamic representation of reproduction. We also discuss upscaling techniques that offer promising solutions for being able to run these models efficiently over large spatial extents. Our aim is to provide directions for future research efforts and to illustrate the value of the DVM approach.

Subfields: Ecological Modeling, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/9557e17e3f9c24e6bd5f3e28e5381d08bafd3ea3

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In Ecological Modeling

In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

Extinction debt and colonization credit delay range shifts of eastern North American trees (2017, unknown): “LANDIS II 15 , FATE-HD 16 ) can easily capture local dynamics, they are inherently data demanding and computationally intensive 17,18 , making the estimation of entire distributions at continental scales challenging.”
Modeling plant–water interactions: an ecohydrological overview from the cell to the global scale (2016, methodology): “Forest demography in terrestrial biosphere models is similar or identical to the one developed for forest-gap models in forestry research.(61,375,376) Forest demography can be handled by an average tree individual(352,353,377) evolving in time or by simulating cohorts of individuals with different a”
Biotic interactions in species distribution modelling: 10 questions to guide interpretation and avoid false conclusions (2018, background): “Many dynamic models explicitly consider species interactions, dispersal, or both (Cabral, Valente, & Hartig, 2017; Gravel, 2013; Snell et al., 2014; Svenning et al., 2014).”